Modulation of Emotion Regulation Deficits in Patients with Heroin Use Disorder by Intermittent Theta-Burst Transcranial Magnetic Stimulation

Modulation of Emotion Regulation Deficits in Patients with Heroin Use Disorder by Intermittent Theta-Burst Transcranial Magnetic Stimulation | 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 Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Modulation of Emotion Regulation Deficits in Patients with Heroin Use Disorder by Intermittent Theta-Burst Transcranial Magnetic Stimulation Xiaobin Ding, Heng Jiang, Tiejun Kang, YueTan Wang, Liang He, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6301058/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 Background Dysfunctional Emotion regulation (ER) strategies may represent a promising treatment target for heroin use disorder (HUD). The therapeutic potential of transcranial magnetic stimulation to improve ER in HUD remains to be evaluated. Methods The present randomized sham-controlled pre-registered clinical trial determined the therapeutic efficacy of intermittent theta-burst transcranial magnetic stimulation (iTBS) over the left dorsolateral prefrontal cortex (DLPFC) for 10 days in 39 HUD patients (21 real iTBS; 18 sham). The ER performance-associated electroencephalographic indices obtained by event-related potential, time-frequency, source localization, and connectivity analysis techniques served as outcomes and were assessed pre- and post-intervention, and one month later follow-up for real iTBS group. Results Compared to the sham iTBS group, the intervention group exhibited significantly more positive difference waves (DW) at 400–600ms, which was significantly related to reduced craving. The real iTBS group specifically showed changes over the intervention, with enhanced event-related synchronization in the delta/theta band during viewing neutral pictures and expressing suppression of unpleasant pictures (US); lower activation in the left supramarginal gyrus and right posterior cingulate cortex (PCC) in the above conditions, separately; and lower connectivity between left DLPFC and right PCC under US condition. During 1000–1200ms, their DW amplitudes at the follow-up period were significantly more negative than baseline. Conclusions The iTBS can improve the ER ability of HUD patients to use ER strategies, particularly expressive suppression, which are maintained following the intervention. Improved ER capability is associated with reduced craving, possibly due to enhanced frontal regulatory control. Health sciences/Diseases/Psychiatric disorders/Addiction Biological sciences/Psychology heroin use disorder emotion regulation expressive suppression cognitive reappraisal event-related synchronization LORETA Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Opioids represent the illicit drug with the highest levels of harm worldwide. According to the World Drug Report 2024, Canada reported 7,500 opioid deaths in 2022. In America, the number of opioid deaths approached 82,000, which is an overall 24-fold increase since 2010 [ 1 ]. Heroin is an opioid with a high risk for physical harm, dependence, and relapse compared to other drugs [ 2 – 4 ], and the second most prevalent illicit drug in China, accounting for an estimated 34% of those with a drug use disorder [ 5 ]. As a transdiagnostic deficit and promising treatment target across multiple mental disorders, including substance use disorders (SUDs) [ 6 , 7 ], emotion regulation (ER) impairments have been demonstrated to play a crucial role from early experimental drug use to the maintenance of addictive behaviors and relapse [ 8 – 10 ]. Successful ER critically relies on the implementation of functional ER strategies [ 11 ]. However, ineffective use of ER strategies has been demonstrated among multiple SUDs [ 10 , 12 , 13 ]. The self-medication hypothesis proposes that individuals would choose a specific drug to alleviate specific symptoms of an underlying mental health issue or emotional distress and in turn, gain a sense of emotional control [ 14 , 15 ]. Heroin can be used to control physical pain but also unpleasant emotional states such as anger or aggression [ 16 ]. Heroin (vs. saline) injection acutely reduces exaggerated left amygdala response to negative facial expressions in heroin use disorder (HUD) patients, to the level of HCs [ 17 ]. The withdrawal/drug-use cycle is moreover characterized by an increased sensitivity to negative emotions, weak cognitive control, and elevated drug incentive value [ 18 ], leading to disruptions in ER strategies and an increased propensity to utilize substance use to satisfy ER needs [ 12 ] Our previous studies [ 19 , 20 ] revealed that HUD patients have deficient neural engagement while using two of the most efficient ER strategies, i.e. cognitive reappraisal and expressive suppression [ 21 , 22 ]. Compared to healthy control (HC), they exhibited significantly lower late positive potential (LPP) and did not show event-related desynchronization (ERD) in delta and theta band power when exposed to negative stimuli, indicating that they cannot mobilize sufficient cognitive resources to use those two ER strategies. Those deficits might be associated with the impaired engagement of frontoparietal regulatory control regions [ 7 , 23 , 24 ]. Altogether, it is essential to modulate the deficits of using ER strategies in HUD patients. As a non-invasive neuromodulation technique to influence cortex excitability, transcranial magnetic stimulation (TMS) has been increasingly employed as a novel treatment option for SUDs [ 25 ]. While most studies primarily used craving or drug use frequency/amount as primary outcomes [ 26 – 29 ], however, effects on underlying domains such as ER capability remain unclear. TMS has been demonstrated as a potential strategy to modulate the emotional state in healthy participants or patients with major depressive disorder (MDD) or obsessive-compulsive disorder (OCD) [ 30 , 31 ]. Previous studies found that high-frequency (HF) rTMS over the left dorsolateral prefrontal cortex (DLPFC) could lead to a significant increase in heart rate variability which indicates diminished physiological stress response to negative social feedback [ 32 ], decreased cortisol stress response in women [ 33 ], and decrease the distress rates of OCD patients [ 34 ]. He et al. (2020) used the right ventrolateral prefrontal as a target and found that HF rTMS could reduce the negative feelings and LPP amplitudes of the participants during reappraisal to a social pain situation. Deep transcranial magnetic stimulation (dTMS) over the left DLPFC could reduce the depression of patients with bipolar disorder (BD) and recurrent MDD, this outcome could last 12 months if with maintenance sessions weekly or twice a week [ 35 ]. To our knowledge, no research has examined the modulatory effects of TMS on ER in HUD patients to date. Jansen et al., (2019) found that HF-rTMS over the left DLPFC reduced self-reported emotional arousal to positive and negative pictures in patients with alcohol use disorder (AUD), whereas increased the emotional response to neutral and positive pictures in HC participants. Notably, only in patients with AUD – but not controls – rTMS reduced right DLPFC activation during the reappraisal of affective pictures relative to sham. These findings may imply that TMS intervention outcomes in ER differ in addicted and healthy individuals. Considering the importance of ER deficits in HUD, it is worth exploring whether the TMS could improve ER deficits and lead to lasting ER improvements post-intervention. The DLPFC is a crucial brain area for both reappraisal and expressive suppression capability [ 37 , 38 ], HUD patients show abnormalities in this region [ 39 ], ER deficits in SUD have been associated with deficient left DLPFC regulation over the amygdala [ 24 ], previous studies of TMS modulation of ER have mostly targeted the left DLPFC [ 31 , 34 , 36 ], and our prior studies also found a left hemispheric dominant effect in