Oxytocin reduces subjective fear in naturalistic social contexts via enhancing top-down middle cingulate-amygdala regulation and brain-wide connectivity

Oxytocin reduces subjective fear in naturalistic social contexts via enhancing top-down middle cingulate-amygdala regulation and brain-wide connectivity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Article Oxytocin reduces subjective fear in naturalistic social contexts via enhancing top-down middle cingulate-amygdala regulation and brain-wide connectivity Benjamin Becker, Kun Fu, Shuyue Xu, Zheng Zhang, Dan Liu, Ting Xu, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4317487/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Accumulating evidence from animal and human studies suggests a fear-regulating potential of the neuropeptide oxytocin (OT), yet the clinical translation into novel interventions for pathological fear requires a behavioral and neurofunctional characterization under close-to-real life conditions. Here, we combined a naturalistic fMRI-design inducing high and immersive fear experience in social and non-social contexts with a preregistered between-subjects randomized double-blind placebo-controlled intranasal OT trial (24 IU, n \(=\) 67 healthy men). OT reduced subjective fear in non-social and social contexts with small or moderate effect sizes, respectively. In the social fear contexts, OT enhanced left middle cingulate cortex (lMCC) activation and its functional connectivity with the contralateral amygdala, with both neural indices significantly and inversely associated with subjective fear following OT. On the network level, OT enhanced communication between the dorsal attention network (DAN) with the fronto-parietal (FPN) and the default-mode network (DMN) as well as on the more fine-grained level brain-wide communication. These findings indicate a fear-reducing potential of OT under naturalistic conditions with pronounced effects in social contexts, highlighting its potential value as a treatment option for disorders characterized by excessive fear in social situations. Biological sciences/Neuroscience Health sciences/Diseases/Psychiatric disorders Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Fear is an evolutionarily conserved and highly adaptive defensive avoidance response, fundamental to surviving and functioning in everyday life 1–4 . The experience of excessive and overwhelming fear represents a hallmark symptom of anxiety and trauma-related disorders 5–7 . These highly prevalent psychiatric disorders have become a leading cause of disability and are accompanied by personal suffering as well as an enormous socio-economic burden. The conventional pharmacological interventions targeting the classical neurotransmitter (GABA-ergic, serotonergic) systems 7–9 are characterized by moderate response rates and potential negative side effects ranging from dizziness towards addiction. While several promising candidate compounds have shown effects in animal models, no new pharmacological treatment for fear or anxiety has entered the clinical practice during the last decades (for recent non-pharmacological developments see e.g. 10, 11 ). Based on promising findings in animal models and preclinical human studies neuropeptides, including oxytocin (OT), vasopressin or angiotensin II, have been suggested as promising new strategies to regulate fear and anxiety 12–16 . Most previous research in this field has focused on OT, a neuropeptide produced in the hypothalamus, and animal models 15, 16 as well as preclinical human proof-of-concept studies demonstrated promising effects of OT on regulating negative emotional processing in the domains of fear and anxiety 16–20 . Some of the effects of OT appear to be specific to social contexts and stimuli, yet in the context of contradictory empirical evidence, debates on the social-specific effects of OT continue 21, 22 . OT neurons from the hypothalamus project to a wide range of brain regions involved in fear, anxiety as well as social processes, including the amygdala, hippocampus, midbrain and frontal lobe 5, 23 , and previous studies indicate that intranasal OT can regulate these processes via influencing activity in the amygdala, dorsal anterior cingulate gyrus and medial prefrontal lobe 7, 18–20, 24–26 . However, despite the initially promising findings from these studies, the fear and anxiety-reducing effects of OT and the underlying neural circuits have been determined under laboratory experimental contexts that strongly differ from the dynamic contexts during which fear arises in everyday life 27 . Specifically, these studies combined the intranasal administration of OT with sparsely presented static experimental stimuli (e.g. pictures of fearful faces or scenes) and primarily focused on treatment-induced changes in brain regional activity during fMRI. This approach stands in contrast to contemporary neuroscience models proposing that fear emerges in interaction between subjective appraisal and dynamic changes in the environment 28, 29 and that the corresponding mental states are mediated by an intricate interplay among distributed yet interacting brain systems 30–32 . To account for the complexity of subjective affective experiences under ecologically valid conditions and to capture the underlying network-level communication in the brain, recent overarching conceptualizations have proposed the combination of movie stimuli as highly immersive and dynamic stimuli with network-level analyses 33, 34 . Initial empirical studies confirmed that these stimuli can induce highly immersive affective experiences in complex social situations 35, 36 as well as the essential role that network-level communication plays in establishing affective and social experiences under naturalistic contexts 27, 34, 37, 38 . Mental disorders, including fear-related disorders, have been reconceptualized as network-level disorders that are characterized by dysregulated regional activity as well as network level connectivity (putatively reflecting communication between brain regions) 32, 39, 40 . Together with a growing number of studies underscoring the potential of OT to regulate neurofunctional network-level interactions in fear-related networks across species 41–44 , which may be partly explained by the physiological properties of the oxytocin-signaling system, including an axonal release, widespread receptor distribution and considerably longer half-life compared to classical neurotransmitters 45 , these findings indicate the necessity to account for network-level effects to fully determine a regulatory effect of OT on fear experience and its therapeutic potential. Against this background, the present pre-registered between-subjects randomized double-blind placebo-controlled pharmaco-fMRI study (n \(=\) 67 healthy male participants) capitalized on recent progress in naturalistic fMRI and network-level analyses to determine whether a single dosage of intranasal OT ( 1 ) reduces the subjective experience of fear under highly immersive and ecologically valid conditions, ( 2 ) modulates concomitant regional activity in brain systems identified in previous studies, ( 3 ) modulates brain communication of the identified regions and on the whole-brain network level, and ( 4 ) effects vary as a function of social context. Based on previous studies 7, 18–20 we hypothesized that intranasal OT would decrease subjective fear in naturalistic contexts with more pronounced effects in the social domain while concomitantly enhancing neural activity in regulatory brain regions and inhibiting activity in fear-processing brain regions. On the network level, we expected that OT would enhance communication between emotion-regulation brain regions and the amygdala as well as communication between large-scale networks with pronounced effects in the social fear context. Methods Participants Sixty-nine right-handed male participants with normal or corrected-normal vision were recruited from the University of Electronic Science and Technology of China. The sample size was determined using G*Power v.3.1 46, 47 indicating that 62 participants were required to detect a significant effect on the behavioral level ( f \(=\) 0.25, α \(=\) 0.05, β \(=\) 0.80, 2 \(\times\) 2 \(\times\) 2 mixed ANOVA interaction effect). The present study focused on male subjects to reduce variance related to sex differences in the effects of OT 48, 49 and adhered to validated exclusion criteria (details see supplementary methods). The final sample size was n \(=\) 67 (mean \(\pm\) SD, age \(=\) 21.03 \(\pm\) 1.95 years) due to two data from two participants being excluded (withdraw due to personal reasons, technical MRI issues). All participants provided written informed consent, protocols were pre-registered on Clinical Trials.gov (clinicaltrials.gov/ NCT05892939), approved by the ethics committee at the University of Electronic Science and Technology of China (UESTC-1061423041725893) and in line with the latest Declaration of Helsinki. Using a double-blind randomized, placebo-controlled, between-subject pharmacological fMRI design, participants were randomly assigned to receive either a single intranasal dose of oxytocin (OT, 24IU-Sichuan Defeng Pharmaceutical Co. Ltd, China) or a placebo (PLC, same ingredients i.e. sodium chloride and glycerin but without the peptide). The spray bottles were identical and dispensed by an independent researcher based on a computer-generated randomization sequence to ensure double-blinding. The investigators involved in data acquisition and analyses were blinded for group allocation. Following recent recommendations 50–52 , the fMRI assessment began 45 minutes after treatment administration. To control for pre-treatment between-group differences, participants completed a series of mood and mental health questionnaires (as detailed in Table 1 ). Participants were asked to guess which treatment they had received after the experiment (with a non-significant treatment guess χ 2 \(=\) 0.39, p \(=\) 0.53, confirming successful double-blinding). Additionally, participants were required to complete a surprise recognition task after the experiment that involved presenting stills of the video clips shown during fMRI and new clips to test the attentive processing of the stimuli. All participants achieved a re-recognition accuracy of over 75% and no significant difference in performance was observed between the two treatment groups ( t (1,65) \(=\) -0.693, p \(=\) 0.491). Naturalistic fear induction paradigm. The task began 45 minutes after the treatment intervention (see Fig. 1 a). During the naturalistic fear induction paradigm, participants were instructed to watch a series of video clips attentively and rate their level of fear experience after each clip. The clips lasted 25 seconds and were followed by a 1–3 second jittered fixation cross to separate the stimuli from the rating period. During the 5-second period following each stimulus, participants were asked to report their level of subjective fear on a 9-point Likert scale, with 1 indicating no fear and 9 indicating very strong fear. This was followed by a jittered inter-trial interval of 9–11 seconds, during which a fixation cross was presented (see Fig. 1 b). A total of 32 short video clips were presented over 2 runs, with each run consisting of 16 randomly presented clips, half of which were neutral and half of which were fear-inducing clips. Given ongoing discussions about the social-specific effects of OT 53, 54 , we carefully pre-selected a balanced set of stimuli that included social as well as non-social fearful or neutral stimuli, respectively. This led to a set of four stimulus categories (fear social clips-FS, fear non-social clips-FNS, neutral social clips-NS, neutral non-social clips-NNS, see Fig. 1 c). For detailed characterization of the video clips, see Supplementary Methods. The video clips used for the naturalistic fear induction paradigm were selected from a larger database based on stimuli evaluation ratings in an independent sample (n = 20; 10 females; age = 22.65 ± 2.01). Key exclusion criteria for the video clips were reported in supplementary methods. Based on the results of the behavioral ratings (see Fig. S2 ), 8 complimentary video clips were selected for each of the four categories. The task was programmed in Python 3.7 using the PsychoPy package (version 2022.2.4). Effects of OT on subjective fear experience. To determine the effects of OT on subjective fear in naturalistic contexts and whether they vary as a function of social context, we computed a repeated measures ANOVA with the between-subject factor treatment (OT vs PLC) and the within-subject factors emotion (fear vs neutral) and social (social vs non-social) and the dependent variable fear ratings during fMRI. To initially ensure that the selected video clips were effective in inducing the intended emotions, repeated measures ANOVA (sex was used as the independent variable, while emotion and social were used as repeated variables) were conducted on five rating metrics (see supplementary methods). Analyses were conducted using GraphPad Prism 9.0 (GraphPad Software, Inc., La Jolla, CA), and corresponding effect sizes were computed using JASP 0.18.3.0 (JASP Team, 2019; jasp-stats.org). All ANOVAs and t-tests used false discovery rate (FDR) 55 recommended by Prism for multiple comparison correction. MRI data acquisition and preprocessing. MRI data were collected on a 3.0-T GE Discovery MR750 system (General Electric Medical System, Milwaukee, WI, USA) and preprocessed using FMRIPREP 21.0.0 56 (RRID: SCR_016216), a Nipype 1.6.1 based tool that integrates preprocessing routines from different software packages and SPM 12 (Statistical Parametric Mapping; http://www.fil.ion.ucl.ac.uk/spm/ ; Wellcome Trust Centre for Neuroimaging, detailed in supplementary methods). Next, a voxel-wise general linear model (GLM) was conducted for each participant. Specifically, a first-level model was designed that included separate regressors for the four conditions and the rating period. In line with a previous study 28 , we removed variance associated with the mean, linear and quadratic trends, the average signal within anatomically-derived CSF mask, the effects of motion estimated during the head-motion correction using an expanded set of 24 motion parameters (six realignment parameters, their squares, their derivatives, and their squared derivatives) and motion spikes (FMRIPREP default: FD \(>\) 0.5mm or standardized DVARS \(>\) 1.5) 57 . Effects of OT on fear-related brain activity. To examine the effects of OT on fear-related neural activity in naturalistic contexts, a GLM-based model was established in SPM 12. The model incorporated five regressors: FS, FNS, NS, NNS, and the rating period. We included the 24 head motion parameters as covariates of no interest. Key first-level contrasts of interest were contrasts that modeled fear in social and non-social contexts separately (i.e., [FS \(-\) NS] or [FNS \(-\) NNS]) as well as their interaction (i.e., [FS \(-\) NS] \(-\) [FNS \(-\) NNS]). In line with the behavioral analyses, the effects of OT were determined using an ANOVA with the factors emotion and social context, implemented in a partitioned error ANOVA approach that subjected the first level interaction contrast to a voxel-wise two-sample t-test with the factor treatment group on the second level. Based on our hypothesis and previous studies reporting that fear is strongly associated with amygdala, cingulate cortex (particularly middle cingulate cortex, MCC), insula, and ventromedial prefrontal cortex (vmPFC) and that oxytocin mediates its anxiolytic effects via these regions 14, 22, 27, 58–60 , our analyses focused on atlas-derived bilateral masks for the amygdala, MCC, insula and vmPFC using separate small volume correction (SVC) and family-wise error (FWE) correction 61 applied at peak level. To further disentangle complex interaction effects involving treatment, parameter estimates were extracted using 8mm radius spheres centered at the peak interaction coordinates using Marsbar ( http://marsbar.sourceforge.net/ ). The extracted Blood Oxygenation Level Dependent (BOLD) signals were then subjected to appropriate post-hoc tests comparing group differences in each of the separate conditions. Additionally, to determine associations between the behavioral (subjective fear) and neural effects of OT (both activation and functional connectivity between specific brain regions) we conducted correlation analysis using JASP. Effects of OT on functional communication of the regions identified. We further examined whether the regions showing altered regional activation following OT also changed their network-level communication via a general Psychophysiological interaction (gPPI) analysis. gPPI examines functional connectivity between brain regions that is contingent on a psychological context. We used the Generalized PPI toolbox 62 as implemented in SPM 12, to conduct gPPI. This method includes additional task regressors to reduce the likelihood that the functional connectivity estimates are driven simply by co-activation and has been widely used in similar studies 63, 64 . Based on our results, OT enhanced activation in the left middle cingulate cortex (lMCC) under the three-way interaction (treatment \(\times\) emotion \(\times\) social), we therefore computed the functional communication of this region (using an 8mm radius which centered in peak Montreal Neurological Institute (MNI), x, y, z = -7, -3, 30) with other voxels in the whole brain under the two-way interaction of emotion and social, and a two-sample t-test was conducted to confirm the treatment effect of OT. Based on previous studies reporting effects of OT on the functional communication of the amygdala 48, 49 , separate atlas-derived bilateral masks for the amygdala, MCC, insula and vmPFC were used for SVC analyses with FWE correction 61 applied at peak level. Marsbar was used to extract information communications between other regions and the seed region to further disentangle complex interaction effects involving treatment. The extracted functional connectivity signals were then subjected to compare the treatment effect under four conditions by using two-sample t-tests separately. Effects of OT on large-scale brain network functional connectivity. Given that several studies reported the effects of OT on large-scale network organization of the brain 65, 66 , we examined OT effects on the whole-brain network level. To this end, time-series of each region of interest (ROI) was extracted according to the template including 463 ROIs across the whole brain (see supplementary methods), resulting in BOLD time series of the size of r \(\times\) t ( r was the number of ROIs and t was the BOLD time series length) for each subject per run. A matrix of size r \(\times\) r was obtained by calculating Pearson's correlation between the average BOLD time series of each pair of ROIs. Additionally, Fisher's z-transform was applied to improve the normality of the correlation coefficients. The brain regions can be divided into nine networks based on their functional divisions, and the neural activities of each network's regions were averaged to calculate network functional connectivity. During each run, four types of video clips were presented in a pseudo-randomized order. The onset time of each video clip was shifted by 3 TRs to account for hemodynamic lag. To extract neural activity time series for a specific condition, we used the time points and durations specified for the appearance of different trials of the same type. This resulted in four r \(\times\) d matrices (where r is the number of ROIs and d is the BOLD time series length of each condition). Additionally, we obtained the r \(\times\) r matrix between ROIs and the n \(\times\) n matrix (where n is the number of networks) between brain networks for different conditions. After performing Fisher-Z transformation on the network functional connectivity matrices for different conditions, matrices of Z-values corresponding to specific conditions (Z FS \Z FNS \Z NS \Z FNS ) are obtained. It is important to note that r values are not additive or subtractive, but Z scores are summative. Matrix of Z-values corresponding to particular contrasts (e.g. Z FS-NS ) can be computed by subtract the matrices of Z-values corresponding to different conditions (e.g. Z FS -Z NS ) 67, 68 . Therefore, each participant in both groups would have their own subtracted Z-values matrix under specific contrasts (Z FS-NS \Z FNS-NNS ). We then conducted two-sample t-tests on each pair of network-level functional connectivity to determine the treatment effect. Effects of OT on whole-brain functional connectivity. To further investigate the impact of OT on a finer spatial scale, we analyzed whole-brain functional connectivity using paired t-tests for key contrasts (FS \(-\) NNS and FNS \(-\) NNS) separately for the two groups. We applied FDR correction ( p FDR−corrected \(<\) 0.05) to identify the most relevant functional connections for each contrast. A Mantel test 69, 70 was performed on the FDR-corrected functional connectivity matrices of the two groups, under specific contrasts, to assess their similarity. Furthermore, to investigate treatment-specific effects on functional connectivity strength at the whole-brain level, we transformed the upper triangular data of the t -value matrices of the two groups under specific contrast into two ( r \(\times\) ( r \(-\) 1)) / 2 by 1 feature vectors, and performed Welch’s t-test between them. Results Demographics and potential confounders. The OT (n \(=\) 33) and PLC (n \(=\) 34) groups were comparable with respect to socio-demographics, mood and mental health indices arguing against nonspecific treatment effects (Table 1 , all ps \(>\) 0.10). Table 1 Demographics and potential confounders in the two treatment groups. Time OT(M \(\pm\) SD) PLC(M \(\pm\) SD) t p Age 21.30 \(\pm\) 2.05 20.76 \(\pm\) 1.83 1.13 0.26 BDI II Before 4.70 \(\pm\) 3.83 5.38 \(\pm\) 5.40 -0.60 0.55 BAI Before 2.36 \(\pm\) 2.56 2.53 \(\pm\) 3.75 -0.21 0.83 LSAS Before 31.36 \(\pm\) 20.35 26.15 \(\pm\) 19.47 1.07 0.29 SAI Before 34.79 \(\pm\) 6.63 33.15 \(\pm\) 9.37 0.83 0.41 TAI Before 37.82 \(\pm\) 7.30 37.97 \(\pm\) 9.99 -0.07 0.94 ERQ-Reappraisal Before 31.00 \(\pm\) 3.98 30.74 \(\pm\) 4.15 0.27 0.79 ERQ-Suppression Before 15.85 \(\pm\) 4.72 14.82 \(\pm\) 4.41 0.92 0.36 PANAS-P Before 1 28.85 \(\pm\) 6.05 28.47 \(\pm\) 7.17 0.23 0.82 2 − 1 -6.12 \(\pm\) 6.71 -4.06 \(\pm\) 5.18 -1.41 0.16 Treatment peak 2 22.73 \(\pm\) 5.95 24.41 \(\pm\) 6.90 -1.07 0.29 3 − 2 -2.85 \(\pm\) 5.50 -1.62 \(\pm\) 5.39 -0.93 0.36 After experiment 3 19.88 \(\pm\) 6.71 22.79 \(\pm\) 7.71 -1.65 0.10 3 − 1 -8.97 \(\pm\) 7.12 -5.68 \(\pm\) 7.53 -1.84 0.07 PANAS-N Before 1 15.09 \(\pm\) 5.17 14.09 \(\pm\) 4.82 0.82 0.41 2 − 1 -3.24 \(\pm\) 4.70 -3.06 \(\pm\) 4.06 -0.17 0.87 Treatment peak 2 11.85 \(\pm\) 3.17 11.03 \(\pm\) 2.32 1.21 0.23 3 − 2 1.33 \(\pm\) 2.97 1.65 \(\pm\) 2.62 -0.46 0.65 After experiment 3 13.18 \(\pm\) 4.15 12.68 \(\pm\) 3.86 0.52 0.61 3 − 1 -1.91 \(\pm\) 6.07 -1.41 \(\pm\) 5.51 -0.35 0.73 Values presented here as mean \(\pm\) standard deviation (M \(\pm\) SD). BDI II Beck Depression Inventory II, BAI Beck Anxiety Index, LSAS Liebowitz Social Anxiety Scale, STAI Spielberger State-Trait Anxiety Inventory, ERQ Emotion Regulation Questionnaire, PANAS Positive and Negative Affect Schedule, OT oxytocin, PLC placebo. OT reduced subjective fear experience in naturalistic contexts, particularly in social contexts. The ANOVA revealed a significant main effect of emotion ( F (1,65) \(=\) 1434, p \(<\) 0.0001, η p 2 \(=\) 0.957, Fig. 2 a) such that participants rated subjective fear considerably higher during fear trials (FS and FNS) than neutral ones, and a significant main effect of social ( F (1,65) \(=\) 76.81, p \(<\) 0.0001, η p 2 \(=\) 0.542, Fig. 2 a) reflecting lower fear during social trials (FS and NS) compared with non-social trials. With respect to the effects of OT we found a significant interaction effect between treatment and emotion ( F (3,65) \(=\) 4.064, p \(=\) 0.048, η p 2 \(=\) 0.059, Fig. 2 a), with post hoc tests indicating that OT significantly decreased fear experience in response to fearful stimuli in naturalistic social contexts while the effects sizes indicated a stronger fear reduction in social contexts ( t (1,65) \(=\) -3.038, p \(=\) 0.0027, Cohen’s d \(=\) -0.742 under FS while t (1,65) \(=\) -1.991, p \(=\) 0.048, Cohen’s d \(=\) -0.487 under FNS, Fig. 2 b). Finally, the interaction between emotion and social was significant ( F (3,65) \(=\) 53.15, p \(<\) 0.0001, η p 2 \(=\) 0.45, Fig. 2 a) reflecting that participants reported generally lower fear experience in social fear contexts. The main effect of treatment and other interactions were not significant. Together the results partly support that OT can reduce subjective fear in naturalistic situations and that the effects are more pronounced in social fear contexts. OT enhanced middle cingulate activation in the social fear contexts. We initially examined brain regions participating in fear processing under naturalistic contexts with different social features compared with neutral control conditions, a series of corresponding voxel-wise one-sample t-tests conducted in the PLC group confirmed previous studies, suggesting that visual and temporal regions were strongly engaged during exposure to dynamic fear movie clips irrespective of social features ( Fig. S3 ). Examining treatment effects revealed a significant interaction between treatment \(\times\) emotion \(\times\) social located in the left middle cingulate cortex (peak MNI, x, y, z \(=\) -7, -3, 30, t (1,65) \(=\) 3.67, k \(=\) 33, p FWE−peak(svc) \(=\) 0.019, Fig. 2 c), with post-hoc t-tests on extracted activity measures from this region indicating that compared to PLC, OT selectively enhanced activation in this region for FS ( t (1,65) \(=\) 2.761, p \(=\) 0.007, Cohen’s d \(=\) 0.675, Fig. 2 d) but not other conditions (all p s \(>\) 0.05, Fig. 2 d). Examining associations between lMCC activation (extracted parameter estimates) and subjective fear experience revealed a significant negative association in the OT ( r \(=\) -0.418, p \(=\) 0.016, Fig. 2 e) but not in PLC group ( r \(=\) 0.090, p \(=\) 0.611, Fig. 2 e). A Fisher r-z transformation indicated that these correlation coefficients were significantly different between the OT and PLC groups (Z \(=\) -2.09, two-tailed p \(=\) 0.037). OT enhanced MCC-amygdala functional communication consistently in the social fear contexts. Examining OT effects on the functional communication of the lMCC revealed a significant interaction effect between treatment \(\times\) emotion \(\times\) social located in the right amygdala (rAmy) (peak MNI, x, y, z = 22, -7, 13, t (1,65) \(=\) 3.81, k \(=\) 19, p FWE−peak(svc) \(=\) 0.021, Fig. 3 a), with post-hoc t-tests indicating that OT relative to PLC selectively enhanced lMCC-rAmy coupling in social fear contexts ( t (1,65) \(=\) 2.70, p \(=\) 0.009, Cohen’s d \(=\) 0.66, Fig. 3 b) but not other contexts (all p s \(>\) 0.05, FDR-corrected, Fig. 3 b), confirming social fear-specific effects of OT on the neural level. In addition, we found that lMCC-rAmy functional coupling was significantly negatively associated with subjective fear experience in the OT ( r \(=\) -0.392, p \(=\) 0.024, Fig. 3 c) but not PLC group ( r \(=\) -0.084, p \(=\) 0.638, Fig. 3 c, Fisher r -to- z transformation revealed a trend-to-significant difference between the treatment groups, Z \(=\) -1.29, one-tailed p \(=\) 0.099). OT enhanced FPN-DAN and DMN-DAN coupling during social fear contexts. Examining the effects of OT on the large-scale network level using separate two-sample t-tests on the matrices of z-values for the two main contrasts of interest (FS \(-\) NS, FNS \(-\) NNS) and following mantel test revealed that OT significantly affected network functional connectivity differently under two contexts (rho mantel test \(=\) -0.1333, p \(>\) 0.05). Specifically, compared to PLC (all p s \(>\) 0.05, Fig. 4 f), OT significantly enhanced the functional communication between FPN and DAN ( t (1,65) \(=\) 2.75, p \(=\) 0.0077, Cohen’s d \(=\) 0.672, Fig. 4 e) as well as between DMN and DAN ( t (1,65) \(=\) 2.02, p \(=\) 0.048, Cohen’s d \(=\) 0.493, Fig. 4 e) under the social fear but not the non-social fear contexts. OT modulated whole-brain functional connectivity in the social fear context. We further conducted exploratory analyses to examine whether OT changes brain-wide communications. Results showed that while under PLC only few positive connections increased activity during the FS versus NS contrast (Fig. 5 a), OT induced a more widespread connectivity between several brain regions (Fig. 5 b). Under the FNS versus NNS contrast, the PLC group exhibited wide-spread connectivity (Fig. 5 c), with no obvious changes following OT (Fig. 5 d). Further Mantel tests and Welch’s t-test were conducted on the t-value matrices (FS \(-\) NS and FNS \(-\) NNS) between both groups showed significant modulating effects of OT under both contrasts (rho mantel test \(=\) 0.0335, t (1,65) \(=\) 9.05, p \(<\) 0.0001 under FS \(-\) NS, rho mantel test \(=\) 0.208, t (1,65) \(=\) -2.51, p \(=\) 0.012 under FNS \(-\) NNS), particularly under the fear social contexts. Discussion The present study determined the acute behavioral and neural effects of a single intranasal OT administration on subjective fear experience in a naturalistic context that resembles dynamic fear processing in social and non-social contexts in a close-to-real life setting. On the behavioral level, OT decreased the experience of subjective fear across social and non-social contexts, supporting a fear-regulating potential of OT under dynamic and ecologically valid conditions. Mirroring the stronger effect sizes of the OT-induced fear reduction in social contexts, neural effects of OT were primarily observed in social fear contexts, such that OT enhanced regional activation in the left MCC and its communication with the contralateral amygdala specifically during fear in social contexts with both neural indices exhibiting a negative association with subjective fear following OT but not PLC. Exploratory network-level analyses further revealed that OT significantly enhanced the functional connectivity between the DAN and the FPN/DMN, respectively, and brain-wide communication selectively in social fear contexts. Together, the findings indicate that a single dose of intranasal OT has the potential to decrease fear in close-to-real life settings by enhancing lMCC activation and its communication with the amygdala while concomitantly affecting network-level communication of the DAN with brain networks involved in regulatory control (FPN 71, 72 ) and social processing (DMN 73, 74 ) as well as brain-wide functional communication. Several previous studies in rodents and humans suggested a fear- and anxiety-reducing potential of OT, however, results remained inconsistent. Studies have described a promising fear- and anxiety-reducing neurofunctional profile of OT across species, yet the neural effects on amygdala-related circuits were often observed in the absence of changes in subjective fear experience or under experimental laboratory settings with limited ecological validity 15, 17–20, 75 . In the context of increasing attempts to enhance the ecological validity of neuroimaging research using dynamic movie stimuli 27, 28, 76 , we here combined naturalistic fMRI employing fear-inducing movie clips with a pre-registered randomized double-blind placebo-controlled OT-administration trial. Across pilot experiments and treatment studies, the procedure induced a highly immersive and comparably strong experience of fear under close-to-real life conditions. Importantly, OT decreased subjective fear experience in the more naturalistic context with small or moderate effect sizes in the non-social or social context, respectively. Although the pronounced fear-reducing effects of OT in the social context may partly reflect the generally more moderate fear experience reported by our participants in this context, pronounced effects of OT in social contexts have been conceptualized in a number of overarching theories and have been reported in several previous studies 21, 22, 77 including studies reporting decreased subjective anxiety 78 . The latter hypothesis on the social-specific effects of OT is also mirrored in the brain functional findings, such that the neurofunctional effects were selectively observed during fear experiences in social contexts. With respect to regional activation, OT increased the activation of the left middle cingulate cortex (lMCC). The MCC represents a highly integrative hub that has been involved in both, fear evaluation 5, 60, 79, 80 as well as the cognitive control of negative affective states including fear 81, 82 . Concomitantly, OT enhanced functional connectivity from the lMCC to the contralateral amygdala (rAmy), a pathway that has been previously involved in implementing top-down inhibitory control over excessive fear-related amygdala engagement 60, 80, 83 . Effects of OT on this circuitry have been previously reported in the context of reduced subjective anxiety in individuals with PTSD 84 and in response to static fearful faces in patients with generalized social anxiety disorders 25 . Exploring brain-behavior associations further revealed that OT established a negative association between higher activity and connectivity in this circuit and subjective fear, underscoring the behavioral relevance of the OT-induced neurofunctional changes. Together, our findings suggest that OT exerts its fear-regulating effects under naturalistic contexts via enhancing MCC engagement and control over the amygdala. On the large-scale network level, OT significantly enhanced the functional connectivity of the DAN with the FPN as well as the DMN in the social fear contexts. The DAN is centered around the intraparietal sulcus and the frontal eye fields and plays a pivotal role in top-down or goal-directed control of attention 85–87 , while the FPN supports goal-directed actions and cognitive control 71, 88, 89 and the DMN supports self-referential 90, 91 and social processing 73, 74 , with more recent findings additionally suggesting a role in emotional experience in dynamic naturalistic contexts 92, 93 . While studies have demonstrated the effects of OT on the interaction between these large-scale networks during the task-free state 65, 94 , the present findings underscore the behavioral relevance of these effects of OT in terms of regulating emotional processes in social contexts. Together with previous studies suggesting an association between dysfunctional interaction between these large-scale networks and emotional dysregulations in anxiety and fear-related disorders 32, 91 , the present findings support a potential therapeutic potential of OT for these disorders 32, 95, 96 . Network-level analyses that explored the effects of OT on the fine-grained level of brain-wide connectivity patterns suggested that OT may broadly facilitate brain-wide exchange of information within and across networks particularly between the FPN and DMN in social fear contexts. The results align with recent findings suggesting that emotional processes such as fear and anxiety are processed in distributed networks and their interactions 27, 34, 97 as well as the distributed network-level properties and effects of the OT signaling system 41, 98, 99 . These findings underscore that OT may exert its effects on human emotion processing under complex naturalistic conditions via regulating extensive network-level interactions. Together with increasing the reconceptualization and increasing evidence indicating that mental disorders are not related to dysfunctions of a single brain region or pathway but rather dysregulated brain-wide communication 32, 91, 100 , these findings may further underscore the therapeutic potential of the OT signaling system. Findings have to be considered in the context of limitations of the present design, including ( 1 ) to avoid variations in the effects of OT related to sex 48, 49 , we only focused on male participants and future studies need to test generalization to females, ( 2 ) the study employed a proof-of-concept design in healthy subjects and future studies need to validate the effects of OT in populations with pathological fear and anxiety, ( 3 ) despite extensive pre-study testing the videos of the social and non-social category differed in terms of the level of fear induced which partly limits conclusions regarding social-specific effects of OT, ( 4 ) the videos included homogenous brief episodes of fear and future studies need to examine effects of OT on fear during longer time scales and longer episodes with dynamic fear 27, 28 . Taken together, this study demonstrated that OT can reduce subjective fear experience under naturalistic conditions via enhancing lMCC engagement and its regulatory control over the amygdala as well as enhancing communication between large-scale networks and brain-wide communication. These findings consistently indicate a high translational therapeutic potential of OT to regulate fear in dynamic and close-to-real life environments. Effects were pronounced or restricted to the social contexts, supporting the role that OT may play in social contexts, and rendering OT as a promising treatment for social context-specific fear experiences, e.g. in social anxiety disorders. Findings indicate that OT may be used as a novel therapeutic strategy to regulate excessive subjective fear symptoms in mental disorders 7, 17, 24 or may help to prevent the development of these disorders during early stages or promote long-term recovery 94 via improving the quality of life, and reduce the social and economic burden related to fear-related disorders. Declarations Competing interests The authors declare no competing interests. Author contributions KF and BB 1 designed the study. KF, ZZ and DL conducted the experiment and collected the data. KF, SX, WZ, ZL performed the data analysis with the help of TX, YZ, XZ, CL, JW, LW, JH and BB 2 . KF and BB 1 wrote the manuscript. SX, FZ, KK, TX, YZ, ZL and WZ critically revised the manuscript draft. Acknowledgement This work was supported by the China MOST2030 Brain Project (Grant No. 2022ZD0208500), the National Natural Science Foundation of China (Grants No. 32250610208, 82271583-BB), the National Key Research and Development Program of China (Grant No. 2018YFA0701400-BB), the Natural Science Foundation of Sichuan Province (Grant number 2022NSFSC1375-WZ) and a start-up grant from The University of Hong Kong. Disclaimer: Any opinions, findings, conclusions or recommendations expressed in this publication do not reflect the views of the Government of the Hong Kong Special Administrative Region or the Innovation and Technology Commission. References Osakada T, Yan R, Jiang Y, Wei D, Tabuchi R, Dai B et al. A dedicated hypothalamic oxytocin circuit controls aversive social learning. Nature 2024. Akinrinade I, Kareklas K, Teles MC, Reis TK, Gliksberg M, Petri G et al. Evolutionarily conserved role of oxytocin in social fear contagion in zebrafish. Science 2023; 379 (6638) : 1232-1237. Faul L, Stjepanović D, Stivers JM, Stewart GW, Graner JL, Morey RA et al. Proximal threats promote enhanced acquisition and persistence of reactive fear-learning circuits. Proceedings of the National Academy of Sciences 2020; 117 (28) : 16678-16689. Becker B, Zhou F. Neural Processing of Fear – From Animal Models to Human Research. 