healthy subjects [ 19 , 20 ], we chose the left DLPFC as stimulation target. Since heroin is a depressant that induces brain hypoxia and reduces neuronal activity [ 40 – 42 ] and HUD patients showed significantly lower activation of multiple brain regions than HC when using ER strategies [ 20 ], we chose an excitatory stimulation protocol, i.e. intermittent theta-burst transcranial magnetic stimulation (iTBS). This is a new type of rTMS and one of the most powerful tools that could induce long-term potentiation like traditional 10Hz stimulation but more efficient [ 43 – 45 ]. We combined event-related potential (ERP), time-frequency (TF), source localization, and connectivity analysis techniques to compare the electroencephalography (EEG) signals between real and sham iTBS groups in post-test and baseline phases from different dimensions, to explore the potential neural mechanisms underlying the modulation of iTBS on deficits in the capability to use ER strategies among HUD patients. Since limited access to ER strategies may be related to heroin craving [ 46 ], we will explore whether the alterations of EEG indices and craving are related. To examine long-term effects, we compared the EEG data of the real iTBS group between the baseline, post-test, and follow-up periods. We hypothesized that while using ER strategies, real (vs. sham) iTBS would significantly increase the ERP amplitudes, induce stronger neural oscillations, and alter brain activation and connectivity of ER-related brain regions. The long-term effects would be maintained in the EEG signatures at one-month follow-up. 2. Methods and Materials 2.1. Study procedure This pre-registered study (Chinese Clinical Trial Registry, ChiCTR2000034542) recruited forty-eight HUD patients and randomly assigned them to the real (n = 24) or sham (n = 24) iTBS group (see Fig. 1 A and Supplementary for details). After baseline data were collected the intervention was conducted over 10 days, three times (morning, noon, and night) per day. Three real iTBS group and two sham group participants dropped out. Post-test data were collected from both groups at the end of the intervention, and a follow-up measurement was taken 30 days later from the real iTBS group. The iTBS protocol was set based on a previous study and details were provided in the supplementary [ 45 ]. The current study adhered to the Declaration of Helsinki, approved by an Ethics Committee from the Northwest Normal University, and provided informed consent. 2.2. Sample characteristics Two groups were well-matched regarding age, education level, anxiety and depression levels, and ERQ scores on reappraisal at baseline (Table 1 ). However, participants in the real iTBS group reported more frequent use of expressive suppression strategy than the sham group. Table 1 Baseline demographics and clinical characteristics Real (n = 21) Sham (n = 18) Statistical Mean SD Mean SD T p -value Demographic data Age (years) 44.05 11.3 45.83 9.84 -0.52 0.605 Sex (male: female ([male]) 21:0 (100%) 18:0 (100%) - - Educational level (years) ① 7.95 3.28 8.26 2.51 -0.32 0.748 Clinical data (Baseline) BAI 30.00 10.92 29.78 8.65 0.07 0.945 BDI 18.33 10.9 19.94 10.94 -0.46 0.649 ERQ cognitive reappraisal 31.81 6.12 28.89 6.60 1.43 0.160 ERQ expressive suppression 21.29 3.52 16.39 7.48 2.55 0.018 SD, standard deviation; BAI, Beck Anxiety Inventory; BDI, Beck Depression Inventory; ERQ, ER Questionnaire. Note: ① One participant in the sham group did not report education level, and the analysis was based on 21 participants in the real iTBS group and 17 participants in the sham group. 2.3. Stimuli and ER task Details are provided in our previous study [ 19 , 20 ], briefly, the task consisted of five blocks, each comprising 40 trials of pictures [ 47 , 48 ]. Participants were instructed to view neutral pictures (NV) or unpleasant pictures (UV), use reappraisal (UR), expressive suppression (US), or a combination of the two strategies (USR) to unpleasant pictures. To avoid affective carry-over effects the NV blocks were presented first, other blocks were presented in random order, starting with eight pictures for participants to practice the corresponding ER strategy. For reappraisal, participants were asked to imagine that the pictures were fake, for expressive suppression to suppress their emotions to not show on their faces. Detailed task procedure see Fig. 1 B. 2.4. EEG data acquisition and preprocessing We used a 64-channel amplifier with scalp electrodes placed according to the international 10/5 system (Advanced Neuro Technology, ANT, Enschede, The Netherlands) to collect EEG data. CPz was used as a reference, and electrode impedances were kept below 10 kΩ. The bandpass filter was set to 0.01–30Hz, sampling rate was 1,000Hz. We used EEGLAB v2021.0 [ 49 ] to re-referenced the EEG data to the average of the left and right mastoids and set the bandpass filter to 0.1–30Hz. For ERP analysis, EEG data were segmented into 2200ms epochs (200ms before and 2,000ms after stimulus appearance); for TF analysis, segmented into 4,800ms epochs (800ms before and 4,000ms after stimulus appearance) [ 19 , 20 ]; for source localization, and connectivity analysis, segmented according to the time window of the significant different cluster between post-test and baseline. Then the independent component analysis method to detect and eliminate artifacts. The criterion of rejected trials was over ± 100µV. Four participants with < 50% of the remaining trials were excluded [ 50 ], as detailed shown in Table 2 . Table 2 Percentage of valid trials of the real vs. sham iTBS group Real iTBS (n = 21) Sham iTBS (n = 18) Baseline Post-test Follow-up Baseline Post-test ERP analysis 95% 96% 92% 91% 88% TF/source/ connectivity analysis 92% 95% 94% 89% 86% 2.5. EEG analysis 2.5.1. ERP analysis We analyzed the average LPP amplitudes (early LPP: 400–1000ms, late LPP: 1000–2000ms) and used difference waves (DW; post-test minus baseline) to separate amplitude changes caused by intervention/placebo effects (see Supplementary for details) [ 51 ]. DW could reduce the number of factors in the analysis of variance (ANOVA) and the clade error rate [ 50 ]. To compare the effect of real vs. sham iTBS, repeated-measures ANOVA was performed to analyze the intervention effect for emotional arousal, ER, and temporal dynamics [ 52 ]. Data from the real iTBS group at baseline, post-test, and follow-up were analyzed to examine the long-term effects of the iTBS intervention. Full results were presented in the Supplement . 2.5.2. Time-frequency analysis FieldTrip toolbox was used to perform the TF analysis [ 53 ]. Used short-time Fourier transform with a fixed 200ms Hanning window to calculate the TF representations in the 2–30Hz. Used a sliding window advanced in 10ms and 1Hz increments to estimate the changes in power over time and frequency. The activity between − 300ms and − 100ms was calculated as a baseline by the “db” approach [ 20 , 54 , 55 ]. For each condition, the results of the short-time Fourier transform were averaged within each participant and then by all participants. The cluster-based permutation test was used to control multiple comparisons [ 56 ]. To compare the effect of real vs. sham iTBS, independent t -tests were used to compare the data from each time point (0–4000ms), frequency range (2–30Hz), and all sensors from each condition between the post-test and baseline of two groups, separately. Compared the follow-up data of the real iTBS group with their baseline, to examine the long-term effects of the iTBS intervention. 2.5.3. Source localization The exact low-resolution brain electromagnetic tomography (eLORETA, https://www.uzh.ch/keyinst/loreta ) algorithm was used to estimate the intracranial sources of the significant clusters (see Results section) calculated from TF analysis in the delta (2–4Hz) and theta (4–8Hz) band [ 57 – 59 ]. EEG epochs were extracted according to the time range of the significant clusters, separately. Subsequently, randomization Statistical nonParametric Mapping (SnPM) 5000 times to correct the multiple comparisons based on the pared-sample t-test of the post-test and baseline for each cluster to identify the significantly different brain regions [ 60 ]. 