2020. Zhou F, Zhao W, Qi Z, Geng Y, Yao S, Kendrick KM et al. A distributed fMRI-based signature for the subjective experience of fear. Nature Communications 2021; 12 (1) : 6643. Bramson B, Meijer S, van Nuland A, Toni I, Roelofs K. Anxious individuals shift emotion control from lateral frontal pole to dorsolateral prefrontal cortex. Nature Communications 2023; 14 (1) : 4880. Kreuder A-K, Scheele D, Schultz J, Hennig J, Marsh N, Dellert T et al. Common and dissociable effects of oxytocin and lorazepam on the neurocircuitry of fear. Proceedings of the National Academy of Sciences 2020; 117 (21) : 11781-11787. Szuhany KL, Simon NM. Anxiety Disorders: A Review. JAMA 2022; 328 (24) : 2431-2445. Slee A, Nazareth I, Bondaronek P, Liu Y, Cheng Z, Freemantle N. Pharmacological treatments for generalised anxiety disorder: a systematic review and network meta-analysis. The Lancet 2019; 393 (10173) : 768-777. Taschereau-Dumouchel V, Cortese A, Chiba T, Knotts JD, Kawato M, Lau H. Towards an unconscious neural reinforcement intervention for common fears. Proceedings of the National Academy of Sciences 2018; 115 (13) : 3470-3475. Zhao Z, Yao S, Li K, Sindermann C, Zhou F, Zhao W et al. Real-Time Functional Connectivity-Informed Neurofeedback of Amygdala-Frontal Pathways Reduces Anxiety. Psychotherapy and Psychosomatics 2019; 88 (1) : 5-15. Paul JM, Raül A, Rene H, Tiffany RL, Moriel Z, Joanna D. Limbic Neuropeptidergic Modulators of Emotion and Their Therapeutic Potential for Anxiety and Post-Traumatic Stress Disorder. The Journal of Neuroscience 2021; 41 (5) : 901. Zhang R, Zhao W, Qi Z, Xu T, Zhou F, Becker B. Angiotensin II Regulates the Neural Expression of Subjective Fear in Humans: A Precision Pharmaco-Neuroimaging Approach. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 2023; 8 (3) : 262-270. Zhou F, Geng Y, Xin F, Li J, Feng P, Liu C et al. Human Extinction Learning Is Accelerated by an Angiotensin Antagonist via Ventromedial Prefrontal Cortex and Its Connections With Basolateral Amygdala. Biol Psychiat 2019; 86 (12) : 910-920. Knobloch HS, Charlet A, Hoffmann Lena C, Eliava M, Khrulev S, Cetin Ali H et al. Evoked Axonal Oxytocin Release in the Central Amygdala Attenuates Fear Response. Neuron 2012; 73 (3) : 553-566. Neumann ID, Slattery DA. Oxytocin in General Anxiety and Social Fear: A Translational Approach. Biol Psychiat 2016; 79 (3) : 213-221. Eckstein M, Becker B, Scheele D, Scholz C, Preckel K, Schlaepfer TE et al. Oxytocin Facilitates the Extinction of Conditioned Fear in Humans. Biol Psychiat 2015; 78 (3) : 194-202. Kou J, Zhang Y, Zhou F, Gao Z, Yao S, Zhao W et al. Anxiolytic Effects of Chronic Intranasal Oxytocin on Neural Responses to Threat Are Dose-Frequency Dependent. Psychotherapy and Psychosomatics 2022; 91 (4) : 253-264. Xin F, Zhou X, Dong D, Zhao Z, Yang X, Wang Q et al. Oxytocin Differentially Modulates Amygdala Responses during Top-Down and Bottom-Up Aversive Anticipation. Adv Sci 2020; 7 (16) : 2001077. Liu C, Lan C, Li K, Zhou F, Yao S, Xu L et al. Oxytocinergic Modulation of Threat-Specific Amygdala Sensitization in Humans Is Critically Mediated by Serotonergic Mechanisms. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 2021; 6 (11) : 1081-1089. Shamay-Tsoory SG, Abu-Akel A. The Social Salience Hypothesis of Oxytocin. Biol Psychiat 2016; 79 (3) : 194-202. Yao S, Zhao W, Geng Y, Chen Y, Zhao Z, Ma X et al. Oxytocin Facilitates Approach Behavior to Positive Social Stimuli via Decreasing Anterior Insula Activity. Int J Neuropsychoph 2018; 21 (10) : 918-925. Oliver JR, Alexandra CP, Brian C, Christian G. The translational neural circuitry of anxiety. Journal of Neurology, Neurosurgery &amp; Psychiatry 2019; 90 (12) : 1353. Scheele D, Lieberz J, Goertzen-Patin A, Engels C, Schneider L, Stoffel-Wagner B et al. Trauma Disclosure Moderates the Effects of Oxytocin on Intrusions and Neural Responses to Fear. Psychotherapy and Psychosomatics 2019; 88 (1) : 61-63. Gorka SM, Fitzgerald DA, Labuschagne I, Hosanagar A, Wood AG, Nathan PJ et al. Oxytocin Modulation of Amygdala Functional Connectivity to Fearful Faces in Generalized Social Anxiety Disorder. Neuropsychopharmacology 2015; 40 (2) : 278-286. Eckstein M, Scheele D, Patin A, Preckel K, Becker B, Walter A et al. Oxytocin Facilitates Pavlovian Fear Learning in Males. Neuropsychopharmacology 2016; 41 (4) : 932-939. Feng Z, Ran Z, Shuxia Y, Debo D, Pan F, Georg K et al. Capturing dynamic fear experiences in naturalistic contexts: An ecologically valid fMRI signature integrating brain activation and connectivity. bioRxiv 2024 : 2023.2008.2018.553808. Chang LJ, Jolly E, Cheong JH, Rapuano KM, Greenstein N, Chen P-HA et al. Endogenous variation in ventromedial prefrontal cortex state dynamics during naturalistic viewing reflects affective experience. Science Advances ; 7 (17) : eabf7129. Meer JNvd, Breakspear M, Chang LJ, Sonkusare S, Cocchi L. Movie viewing elicits rich and reliable brain state dynamics. Nature Communications 2020; 11 (1) : 5004. Adolphs R. How should neuroscience study emotions? by distinguishing emotion states, concepts, and experiences. Soc Cogn Affect Neur 2017; 12 (1) : 24-31. Pessoa L. A Network Model of the Emotional Brain. Trends in Cognitive Sciences 2017; 21 (5) : 357-371. Wen Z, Seo J, Pace-Schott EF, Milad MR. Abnormal dynamic functional connectivity during fear extinction learning in PTSD and anxiety disorders. Molecular Psychiatry 2022; 27 (4) : 2216-2224. Eickhoff SB, Milham M, Vanderwal T. Towards clinical applications of movie fMRI. NeuroImage 2020; 217: 116860. Saarimäki H, Glerean E, Smirnov D, Mynttinen H, Jääskeläinen IP, Sams M et al. Classification of emotion categories based on functional connectivity patterns of the human brain. NeuroImage 2022; 247: 118800. de Vries IEJ, Wurm MF. Predictive neural representations of naturalistic dynamic input. Nature Communications 2023; 14 (1) : 3858. Redcay E, Moraczewski D. Social cognition in context: A naturalistic imaging approach. NeuroImage 2020; 216: 116392. Lee J-J, Kim HJ, Čeko M, Park B-y, Lee SA, Park H et al. A neuroimaging biomarker for sustained experimental and clinical pain. Nature Medicine 2021; 27 (1) : 174-182. Hayoung S, Bo-yong P, Hyunjin P, Won Mok S. Cognitive and Neural State Dynamics of Narrative Comprehension. The Journal of Neuroscience 2021; 41 (43) : 8972. Etkin A, Maron-Katz A, Wu W, Fonzo GA, Huemer J, Vértes PE et al. Using fMRI connectivity to define a treatment-resistant form of post-traumatic stress disorder. Science Translational Medicine 2019; 11 (486) : eaal3236. Xu X, Dai J, Chen Y, Liu C, Xin F, Zhou X et al. Intrinsic connectivity of the prefrontal cortex and striato-limbic system respectively differentiate major depressive from generalized anxiety disorder. Neuropsychopharmacology 2021; 46 (4) : 791-798. Jiang X, Ma X, Geng Y, Zhao Z, Zhou F, Zhao W et al. Intrinsic, dynamic and effective connectivity among large-scale brain networks modulated by oxytocin. NeuroImage 2021; 227: 117668. Zhao Z, Ma X, Geng Y, Zhao W, Zhou F, Wang J et al. Oxytocin differentially modulates specific dorsal and ventral striatal functional connections with frontal and cerebellar regions. NeuroImage 2019; 184: 781-789. Liu N, Hadj-Bouziane F, Jones KB, Turchi JN, Averbeck BB, Ungerleider LG. Oxytocin modulates fMRI responses to facial expression in macaques. Proceedings of the National Academy of Sciences 2015; 112 (24) : E3123-E3130. Wahis J, Baudon A, Althammer F, Kerspern D, Goyon S, Hagiwara D et al. Astrocytes mediate the effect of oxytocin in the central amygdala on neuronal activity and affective states in rodents. Nat Neurosci 2021; 24 (4) : 529-541. Bethlehem RAI, van Honk J, Auyeung B, Baron-Cohen S. Oxytocin, brain physiology, and functional connectivity: A review of intranasal oxytocin fMRI studies. Psychoneuroendocrino 2013; 38 (7) : 962-974. Faul F, Erdfelder E, Buchner A, Lang A-G. Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods 2009; 41 (4) : 1149-1160. Liu Y, Li S, Lin W, Li W, Yan X, Wang X et al. Oxytocin modulates social value representations in the amygdala. Nat Neurosci 2019; 22 (4) : 633-641. Gao S, Becker B, Luo L, Geng Y, Zhao W, Yin Y et al. Oxytocin, the peptide that bonds the sexes also divides them. Proceedings of the National Academy of Sciences 2016; 113 (27) : 7650-7654. Ma X, Zhao W, Luo R, Zhou F, Geng Y, Xu L et al. Sex- and context-dependent effects of oxytocin on social sharing. NeuroImage 2018; 183: 62-72. Watanabe T, Abe O, Kuwabara H, Yahata N, Takano Y, Iwashiro N et al. Mitigation of Sociocommunicational Deficits of Autism Through Oxytocin-Induced Recovery of Medial Prefrontal Activity A Randomized Trial. Jama Psychiat 2014; 71 (2) : 166-175. Spengler FB, Schultz J, Scheele D, Essel M, Maier W, Heinrichs M et al. Kinetics and Dose Dependency of Intranasal Oxytocin Effects on Amygdala Reactivity. Biol Psychiat 2017; 82 (12) : 885-894. Lan CM, Liu CC, Li KS, Zhao ZY, Yang JX, Ma YN et al. Oxytocinergic Modulation of Stress-Associated Amygdala-Hippocampus Pathways in Humans Is Mediated by Serotonergic Mechanisms. Int J Neuropsychoph 2022; 25 (10) : 807-817. Bartz JA, Zaki J, Bolger N, Ochsner KN. Social effects of oxytocin in humans: context and person matter. Trends in Cognitive Sciences 2011; 15 (7) : 301-309. Andari E, Duhamel J-R, Zalla T, Herbrecht E, Leboyer M, Sirigu A. Promoting social behavior with oxytocin in high-functioning autism spectrum disorders. Proceedings of the National Academy of Sciences 2010; 107 (9) : 4389-4394. Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society: Series B (Methodological) 1995; 57 (1) : 289-300. Esteban O, Markiewicz CJ, Blair RW, Moodie CA, Isik AI, Erramuzpe A et al. fMRIPrep: a robust preprocessing pipeline for functional MRI. Nature Methods 2019; 16 (1) : 111-116. Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage 2012; 59 (3) : 2142-2154. Motzkin JC, Philippi CL, Wolf RC, Baskaya MK, Koenigs M. Ventromedial Prefrontal Cortex Is Critical for the Regulation of Amygdala Activity in Humans. Biol Psychiat 2015; 77 (3) : 276-284. Mihov Y, Kendrick KM, Becker B, Zschernack J, Reich H, Maier W et al. Mirroring Fear in the Absence of a Functional Amygdala. Biol Psychiat 2013; 73 (7) : e9-e11. Qi S, Hassabis D, Sun J, Guo F, Daw N, Mobbs D. How cognitive and reactive fear circuits optimize escape decisions in humans. Proceedings of the National Academy of Sciences 2018; 115 (12) : 3186-3191. Yekutieli D, Benjamini Y. Resampling-based false discovery rate controlling multiple test procedures for correlated test statistics. Journal of Statistical Planning and Inference 1999; 82 (1) : 171-196. McLaren DG, Ries ML, Xu G, Johnson SC. A generalized form of context-dependent psychophysiological interactions (gPPI): A comparison to standard approaches. NeuroImage 2012; 61 (4) : 1277-1286. Fung BJ, Qi S, Hassabis D, Daw N, Mobbs D. Slow escape decisions are swayed by trait anxiety. Nature Human Behaviour 2019; 3 (7) : 702-708. Xu T, Zhou X, Kanen JW, Wang L, Li J, Chen Z et al. Angiotensin blockade enhances motivational reward learning via enhancing striatal prediction error signaling and frontostriatal communication. Molecular Psychiatry 2023; 28 (4) : 1692-1702. Xin F, Zhou F, Zhou X, Ma X, Geng Y, Zhao W et al. Oxytocin Modulates the Intrinsic Dynamics Between Attention-Related Large-Scale Networks. Cerebral Cortex 2021; 31 (3) : 1848-1860. Brodmann K, Gruber O, Goya-Maldonado R. Intranasal Oxytocin Selectively Modulates Large-Scale Brain Networks in Humans. Brain Connectivity 2017; 7 (7) : 454-463. Ruslan M, Irina K, Alexander K, Denis C, Maxim K. Comparison of whole-brain task-modulated functional connectivity methods for fMRI task connectomics. bioRxiv 2024 : 2024.2001.2022.576622. Schmälzle R, Brook O’Donnell M, Garcia JO, Cascio CN, Bayer J, Bassett DS et al. Brain connectivity dynamics during social interaction reflect social network structure. Proceedings of the National Academy of Sciences 2017; 114 (20) : 5153-5158. Foster Brett L, Rangarajan V, Shirer William R, Parvizi J. Intrinsic and Task-Dependent Coupling of Neuronal Population Activity in Human Parietal Cortex. Neuron 2015; 86 (2) : 578-590. Giordano BL, Whiting C, Kriegeskorte N, Kotz SA, Gross J, Belin P. The representational dynamics of perceived voice emotions evolve from categories to dimensions. Nature Human Behaviour 2021; 5 (9) : 1203-1213. Cole MW, Reynolds JR, Power JD, Repovs G, Anticevic A, Braver TS. Multi-task connectivity reveals flexible hubs for adaptive task control. Nat Neurosci 2013; 16 (9) : 1348-1355. Uddin LQ. Cognitive and behavioural flexibility: neural mechanisms and clinical considerations. Nature Reviews Neuroscience 2021; 22 (3) : 167-179. Simony E, Honey CJ, Chen J, Lositsky O, Yeshurun Y, Wiesel A et al. Dynamic reconfiguration of the default mode network during narrative comprehension. Nature Communications 2016; 7 (1) : 12141. Axelrod V, Rees G, Bar M. The default network and the combination of cognitive processes that mediate self-generated thought. Nature Human Behaviour 2017; 1 (12) : 896-910. Peter K, Christine E, Qiang C, Daniela M, Stefanie L, Sarina S et al. Oxytocin Modulates Neural Circuitry for Social Cognition and Fear in Humans. The Journal of Neuroscience 2005; 25 (49) : 11489. Sonkusare S, Breakspear M, Guo C. Naturalistic Stimuli in Neuroscience: Critically Acclaimed. Trends in Cognitive Sciences 2019; 23 (8) : 699-714. Menon R, Neumann ID. Detection, processing and reinforcement of social cues: regulation by the oxytocin system. Nature Reviews Neuroscience 2023; 24 (12) : 761-777. Xu X, Li J, Chen Z, Kendrick KM, Becker B. Oxytocin reduces top-down control of attention by increasing bottom-up attention allocation to social but not non-social stimuli – A randomized controlled trial. Psychoneuroendocrino 2019; 108: 62-69. Mobbs D, Trimmer PC, Blumstein DT, Dayan P. Foraging for foundations in decision neuroscience: insights from ethology. Nature Reviews Neuroscience 2018; 19 (7) : 419-427. Tashjian SM, Zbozinek TD, Mobbs D. A Decision Architecture for Safety Computations. Trends in Cognitive Sciences 2021; 25 (5) : 342-354. van Heukelum S, Mars RB, Guthrie M, Buitelaar JK, Beckmann CF, Tiesinga PHE et al. Where is Cingulate Cortex? A Cross-Species View. Trends in Neurosciences 2020; 43 (5) : 285-299. Loh KK, Procyk E, Neveu R, Lamberton F, Hopkins WD, Petrides M et al. Cognitive control of orofacial motor and vocal responses in the ventrolateral and dorsomedial human frontal cortex. Proceedings of the National Academy of Sciences 2020; 117 (9) : 4994-5005. Shackman AJ, Salomons TV, Slagter HA, Fox AS, Winter JJ, Davidson RJ. The integration of negative affect, pain and cognitive control in the cingulate cortex. Nature Reviews Neuroscience 2011; 12 (3) : 154-167. Koch SBJ, van Zuiden M, Nawijn L, Frijling JL, Veltman DJ, Olff M. Intranasal Oxytocin Normalizes Amygdala Functional Connectivity in Posttraumatic Stress Disorder. Neuropsychopharmacology 2016; 41 (8) : 2041-2051. Patel GH, Yang D, Jamerson EC, Snyder LH, Corbetta M, Ferrera VP. Functional evolution of new and expanded attention networks in humans. Proceedings of the National Academy of Sciences 2015; 112 (30) : 9454-9459. Womelsdorf T, Everling S. Long-Range Attention Networks: Circuit Motifs Underlying Endogenously Controlled Stimulus Selection. Trends in Neurosciences 2015; 38 (11) : 682-700. Rosenberg MD, Finn ES, Scheinost D, Constable RT, Chun MM. Characterizing Attention with Predictive Network Models. Trends in Cognitive Sciences 2017; 21 (4) : 290-302. Dixon ML, De La Vega A, Mills C, Andrews-Hanna J, Spreng RN, Cole MW et al. Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks. Proceedings of the National Academy of Sciences 2018; 115 (7) : E1598-E1607. Keller AS, Sydnor VJ, Pines A, Fair DA, Bassett DS, Satterthwaite TD. Hierarchical functional system development supports executive function. Trends in Cognitive Sciences 2023; 27 (2) : 160-174. Satpute AB, Lindquist KA. The Default Mode Network’s Role in Discrete Emotion. Trends in Cognitive Sciences 2019; 23 (10) : 851-864. Sylvester CM, Corbetta M, Raichle ME, Rodebaugh TL, Schlaggar BL, Sheline YI et al. Functional network dysfunction in anxiety and anxiety disorders. Trends in Neurosciences 2012; 35 (9) : 527-535. Xu S, Zhang Z, Li L, Zhou Y, Lin D, Zhang M et al. Functional connectivity profiles of the default mode and visual networks reflect temporal accumulative effects of sustained naturalistic emotional experience. NeuroImage 2023; 269: 119941. Brandman T, Malach R, Simony E. The surprising role of the default mode network in naturalistic perception. Communications Biology 2021; 4 (1) : 79. Davies C, Martins D, Dipasquale O, McCutcheon RA, De Micheli A, Ramella-Cravaro V et al. Connectome dysfunction in patients at clinical high risk for psychosis and modulation by oxytocin. Molecular Psychiatry 2024. Chai Y, Sheline YI, Oathes DJ, Balderston NL, Rao H, Yu M. Functional connectomics in depression: insights into therapies. Trends in Cognitive Sciences 2023; 27 (9) : 814-832. Yan C-G, Chen X, Li L, Castellanos FX, Bai T-J, Bo Q-J et al. Reduced default mode network functional connectivity in patients with recurrent major depressive disorder. Proceedings of the National Academy of Sciences 2019; 116 (18) : 9078-9083. Liu X, Jiao G, Zhou F, Kendrick KM, Yao D, Gong Q et al. A neural signature for the subjective experience of threat anticipation under uncertainty. Nature Communications 2024; 15 (1) : 1544. Zhang H, Chen K, Bao J, Wu H. Oxytocin enhances the triangular association among behavior, resting-state, and task-state functional connectivity. Human Brain Mapping 2023; 44 (17) : 6074-6089. Quintana DS, Rokicki J, van der Meer D, Alnæs D, Kaufmann T, Córdova-Palomera A et al. Oxytocin pathway gene networks in the human brain. Nature Communications 2019; 10 (1) : 668. Deco G, Kringelbach Morten L. Great Expectations: Using Whole-Brain Computational Connectomics for Understanding Neuropsychiatric Disorders. Neuron 2014; 84 (5) : 892-905. Additional Declarations The authors have declared there is NO conflict of interest to disclose Supplementary Files 002OTfearSI.