2.5.4. Functional connectivity analysis The eLORETA algorithm was used to estimate the connectivity changes based on the results of the source analysis. The right posterior cingulate cortex (PCC, Brodmann's area, BA 30) and intervention target - left DLPFC (BA 9) were set as regions of interest (ROIs) [ 61 , 62 ]. Lagged phase synchronization (LPS) was used to calculate the connectivity between multivariate time series of the ROIs in the frequency domain using 200ms Hanning windows [ 63 , 64 ]. We focus on the delta band power based on TF results. Perform randomization SnPM 5000 times based on the pared-sample t-test. 2.6. Cue-induced craving Our previous study demonstrated that iTBS significantly reduced craving in the real iTBS group [ 65 ]. In the current study, Pearson's correlation was used to calculate the correlation between the changed craving (post-test minus baseline) and the significant indicators obtained from ERP and TF analyses, for both groups, separately; used Fisher’s r -to- z transformation to examine whether the group difference was significant. 3. Results 3.1.1. Behavioural results Operational validity check There was a significant main effect of strategy (UR, US, USR) ( F (2, 51) = 6.09, p = 0.004, η2 p = 0.16), participants reported more successful using expressive suppression (6.01 ± 0.25) than reappraisal (5.35 ± 0.24) (Fig.2A). Mood assessment Emotional arousal effect. The main effect of stimulus type (NV, UV) was significant ( F (1, 32) = 11.49, p = 0.002, η2 p = 0.26, Fig.2B); participants reported significantly stronger emotion arousal in the UV (2.61 ± 0.28) than NV (1.76 ± 0.16) condition. The period × group interaction was significant ( F (1, 32) = 4.26, p = 0.047, η2 p = 0.12). Only the real iTBS group felt significantly less negative at post-test (1.88 ± 0.23) than baseline (2.48 ± 0.29) ( F (1, 32) = 5.79, p = 0.022, η2 p = 0.15). ER effect. There was a significant main effect of time point (pre-block, post-block) ( F (1, 32) = 10.72, p = 0.003, η2 p = 0.25). The post-block score (2.60 ± 0.25) was significantly higher than the pre-block (1.94 ± 0.16). The period × group interaction was significant ( F (1, 32) = 5.81, p = 0.022, η2 p = 0.15). However, no significant results after the Bonferroni correction. 3.1.2. Scalp-level ERP results Early LPP time window Emotional arousal effect. The DW waveforms are represented in Fig.3A. No significant results were found. ER effect. A significant main effect of scalp position (left, middle, right) was revealed ( F (2, 74) = 3.62, p = 0.032, η2 p = 0.09). However, no significant results after the Bonferroni correction. The temporal dynamics analysis revealed a significant interaction of segment (400–600ms, 600–800ms, 800–1000ms) × group ( F (2, 55) = 4.90, p = 0.019, η2 p = 0.12). Compared to the sham group (-0.4 ± 0.26μV), the real iTBS group (0.65 ± 0.24μV) showed significantly more positive DW within 400–600ms ( F (1, 37) = 8.64, p = 0.006, η2 p = 0.19). Only in the real iTBS group, the average amplitude in the 400–600ms (0.65 ± 0.24μV) and 600–800ms (0.15 ± 0.48μV) was significantly more positive than that in the 800–1000ms ( F (2, 36) = 7.10, p = 0.003, η2 p = 0.28). Late LPP time window Emotional arousal effect. There was a significant main effect of the scalp region ( F (2, 61) = 4.68, p = 0.012, η2 p = 0.11), the wave amplitude of the middle region (-0.72 ± 0.30μV) being more negative than the left (-0.48 ± 0.26μV) and right side (-0.37 ± 0.28μV). ER effect. No significant results were found for the ER effect. 3.1.3. Scalp-level TF results Emotional arousal effect. Cluster-based permutation tests revealed that in the NV condition, compared to the baseline phase, only the real iTBS group had a more significant event-related synchronization (ERS) at post-test ( p < 0.01), mainly in the delta (2–4Hz) and theta (4–8Hz) bands (Fig.3B). The role of sensors in the anterior and apical scalp regions was more prominent, during approximately 0–2740ms, overall ERS peak at ~2000ms. ER effect. For the US condition, compared to the baseline phase, only the real iTBS group had a more significant ERS at the post-test ( p < 0.05), mainly in the delta (2–4Hz) and theta (4–8Hz) bands. The role of sensors in the posterior and right scalp regions was more prominent, with a duration lasting approximately 710–2940ms, overall ERS peak at ~1980ms. 3.1.4. Brain state-level sLORETA results Emotional arousal effect. In the delta band, compared to the baseline, the cortical current density was significantly lower in the left parietal lobe at the post-test of the real iTBS group under NV condition ( t max = -4.22, p < 0.05, supramarginal gyrus, Fig.3C). ER effect . When using the expressive suppression strategy, compared to the baseline, the real iTBS group had a significantly lower cortical current density of the delta band energy on the right limbic lobe at the post-test ( t max = -4.16, p < 0.05, PCC). 3.1.5. Brain state-level connectivity results Compared to the baseline, the real iTBS group had significantly lower connectivity between the left DLPFC (intervention target) and right PCC at the post-test ( t = -1.80, p < 0.05, Fig.3D). 3.1.6. Relationship between altered EEG signatures and craving While using the expressive suppression strategy, compared to the sham iTBS group, the real group has a significantly higher correlation between altered DW amplitudes and craving ( Z = -2.52, p = 0.012, Fig.4B). Only the real iTBS group showed a significant correlation between average DW amplitudes and altered craving under UR condition. However, no significant group difference revealed (Z = -1.681, p = 0.093). No significant results were found regarding the significant clusters. 3.2. Long-term effect of iTBS intervention 3.2.1. Behavioural results Operational validity check No significant main effect or interaction was found. Mood assessment Emotional arousal effect. Compared to NV condition (1.94 ± 0.22), participants have higher emotional arousal in UV condition (2.73 ± 0.31) ( F (1, 20) = 9.27, p = 0.006, η2 p = 0.32, Fig.5); higher arousal at follow-up (1.88 ± 0.20) than post-test (2.64 ± 0.13) stage ( F (2, 40) = 4.41, p = 0.019, η2 p = 0.18). ER effect. A significant main effect of time point was revealed ( F (1, 20) = 7.26, p = 0.014, η2 p = 0.27). The post-block scores (2.68 ± 0.30) were significantly higher than the pre-block score (2.03 ± 0.21). 3.2.2. Scalp-level ERP results Below only focused on the long-term effects of iTBS intervention on ER capability. Early LPP time window A significant main effect for the segment (400–600, 600–800, 800–1000ms) was found ( F (2, 40) = 22.40, p < 0.001, η2 p = 0.53, Fig.6). The average amplitudes were most positive during 400–600ms (0.71 ± 0.18μV), followed by 600–800ms (-0.02 ± 0.28μV), and 800–1000ms (-0.83 ± 0.26μV). The interactions of segment × period ( F (2, 40) = 6.80, p = 0.003, η2 p = 0.25) and segment × ER strategy ( F (4, 74) = 5.11, p = 0.001, η2 p = 0.20) were significant. During 400–600ms, the amplitudes of post-test (0.95 ± 0.26μV) were significantly more positive than baseline (0.30 ± 0.18μV); during 800–1000ms, the amplitudes of follow-up (-1.46 ± 0.38μV) was more negative than the baseline (-1.12 ± 0.30μV). For ER strategies, during 400–600ms, the amplitudes in USR (1.06 ± 0.23μV) were significantly more positive than in UV (0.51 ± 0.22μV) and UR (0.57 ± 0.18μV) conditions. Late LPP time window The main effect of segment (1000–1200, 1200–1400, 1400–1600, 1600–1800, 1800–2000ms) was significant ( F (1, 27) = 20.07, p < 0.001, η2 p = 0.50). The average amplitudes were most negative during 1200–1400ms (-1.34 ± 0.18μV), followed by 1400–1600ms (-0.97 ± 0.15μV), 1600–1800ms (-0.43 ± 0.15μV) and 1800–2000ms (-0.12 ± 0.13μV). The average amplitudes in 1000–1200ms were significantly more negative than 1600–1800ms and 1800–2000ms. The interactions of segment × period ( F (3, 57) = 20.07, p < 0.001, η2 p = 0.28) and segment × ER strategy ( F (4, 78) = 3.33, p = 0.015, η2 p = 0.14) were significant. During 1000–1200ms, the amplitudes of follow-up (-1.89 ± 0.33μV) were significantly more negative than baseline (-0.54 ± 0.30μV); the amplitudes in UR (-1.52 ± 0.24μV) were significantly more negative than in UV (-0.91 ± 0.22μV) condition. 4. Discussion This study aimed to investigate whether iTBS targeting the left DLPFC could improve the ineffective use of ER strategies in HUD patients. We compared the EEG signals of participants between the real and sham iTBS groups while using ER strategies combining ERP, TF, source localization, and connectivity analysis techniques. Results verified our hypothesis that iTBS could significantly improve deficits in the use of ER strategies in HUD patients, particularly for expressive suppression. The increased ER capability was related to the reduced cue-induced heroin use craving. The intervention effect was maintained at the one-month follow-up. The most obvious finding is that iTBS could improve the ER capability of HUD patients. Compared to the sham group, the real iTBS group showed a significantly stronger positive DW in the 400–600ms range when using ER strategies, those altered DW were significantly correlated with reduced cue-induced craving. Compared to the baseline, they had stronger ERS in the delta and theta frequency bands, a reduction in right PCC activity, and lower connectivity between the left DLPFC and right PCC at the post-test while using the expressive suppression strategy. Some ERP indicators were still significant at the one-month late follow-up period. The amplitude of the DW demonstrated may reflect the degree of allocation of cognitive resources [ 67 ]. The intensity of the ERS correlates with the intensity of cognitive processing and reflects inhibitory processes [ 68 , 69 ]. The PCC is a core region of the default-mode network (DMN) and has been suggested associated with control, inhibition processes, and the use of expressive suppression regulation of negative emotions [ 70 – 74 ]. The current findings may indicate that after the iTBS intervention, HUD patients showed increased cognitive resource recruitment when using ER strategies, especially when using expressive suppression strategy. In line with the current study, a recent study found iTBS over the left DLPFC induced decreased theta power while using self-compassion strategies to socially rejected scenarios [ 75 ]. HF rTMS over the left DLPFC could significantly decrease the level of distress in OCD participants. De Wit et al. (2015) proposed that deficient ER in OCD patients is based on a failure of cognitive control in the DLPFC and rTMS can change the frontal-limbic connectivity thereby affecting their ability to automate ER [ 34 ]. The frontal lobe and how it regulates limbic brain regions has been suggested to play a crucial role in emotion dysregulation among psychiatric disorders [ 76 , 77 ]. Alterations in the frontal-limbic systemic interactions have been detected in the current study, which may serve as potential neurophysiological bases for the modulatory role of iTBS. Compared to reappraisal, iTBS was more effective in enhancing the expressive suppression strategy for HUD patients. One possible reason might be that as a preferred strategy in the Chinese culture [ 22 , 78 ], at baseline, the real iTBS group reported more habituated to expressive suppression. However, after controlling the expressive suppression score as a covariate, the results were still significant (see supplement). Another possible explanation is that although reappraisal and expressive suppression may conjointly involve the activation of certain brain regions (e.g., the bilateral DLPFC, dorsomedial prefrontal cortex (DMPFC), inferior parietal cortex (IPC), and anterior insula), the role of the current target, left DLPFC and the specific underlying neural circuits of those two strategies may be different [ 38 , 70 , 79 , 80 ]. Their regulation timing may also differ (reappraisal: 0–4.5sec, suppression 10.5–15sec), while the former reduced the activation of the amygdala and insula, the latter enhanced them [ 79 ]. The characteristics of HUD patients [ 10 ], stimulation protocol, choice of target [ 30 ], or the duration of the intervention [ 81 , 82 ] may also play some roles. One recent review suggested that SUDs more frequently use expressive suppression strategies than HCs [ 10 ]. In healthy participants, HF rTMS over the right ventrolateral prefrontal cortex could significantly reduce the LPP amplitude during the reappraisal of social pain [ 30 ]. Further investigation of the above factors may help to facilitate better intervention protocol for the emotion dysregulation of the HUD population. One unanticipated result was that compared to the baseline, there was a significant ERS in the delta/theta band at the post-test of the real iTBS group during free viewing of neutral pictures and the activation in the left supramarginal gyrus was significantly lower at the post-test. These cases were not found while viewing unpleasant pictures. The supramarginal gyrus has been suggested related to attentional processes [ 83 ]. In our experimental paradigm, to avoid the effect of unpleasant pictures on neutral pictures, the NV condition was presented fixedly first [ 19 , 20 , 52 ]. Possible explanations might be that iTBS enhanced the cognitive engagement of attentional processes to neutral stimuli or the specificity of the NV condition. Future studies could explore this issue based on our study. 5. Limitations and Prospects Several limitations be considered. First, female participants were missing due to the hospital only admitted male patients. Gender differences were previously found in ER processing and the effectiveness of TMS intervention [ 52 , 84 – 86 ]. Future studies could investigate whether the present results generalize to women with HUD. Second, the follow-up period didn’t include a sham iTBS group. Although numerous studies demonstrated the transdiagnostically long-term post-intervention effect of iTBS across multiple disorders [ 87 – 90 ], and the pattern of ERP amplitudes during the follow-up period are very similar to the post-test phase, sham-controlled follow-up studies with different tracking intervals to explore the dynamic process of iTBS post-effectiveness merit further investigation. Third, the low signal-to-noise ratio of the DW may have some influence on the current results [ 50 ]. Although the results of our analysis have relatively satisfactory effect sizes, future studies could validate our findings by including more participants. Moreover, it is also merited to use higher spatial resolution techniques, e.g., fMRI, to explore the important role of frontal-limbic connectivity in TMS interventions for ER capability in patients with HUD or other SUDs. 6. Conclusion This study demonstrates that iTBS could significantly improve the capability of HUD patients to use ER strategies with long-term effects, especially for expressive suppression. Effects on frontal-limbic connectivity might be a potential therapeutic mechanism of action. Improving the ER capability of HUD patients was related to reduced craving, merits further exploration in their withdrawal treatment and relapse prevention. Declarations Acknowledgements This work was supported by the Regional Project of the National Natural Science Foundation of China (31960181, 32360213) and the scientific and technological innovation 2030 - the major project of the Brain Science and Brain-Inspired Intelligence Technology (2021ZD0200500). The authors would like to sincerely thank all the patients in the Lanzhou Drug Rehabilitation Hospital who participated in the current study; Wenwen Gao, Shaoqiong Wang, Yanyun Lu, Limei Xie, and other staff for their assistance; all the healthy control participants for their participation; and strong support from Prof. Tifei Yuan and his team from Shanghai Jiaotong University School of Medicine. Conflict of Interest This work was conducted without any commercial or financial relationship that could be considered a potential conflict of interest. References United Nations publication. World Drug Report 2024. 