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4317487","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":314663549,"identity":"8663c313-f35c-4809-bf72-e68157215f03","order_by":0,"name":"Benjamin Becker","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYBACAyBmhtDMB0ACjA0kaGFLIFkLjwFxWszZew8wF1TYGfNLn/n86mYbg2w/IS2WPecSmGecSTaT7MvdZp1zhsF4JiFrDG7kGDDzth2wMTjDu804p4IhccMBQlruvwFq+XfAxv4MzzPjHAOGxP0EtdzgAWppOGBmwMPD/BhsC2G/AB0241iyscQZNjPmnDMSxjMI2WLOfsaAuaDGzrC/h/nx59w2G9n+BkLWMDCw/4Ay2CQYGCQIq0cGzB9IUz8KRsEoGAUjBQAAOO08Y1eH/YkAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-9014-9671","institution":"The University of Hong Kong","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"","lastName":"Becker","suffix":""},{"id":314663550,"identity":"ae38d235-495c-447f-839a-f0bf4f65129a","order_by":1,"name":"Kun Fu","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kun","middleName":"","lastName":"Fu","suffix":""},{"id":314663551,"identity":"013d3633-0779-44eb-8c51-e9915b308e91","order_by":2,"name":"Shuyue Xu","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shuyue","middleName":"","lastName":"Xu","suffix":""},{"id":314663552,"identity":"5a2f759e-cad8-45c7-a092-bf147d5b51d6","order_by":3,"name":"Zheng Zhang","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zheng","middleName":"","lastName":"Zhang","suffix":""},{"id":314663553,"identity":"54f5367c-d0c4-44e3-b4cb-fac9d830bfcd","order_by":4,"name":"Dan Liu","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Dan","middleName":"","lastName":"Liu","suffix":""},{"id":314663554,"identity":"63e1d366-29a1-4d5b-8585-55b5ce30ebf0","order_by":5,"name":"Ting Xu","email":"","orcid":"","institution":"University of Electronic Science and Technology of China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ting","middleName":"","lastName":"Xu","suffix":""},{"id":314663555,"identity":"a2289cb4-9dcb-427d-b867-f71c22675bbb","order_by":6,"name":"Yuan Zhang","email":"","orcid":"","institution":"University of Electronic Science and Technology of China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuan","middleName":"","lastName":"Zhang","suffix":""},{"id":314663556,"identity":"7e924664-e791-43ca-b860-739cb2a23857","order_by":7,"name":"Feng Zhou","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Zhou","suffix":""},{"id":314663557,"identity":"63cfb511-1281-4d5f-99a7-0d8f915daa3a","order_by":8,"name":"Xiaodong Zhang","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaodong","middleName":"","lastName":"Zhang","suffix":""},{"id":314663558,"identity":"31defd63-49a8-4bef-bf5f-fef6399288e1","order_by":9,"name":"Chunmei Lan","email":"","orcid":"https://orcid.org/0000-0002-6466-1217","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chunmei","middleName":"","lastName":"Lan","suffix":""},{"id":314663559,"identity":"72ebcfc5-4618-40d6-a951-a675a0b99734","order_by":10,"name":"Junjie Wang","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Junjie","middleName":"","lastName":"Wang","suffix":""},{"id":314663560,"identity":"2200a9d9-ab55-40b5-bb20-14434b94b5d9","order_by":11,"name":"Lan Wang","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lan","middleName":"","lastName":"Wang","suffix":""},{"id":314663561,"identity":"d8e2a269-7ae2-4155-9d67-70a3c0ae2c8b","order_by":12,"name":"Jingxian He","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jingxian","middleName":"","lastName":"He","suffix":""},{"id":314663562,"identity":"216451db-78c9-4943-9ee5-e59e9aacafd8","order_by":13,"name":"Keith Kendrick","email":"","orcid":"https://orcid.org/0000-0002-0371-5904","institution":"University of Electronic Science and Technology of China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Keith","middleName":"","lastName":"Kendrick","suffix":""},{"id":314663563,"identity":"ab889395-bf97-4285-8705-31cecaeab0c4","order_by":14,"name":"Bharat Biswal","email":"","orcid":"https://orcid.org/0000-0002-3710-3500","institution":"New Jersey Institute of Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bharat","middleName":"","lastName":"Biswal","suffix":""},{"id":314663564,"identity":"2294b866-22b0-4f6d-a247-59c65f71e550","order_by":15,"name":"Zhen Liang","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhen","middleName":"","lastName":"Liang","suffix":""},{"id":314663565,"identity":"fba44ab9-e468-4428-9497-b241f57f5ee6","order_by":16,"name":"Weihua Zhao","email":"","orcid":"https://orcid.org/0000-0003-1780-4606","institution":"University of Electronic Science and Technology of China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Weihua","middleName":"","lastName":"Zhao","suffix":""}],"badges":[],"createdAt":"2024-04-24 10:30:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4317487/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4317487/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59481882,"identity":"aa0a32fb-0fd8-4df9-9bcb-414f0a22fa0d","added_by":"auto","created_at":"2024-07-02 10:09:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":608974,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExperimental timeline, paradigm and schematic depiction of stimuli.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e The timeline of the whole experiment. \u003cstrong\u003eb\u003c/strong\u003e Naturalistic fear induction and rating paradigm. \u003cstrong\u003ec \u003c/strong\u003eExample stimuli. In each run, 4 types of video clips were presented (FS, FNS, NS, NNS) according to a randomized order. Abbreviations: OT oxytocin, PLC placebo, fMRI functional magnetic resonance imaging, FS fear social, FNS fear non-social, NS neutral social, NNS neutral non-social. License: Images in 1a and 1b were obtained from Flaticon.com under the free license with attribution.\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4317487/v1/9586ab6b0ff8b421e61ab4e9.png"},{"id":59481887,"identity":"1d38dd5e-386b-427f-8740-274a99e256e1","added_by":"auto","created_at":"2024-07-02 10:09:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1227579,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe effects of OT on behavioral fear rating and cingulate activity.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e OT reduced subjective fear rating in naturalistic situations particularly in contexts, \u003cstrong\u003eb\u003c/strong\u003e OT effects on fear rating under four conditions separately, \u003cstrong\u003ec\u003c/strong\u003e OT but not PLC could strengthen the activation in the left middle cingulate cortex (lMCC) under the interaction of valence and social. Particularly, \u003cstrong\u003ed\u003c/strong\u003e OT specifically increased the activation in lMCC under FS but not other conditions. \u003cstrong\u003ee\u003c/strong\u003e The activation in lMCC was significantly negatively correlated with subjective fear experience in OT group but not PLC group. OT oxytocin, PLC placebo, FS fear social, FNS fear non-social, NS neutral social, NNS neutral non-social. **** \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR-corrected\u003c/sub\u003e0.0001, ***\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR-corrected\u003c/sub\u003e0.001, ** \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR-corrected\u003c/sub\u003e0.01, * \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR-corrected\u003c/sub\u003e0.05, ns not significant.\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4317487/v1/9f1b69fde3d88d86c368a5d1.png"},{"id":59481886,"identity":"23029cbc-96a4-458b-854e-e99011a5b10d","added_by":"auto","created_at":"2024-07-02 10:09:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":990885,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOT strengthened lMCC-rAmy communication specifically in social fear contexts.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e Interaction effect between treatmentemotionsocial on lMCC connectivity with the right amygdala \u003cstrong\u003eb\u003c/strong\u003e OT specifically increased functional connectivity between lMCC and rAmy in the FS contexts but not other conditions and \u003cstrong\u003ec\u003c/strong\u003e The functional connectivity between lMCC and rAmy was significantly negatively correlated with subjective fear experience in OT group but not PLC group. OT oxytocin, PLC placebo, FS fear social, FNS fear non-social, NS neutral social, NNS neutral non-social. ** \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR-corrected\u003c/sub\u003e0.01, * \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR-corrected\u003c/sub\u003e0.05, # \u003cem\u003ep\u003c/em\u003e\u003csub\u003eun-corrected\u003c/sub\u003e0.05.\u0026nbsp; \u0026nbsp;\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4317487/v1/6fe83910e014e78c0a6d6ef9.png"},{"id":59482399,"identity":"164b0a8d-6ef4-471c-b5bc-35d71ffc9912","added_by":"auto","created_at":"2024-07-02 10:17:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2448575,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOT enhanced functional connectivity on the level of large-scale networks\u003c/strong\u003e. \u003cstrong\u003ea b c d\u003c/strong\u003e Flow of z-value matrix calculation for the degree of response functional connectivity under specific contrasts. (1) The Fisher r-z matrices of each condition for each participant were subtracted to yield a new matrix of z-value corresponding to the contrast (e.g. z\u003csub\u003eFSNS\u003c/sub\u003e = z\u003csub\u003eFS\u003c/sub\u003ez\u003csub\u003eNS\u003c/sub\u003e). (2) New matrices of z-value corresponding to a specific contrast were generated for each participant in each group, which were used as features in a two-sample t-test to derive the between-group differences under the specified contrast. \u003cstrong\u003ee\u003c/strong\u003e OT significantly strengthened the functional connectivity between FPN and DAN as well as DMN and DAN in the fear social-related contrast \u003cstrong\u003ef\u003c/strong\u003e but not in the fear non-social-related contrast. OT oxytocin, PLC placebo, FS fear social, FNS fear non-social, NS neutral social, NNS neutral non-social, VN visual network, SMN somatomotor network, DAN dorsal attention network, VAN ventral attention network, LN limbic network, FPN frontoparietal network, DMN default mode network, SCT subcortical network, B/C brainstem and cerebellum. ##\u003cem\u003ep\u003c/em\u003e\u003csub\u003eun-corrected\u003c/sub\u003e0.01, # \u003cem\u003ep\u003c/em\u003e\u003csub\u003eun-corrected\u003c/sub\u003e0.05.\u0026nbsp; \u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e","description":"","filename":"fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-4317487/v1/fbaa8f97fddd320c20021ebd.png"},{"id":59481884,"identity":"dddb8570-6714-4114-bbc0-786802b47bf0","added_by":"auto","created_at":"2024-07-02 10:09:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":655797,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison between treatment groups for whole-brain functional connectivity during social and non-social fear separately. \u003c/strong\u003eUnder fear social contexts,\u003cstrong\u003e a\u003c/strong\u003e PLC group showed a sparse connectivity between brain regions \u003cstrong\u003eb\u003c/strong\u003e the OT group exhibited stronger functional interactions at the whole-brain level. In contrast, under the fear non-social context \u003cstrong\u003ec\u003c/strong\u003e PLC and \u003cstrong\u003ed\u003c/strong\u003e OT groups showed similar whole-brain functional connectivity patterns. OT oxytocin, PLC placebo, FS fear social, FNS fear non-social, NS neutral social, NNS neutral non-social, VN visual network, SMN somatomotor network, DAN dorsal attention network, VAN ventral attention network, LN limbic network, FPN frontoparietal network, DMN default mode network, SCT subcortical network, B/C brainstem and cerebellum.\u003c/p\u003e","description":"","filename":"fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-4317487/v1/c2da68b7d7dbf6ba8eaefebd.png"},{"id":61944086,"identity":"62092157-3e5b-42e0-9b59-cea94a62737e","added_by":"auto","created_at":"2024-08-07 11:06:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8287331,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4317487/v1/6af1f69e-7b56-433b-add6-06020e001054.pdf"},{"id":59481883,"identity":"e991ba02-3de5-4a3c-a91f-6736a8574430","added_by":"auto","created_at":"2024-07-02 10:09:49","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":8015194,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"002OTfearSI.docx","url":"https://assets-eu.researchsquare.com/files/rs-4317487/v1/e60e61275d5b6d6c327732b9.docx"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Oxytocin reduces subjective fear in naturalistic social contexts via enhancing top-down middle cingulate-amygdala regulation and brain-wide connectivity","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFear is an evolutionarily conserved and highly adaptive defensive avoidance response, fundamental to surviving and functioning in everyday life \u003csup\u003e1–4\u003c/sup\u003e. The experience of excessive and overwhelming fear represents a hallmark symptom of anxiety and trauma-related disorders \u003csup\u003e5–7\u003c/sup\u003e. These highly prevalent psychiatric disorders have become a leading cause of disability and are accompanied by personal suffering as well as an enormous socio-economic burden. The conventional pharmacological interventions targeting the classical neurotransmitter (GABA-ergic, serotonergic) systems \u003csup\u003e7–9\u003c/sup\u003e are characterized by moderate response rates and potential negative side effects ranging from dizziness towards addiction. While several promising candidate compounds have shown effects in animal models, no new pharmacological treatment for fear or anxiety has entered the clinical practice during the last decades (for recent non-pharmacological developments see e.g. \u003csup\u003e10, 11\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eBased on promising findings in animal models and preclinical human studies neuropeptides, including oxytocin (OT), vasopressin or angiotensin II, have been suggested as promising new strategies to regulate fear and anxiety \u003csup\u003e12–16\u003c/sup\u003e. Most previous research in this field has focused on OT, a neuropeptide produced in the hypothalamus, and animal models \u003csup\u003e15, 16\u003c/sup\u003e as well as preclinical human proof-of-concept studies demonstrated promising effects of OT on regulating negative emotional processing in the domains of fear and anxiety \u003csup\u003e16–20\u003c/sup\u003e. Some of the effects of OT appear to be specific to social contexts and stimuli, yet in the context of contradictory empirical evidence, debates on the social-specific effects of OT continue \u003csup\u003e21, 22\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOT neurons from the hypothalamus project to a wide range of brain regions involved in fear, anxiety as well as social processes, including the amygdala, hippocampus, midbrain and frontal lobe \u003csup\u003e5, 23\u003c/sup\u003e, and previous studies indicate that intranasal OT can regulate these processes via influencing activity in the amygdala, dorsal anterior cingulate gyrus and medial prefrontal lobe \u003csup\u003e7, 18–20, 24–26\u003c/sup\u003e. However, despite the initially promising findings from these studies, the fear and anxiety-reducing effects of OT and the underlying neural circuits have been determined under laboratory experimental contexts that strongly differ from the dynamic contexts during which fear arises in everyday life \u003csup\u003e27\u003c/sup\u003e. Specifically, these studies combined the intranasal administration of OT with sparsely presented static experimental stimuli (e.g. pictures of fearful faces or scenes) and primarily focused on treatment-induced changes in brain regional activity during fMRI.\u003c/p\u003e \u003cp\u003eThis approach stands in contrast to contemporary neuroscience models proposing that fear emerges in interaction between subjective appraisal and dynamic changes in the environment \u003csup\u003e28, 29\u003c/sup\u003e and that the corresponding mental states are mediated by an intricate interplay among distributed yet interacting brain systems \u003csup\u003e30–32\u003c/sup\u003e. To account for the complexity of subjective affective experiences under ecologically valid conditions and to capture the underlying network-level communication in the brain, recent overarching conceptualizations have proposed the combination of movie stimuli as highly immersive and dynamic stimuli with network-level analyses \u003csup\u003e33, 34\u003c/sup\u003e. Initial empirical studies confirmed that these stimuli can induce highly immersive affective experiences in complex social situations \u003csup\u003e35, 36\u003c/sup\u003e as well as the essential role that network-level communication plays in establishing affective and social experiences under naturalistic contexts \u003csup\u003e27, 34, 37, 38\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMental disorders, including fear-related disorders, have been reconceptualized as network-level disorders that are characterized by dysregulated regional activity as well as network level connectivity (putatively reflecting communication between brain regions) \u003csup\u003e32, 39, 40\u003c/sup\u003e. Together with a growing number of studies underscoring the potential of OT to regulate neurofunctional network-level interactions in fear-related networks across species \u003csup\u003e41–44\u003c/sup\u003e, which may be partly explained by the physiological properties of the oxytocin-signaling system, including an axonal release, widespread receptor distribution and considerably longer half-life compared to classical neurotransmitters \u003csup\u003e45\u003c/sup\u003e, these findings indicate the necessity to account for network-level effects to fully determine a regulatory effect of OT on fear experience and its therapeutic potential.\u003c/p\u003e \u003cp\u003eAgainst this background, the present pre-registered between-subjects randomized double-blind placebo-controlled pharmaco-fMRI study (n\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e67 healthy male participants) capitalized on recent progress in naturalistic fMRI and network-level analyses to determine whether a single dosage of intranasal OT (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) reduces the subjective experience of fear under highly immersive and ecologically valid conditions, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) modulates concomitant regional activity in brain systems identified in previous studies, (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) modulates brain communication of the identified regions and on the whole-brain network level, and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) effects vary as a function of social context. Based on previous studies \u003csup\u003e7, 18–20\u003c/sup\u003e we hypothesized that intranasal OT would decrease subjective fear in naturalistic contexts with more pronounced effects in the social domain while concomitantly enhancing neural activity in regulatory brain regions and inhibiting activity in fear-processing brain regions. On the network level, we expected that OT would enhance communication between emotion-regulation brain regions and the amygdala as well as communication between large-scale networks with pronounced effects in the social fear context.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eParticipants\u003c/p\u003e\u003cp\u003eSixty-nine right-handed male participants with normal or corrected-normal vision were recruited from the University of Electronic Science and Technology of China. The sample size was determined using G*Power v.3.1 \u003csup\u003e46, 47\u003c/sup\u003e indicating that 62 participants were required to detect a significant effect on the behavioral level (\u003cem\u003ef\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.25, \u003cem\u003eα\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.05, \u003cem\u003eβ\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.80, 2\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e2\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e2 mixed ANOVA interaction effect). The present study focused on male subjects to reduce variance related to sex differences in the effects of OT \u003csup\u003e48, 49\u003c/sup\u003e and adhered to validated exclusion criteria (details see supplementary methods). The final sample size was n\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e67 (mean\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003eSD, age\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e21.03\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e1.95 years) due to two data from two participants being excluded (withdraw due to personal reasons, technical MRI issues). All participants provided written informed consent, protocols were pre-registered on Clinical Trials.gov (clinicaltrials.gov/ NCT05892939), approved by the ethics committee at the University of Electronic Science and Technology of China (UESTC-1061423041725893) and in line with the latest Declaration of Helsinki.\u003c/p\u003e\u003cp\u003eUsing a double-blind randomized, placebo-controlled, between-subject pharmacological fMRI design, participants were randomly assigned to receive either a single intranasal dose of oxytocin (OT, 24IU-Sichuan Defeng Pharmaceutical Co. Ltd, China) or a placebo (PLC, same ingredients i.e. sodium chloride and glycerin but without the peptide). The spray bottles were identical and dispensed by an independent researcher based on a computer-generated randomization sequence to ensure double-blinding. The investigators involved in data acquisition and analyses were blinded for group allocation. Following recent recommendations \u003csup\u003e50–52\u003c/sup\u003e, the fMRI assessment began 45 minutes after treatment administration.