2024. Khan Z, Cloete KJ, Harvey J, Weich L. Outcomes of adult heroin users v. abstinent users four years after presenting for heroin detoxification treatment. South Afr J Psychiatry. 2014;20:82. Nutt D, King LA, Saulsbury W, Blakemore C. Development of a rational scale to assess the harm of drugs of potential misuse. Lancet. 2007;369:1047–1053. 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Philip NS, Barredo J, Aiken E, Larson V, Jones RN, Shea MT, et al. Theta-Burst Transcranial Magnetic Stimulation for Posttraumatic Stress Disorder. Am J Psychiatry. 2019;176:939–948. Additional Declarations The authors have declared there is NO conflict of interest to disclose Supplementary Files 005SupplementalMaterial.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. 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Introduction","content":"\u003cp\u003eOpioids represent the illicit drug with the highest levels of harm worldwide. According to the World Drug Report 2024, Canada reported 7,500 opioid deaths in 2022. In America, the number of opioid deaths approached 82,000, which is an overall 24-fold increase since 2010 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Heroin is an opioid with a high risk for physical harm, dependence, and relapse compared to other drugs [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and the second most prevalent illicit drug in China, accounting for an estimated 34% of those with a drug use disorder [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs a transdiagnostic deficit and promising treatment target across multiple mental disorders, including substance use disorders (SUDs) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], emotion regulation (ER) impairments have been demonstrated to play a crucial role from early experimental drug use to the maintenance of addictive behaviors and relapse [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Successful ER critically relies on the implementation of functional ER strategies [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, ineffective use of ER strategies has been demonstrated among multiple SUDs [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The self-medication hypothesis proposes that individuals would choose a specific drug to alleviate specific symptoms of an underlying mental health issue or emotional distress and in turn, gain a sense of emotional control [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Heroin can be used to control physical pain but also unpleasant emotional states such as anger or aggression [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Heroin (vs. saline) injection acutely reduces exaggerated left amygdala response to negative facial expressions in heroin use disorder (HUD) patients, to the level of HCs [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The withdrawal/drug-use cycle is moreover characterized by an increased sensitivity to negative emotions, weak cognitive control, and elevated drug incentive value [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], leading to disruptions in ER strategies and an increased propensity to utilize substance use to satisfy ER needs [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] Our previous studies [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] revealed that HUD patients have deficient neural engagement while using two of the most efficient ER strategies, i.e. cognitive reappraisal and expressive suppression [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Compared to healthy control (HC), they exhibited significantly lower late positive potential (LPP) and did not show event-related desynchronization (ERD) in delta and theta band power when exposed to negative stimuli, indicating that they cannot mobilize sufficient cognitive resources to use those two ER strategies. Those deficits might be associated with the impaired engagement of frontoparietal regulatory control regions [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Altogether, it is essential to modulate the deficits of using ER strategies in HUD patients.\u003c/p\u003e \u003cp\u003eAs a non-invasive neuromodulation technique to influence cortex excitability, transcranial magnetic stimulation (TMS) has been increasingly employed as a novel treatment option for SUDs [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. While most studies primarily used craving or drug use frequency/amount as primary outcomes [\u003cspan additionalcitationids=\"CR27 CR28\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], however, effects on underlying domains such as ER capability remain unclear. TMS has been demonstrated as a potential strategy to modulate the emotional state in healthy participants or patients with major depressive disorder (MDD) or obsessive-compulsive disorder (OCD) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Previous studies found that high-frequency (HF) rTMS over the left dorsolateral prefrontal cortex (DLPFC) could lead to a significant increase in heart rate variability which indicates diminished physiological stress response to negative social feedback [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], decreased cortisol stress response in women [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], and decrease the distress rates of OCD patients [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. He et al. (2020) used the right ventrolateral prefrontal as a target and found that HF rTMS could reduce the negative feelings and LPP amplitudes of the participants during reappraisal to a social pain situation. Deep transcranial magnetic stimulation (dTMS) over the left DLPFC could reduce the depression of patients with bipolar disorder (BD) and recurrent MDD, this outcome could last 12 months if with maintenance sessions weekly or twice a week [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo our knowledge, no research has examined the modulatory effects of TMS on ER in HUD patients to date. Jansen et al., (2019) found that HF-rTMS over the left DLPFC reduced self-reported emotional arousal to positive and negative pictures in patients with alcohol use disorder (AUD), whereas increased the emotional response to neutral and positive pictures in HC participants. Notably, only in patients with AUD \u0026ndash; but not controls \u0026ndash; rTMS reduced right DLPFC activation during the reappraisal of affective pictures relative to sham. These findings may imply that TMS intervention outcomes in ER differ in addicted and healthy individuals. Considering the importance of ER deficits in HUD, it is worth exploring whether the TMS could improve ER deficits and lead to lasting ER improvements post-intervention.\u003c/p\u003e \u003cp\u003eThe DLPFC is a crucial brain area for both reappraisal and expressive suppression capability [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], HUD patients show abnormalities in this region [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], ER deficits in SUD have been associated with deficient left DLPFC regulation over the amygdala [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], previous studies of TMS modulation of ER have mostly targeted the left DLPFC [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], and our prior studies also found a left hemispheric dominant effect in healthy subjects [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], we chose the left DLPFC as stimulation target. Since heroin is a depressant that induces brain hypoxia and reduces neuronal activity [\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] and HUD patients showed significantly lower activation of multiple brain regions than HC when using ER strategies [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], we chose an excitatory stimulation protocol, i.e. intermittent theta-burst transcranial magnetic stimulation (iTBS). This is a new type of rTMS and one of the most powerful tools that could induce long-term potentiation like traditional 10Hz stimulation but more efficient [\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe combined event-related potential (ERP), time-frequency (TF), source localization, and connectivity analysis techniques to compare the electroencephalography (EEG) signals between real and sham iTBS groups in post-test and baseline phases from different dimensions, to explore the potential neural mechanisms underlying the modulation of iTBS on deficits in the capability to use ER strategies among HUD patients. Since limited access to ER strategies may be related to heroin craving [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], we will explore whether the alterations of EEG indices and craving are related. To examine long-term effects, we compared the EEG data of the real iTBS group between the baseline, post-test, and follow-up periods. We hypothesized that while using ER strategies, real (vs. sham) iTBS would significantly increase the ERP amplitudes, induce stronger neural oscillations, and alter brain activation and connectivity of ER-related brain regions. The long-term effects would be maintained in the EEG signatures at one-month follow-up.\u003c/p\u003e"},{"header":"2. Methods and Materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study procedure\u003c/h2\u003e \u003cp\u003eThis pre-registered study (Chinese Clinical Trial Registry, ChiCTR2000034542) recruited forty-eight HUD patients and randomly assigned them to the real (n\u0026thinsp;=\u0026thinsp;24) or sham (n\u0026thinsp;=\u0026thinsp;24) iTBS group (see Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and Supplementary for details). After baseline data were collected the intervention was conducted over 10 days, three times (morning, noon, and night) per day. Three real iTBS group and two sham group participants dropped out. Post-test data were collected from both groups at the end of the intervention, and a follow-up measurement was taken 30 days later from the real iTBS group. The iTBS protocol was set based on a previous study and details were provided in the supplementary [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e The current study adhered to the Declaration of Helsinki, approved by an Ethics Committee from the Northwest Normal University, and provided informed consent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Sample characteristics\u003c/h2\u003e \u003cp\u003eTwo groups were well-matched regarding age, education level, anxiety and depression levels, and ERQ scores on reappraisal at baseline (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). However, participants in the real iTBS group reported more frequent use of expressive suppression strategy than the sham group.\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\u003eBaseline demographics and clinical characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eReal (n\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eSham (n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eStatistical\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eT\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.605\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male: female ([male])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level (years)\u003csup\u003e①\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.748\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical data (Baseline)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.649\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eERQ cognitive reappraisal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eERQ expressive suppression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.018\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eSD, standard deviation; BAI, Beck Anxiety Inventory; BDI, Beck Depression Inventory; ERQ, ER Questionnaire. Note: \u003csup\u003e①\u003c/sup\u003eOne participant in the sham group did not report education level, and the analysis was based on 21 participants in the real iTBS group and 17 participants in the sham group.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Stimuli and ER task\u003c/h2\u003e \u003cp\u003eDetails are provided in our previous study [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], briefly, the task consisted of five blocks, each comprising 40 trials of pictures [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Participants were instructed to view neutral pictures (NV) or unpleasant pictures (UV), use reappraisal (UR), expressive suppression (US), or a combination of the two strategies (USR) to unpleasant pictures.\u003c/p\u003e \u003cp\u003eTo avoid affective carry-over effects the NV blocks were presented first, other blocks were presented in random order, starting with eight pictures for participants to practice the corresponding ER strategy. For reappraisal, participants were asked to imagine that the pictures were fake, for expressive suppression to suppress their emotions to not show on their faces. Detailed task procedure see Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e1\u003c/span\u003eB.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. EEG data acquisition and preprocessing\u003c/h2\u003e \u003cp\u003eWe used a 64-channel amplifier with scalp electrodes placed according to the international 10/5 system (Advanced Neuro Technology, ANT, Enschede, The Netherlands) to collect EEG data. CPz was used as a reference, and electrode impedances were kept below 10 kΩ. The bandpass filter was set to 0.01\u0026ndash;30Hz, sampling rate was 1,000Hz.\u003c/p\u003e \u003cp\u003eWe used EEGLAB v2021.0 [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] to re-referenced the EEG data to the average of the left and right mastoids and set the bandpass filter to 0.1\u0026ndash;30Hz. For ERP analysis, EEG data were segmented into 2200ms epochs (200ms before and 2,000ms after stimulus appearance); for TF analysis, segmented into 4,800ms epochs (800ms before and 4,000ms after stimulus appearance) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]; for source localization, and connectivity analysis, segmented according to the time window of the significant different cluster between post-test and baseline. Then the independent component analysis method to detect and eliminate artifacts. The criterion of rejected trials was over \u0026plusmn;\u0026thinsp;100\u0026micro;V. Four participants with \u0026lt;\u0026thinsp;50% of the remaining trials were excluded [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], as detailed shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePercentage of valid trials of the real vs. sham iTBS group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eReal iTBS (n\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eSham iTBS (n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePost-test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFollow-up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePost-test\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eERP analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e88%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTF/source/\u003c/p\u003e \u003cp\u003econnectivity analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e94%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e89%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e86%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. EEG analysis\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.5.1. ERP analysis\u003c/h2\u003e \u003cp\u003eWe analyzed the average LPP amplitudes (early LPP: 400\u0026ndash;1000ms, late LPP: 1000\u0026ndash;2000ms) and used difference waves (DW; post-test minus baseline) to separate amplitude changes caused by intervention/placebo effects (see Supplementary for details) [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. DW could reduce the number of factors in the analysis of variance (ANOVA) and the clade error rate [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo compare the effect of real vs. sham iTBS, repeated-measures ANOVA was performed to analyze the intervention effect for emotional arousal, ER, and temporal dynamics [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Data from the real iTBS group at baseline, post-test, and follow-up were analyzed to examine the long-term effects of the iTBS intervention.