\u003c/p\u003e\u003cp\u003eTo control for pre-treatment between-group differences, participants completed a series of mood and mental health questionnaires (as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Participants were asked to guess which treatment they had received after the experiment (with a non-significant treatment guess \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.39, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.53, confirming successful double-blinding). Additionally, participants were required to complete a surprise recognition task after the experiment that involved presenting stills of the video clips shown during fMRI and new clips to test the attentive processing of the stimuli. All participants achieved a re-recognition accuracy of over 75% and no significant difference in performance was observed between the two treatment groups (\u003cem\u003et\u003c/em\u003e\u003csub\u003e(1,65)\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e-0.693, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.491).\u003c/p\u003e\u003cp\u003eNaturalistic fear induction paradigm.\u003c/p\u003e\u003cp\u003eThe task began 45 minutes after the treatment intervention (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). During the naturalistic fear induction paradigm, participants were instructed to watch a series of video clips attentively and rate their level of fear experience after each clip. The clips lasted 25 seconds and were followed by a 1–3 second jittered fixation cross to separate the stimuli from the rating period. During the 5-second period following each stimulus, participants were asked to report their level of subjective fear on a 9-point Likert scale, with 1 indicating no fear and 9 indicating very strong fear. This was followed by a jittered inter-trial interval of 9–11 seconds, during which a fixation cross was presented (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). A total of 32 short video clips were presented over 2 runs, with each run consisting of 16 randomly presented clips, half of which were neutral and half of which were fear-inducing clips.\u003c/p\u003e\u003cp\u003eGiven ongoing discussions about the social-specific effects of OT \u003csup\u003e53, 54\u003c/sup\u003e, we carefully pre-selected a balanced set of stimuli that included social as well as non-social fearful or neutral stimuli, respectively. This led to a set of four stimulus categories (fear social clips-FS, fear non-social clips-FNS, neutral social clips-NS, neutral non-social clips-NNS, see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). For detailed characterization of the video clips, see Supplementary Methods. The video clips used for the naturalistic fear induction paradigm were selected from a larger database based on stimuli evaluation ratings in an independent sample (n = 20; 10 females; age = 22.65 ± 2.01). Key exclusion criteria for the video clips were reported in supplementary methods. Based on the results of the behavioral ratings (see \u003cb\u003eFig. S2\u003c/b\u003e), 8 complimentary video clips were selected for each of the four categories. The task was programmed in Python 3.7 using the PsychoPy package (version 2022.2.4).\u003c/p\u003e\u003cp\u003eEffects of OT on subjective fear experience.\u003c/p\u003e\u003cp\u003eTo determine the effects of OT on subjective fear in naturalistic contexts and whether they vary as a function of social context, we computed a repeated measures ANOVA with the between-subject factor treatment (OT vs PLC) and the within-subject factors emotion (fear vs neutral) and social (social vs non-social) and the dependent variable fear ratings during fMRI. To initially ensure that the selected video clips were effective in inducing the intended emotions, repeated measures ANOVA (sex was used as the independent variable, while emotion and social were used as repeated variables) were conducted on five rating metrics (see supplementary methods). Analyses were conducted using GraphPad Prism 9.0 (GraphPad Software, Inc., La Jolla, CA), and corresponding effect sizes were computed using JASP 0.18.3.0 (JASP Team, 2019; jasp-stats.org). All ANOVAs and t-tests used false discovery rate (FDR) \u003csup\u003e55\u003c/sup\u003e recommended by Prism for multiple comparison correction.\u003c/p\u003e\u003cp\u003eMRI data acquisition and preprocessing.\u003c/p\u003e\u003cp\u003eMRI data were collected on a 3.0-T GE Discovery MR750 system (General Electric Medical System, Milwaukee, WI, USA) and preprocessed using FMRIPREP 21.0.0\u003csup\u003e56\u003c/sup\u003e (RRID: SCR_016216), a Nipype 1.6.1 based tool that integrates preprocessing routines from different software packages and SPM 12 (Statistical Parametric Mapping; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.fil.ion.ucl.ac.uk/spm/\u003c/span\u003e\u003cspan address=\"http://www.fil.ion.ucl.ac.uk/spm/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; Wellcome Trust Centre for Neuroimaging, detailed in supplementary methods).\u003c/p\u003e\u003cp\u003eNext, a voxel-wise general linear model (GLM) was conducted for each participant. Specifically, a first-level model was designed that included separate regressors for the four conditions and the rating period. In line with a previous study \u003csup\u003e28\u003c/sup\u003e, we removed variance associated with the mean, linear and quadratic trends, the average signal within anatomically-derived CSF mask, the effects of motion estimated during the head-motion correction using an expanded set of 24 motion parameters (six realignment parameters, their squares, their derivatives, and their squared derivatives) and motion spikes (FMRIPREP default: FD\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026gt;\\)\u003c/span\u003e\u003c/span\u003e0.5mm or standardized DVARS\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026gt;\\)\u003c/span\u003e\u003c/span\u003e1.5)\u003csup\u003e57\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eEffects of OT on fear-related brain activity.\u003c/p\u003e\u003cp\u003eTo examine the effects of OT on fear-related neural activity in naturalistic contexts, a GLM-based model was established in SPM 12. The model incorporated five regressors: FS, FNS, NS, NNS, and the rating period. We included the 24 head motion parameters as covariates of no interest. Key first-level contrasts of interest were contrasts that modeled fear in social and non-social contexts separately (i.e., [FS\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003eNS] or [FNS\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003eNNS]) as well as their interaction (i.e., [FS\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003eNS] \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003e[FNS\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003eNNS]). In line with the behavioral analyses, the effects of OT were determined using an ANOVA with the factors emotion and social context, implemented in a partitioned error ANOVA approach that subjected the first level interaction contrast to a voxel-wise two-sample t-test with the factor treatment group on the second level. Based on our hypothesis and previous studies reporting that fear is strongly associated with amygdala, cingulate cortex (particularly middle cingulate cortex, MCC), insula, and ventromedial prefrontal cortex (vmPFC) and that oxytocin mediates its anxiolytic effects via these regions \u003csup\u003e14, 22, 27, 58–60\u003c/sup\u003e, our analyses focused on atlas-derived bilateral masks for the amygdala, MCC, insula and vmPFC using separate small volume correction (SVC) and family-wise error (FWE) correction \u003csup\u003e61\u003c/sup\u003e applied at peak level.\u003c/p\u003e\u003cp\u003eTo further disentangle complex interaction effects involving treatment, parameter estimates were extracted using 8mm radius spheres centered at the peak interaction coordinates using Marsbar (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://marsbar.sourceforge.net/\u003c/span\u003e\u003cspan address=\"http://marsbar.sourceforge.net/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The extracted Blood Oxygenation Level Dependent (BOLD) signals were then subjected to appropriate post-hoc tests comparing group differences in each of the separate conditions.\u003c/p\u003e\u003cp\u003eAdditionally, to determine associations between the behavioral (subjective fear) and neural effects of OT (both activation and functional connectivity between specific brain regions) we conducted correlation analysis using JASP.\u003c/p\u003e\u003cp\u003eEffects of OT on functional communication of the regions identified.\u003c/p\u003e\u003cp\u003eWe further examined whether the regions showing altered regional activation following OT also changed their network-level communication via a general Psychophysiological interaction (gPPI) analysis. gPPI examines functional connectivity between brain regions that is contingent on a psychological context. We used the Generalized PPI toolbox \u003csup\u003e62\u003c/sup\u003e as implemented in SPM 12, to conduct gPPI. This method includes additional task regressors to reduce the likelihood that the functional connectivity estimates are driven simply by co-activation and has been widely used in similar studies \u003csup\u003e63, 64\u003c/sup\u003e. Based on our results, OT enhanced activation in the left middle cingulate cortex (lMCC) under the three-way interaction (treatment\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003eemotion\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003esocial), we therefore computed the functional communication of this region (using an 8mm radius which centered in peak Montreal Neurological Institute (MNI), x, y, z = -7, -3, 30) with other voxels in the whole brain under the two-way interaction of emotion and social, and a two-sample t-test was conducted to confirm the treatment effect of OT. Based on previous studies reporting effects of OT on the functional communication of the amygdala \u003csup\u003e48, 49\u003c/sup\u003e, separate atlas-derived bilateral masks for the amygdala, MCC, insula and vmPFC were used for SVC analyses with FWE correction \u003csup\u003e61\u003c/sup\u003e applied at peak level.\u003c/p\u003e\u003cp\u003eMarsbar was used to extract information communications between other regions and the seed region to further disentangle complex interaction effects involving treatment. The extracted functional connectivity signals were then subjected to compare the treatment effect under four conditions by using two-sample t-tests separately.\u003c/p\u003e\u003cp\u003eEffects of OT on large-scale brain network functional connectivity.\u003c/p\u003e\u003cp\u003eGiven that several studies reported the effects of OT on large-scale network organization of the brain \u003csup\u003e65, 66\u003c/sup\u003e, we examined OT effects on the whole-brain network level. To this end, time-series of each region of interest (ROI) was extracted according to the template including 463 ROIs across the whole brain (see supplementary methods), resulting in BOLD time series of the size of \u003cem\u003er\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e\u003cem\u003et\u003c/em\u003e (\u003cem\u003er\u003c/em\u003e was the number of ROIs and \u003cem\u003et\u003c/em\u003e was the BOLD time series length) for each subject per run. A matrix of size \u003cem\u003er\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e\u003cem\u003er\u003c/em\u003e was obtained by calculating Pearson's correlation between the average BOLD time series of each pair of ROIs. Additionally, Fisher's z-transform was applied to improve the normality of the correlation coefficients. The brain regions can be divided into nine networks based on their functional divisions, and the neural activities of each network's regions were averaged to calculate network functional connectivity.\u003c/p\u003e\u003cp\u003eDuring each run, four types of video clips were presented in a pseudo-randomized order. The onset time of each video clip was shifted by 3 TRs to account for hemodynamic lag. To extract neural activity time series for a specific condition, we used the time points and durations specified for the appearance of different trials of the same type. This resulted in four \u003cem\u003er\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e\u003cem\u003ed\u003c/em\u003e matrices (where \u003cem\u003er\u003c/em\u003e is the number of ROIs and \u003cem\u003ed\u003c/em\u003e is the BOLD time series length of each condition). Additionally, we obtained the \u003cem\u003er\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e\u003cem\u003er\u003c/em\u003e matrix between ROIs and the \u003cem\u003en\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e\u003cem\u003en\u003c/em\u003e matrix (where \u003cem\u003en\u003c/em\u003e is the number of networks) between brain networks for different conditions.\u003c/p\u003e\u003cp\u003eAfter performing Fisher-Z transformation on the network functional connectivity matrices for different conditions, matrices of Z-values corresponding to specific conditions (Z\u003csub\u003eFS\u003c/sub\u003e\\Z\u003csub\u003eFNS\u003c/sub\u003e\\Z\u003csub\u003eNS\u003c/sub\u003e\\Z\u003csub\u003eFNS\u003c/sub\u003e) are obtained. It is important to note that r values are not additive or subtractive, but Z scores are summative. Matrix of Z-values corresponding to particular contrasts (e.g. Z\u003csub\u003eFS-NS\u003c/sub\u003e) can be computed by subtract the matrices of Z-values corresponding to different conditions (e.g. Z\u003csub\u003eFS\u003c/sub\u003e-Z\u003csub\u003eNS\u003c/sub\u003e)\u003csup\u003e67, 68\u003c/sup\u003e. Therefore, each participant in both groups would have their own subtracted Z-values matrix under specific contrasts (Z\u003csub\u003eFS-NS\u003c/sub\u003e\\Z\u003csub\u003eFNS-NNS\u003c/sub\u003e). We then conducted two-sample t-tests on each pair of network-level functional connectivity to determine the treatment effect.\u003c/p\u003e\u003cp\u003eEffects of OT on whole-brain functional connectivity.\u003c/p\u003e\u003cp\u003eTo further investigate the impact of OT on a finer spatial scale, we analyzed whole-brain functional connectivity using paired t-tests for key contrasts (FS\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003eNNS and FNS\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003eNNS) separately for the two groups. We applied FDR correction (\u003cem\u003ep\u003c/em\u003e\u003csub\u003eFDR−corrected\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e0.05) to identify the most relevant functional connections for each contrast. A Mantel test \u003csup\u003e69, 70\u003c/sup\u003e was performed on the FDR-corrected functional connectivity matrices of the two groups, under specific contrasts, to assess their similarity. Furthermore, to investigate treatment-specific effects on functional connectivity strength at the whole-brain level, we transformed the upper triangular data of the \u003cem\u003et\u003c/em\u003e-value matrices of the two groups under specific contrast into two (\u003cem\u003er\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e(\u003cem\u003er\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003e1)) / 2 by 1 feature vectors, and performed Welch’s t-test between them.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eDemographics and potential confounders.\u003c/p\u003e \u003cp\u003eThe OT (n\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e33) and PLC (n\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e34) groups were comparable with respect to socio-demographics, mood and mental health indices arguing against nonspecific treatment effects (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, all \u003cem\u003eps\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026gt;\\)\u003c/span\u003e\u003c/span\u003e0.10).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographics and potential confounders in the two treatment groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOT(M\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003eSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePLC(M\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003eSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.30\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.76\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBDI II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.70\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e3.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.38\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e5.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.36\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e2.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.53\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLSAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.36\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e20.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.15\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e19.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.79\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e6.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.15\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e9.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.82\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e7.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.97\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e9.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eERQ-Reappraisal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.00\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e3.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.74\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e4.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eERQ-Suppression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.85\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.82\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e4.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePANAS-P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.85\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e6.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.47\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e7.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-6.12\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e6.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.06\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e5.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreatment peak\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.73\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e5.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.41\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e6.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.85\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e5.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.62\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e5.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAfter experiment\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.88\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e6.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.79\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e7.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-8.97\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e7.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-5.68\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e7.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePANAS-N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.09\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e5.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.09\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e4.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.24\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e4.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.06\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e4.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreatment peak\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.85\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.03\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.33\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e2.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.65\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAfter experiment\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.18\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e4.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.68\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e3.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.91\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e6.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.41\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003e5.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues presented here as mean\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003estandard deviation (M\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm\\)\u003c/span\u003e\u003c/span\u003eSD). \u003cem\u003eBDI II\u003c/em\u003e Beck Depression Inventory II, \u003cem\u003eBAI\u003c/em\u003e Beck Anxiety Index, \u003cem\u003eLSAS\u003c/em\u003e Liebowitz Social Anxiety Scale, \u003cem\u003eSTAI\u003c/em\u003e Spielberger State-Trait Anxiety Inventory, \u003cem\u003eERQ\u003c/em\u003e Emotion Regulation Questionnaire, \u003cem\u003ePANAS\u003c/em\u003e Positive and Negative Affect Schedule, \u003cem\u003eOT\u003c/em\u003e oxytocin, \u003cem\u003ePLC\u003c/em\u003e placebo.\u003c/p\u003e \u003cp\u003eOT reduced subjective fear experience in naturalistic contexts, particularly in social contexts.\u003c/p\u003e \u003cp\u003eThe ANOVA revealed a significant main effect of emotion (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e(1,65)\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e1434, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e0.0001,\u003cem\u003eη\u003c/em\u003e\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.957, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea) such that participants rated subjective fear considerably higher during fear trials (FS and FNS) than neutral ones, and a significant main effect of social (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e(1,65)\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e76.81, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e0.0001,\u003cem\u003eη\u003c/em\u003e\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.542, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea) reflecting lower fear during social trials (FS and NS) compared with non-social trials. With respect to the effects of OT we found a significant interaction effect between treatment and emotion (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e(3,65)\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e4.064, \u003cem\u003ep\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.048,\u003cem\u003eη\u003c/em\u003e\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.059, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea), with post hoc tests indicating that OT significantly decreased fear experience in response to fearful stimuli in naturalistic social contexts while the effects sizes indicated a stronger fear reduction in social contexts (\u003cem\u003et\u003c/em\u003e\u003csub\u003e(1,65)\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e-3.038, \u003cem\u003ep\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.0027, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e-0.742 under FS while \u003cem\u003et\u003c/em\u003e\u003csub\u003e(1,65)\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e-1.991, \u003cem\u003ep\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.048, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e-0.487 under FNS, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Finally, the interaction between emotion and social was significant (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e(3,65)\u003c/sub\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e53.15, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e0.0001,\u003cem\u003eη\u003c/em\u003e\u003csub\u003ep\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.45, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea) reflecting that participants reported generally lower fear experience in social fear contexts. The main effect of treatment and other interactions were not significant. Together the results partly support that OT can reduce subjective fear in naturalistic situations and that the effects are more pronounced in social fear contexts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOT enhanced middle cingulate activation in the social fear contexts.\u003c/p\u003e \u003cp\u003eWe initially examined brain regions participating in fear processing under naturalistic contexts with different social features compared with neutral control conditions, a series of corresponding voxel-wise one-sample t-tests conducted in the PLC group confirmed previous studies, suggesting that visual and temporal regions were strongly engaged during exposure to dynamic fear movie clips irrespective of social features (\u003cb\u003eFig. S3\u003c/b\u003e). Examining treatment effects revealed a significant interaction between treatment\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003eemotion\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003esocial located in the left middle cingulate cortex (peak MNI, x, y, z\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e-7, -3, 30, \u003cem\u003et\u003c/em\u003e\u003csub\u003e(1,65)\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e3.67, k\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e33, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFWE\u0026minus;peak(svc)\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.019, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec), with post-hoc t-tests on extracted activity measures from this region indicating that compared to PLC, OT selectively enhanced activation in this region for FS (\u003cem\u003et\u003c/em\u003e\u003csub\u003e(1,65)\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e2.761, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.007, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.675, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed) but not other conditions (all \u003cem\u003ep\u003c/em\u003es\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026gt;\\)\u003c/span\u003e\u003c/span\u003e0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). Examining associations between lMCC activation (extracted parameter estimates) and subjective fear experience revealed a significant negative association in the OT (\u003cem\u003er\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e-0.418, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.016, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee) but not in PLC group (\u003cem\u003er\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.090, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.611, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). A Fisher r-z transformation indicated that these correlation coefficients were significantly different between the OT and PLC groups (Z\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e-2.09, two-tailed \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.037).\u003c/p\u003e \u003cp\u003eOT enhanced MCC-amygdala functional communication consistently in the social fear contexts.\u003c/p\u003e \u003cp\u003eExamining OT effects on the functional communication of the lMCC revealed a significant interaction effect between treatment\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003eemotion\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003esocial located in the right amygdala (rAmy) (peak MNI, x, y, z\u0026thinsp;=\u0026thinsp;22, -7, 13, \u003cem\u003et\u003c/em\u003e\u003csub\u003e(1,65)\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e3.81, k\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e19, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eFWE\u0026minus;peak(svc)\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.021, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea), with post-hoc t-tests indicating that OT relative to PLC selectively enhanced lMCC-rAmy coupling in social fear contexts (\u003cem\u003et\u003c/em\u003e\u003csub\u003e(1,65)\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e2.70, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.009, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.66, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb) but not other contexts (all \u003cem\u003ep\u003c/em\u003es\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026gt;\\)\u003c/span\u003e\u003c/span\u003e0.05, FDR-corrected, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb), confirming social fear-specific effects of OT on the neural level. In addition, we found that lMCC-rAmy functional coupling was significantly negatively associated with subjective fear experience in the OT (\u003cem\u003er\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e-0.392, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.024, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec) but not PLC group (\u003cem\u003er\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e-0.084, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.638, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, Fisher \u003cem\u003er\u003c/em\u003e-to-\u003cem\u003ez\u003c/em\u003e transformation revealed a trend-to-significant difference between the treatment groups, Z\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e-1.29, one-tailed \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.099).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOT enhanced FPN-DAN and DMN-DAN coupling during social fear contexts.\u003c/p\u003e \u003cp\u003eExamining the effects of OT on the large-scale network level using separate two-sample t-tests on the matrices of z-values for the two main contrasts of interest (FS\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003eNS, FNS\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003eNNS) and following mantel test revealed that OT significantly affected network functional connectivity differently under two contexts (rho\u003csub\u003emantel test\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e-0.1333, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026gt;\\)\u003c/span\u003e\u003c/span\u003e0.05). Specifically, compared to PLC (all \u003cem\u003ep\u003c/em\u003es\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026gt;\\)\u003c/span\u003e\u003c/span\u003e0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef), OT significantly enhanced the functional communication between FPN and DAN (\u003cem\u003et\u003c/em\u003e\u003csub\u003e(1,65)\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e2.75, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.0077, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.672, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee) as well as between DMN and DAN (\u003cem\u003et\u003c/em\u003e\u003csub\u003e(1,65)\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e2.02, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.048, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.493, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee) under the social fear but not the non-social fear contexts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOT modulated whole-brain functional connectivity in the social fear context.\u003c/p\u003e \u003cp\u003eWe further conducted exploratory analyses to examine whether OT changes brain-wide communications. Results showed that while under PLC only few positive connections increased activity during the FS versus NS contrast (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea), OT induced a more widespread connectivity between several brain regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Under the FNS versus NNS contrast, the PLC group exhibited wide-spread connectivity (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec), with no obvious changes following OT (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed). Further Mantel tests and Welch\u0026rsquo;s t-test were conducted on the t-value matrices (FS\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003eNS and FNS\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003eNNS) between both groups showed significant modulating effects of OT under both contrasts (rho\u003csub\u003emantel test\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.0335, \u003cem\u003et\u003c/em\u003e\u003csub\u003e(1,65)\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e9.05, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e0.0001 under FS\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003eNS, rho\u003csub\u003emantel test\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.208, \u003cem\u003et\u003c/em\u003e\u003csub\u003e(1,65)\u003c/sub\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e-2.51, \u003cem\u003ep\u003c/em\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e0.012 under FNS\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(-\\)\u003c/span\u003e\u003c/span\u003eNNS), particularly under the fear social contexts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study determined the acute behavioral and neural effects of a single intranasal OT administration on subjective fear experience in a naturalistic context that resembles dynamic fear processing in social and non-social contexts in a close-to-real life setting. On the behavioral level, OT decreased the experience of subjective fear across social and non-social contexts, supporting a fear-regulating potential of OT under dynamic and ecologically valid conditions. Mirroring the stronger effect sizes of the OT-induced fear reduction in social contexts, neural effects of OT were primarily observed in social fear contexts, such that OT enhanced regional activation in the left MCC and its communication with the contralateral amygdala specifically during fear in social contexts with both neural indices exhibiting a negative association with subjective fear following OT but not PLC. Exploratory network-level analyses further revealed that OT significantly enhanced the functional connectivity between the DAN and the FPN/DMN, respectively, and brain-wide communication selectively in social fear contexts. Together, the findings indicate that a single dose of intranasal OT has the potential to decrease fear in close-to-real life settings by enhancing lMCC activation and its communication with the amygdala while concomitantly affecting network-level communication of the DAN with brain networks involved in regulatory control (FPN \u003csup\u003e71, 72\u003c/sup\u003e) and social processing (DMN \u003csup\u003e73, 74\u003c/sup\u003e) as well as brain-wide functional communication.\u003c/p\u003e \u003cp\u003eSeveral previous studies in rodents and humans suggested a fear- and anxiety-reducing potential of OT, however, results remained inconsistent. Studies have described a promising fear- and anxiety-reducing neurofunctional profile of OT across species, yet the neural effects on amygdala-related circuits were often observed in the absence of changes in subjective fear experience or under experimental laboratory settings with limited ecological validity \u003csup\u003e15, 17\u0026ndash;20, 75\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the context of increasing attempts to enhance the ecological validity of neuroimaging research using dynamic movie stimuli \u003csup\u003e27, 28, 76\u003c/sup\u003e, we here combined naturalistic fMRI employing fear-inducing movie clips with a pre-registered randomized double-blind placebo-controlled OT-administration trial. Across pilot experiments and treatment studies, the procedure induced a highly immersive and comparably strong experience of fear under close-to-real life conditions. Importantly, OT decreased subjective fear experience in the more naturalistic context with small or moderate effect sizes in the non-social or social context, respectively. Although the pronounced fear-reducing effects of OT in the social context may partly reflect the generally more moderate fear experience reported by our participants in this context, pronounced effects of OT in social contexts have been conceptualized in a number of overarching theories and have been reported in several previous studies \u003csup\u003e21, 22, 77\u003c/sup\u003e including studies reporting decreased subjective anxiety \u003csup\u003e78\u003c/sup\u003e. The latter hypothesis on the social-specific effects of OT is also mirrored in the brain functional findings, such that the neurofunctional effects were selectively observed during fear experiences in social contexts.\u003c/p\u003e \u003cp\u003eWith respect to regional activation, OT increased the activation of the left middle cingulate cortex (lMCC). The MCC represents a highly integrative hub that has been involved in both, fear evaluation \u003csup\u003e5, 60, 79, 80\u003c/sup\u003e as well as the cognitive control of negative affective states including fear \u003csup\u003e81, 82\u003c/sup\u003e. Concomitantly, OT enhanced functional connectivity from the lMCC to the contralateral amygdala (rAmy), a pathway that has been previously involved in implementing top-down inhibitory control over excessive fear-related amygdala engagement \u003csup\u003e60, 80, 83\u003c/sup\u003e. Effects of OT on this circuitry have been previously reported in the context of reduced subjective anxiety in individuals with PTSD \u003csup\u003e84\u003c/sup\u003e and in response to static fearful faces in patients with generalized social anxiety disorders \u003csup\u003e25\u003c/sup\u003e. Exploring brain-behavior associations further revealed that OT established a negative association between higher activity and connectivity in this circuit and subjective fear, underscoring the behavioral relevance of the OT-induced neurofunctional changes. Together, our findings suggest that OT exerts its fear-regulating effects under naturalistic contexts via enhancing MCC engagement and control over the amygdala.