\u003c/p\u003e \u003cp\u003eFull results were presented in the \u003cb\u003eSupplement\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.5.2. Time-frequency analysis\u003c/h2\u003e \u003cp\u003eFieldTrip toolbox was used to perform the TF analysis [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Used short-time Fourier transform with a fixed 200ms Hanning window to calculate the TF representations in the 2\u0026ndash;30Hz. Used a sliding window advanced in 10ms and 1Hz increments to estimate the changes in power over time and frequency. The activity between \u0026minus;\u0026thinsp;300ms and \u0026minus;\u0026thinsp;100ms was calculated as a baseline by the \u0026ldquo;db\u0026rdquo; approach [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. For each condition, the results of the short-time Fourier transform were averaged within each participant and then by all participants.\u003c/p\u003e \u003cp\u003eThe cluster-based permutation test was used to control multiple comparisons [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. To compare the effect of real vs. sham iTBS, independent \u003cem\u003et\u003c/em\u003e-tests were used to compare the data from each time point (0\u0026ndash;4000ms), frequency range (2\u0026ndash;30Hz), and all sensors from each condition between the post-test and baseline of two groups, separately. Compared the follow-up data of the real iTBS group with their baseline, to examine the long-term effects of the iTBS intervention.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.5.3. Source localization\u003c/h2\u003e \u003cp\u003eThe exact low-resolution brain electromagnetic tomography (eLORETA, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.uzh.ch/keyinst/loreta\u003c/span\u003e\u003cspan address=\"https://www.uzh.ch/keyinst/loreta\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) algorithm was used to estimate the intracranial sources of the significant clusters (see Results section) calculated from TF analysis in the delta (2\u0026ndash;4Hz) and theta (4\u0026ndash;8Hz) band [\u003cspan additionalcitationids=\"CR58\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. EEG epochs were extracted according to the time range of the significant clusters, separately. Subsequently, randomization Statistical nonParametric Mapping (SnPM) 5000 times to correct the multiple comparisons based on the pared-sample t-test of the post-test and baseline for each cluster to identify the significantly different brain regions [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.5.4. Functional connectivity analysis\u003c/h2\u003e \u003cp\u003eThe eLORETA algorithm was used to estimate the connectivity changes based on the results of the source analysis. The right posterior cingulate cortex (PCC, Brodmann's area, BA 30) and intervention target - left DLPFC (BA 9) were set as regions of interest (ROIs) [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Lagged phase synchronization (LPS) was used to calculate the connectivity between multivariate time series of the ROIs in the frequency domain using 200ms Hanning windows [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. We focus on the delta band power based on TF results. Perform randomization SnPM 5000 times based on the pared-sample t-test.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Cue-induced craving\u003c/h2\u003e \u003cp\u003eOur previous study demonstrated that iTBS significantly reduced craving in the real iTBS group [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. In the current study, Pearson's correlation was used to calculate the correlation between the changed craving (post-test minus baseline) and the significant indicators obtained from ERP and TF analyses, for both groups, separately; used Fisher\u0026rsquo;s \u003cem\u003er\u003c/em\u003e-to-\u003cem\u003ez\u003c/em\u003e transformation to examine whether the group difference was significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003ch2\u003e3.1.1. Behavioural results\u003c/h2\u003e\n\u003ch2\u003eOperational validity check\u003c/h2\u003e\n\u003cp\u003eThere was a significant main effect of strategy (UR, US, USR) (\u003cem\u003eF\u003c/em\u003e(2, 51) = 6.09, \u003cem\u003ep\u003c/em\u003e = 0.004, \u0026eta;2 p = 0.16), participants reported more successful using expressive suppression (6.01 \u0026plusmn; 0.25) than reappraisal (5.35 \u0026plusmn; 0.24) (Fig.2A).\u003c/p\u003e\n\u003ch2\u003eMood assessment\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eEmotional arousal effect.\u003c/strong\u003e The main effect of stimulus type (NV, UV) was significant (\u003cem\u003eF\u003c/em\u003e(1, 32) = 11.49, \u003cem\u003ep =\u0026nbsp;\u003c/em\u003e0.002,\u0026nbsp;\u0026eta;2 p = 0.26,\u0026nbsp;Fig.2B); participants reported significantly stronger emotion arousal in the UV (2.61 \u0026plusmn; 0.28) than NV (1.76 \u0026plusmn; 0.16) condition.\u003c/p\u003e\n\u003cp\u003eThe period \u0026times; group interaction was significant (\u003cem\u003eF\u003c/em\u003e(1, 32) = 4.26, \u003cem\u003ep\u003c/em\u003e = 0.047,\u0026nbsp;\u0026eta;2 p = 0.12). Only the real\u0026nbsp;iTBS\u0026nbsp;group felt significantly less negative at post-test (1.88 \u0026plusmn; 0.23) than baseline (2.48 \u0026plusmn; 0.29)\u0026nbsp;(\u003cem\u003eF\u003c/em\u003e(1, 32) = 5.79, \u003cem\u003ep =\u0026nbsp;\u003c/em\u003e0.022,\u0026nbsp;\u0026eta;2 p = 0.15).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eER effect.\u003c/strong\u003e There was a significant main effect of time point (pre-block, post-block) (\u003cem\u003eF\u003c/em\u003e(1, 32) = 10.72, \u003cem\u003ep =\u0026nbsp;\u003c/em\u003e0.003,\u0026nbsp;\u0026eta;2 p = 0.25). The post-block score (2.60 \u0026plusmn; 0.25) was significantly higher than the pre-block (1.94 \u0026plusmn; 0.16).\u003c/p\u003e\n\u003cp\u003eThe period \u0026times; group interaction was significant (\u003cem\u003eF\u003c/em\u003e(1, 32) = 5.81, \u003cem\u003ep =\u0026nbsp;\u003c/em\u003e0.022,\u0026nbsp;\u0026eta;2 p = 0.15). However, no significant results after the Bonferroni correction.\u003c/p\u003e\n\u003ch2\u003e3.1.2. Scalp-level ERP results\u003c/h2\u003e\n\u003ch2\u003eEarly LPP time window\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eEmotional arousal effect.\u003c/strong\u003e The DW waveforms are represented in Fig.3A. No significant results were found.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eER effect.\u0026nbsp;\u003c/strong\u003eA significant main effect of scalp position (left, middle, right) was revealed (\u003cem\u003eF\u003c/em\u003e(2, 74) = 3.62, \u003cem\u003ep =\u0026nbsp;\u003c/em\u003e0.032,\u0026nbsp;\u0026eta;2 p = 0.09). However, no significant results after the Bonferroni correction.\u003c/p\u003e\n\u003cp\u003eThe temporal dynamics analysis revealed a significant interaction of segment (400\u0026ndash;600ms, 600\u0026ndash;800ms, 800\u0026ndash;1000ms) \u0026times; group (\u003cem\u003eF\u003c/em\u003e(2, 55) = 4.90, \u003cem\u003ep =\u0026nbsp;\u003c/em\u003e0.019,\u0026nbsp;\u0026eta;2 p = 0.12). Compared to the sham group (-0.4 \u0026plusmn; 0.26\u0026mu;V), the real iTBS group (0.65 \u0026plusmn; 0.24\u0026mu;V) showed significantly more positive DW within 400\u0026ndash;600ms\u0026nbsp;(\u003cem\u003eF\u003c/em\u003e(1, 37) = 8.64, \u003cem\u003ep =\u0026nbsp;\u003c/em\u003e0.006,\u0026nbsp;\u0026eta;2 p = 0.19). Only in the real\u0026nbsp;iTBS group, the average amplitude in the 400\u0026ndash;600ms (0.65 \u0026plusmn; 0.24\u0026mu;V) and 600\u0026ndash;800ms (0.15 \u0026plusmn; 0.48\u0026mu;V) was significantly more positive than that in the 800\u0026ndash;1000ms\u0026nbsp;(\u003cem\u003eF\u003c/em\u003e(2, 36) = 7.10, \u003cem\u003ep =\u0026nbsp;\u003c/em\u003e0.003,\u0026nbsp;\u0026eta;2 p = 0.28).