\u003c/p\u003e \u003cp\u003eOn the large-scale network level, OT significantly enhanced the functional connectivity of the DAN with the FPN as well as the DMN in the social fear contexts. The DAN is centered around the intraparietal sulcus and the frontal eye fields and plays a pivotal role in top-down or goal-directed control of attention \u003csup\u003e85\u0026ndash;87\u003c/sup\u003e, while the FPN supports goal-directed actions and cognitive control \u003csup\u003e71, 88, 89\u003c/sup\u003e and the DMN supports self-referential \u003csup\u003e90, 91\u003c/sup\u003e and social processing \u003csup\u003e73, 74\u003c/sup\u003e, with more recent findings additionally suggesting a role in emotional experience in dynamic naturalistic contexts \u003csup\u003e92, 93\u003c/sup\u003e. While studies have demonstrated the effects of OT on the interaction between these large-scale networks during the task-free state \u003csup\u003e65, 94\u003c/sup\u003e, the present findings underscore the behavioral relevance of these effects of OT in terms of regulating emotional processes in social contexts. Together with previous studies suggesting an association between dysfunctional interaction between these large-scale networks and emotional dysregulations in anxiety and fear-related disorders \u003csup\u003e32, 91\u003c/sup\u003e, the present findings support a potential therapeutic potential of OT for these disorders \u003csup\u003e32, 95, 96\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eNetwork-level analyses that explored the effects of OT on the fine-grained level of brain-wide connectivity patterns suggested that OT may broadly facilitate brain-wide exchange of information within and across networks particularly between the FPN and DMN in social fear contexts. The results align with recent findings suggesting that emotional processes such as fear and anxiety are processed in distributed networks and their interactions \u003csup\u003e27, 34, 97\u003c/sup\u003e as well as the distributed network-level properties and effects of the OT signaling system \u003csup\u003e41, 98, 99\u003c/sup\u003e. These findings underscore that OT may exert its effects on human emotion processing under complex naturalistic conditions via regulating extensive network-level interactions. Together with increasing the reconceptualization and increasing evidence indicating that mental disorders are not related to dysfunctions of a single brain region or pathway but rather dysregulated brain-wide communication \u003csup\u003e32, 91, 100\u003c/sup\u003e, these findings may further underscore the therapeutic potential of the OT signaling system.\u003c/p\u003e \u003cp\u003eFindings have to be considered in the context of limitations of the present design, including (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) to avoid variations in the effects of OT related to sex \u003csup\u003e48, 49\u003c/sup\u003e, we only focused on male participants and future studies need to test generalization to females, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) the study employed a proof-of-concept design in healthy subjects and future studies need to validate the effects of OT in populations with pathological fear and anxiety, (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) despite extensive pre-study testing the videos of the social and non-social category differed in terms of the level of fear induced which partly limits conclusions regarding social-specific effects of OT, (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) the videos included homogenous brief episodes of fear and future studies need to examine effects of OT on fear during longer time scales and longer episodes with dynamic fear \u003csup\u003e27, 28\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTaken together, this study demonstrated that OT can reduce subjective fear experience under naturalistic conditions via enhancing lMCC engagement and its regulatory control over the amygdala as well as enhancing communication between large-scale networks and brain-wide communication. These findings consistently indicate a high translational therapeutic potential of OT to regulate fear in dynamic and close-to-real life environments. Effects were pronounced or restricted to the social contexts, supporting the role that OT may play in social contexts, and rendering OT as a promising treatment for social context-specific fear experiences, e.g. in social anxiety disorders. Findings indicate that OT may be used as a novel therapeutic strategy to regulate excessive subjective fear symptoms in mental disorders \u003csup\u003e7, 17, 24\u003c/sup\u003e or may help to prevent the development of these disorders during early stages or promote long-term recovery \u003csup\u003e94\u003c/sup\u003e via improving the quality of life, and reduce the social and economic burden related to fear-related disorders.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003ch2\u003eAuthor contributions\u003c/h2\u003e \u003cp\u003eKF and BB\u003csup\u003e1\u003c/sup\u003e designed the study. KF, ZZ and DL conducted the experiment and collected the data. KF, SX, WZ, ZL performed the data analysis with the help of TX, YZ, XZ, CL, JW, LW, JH and BB\u003csup\u003e2\u003c/sup\u003e. KF and BB\u003csup\u003e1\u003c/sup\u003e wrote the manuscript. SX, FZ, KK, TX, YZ, ZL and WZ critically revised the manuscript draft.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e \u003cp\u003eThis work was supported by the China MOST2030 Brain Project (Grant No. 2022ZD0208500), the National Natural Science Foundation of China (Grants No. 32250610208, 82271583-BB), the National Key Research and Development Program of China (Grant No. 2018YFA0701400-BB), the Natural Science Foundation of Sichuan Province (Grant number 2022NSFSC1375-WZ) and a start-up grant from The University of Hong Kong. Disclaimer: Any opinions, findings, conclusions or recommendations expressed in this publication do not reflect the views of the Government of the Hong Kong Special Administrative Region or the Innovation and Technology Commission.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOsakada T, Yan R, Jiang Y, Wei D, Tabuchi R, Dai B\u003cem\u003e et al.\u003c/em\u003e A dedicated hypothalamic oxytocin circuit controls aversive social learning. \u003cem\u003eNature\u003c/em\u003e 2024.\u003c/li\u003e\n\u003cli\u003eAkinrinade I, Kareklas K, Teles MC, Reis TK, Gliksberg M, Petri G\u003cem\u003e et al.\u003c/em\u003e Evolutionarily conserved role of oxytocin in social fear contagion in zebrafish. \u003cem\u003eScience\u003c/em\u003e 2023; \u003cstrong\u003e379\u003c/strong\u003e(6638)\u003cstrong\u003e: \u003c/strong\u003e1232-1237.\u003c/li\u003e\n\u003cli\u003eFaul L, Stjepanović D, Stivers JM, Stewart GW, Graner JL, Morey RA\u003cem\u003e et al.\u003c/em\u003e Proximal threats promote enhanced acquisition and persistence of reactive fear-learning circuits. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 2020; \u003cstrong\u003e117\u003c/strong\u003e(28)\u003cstrong\u003e: \u003c/strong\u003e16678-16689.\u003c/li\u003e\n\u003cli\u003eBecker B, Zhou F. Neural Processing of Fear \u0026ndash; From Animal Models to Human Research. 2020.\u003c/li\u003e\n\u003cli\u003eZhou F, Zhao W, Qi Z, Geng Y, Yao S, Kendrick KM\u003cem\u003e et al.\u003c/em\u003e A distributed fMRI-based signature for the subjective experience of fear. \u003cem\u003eNature Communications\u003c/em\u003e 2021; \u003cstrong\u003e12\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e6643.\u003c/li\u003e\n\u003cli\u003eBramson B, Meijer S, van Nuland A, Toni I, Roelofs K. Anxious individuals shift emotion control from lateral frontal pole to dorsolateral prefrontal cortex. \u003cem\u003eNature Communications\u003c/em\u003e 2023; \u003cstrong\u003e14\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e4880.\u003c/li\u003e\n\u003cli\u003eKreuder A-K, Scheele D, Schultz J, Hennig J, Marsh N, Dellert T\u003cem\u003e et al.\u003c/em\u003e Common and dissociable effects of oxytocin and lorazepam on the neurocircuitry of fear. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 2020; \u003cstrong\u003e117\u003c/strong\u003e(21)\u003cstrong\u003e: \u003c/strong\u003e11781-11787.\u003c/li\u003e\n\u003cli\u003eSzuhany KL, Simon NM. Anxiety Disorders: A Review. \u003cem\u003eJAMA\u003c/em\u003e 2022; \u003cstrong\u003e328\u003c/strong\u003e(24)\u003cstrong\u003e: \u003c/strong\u003e2431-2445.\u003c/li\u003e\n\u003cli\u003eSlee A, Nazareth I, Bondaronek P, Liu Y, Cheng Z, Freemantle N. Pharmacological treatments for generalised anxiety disorder: a systematic review and network meta-analysis. \u003cem\u003eThe Lancet\u003c/em\u003e 2019; \u003cstrong\u003e393\u003c/strong\u003e(10173)\u003cstrong\u003e: \u003c/strong\u003e768-777.\u003c/li\u003e\n\u003cli\u003eTaschereau-Dumouchel V, Cortese A, Chiba T, Knotts JD, Kawato M, Lau H. Towards an unconscious neural reinforcement intervention for common fears. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 2018; \u003cstrong\u003e115\u003c/strong\u003e(13)\u003cstrong\u003e: \u003c/strong\u003e3470-3475.\u003c/li\u003e\n\u003cli\u003eZhao Z, Yao S, Li K, Sindermann C, Zhou F, Zhao W\u003cem\u003e et al.\u003c/em\u003e Real-Time Functional Connectivity-Informed Neurofeedback of Amygdala-Frontal Pathways Reduces Anxiety. \u003cem\u003ePsychotherapy and Psychosomatics\u003c/em\u003e 2019; \u003cstrong\u003e88\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e5-15.\u003c/li\u003e\n\u003cli\u003ePaul JM, Ra\u0026uuml;l A, Rene H, Tiffany RL, Moriel Z, Joanna D. Limbic Neuropeptidergic Modulators of Emotion and Their Therapeutic Potential for Anxiety and Post-Traumatic Stress Disorder. \u003cem\u003eThe Journal of Neuroscience\u003c/em\u003e 2021; \u003cstrong\u003e41\u003c/strong\u003e(5)\u003cstrong\u003e: \u003c/strong\u003e901.\u003c/li\u003e\n\u003cli\u003eZhang R, Zhao W, Qi Z, Xu T, Zhou F, Becker B. Angiotensin II Regulates the Neural Expression of Subjective Fear in Humans: A Precision Pharmaco-Neuroimaging Approach. \u003cem\u003eBiological Psychiatry: Cognitive Neuroscience and Neuroimaging\u003c/em\u003e 2023; \u003cstrong\u003e8\u003c/strong\u003e(3)\u003cstrong\u003e: \u003c/strong\u003e262-270.\u003c/li\u003e\n\u003cli\u003eZhou F, Geng Y, Xin F, Li J, Feng P, Liu C\u003cem\u003e et al.\u003c/em\u003e Human Extinction Learning Is Accelerated by an Angiotensin Antagonist via Ventromedial Prefrontal Cortex and Its Connections With Basolateral Amygdala. \u003cem\u003eBiol Psychiat\u003c/em\u003e 2019; \u003cstrong\u003e86\u003c/strong\u003e(12)\u003cstrong\u003e: \u003c/strong\u003e910-920.\u003c/li\u003e\n\u003cli\u003eKnobloch HS, Charlet A, Hoffmann Lena C, Eliava M, Khrulev S, Cetin Ali H\u003cem\u003e et al.\u003c/em\u003e Evoked Axonal Oxytocin Release in the Central Amygdala Attenuates Fear Response. \u003cem\u003eNeuron\u003c/em\u003e 2012; \u003cstrong\u003e73\u003c/strong\u003e(3)\u003cstrong\u003e: \u003c/strong\u003e553-566.\u003c/li\u003e\n\u003cli\u003eNeumann ID, Slattery DA. Oxytocin in General Anxiety and Social Fear: A Translational Approach. \u003cem\u003eBiol Psychiat\u003c/em\u003e 2016; \u003cstrong\u003e79\u003c/strong\u003e(3)\u003cstrong\u003e: \u003c/strong\u003e213-221.\u003c/li\u003e\n\u003cli\u003eEckstein M, Becker B, Scheele D, Scholz C, Preckel K, Schlaepfer TE\u003cem\u003e et al.\u003c/em\u003e Oxytocin Facilitates the Extinction of Conditioned Fear in Humans. \u003cem\u003eBiol Psychiat\u003c/em\u003e 2015; \u003cstrong\u003e78\u003c/strong\u003e(3)\u003cstrong\u003e: \u003c/strong\u003e194-202.\u003c/li\u003e\n\u003cli\u003eKou J, Zhang Y, Zhou F, Gao Z, Yao S, Zhao W\u003cem\u003e et al.\u003c/em\u003e Anxiolytic Effects of Chronic Intranasal Oxytocin on Neural Responses to Threat Are Dose-Frequency Dependent. \u003cem\u003ePsychotherapy and Psychosomatics\u003c/em\u003e 2022; \u003cstrong\u003e91\u003c/strong\u003e(4)\u003cstrong\u003e: \u003c/strong\u003e253-264.\u003c/li\u003e\n\u003cli\u003eXin F, Zhou X, Dong D, Zhao Z, Yang X, Wang Q\u003cem\u003e et al.\u003c/em\u003e Oxytocin Differentially Modulates Amygdala Responses during Top-Down and Bottom-Up Aversive Anticipation. \u003cem\u003eAdv Sci\u003c/em\u003e 2020; \u003cstrong\u003e7\u003c/strong\u003e(16)\u003cstrong\u003e: \u003c/strong\u003e2001077.\u003c/li\u003e\n\u003cli\u003eLiu C, Lan C, Li K, Zhou F, Yao S, Xu L\u003cem\u003e et al.\u003c/em\u003e Oxytocinergic Modulation of Threat-Specific Amygdala Sensitization in Humans Is Critically Mediated by Serotonergic Mechanisms. \u003cem\u003eBiological Psychiatry: Cognitive Neuroscience and Neuroimaging\u003c/em\u003e 2021; \u003cstrong\u003e6\u003c/strong\u003e(11)\u003cstrong\u003e: \u003c/strong\u003e1081-1089.\u003c/li\u003e\n\u003cli\u003eShamay-Tsoory SG, Abu-Akel A. The Social Salience Hypothesis of Oxytocin. \u003cem\u003eBiol Psychiat\u003c/em\u003e 2016; \u003cstrong\u003e79\u003c/strong\u003e(3)\u003cstrong\u003e: \u003c/strong\u003e194-202.\u003c/li\u003e\n\u003cli\u003eYao S, Zhao W, Geng Y, Chen Y, Zhao Z, Ma X\u003cem\u003e et al.\u003c/em\u003e Oxytocin Facilitates Approach Behavior to Positive Social Stimuli via Decreasing Anterior Insula Activity. \u003cem\u003eInt J Neuropsychoph\u003c/em\u003e 2018; \u003cstrong\u003e21\u003c/strong\u003e(10)\u003cstrong\u003e: \u003c/strong\u003e918-925.\u003c/li\u003e\n\u003cli\u003eOliver JR, Alexandra CP, Brian C, Christian G. The translational neural circuitry of anxiety. \u003cem\u003eJournal of Neurology, Neurosurgery \u0026amp;amp;amp; Psychiatry\u003c/em\u003e 2019; \u003cstrong\u003e90\u003c/strong\u003e(12)\u003cstrong\u003e: \u003c/strong\u003e1353.\u003c/li\u003e\n\u003cli\u003eScheele D, Lieberz J, Goertzen-Patin A, Engels C, Schneider L, Stoffel-Wagner B\u003cem\u003e et al.\u003c/em\u003e Trauma Disclosure Moderates the Effects of Oxytocin on Intrusions and Neural Responses to Fear. \u003cem\u003ePsychotherapy and Psychosomatics\u003c/em\u003e 2019; \u003cstrong\u003e88\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e61-63.\u003c/li\u003e\n\u003cli\u003eGorka SM, Fitzgerald DA, Labuschagne I, Hosanagar A, Wood AG, Nathan PJ\u003cem\u003e et al.\u003c/em\u003e Oxytocin Modulation of Amygdala Functional Connectivity to Fearful Faces in Generalized Social Anxiety Disorder. \u003cem\u003eNeuropsychopharmacology\u003c/em\u003e 2015; \u003cstrong\u003e40\u003c/strong\u003e(2)\u003cstrong\u003e: \u003c/strong\u003e278-286.\u003c/li\u003e\n\u003cli\u003eEckstein M, Scheele D, Patin A, Preckel K, Becker B, Walter A\u003cem\u003e et al.\u003c/em\u003e Oxytocin Facilitates Pavlovian Fear Learning in Males. \u003cem\u003eNeuropsychopharmacology\u003c/em\u003e 2016; \u003cstrong\u003e41\u003c/strong\u003e(4)\u003cstrong\u003e: \u003c/strong\u003e932-939.\u003c/li\u003e\n\u003cli\u003eFeng Z, Ran Z, Shuxia Y, Debo D, Pan F, Georg K\u003cem\u003e et al.\u003c/em\u003e Capturing dynamic fear experiences in naturalistic contexts: An ecologically valid fMRI signature integrating brain activation and connectivity. \u003cem\u003ebioRxiv\u003c/em\u003e 2024\u003cstrong\u003e: \u003c/strong\u003e2023.2008.2018.553808.\u003c/li\u003e\n\u003cli\u003eChang LJ, Jolly E, Cheong JH, Rapuano KM, Greenstein N, Chen P-HA\u003cem\u003e et al.\u003c/em\u003e Endogenous variation in ventromedial prefrontal cortex state dynamics during naturalistic viewing reflects affective experience. \u003cem\u003eScience Advances\u003c/em\u003e; \u003cstrong\u003e7\u003c/strong\u003e(17)\u003cstrong\u003e: \u003c/strong\u003eeabf7129.\u003c/li\u003e\n\u003cli\u003eMeer JNvd, Breakspear M, Chang LJ, Sonkusare S, Cocchi L. Movie viewing elicits rich and reliable brain state dynamics. \u003cem\u003eNature Communications\u003c/em\u003e 2020; \u003cstrong\u003e11\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e5004.\u003c/li\u003e\n\u003cli\u003eAdolphs R. How should neuroscience study emotions? by distinguishing emotion states, concepts, and experiences. \u003cem\u003eSoc Cogn Affect Neur\u003c/em\u003e 2017; \u003cstrong\u003e12\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e24-31.\u003c/li\u003e\n\u003cli\u003ePessoa L. A Network Model of the Emotional Brain. \u003cem\u003eTrends in Cognitive Sciences\u003c/em\u003e 2017; \u003cstrong\u003e21\u003c/strong\u003e(5)\u003cstrong\u003e: \u003c/strong\u003e357-371.\u003c/li\u003e\n\u003cli\u003eWen Z, Seo J, Pace-Schott EF, Milad MR. Abnormal dynamic functional connectivity during fear extinction learning in PTSD and anxiety disorders. \u003cem\u003eMolecular Psychiatry\u003c/em\u003e 2022; \u003cstrong\u003e27\u003c/strong\u003e(4)\u003cstrong\u003e: \u003c/strong\u003e2216-2224.\u003c/li\u003e\n\u003cli\u003eEickhoff SB, Milham M, Vanderwal T. Towards clinical applications of movie fMRI. \u003cem\u003eNeuroImage\u003c/em\u003e 2020; \u003cstrong\u003e217: \u003c/strong\u003e116860.\u003c/li\u003e\n\u003cli\u003eSaarim\u0026auml;ki H, Glerean E, Smirnov D, Mynttinen H, J\u0026auml;\u0026auml;skel\u0026auml;inen IP, Sams M\u003cem\u003e et al.\u003c/em\u003e Classification of emotion categories based on functional connectivity patterns of the human brain. \u003cem\u003eNeuroImage\u003c/em\u003e 2022; \u003cstrong\u003e247: \u003c/strong\u003e118800.\u003c/li\u003e\n\u003cli\u003ede Vries IEJ, Wurm MF. Predictive neural representations of naturalistic dynamic input. \u003cem\u003eNature Communications\u003c/em\u003e 2023; \u003cstrong\u003e14\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e3858.\u003c/li\u003e\n\u003cli\u003eRedcay E, Moraczewski D. Social cognition in context: A naturalistic imaging approach. \u003cem\u003eNeuroImage\u003c/em\u003e 2020; \u003cstrong\u003e216: \u003c/strong\u003e116392.\u003c/li\u003e\n\u003cli\u003eLee J-J, Kim HJ, Čeko M, Park B-y, Lee SA, Park H\u003cem\u003e et al.\u003c/em\u003e A neuroimaging biomarker for sustained experimental and clinical pain. \u003cem\u003eNature Medicine\u003c/em\u003e 2021; \u003cstrong\u003e27\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e174-182.\u003c/li\u003e\n\u003cli\u003eHayoung S, Bo-yong P, Hyunjin P, Won Mok S. Cognitive and Neural State Dynamics of Narrative Comprehension. \u003cem\u003eThe Journal of Neuroscience\u003c/em\u003e 2021; \u003cstrong\u003e41\u003c/strong\u003e(43)\u003cstrong\u003e: \u003c/strong\u003e8972.\u003c/li\u003e\n\u003cli\u003eEtkin A, Maron-Katz A, Wu W, Fonzo GA, Huemer J, V\u0026eacute;rtes PE\u003cem\u003e et al.\u003c/em\u003e Using fMRI connectivity to define a treatment-resistant form of post-traumatic stress disorder. \u003cem\u003eScience Translational Medicine\u003c/em\u003e 2019; \u003cstrong\u003e11\u003c/strong\u003e(486)\u003cstrong\u003e: \u003c/strong\u003eeaal3236.\u003c/li\u003e\n\u003cli\u003eXu X, Dai J, Chen Y, Liu C, Xin F, Zhou X\u003cem\u003e et al.\u003c/em\u003e Intrinsic connectivity of the prefrontal cortex and striato-limbic system respectively differentiate major depressive from generalized anxiety disorder. \u003cem\u003eNeuropsychopharmacology\u003c/em\u003e 2021; \u003cstrong\u003e46\u003c/strong\u003e(4)\u003cstrong\u003e: \u003c/strong\u003e791-798.\u003c/li\u003e\n\u003cli\u003eJiang X, Ma X, Geng Y, Zhao Z, Zhou F, Zhao W\u003cem\u003e et al.\u003c/em\u003e Intrinsic, dynamic and effective connectivity among large-scale brain networks modulated by oxytocin. \u003cem\u003eNeuroImage\u003c/em\u003e 2021; \u003cstrong\u003e227: \u003c/strong\u003e117668.\u003c/li\u003e\n\u003cli\u003eZhao Z, Ma X, Geng Y, Zhao W, Zhou F, Wang J\u003cem\u003e et al.\u003c/em\u003e Oxytocin differentially modulates specific dorsal and ventral striatal functional connections with frontal and cerebellar regions. \u003cem\u003eNeuroImage\u003c/em\u003e 2019; \u003cstrong\u003e184: \u003c/strong\u003e781-789.\u003c/li\u003e\n\u003cli\u003eLiu N, Hadj-Bouziane F, Jones KB, Turchi JN, Averbeck BB, Ungerleider LG. Oxytocin modulates fMRI responses to facial expression in macaques. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 2015; \u003cstrong\u003e112\u003c/strong\u003e(24)\u003cstrong\u003e: \u003c/strong\u003eE3123-E3130.\u003c/li\u003e\n\u003cli\u003eWahis J, Baudon A, Althammer F, Kerspern D, Goyon S, Hagiwara D\u003cem\u003e et al.\u003c/em\u003e Astrocytes mediate the effect of oxytocin in the central amygdala on neuronal activity and affective states in rodents. \u003cem\u003eNat Neurosci\u003c/em\u003e 2021; \u003cstrong\u003e24\u003c/strong\u003e(4)\u003cstrong\u003e: \u003c/strong\u003e529-541.\u003c/li\u003e\n\u003cli\u003eBethlehem RAI, van Honk J, Auyeung B, Baron-Cohen S. Oxytocin, brain physiology, and functional connectivity: A review of intranasal oxytocin fMRI studies. \u003cem\u003ePsychoneuroendocrino\u003c/em\u003e 2013; \u003cstrong\u003e38\u003c/strong\u003e(7)\u003cstrong\u003e: \u003c/strong\u003e962-974.\u003c/li\u003e\n\u003cli\u003eFaul F, Erdfelder E, Buchner A, Lang A-G. Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. \u003cem\u003eBehavior Research Methods\u003c/em\u003e 2009; \u003cstrong\u003e41\u003c/strong\u003e(4)\u003cstrong\u003e: \u003c/strong\u003e1149-1160.\u003c/li\u003e\n\u003cli\u003eLiu Y, Li S, Lin W, Li W, Yan X, Wang X\u003cem\u003e et al.\u003c/em\u003e Oxytocin modulates social value representations in the amygdala. \u003cem\u003eNat Neurosci\u003c/em\u003e 2019; \u003cstrong\u003e22\u003c/strong\u003e(4)\u003cstrong\u003e: \u003c/strong\u003e633-641.\u003c/li\u003e\n\u003cli\u003eGao S, Becker B, Luo L, Geng Y, Zhao W, Yin Y\u003cem\u003e et al.\u003c/em\u003e Oxytocin, the peptide that bonds the sexes also divides them. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 2016; \u003cstrong\u003e113\u003c/strong\u003e(27)\u003cstrong\u003e: \u003c/strong\u003e7650-7654.\u003c/li\u003e\n\u003cli\u003eMa X, Zhao W, Luo R, Zhou F, Geng Y, Xu L\u003cem\u003e et al.\u003c/em\u003e Sex- and context-dependent effects of oxytocin on social sharing. \u003cem\u003eNeuroImage\u003c/em\u003e 2018; \u003cstrong\u003e183: \u003c/strong\u003e62-72.\u003c/li\u003e\n\u003cli\u003eWatanabe T, Abe O, Kuwabara H, Yahata N, Takano Y, Iwashiro N\u003cem\u003e et al.\u003c/em\u003e Mitigation of Sociocommunicational Deficits of Autism Through Oxytocin-Induced Recovery of Medial Prefrontal Activity A Randomized Trial. \u003cem\u003eJama Psychiat\u003c/em\u003e 2014; \u003cstrong\u003e71\u003c/strong\u003e(2)\u003cstrong\u003e: \u003c/strong\u003e166-175.\u003c/li\u003e\n\u003cli\u003eSpengler FB, Schultz J, Scheele D, Essel M, Maier W, Heinrichs M\u003cem\u003e et al.\u003c/em\u003e Kinetics and Dose Dependency of Intranasal Oxytocin Effects on Amygdala Reactivity. \u003cem\u003eBiol Psychiat\u003c/em\u003e 2017; \u003cstrong\u003e82\u003c/strong\u003e(12)\u003cstrong\u003e: \u003c/strong\u003e885-894.\u003c/li\u003e\n\u003cli\u003eLan CM, Liu CC, Li KS, Zhao ZY, Yang JX, Ma YN\u003cem\u003e et al.\u003c/em\u003e Oxytocinergic Modulation of Stress-Associated Amygdala-Hippocampus Pathways in Humans Is Mediated by Serotonergic Mechanisms. \u003cem\u003eInt J Neuropsychoph\u003c/em\u003e 2022; \u003cstrong\u003e25\u003c/strong\u003e(10)\u003cstrong\u003e: \u003c/strong\u003e807-817.\u003c/li\u003e\n\u003cli\u003eBartz JA, Zaki J, Bolger N, Ochsner KN. Social effects of oxytocin in humans: context and person matter. \u003cem\u003eTrends in Cognitive Sciences\u003c/em\u003e 2011; \u003cstrong\u003e15\u003c/strong\u003e(7)\u003cstrong\u003e: \u003c/strong\u003e301-309.\u003c/li\u003e\n\u003cli\u003eAndari E, Duhamel J-R, Zalla T, Herbrecht E, Leboyer M, Sirigu A. Promoting social behavior with oxytocin in high-functioning autism spectrum disorders. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 2010; \u003cstrong\u003e107\u003c/strong\u003e(9)\u003cstrong\u003e: \u003c/strong\u003e4389-4394.\u003c/li\u003e\n\u003cli\u003eBenjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. \u003cem\u003eJournal of the Royal Statistical Society: Series B (Methodological)\u003c/em\u003e 1995; \u003cstrong\u003e57\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e289-300.\u003c/li\u003e\n\u003cli\u003eEsteban O, Markiewicz CJ, Blair RW, Moodie CA, Isik AI, Erramuzpe A\u003cem\u003e et al.\u003c/em\u003e fMRIPrep: a robust preprocessing pipeline for functional MRI. \u003cem\u003eNature Methods\u003c/em\u003e 2019; \u003cstrong\u003e16\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e111-116.\u003c/li\u003e\n\u003cli\u003ePower JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. \u003cem\u003eNeuroImage\u003c/em\u003e 2012; \u003cstrong\u003e59\u003c/strong\u003e(3)\u003cstrong\u003e: \u003c/strong\u003e2142-2154.\u003c/li\u003e\n\u003cli\u003eMotzkin JC, Philippi CL, Wolf RC, Baskaya MK, Koenigs M. Ventromedial Prefrontal Cortex Is Critical for the Regulation of Amygdala Activity in Humans. \u003cem\u003eBiol Psychiat\u003c/em\u003e 2015; \u003cstrong\u003e77\u003c/strong\u003e(3)\u003cstrong\u003e: \u003c/strong\u003e276-284.\u003c/li\u003e\n\u003cli\u003eMihov Y, Kendrick KM, Becker B, Zschernack J, Reich H, Maier W\u003cem\u003e et al.\u003c/em\u003e Mirroring Fear in the Absence of a Functional Amygdala. \u003cem\u003eBiol Psychiat\u003c/em\u003e 2013; \u003cstrong\u003e73\u003c/strong\u003e(7)\u003cstrong\u003e: \u003c/strong\u003ee9-e11.\u003c/li\u003e\n\u003cli\u003eQi S, Hassabis D, Sun J, Guo F, Daw N, Mobbs D. How cognitive and reactive fear circuits optimize escape decisions in humans. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 2018; \u003cstrong\u003e115\u003c/strong\u003e(12)\u003cstrong\u003e: \u003c/strong\u003e3186-3191.\u003c/li\u003e\n\u003cli\u003eYekutieli D, Benjamini Y. Resampling-based false discovery rate controlling multiple test procedures for correlated test statistics. \u003cem\u003eJournal of Statistical Planning and Inference\u003c/em\u003e 1999; \u003cstrong\u003e82\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e171-196.\u003c/li\u003e\n\u003cli\u003eMcLaren DG, Ries ML, Xu G, Johnson SC. A generalized form of context-dependent psychophysiological interactions (gPPI): A comparison to standard approaches. \u003cem\u003eNeuroImage\u003c/em\u003e 2012; \u003cstrong\u003e61\u003c/strong\u003e(4)\u003cstrong\u003e: \u003c/strong\u003e1277-1286.\u003c/li\u003e\n\u003cli\u003eFung BJ, Qi S, Hassabis D, Daw N, Mobbs D. Slow escape decisions are swayed by trait anxiety. \u003cem\u003eNature Human Behaviour\u003c/em\u003e 2019; \u003cstrong\u003e3\u003c/strong\u003e(7)\u003cstrong\u003e: \u003c/strong\u003e702-708.\u003c/li\u003e\n\u003cli\u003eXu T, Zhou X, Kanen JW, Wang L, Li J, Chen Z\u003cem\u003e et al.\u003c/em\u003e Angiotensin blockade enhances motivational reward learning via enhancing striatal prediction error signaling and frontostriatal communication. \u003cem\u003eMolecular Psychiatry\u003c/em\u003e 2023; \u003cstrong\u003e28\u003c/strong\u003e(4)\u003cstrong\u003e: \u003c/strong\u003e1692-1702.\u003c/li\u003e\n\u003cli\u003eXin F, Zhou F, Zhou X, Ma X, Geng Y, Zhao W\u003cem\u003e et al.\u003c/em\u003e Oxytocin Modulates the Intrinsic Dynamics Between Attention-Related Large-Scale Networks. \u003cem\u003eCerebral Cortex\u003c/em\u003e 2021; \u003cstrong\u003e31\u003c/strong\u003e(3)\u003cstrong\u003e: \u003c/strong\u003e1848-1860.\u003c/li\u003e\n\u003cli\u003eBrodmann K, Gruber O, Goya-Maldonado R. Intranasal Oxytocin Selectively Modulates Large-Scale Brain Networks in Humans. \u003cem\u003eBrain Connectivity\u003c/em\u003e 2017; \u003cstrong\u003e7\u003c/strong\u003e(7)\u003cstrong\u003e: \u003c/strong\u003e454-463.\u003c/li\u003e\n\u003cli\u003eRuslan M, Irina K, Alexander K, Denis C, Maxim K. Comparison of whole-brain task-modulated functional connectivity methods for fMRI task connectomics. \u003cem\u003ebioRxiv\u003c/em\u003e 2024\u003cstrong\u003e: \u003c/strong\u003e2024.2001.2022.576622.\u003c/li\u003e\n\u003cli\u003eSchm\u0026auml;lzle R, Brook O\u0026rsquo;Donnell M, Garcia JO, Cascio CN, Bayer J, Bassett DS\u003cem\u003e et al.\u003c/em\u003e Brain connectivity dynamics during social interaction reflect social network structure. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 2017; \u003cstrong\u003e114\u003c/strong\u003e(20)\u003cstrong\u003e: \u003c/strong\u003e5153-5158.\u003c/li\u003e\n\u003cli\u003eFoster Brett L, Rangarajan V, Shirer William R, Parvizi J. Intrinsic and Task-Dependent Coupling of Neuronal Population Activity in Human Parietal Cortex. \u003cem\u003eNeuron\u003c/em\u003e 2015; \u003cstrong\u003e86\u003c/strong\u003e(2)\u003cstrong\u003e: \u003c/strong\u003e578-590.\u003c/li\u003e\n\u003cli\u003eGiordano BL, Whiting C, Kriegeskorte N, Kotz SA, Gross J, Belin P. The representational dynamics of perceived voice emotions evolve from categories to dimensions. \u003cem\u003eNature Human Behaviour\u003c/em\u003e 2021; \u003cstrong\u003e5\u003c/strong\u003e(9)\u003cstrong\u003e: \u003c/strong\u003e1203-1213.\u003c/li\u003e\n\u003cli\u003eCole MW, Reynolds JR, Power JD, Repovs G, Anticevic A, Braver TS. Multi-task connectivity reveals flexible hubs for adaptive task control. \u003cem\u003eNat Neurosci\u003c/em\u003e 2013; \u003cstrong\u003e16\u003c/strong\u003e(9)\u003cstrong\u003e: \u003c/strong\u003e1348-1355.\u003c/li\u003e\n\u003cli\u003eUddin LQ. Cognitive and behavioural flexibility: neural mechanisms and clinical considerations. \u003cem\u003eNature Reviews Neuroscience\u003c/em\u003e 2021; \u003cstrong\u003e22\u003c/strong\u003e(3)\u003cstrong\u003e: \u003c/strong\u003e167-179.\u003c/li\u003e\n\u003cli\u003eSimony E, Honey CJ, Chen J, Lositsky O, Yeshurun Y, Wiesel A\u003cem\u003e et al.\u003c/em\u003e Dynamic reconfiguration of the default mode network during narrative comprehension. \u003cem\u003eNature Communications\u003c/em\u003e 2016; \u003cstrong\u003e7\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e12141.\u003c/li\u003e\n\u003cli\u003eAxelrod V, Rees G, Bar M. The default network and the combination of cognitive processes that mediate self-generated thought. \u003cem\u003eNature Human Behaviour\u003c/em\u003e 2017; \u003cstrong\u003e1\u003c/strong\u003e(12)\u003cstrong\u003e: \u003c/strong\u003e896-910.\u003c/li\u003e\n\u003cli\u003ePeter K, Christine E, Qiang C, Daniela M, Stefanie L, Sarina S\u003cem\u003e et al.\u003c/em\u003e Oxytocin Modulates Neural Circuitry for Social Cognition and Fear in Humans. \u003cem\u003eThe Journal of Neuroscience\u003c/em\u003e 2005; \u003cstrong\u003e25\u003c/strong\u003e(49)\u003cstrong\u003e: \u003c/strong\u003e11489.\u003c/li\u003e\n\u003cli\u003eSonkusare S, Breakspear M, Guo C. Naturalistic Stimuli in Neuroscience: Critically Acclaimed. \u003cem\u003eTrends in Cognitive Sciences\u003c/em\u003e 2019; \u003cstrong\u003e23\u003c/strong\u003e(8)\u003cstrong\u003e: \u003c/strong\u003e699-714.\u003c/li\u003e\n\u003cli\u003eMenon R, Neumann ID. Detection, processing and reinforcement of social cues: regulation by the oxytocin system. \u003cem\u003eNature Reviews Neuroscience\u003c/em\u003e 2023; \u003cstrong\u003e24\u003c/strong\u003e(12)\u003cstrong\u003e: \u003c/strong\u003e761-777.\u003c/li\u003e\n\u003cli\u003eXu X, Li J, Chen Z, Kendrick KM, Becker B. Oxytocin reduces top-down control of attention by increasing bottom-up attention allocation to social but not non-social stimuli \u0026ndash; A randomized controlled trial. \u003cem\u003ePsychoneuroendocrino\u003c/em\u003e 2019; \u003cstrong\u003e108: \u003c/strong\u003e62-69.\u003c/li\u003e\n\u003cli\u003eMobbs D, Trimmer PC, Blumstein DT, Dayan P. Foraging for foundations in decision neuroscience: insights from ethology. \u003cem\u003eNature Reviews Neuroscience\u003c/em\u003e 2018; \u003cstrong\u003e19\u003c/strong\u003e(7)\u003cstrong\u003e: \u003c/strong\u003e419-427.\u003c/li\u003e\n\u003cli\u003eTashjian SM, Zbozinek TD, Mobbs D. A Decision Architecture for Safety Computations. \u003cem\u003eTrends in Cognitive Sciences\u003c/em\u003e 2021; \u003cstrong\u003e25\u003c/strong\u003e(5)\u003cstrong\u003e: \u003c/strong\u003e342-354.\u003c/li\u003e\n\u003cli\u003evan Heukelum S, Mars RB, Guthrie M, Buitelaar JK, Beckmann CF, Tiesinga PHE\u003cem\u003e et al.\u003c/em\u003e Where is Cingulate Cortex? A Cross-Species View. \u003cem\u003eTrends in Neurosciences\u003c/em\u003e 2020; \u003cstrong\u003e43\u003c/strong\u003e(5)\u003cstrong\u003e: \u003c/strong\u003e285-299.\u003c/li\u003e\n\u003cli\u003eLoh KK, Procyk E, Neveu R, Lamberton F, Hopkins WD, Petrides M\u003cem\u003e et al.\u003c/em\u003e Cognitive control of orofacial motor and vocal responses in the ventrolateral and dorsomedial human frontal cortex. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 2020; \u003cstrong\u003e117\u003c/strong\u003e(9)\u003cstrong\u003e: \u003c/strong\u003e4994-5005.\u003c/li\u003e\n\u003cli\u003eShackman AJ, Salomons TV, Slagter HA, Fox AS, Winter JJ, Davidson RJ. The integration of negative affect, pain and cognitive control in the cingulate cortex. \u003cem\u003eNature Reviews Neuroscience\u003c/em\u003e 2011; \u003cstrong\u003e12\u003c/strong\u003e(3)\u003cstrong\u003e: \u003c/strong\u003e154-167.\u003c/li\u003e\n\u003cli\u003eKoch SBJ, van Zuiden M, Nawijn L, Frijling JL, Veltman DJ, Olff M. Intranasal Oxytocin Normalizes Amygdala Functional Connectivity in Posttraumatic Stress Disorder. \u003cem\u003eNeuropsychopharmacology\u003c/em\u003e 2016; \u003cstrong\u003e41\u003c/strong\u003e(8)\u003cstrong\u003e: \u003c/strong\u003e2041-2051.\u003c/li\u003e\n\u003cli\u003ePatel GH, Yang D, Jamerson EC, Snyder LH, Corbetta M, Ferrera VP. Functional evolution of new and expanded attention networks in humans. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 2015; \u003cstrong\u003e112\u003c/strong\u003e(30)\u003cstrong\u003e: \u003c/strong\u003e9454-9459.\u003c/li\u003e\n\u003cli\u003eWomelsdorf T, Everling S. Long-Range Attention Networks: Circuit Motifs Underlying Endogenously Controlled Stimulus Selection. \u003cem\u003eTrends in Neurosciences\u003c/em\u003e 2015; \u003cstrong\u003e38\u003c/strong\u003e(11)\u003cstrong\u003e: \u003c/strong\u003e682-700.\u003c/li\u003e\n\u003cli\u003eRosenberg MD, Finn ES, Scheinost D, Constable RT, Chun MM. Characterizing Attention with Predictive Network Models. \u003cem\u003eTrends in Cognitive Sciences\u003c/em\u003e 2017; \u003cstrong\u003e21\u003c/strong\u003e(4)\u003cstrong\u003e: \u003c/strong\u003e290-302.\u003c/li\u003e\n\u003cli\u003eDixon ML, De La Vega A, Mills C, Andrews-Hanna J, Spreng RN, Cole MW\u003cem\u003e et al.\u003c/em\u003e Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 2018; \u003cstrong\u003e115\u003c/strong\u003e(7)\u003cstrong\u003e: \u003c/strong\u003eE1598-E1607.\u003c/li\u003e\n\u003cli\u003eKeller AS, Sydnor VJ, Pines A, Fair DA, Bassett DS, Satterthwaite TD. Hierarchical functional system development supports executive function. \u003cem\u003eTrends in Cognitive Sciences\u003c/em\u003e 2023; \u003cstrong\u003e27\u003c/strong\u003e(2)\u003cstrong\u003e: \u003c/strong\u003e160-174.\u003c/li\u003e\n\u003cli\u003eSatpute AB, Lindquist KA. The Default Mode Network\u0026amp;#x2019;s Role in Discrete Emotion. \u003cem\u003eTrends in Cognitive Sciences\u003c/em\u003e 2019; \u003cstrong\u003e23\u003c/strong\u003e(10)\u003cstrong\u003e: \u003c/strong\u003e851-864.\u003c/li\u003e\n\u003cli\u003eSylvester CM, Corbetta M, Raichle ME, Rodebaugh TL, Schlaggar BL, Sheline YI\u003cem\u003e et al.\u003c/em\u003e Functional network dysfunction in anxiety and anxiety disorders. \u003cem\u003eTrends in Neurosciences\u003c/em\u003e 2012; \u003cstrong\u003e35\u003c/strong\u003e(9)\u003cstrong\u003e: \u003c/strong\u003e527-535.\u003c/li\u003e\n\u003cli\u003eXu S, Zhang Z, Li L, Zhou Y, Lin D, Zhang M\u003cem\u003e et al.\u003c/em\u003e Functional connectivity profiles of the default mode and visual networks reflect temporal accumulative effects of sustained naturalistic emotional experience. \u003cem\u003eNeuroImage\u003c/em\u003e 2023; \u003cstrong\u003e269: \u003c/strong\u003e119941.\u003c/li\u003e\n\u003cli\u003eBrandman T, Malach R, Simony E. The surprising role of the default mode network in naturalistic perception. \u003cem\u003eCommunications Biology\u003c/em\u003e 2021; \u003cstrong\u003e4\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e79.\u003c/li\u003e\n\u003cli\u003eDavies C, Martins D, Dipasquale O, McCutcheon RA, De Micheli A, Ramella-Cravaro V\u003cem\u003e et al.\u003c/em\u003e Connectome dysfunction in patients at clinical high risk for psychosis and modulation by oxytocin. \u003cem\u003eMolecular Psychiatry\u003c/em\u003e 2024.\u003c/li\u003e\n\u003cli\u003eChai Y, Sheline YI, Oathes DJ, Balderston NL, Rao H, Yu M. Functional connectomics in depression: insights into therapies. \u003cem\u003eTrends in Cognitive Sciences\u003c/em\u003e 2023; \u003cstrong\u003e27\u003c/strong\u003e(9)\u003cstrong\u003e: \u003c/strong\u003e814-832.\u003c/li\u003e\n\u003cli\u003eYan C-G, Chen X, Li L, Castellanos FX, Bai T-J, Bo Q-J\u003cem\u003e et al.\u003c/em\u003e Reduced default mode network functional connectivity in patients with recurrent major depressive disorder. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 2019; \u003cstrong\u003e116\u003c/strong\u003e(18)\u003cstrong\u003e: \u003c/strong\u003e9078-9083.\u003c/li\u003e\n\u003cli\u003eLiu X, Jiao G, Zhou F, Kendrick KM, Yao D, Gong Q\u003cem\u003e et al.\u003c/em\u003e A neural signature for the subjective experience of threat anticipation under uncertainty. \u003cem\u003eNature Communications\u003c/em\u003e 2024; \u003cstrong\u003e15\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e1544.\u003c/li\u003e\n\u003cli\u003eZhang H, Chen K, Bao J, Wu H. Oxytocin enhances the triangular association among behavior, resting-state, and task-state functional connectivity. \u003cem\u003eHuman Brain Mapping\u003c/em\u003e 2023; \u003cstrong\u003e44\u003c/strong\u003e(17)\u003cstrong\u003e: \u003c/strong\u003e6074-6089.\u003c/li\u003e\n\u003cli\u003eQuintana DS, Rokicki J, van der Meer D, Aln\u0026aelig;s D, Kaufmann T, C\u0026oacute;rdova-Palomera A\u003cem\u003e et al.\u003c/em\u003e Oxytocin pathway gene networks in the human brain. \u003cem\u003eNature Communications\u003c/em\u003e 2019; \u003cstrong\u003e10\u003c/strong\u003e(1)\u003cstrong\u003e: \u003c/strong\u003e668.\u003c/li\u003e\n\u003cli\u003eDeco G, Kringelbach Morten L. Great Expectations: Using Whole-Brain Computational Connectomics for Understanding Neuropsychiatric Disorders. \u003cem\u003eNeuron\u003c/em\u003e 2014; \u003cstrong\u003e84\u003c/strong\u003e(5)\u003cstrong\u003e: \u003c/strong\u003e892-905.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4317487/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4317487/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAccumulating evidence from animal and human studies suggests a fear-regulating potential of the neuropeptide oxytocin (OT), yet the clinical translation into novel interventions for pathological fear requires a behavioral and neurofunctional characterization under close-to-real life conditions. Here, we combined a naturalistic fMRI-design inducing high and immersive fear experience in social and non-social contexts with a preregistered between-subjects randomized double-blind placebo-controlled intranasal OT trial (24 IU, n\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=\\)\u003c/span\u003e\u003c/span\u003e67 healthy men). OT reduced subjective fear in non-social and social contexts with small or moderate effect sizes, respectively. In the social fear contexts, OT enhanced left middle cingulate cortex (lMCC) activation and its functional connectivity with the contralateral amygdala, with both neural indices significantly and inversely associated with subjective fear following OT. On the network level, OT enhanced communication between the dorsal attention network (DAN) with the fronto-parietal (FPN) and the default-mode network (DMN) as well as on the more fine-grained level brain-wide communication. These findings indicate a fear-reducing potential of OT under naturalistic conditions with pronounced effects in social contexts, highlighting its potential value as a treatment option for disorders characterized by excessive fear in social situations.\u003c/p\u003e","manuscriptTitle":"Oxytocin reduces subjective fear in naturalistic social contexts via enhancing top-down middle cingulate-amygdala regulation and brain-wide connectivity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-02 10:09:44","doi":"10.21203/rs.3.rs-4317487/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8f7ce20a-bb64-4725-84d1-07b3cceb91d4","owner":[],"postedDate":"July 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":33283643,"name":"Biological sciences/Neuroscience"},{"id":33283644,"name":"Health sciences/Diseases/Psychiatric disorders"}],"tags":[],"updatedAt":"2024-08-07T10:41:49+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-02 10:09:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4317487","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4317487","identity":"rs-4317487","version":["v1"]},"buildId":"GqpaHPwrfC8PjnIFayRh5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}