\u003c/p\u003e\n\u003ch2\u003eLate LPP time window\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eEmotional arousal effect.\u003c/strong\u003e There was a significant main effect of the scalp region (\u003cem\u003eF\u003c/em\u003e(2, 61) = 4.68, \u003cem\u003ep\u003c/em\u003e = 0.012, \u0026eta;2 p = 0.11), the wave amplitude of the middle region (-0.72 \u0026plusmn; 0.30\u0026mu;V) being more negative than the left (-0.48 \u0026plusmn; 0.26\u0026mu;V) and right side (-0.37 \u0026plusmn; 0.28\u0026mu;V).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eER effect.\u003c/strong\u003e No significant results were found for the ER effect.\u003c/p\u003e\n\u003ch2\u003e3.1.3. Scalp-level TF results\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eEmotional arousal effect.\u003c/strong\u003e Cluster-based permutation tests revealed that in the NV condition, compared to the baseline phase, only the real iTBS group had a more significant event-related synchronization (ERS) at post-test (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), mainly in the delta (2\u0026ndash;4Hz) and theta (4\u0026ndash;8Hz) bands (Fig.3B). The role of sensors in the anterior and apical scalp regions was more prominent, during approximately 0\u0026ndash;2740ms, overall ERS peak at ~2000ms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eER effect.\u003c/strong\u003e For the US condition, compared to the baseline phase, only the real iTBS group had a more significant ERS at the post-test (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), mainly in the delta (2\u0026ndash;4Hz) and theta (4\u0026ndash;8Hz) bands. The role of sensors in the posterior and right scalp regions was more prominent, with a duration lasting approximately 710\u0026ndash;2940ms, overall ERS peak at ~1980ms.\u003c/p\u003e\n\u003ch2\u003e3.1.4. Brain state-level sLORETA results\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eEmotional arousal effect.\u003c/strong\u003e In the delta band, compared to the baseline, the cortical current density was significantly lower in the left parietal lobe at the post-test of the real iTBS group under NV condition (\u003cem\u003et\u003c/em\u003e\u003csub\u003emax\u003c/sub\u003e = -4.22, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, supramarginal gyrus, Fig.3C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eER effect\u003c/strong\u003e. When using the expressive suppression strategy, compared to the baseline, the real iTBS group had a significantly lower cortical current density of the delta band energy on the right limbic lobe at the post-test (\u003cem\u003et\u003c/em\u003e\u003csub\u003emax\u003c/sub\u003e = -4.16, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, PCC).\u003c/p\u003e\n\u003ch2\u003e3.1.5. Brain state-level connectivity results\u003c/h2\u003e\n\u003cp\u003eCompared to the baseline, the real iTBS group had significantly lower connectivity between the left DLPFC (intervention target) and right PCC at the post-test (\u003cem\u003et\u003c/em\u003e = -1.80, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Fig.3D).\u003c/p\u003e\n\u003ch2\u003e3.1.6. Relationship between altered EEG signatures and craving\u003c/h2\u003e\n\u003cp\u003eWhile using the expressive suppression strategy, compared to the sham iTBS group, the real group has a significantly higher correlation between altered DW amplitudes and craving (\u003cem\u003eZ\u003c/em\u003e = -2.52, \u003cem\u003ep\u003c/em\u003e = 0.012, Fig.4B). Only the real iTBS group showed a significant correlation between average DW amplitudes and altered craving under UR condition. However, no significant group difference revealed (Z = -1.681, \u003cem\u003ep\u003c/em\u003e = 0.093). No significant results were found regarding the significant clusters.\u003c/p\u003e\n\u003ch2\u003e3.2.\u0026nbsp;Long-term effect of iTBS intervention\u003c/h2\u003e\n\u003ch2\u003e3.2.1. Behavioural results\u003c/h2\u003e\n\u003ch2\u003eOperational validity check\u003c/h2\u003e\n\u003cp\u003eNo significant main effect or interaction was found.\u003c/p\u003e\n\u003ch2\u003eMood assessment\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eEmotional arousal effect.\u0026nbsp;\u003c/strong\u003eCompared to NV condition (1.94 \u0026plusmn; 0.22), participants have higher emotional arousal in UV condition (2.73 \u0026plusmn; 0.31) (\u003cem\u003eF\u003c/em\u003e(1, 20) = 9.27, \u003cem\u003ep\u003c/em\u003e = 0.006,\u0026nbsp;\u0026eta;2 p = 0.32, Fig.5); higher arousal at follow-up (1.88 \u0026plusmn; 0.20) than post-test (2.64 \u0026plusmn; 0.13) stage (\u003cem\u003eF\u003c/em\u003e(2, 40) = 4.41, \u003cem\u003ep\u003c/em\u003e = 0.019,\u0026nbsp;\u0026eta;2 p = 0.18).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eER effect.\u0026nbsp;\u003c/strong\u003eA significant main effect of time point was revealed (\u003cem\u003eF\u003c/em\u003e(1, 20) = 7.26, \u003cem\u003ep =\u0026nbsp;\u003c/em\u003e0.014,\u0026nbsp;\u0026eta;2 p = 0.27).\u0026nbsp;The post-block scores (2.68 \u0026plusmn; 0.30) were significantly higher than the pre-block score (2.03 \u0026plusmn; 0.21).\u003c/p\u003e\n\u003ch2\u003e3.2.2. Scalp-level ERP results\u003c/h2\u003e\n\u003cp\u003eBelow only focused on the long-term effects of iTBS intervention on ER capability.\u003c/p\u003e\n\u003ch2\u003eEarly LPP time window\u003c/h2\u003e\n\u003cp\u003eA significant main effect for the segment (400\u0026ndash;600, 600\u0026ndash;800, 800\u0026ndash;1000ms) was found\u0026nbsp;(\u003cem\u003eF\u003c/em\u003e(2, 40) = 22.40, \u003cem\u003ep \u0026lt;\u0026nbsp;\u003c/em\u003e0.001,\u0026nbsp;\u0026eta;2 p = 0.53, Fig.6). The average amplitudes were most positive during 400\u0026ndash;600ms (0.71 \u0026plusmn; 0.18\u0026mu;V), followed by 600\u0026ndash;800ms (-0.02 \u0026plusmn; 0.28\u0026mu;V), and 800\u0026ndash;1000ms (-0.83 \u0026plusmn; 0.26\u0026mu;V).\u003c/p\u003e\n\u003cp\u003eThe interactions of segment \u0026times; period (\u003cem\u003eF\u003c/em\u003e(2, 40) = 6.80, \u003cem\u003ep =\u0026nbsp;\u003c/em\u003e0.003,\u0026nbsp;\u0026eta;2 p = 0.25) and\u0026nbsp;segment \u0026times; ER strategy\u0026nbsp;(\u003cem\u003eF\u003c/em\u003e(4, 74) = 5.11, \u003cem\u003ep =\u0026nbsp;\u003c/em\u003e0.001,\u0026nbsp;\u0026eta;2 p = 0.20)\u0026nbsp;were significant. During 400\u0026ndash;600ms, the amplitudes of post-test (0.95 \u0026plusmn; 0.26\u0026mu;V) were significantly more positive than baseline (0.30 \u0026plusmn; 0.18\u0026mu;V); during 800\u0026ndash;1000ms, the amplitudes of follow-up (-1.46 \u0026plusmn; 0.38\u0026mu;V) was more negative than the baseline (-1.12 \u0026plusmn; 0.30\u0026mu;V). For ER strategies, during 400\u0026ndash;600ms, the amplitudes in USR (1.06 \u0026plusmn; 0.23\u0026mu;V) were significantly more positive than in UV (0.51 \u0026plusmn; 0.22\u0026mu;V) and UR (0.57 \u0026plusmn; 0.18\u0026mu;V) conditions.\u003c/p\u003e\n\u003ch2\u003eLate LPP time window\u003c/h2\u003e\n\u003cp\u003eThe main effect of segment (1000\u0026ndash;1200, 1200\u0026ndash;1400, 1400\u0026ndash;1600, 1600\u0026ndash;1800, 1800\u0026ndash;2000ms) was significant (\u003cem\u003eF\u003c/em\u003e(1, 27) = 20.07, \u003cem\u003ep \u0026lt;\u0026nbsp;\u003c/em\u003e0.001,\u0026nbsp;\u0026eta;2 p = 0.50). The average amplitudes were most negative during 1200\u0026ndash;1400ms (-1.34 \u0026plusmn; 0.18\u0026mu;V), followed by 1400\u0026ndash;1600ms (-0.97 \u0026plusmn; 0.15\u0026mu;V), 1600\u0026ndash;1800ms (-0.43 \u0026plusmn; 0.15\u0026mu;V) and 1800\u0026ndash;2000ms (-0.12 \u0026plusmn; 0.13\u0026mu;V). The average amplitudes in 1000\u0026ndash;1200ms were significantly more negative than 1600\u0026ndash;1800ms and 1800\u0026ndash;2000ms.\u003c/p\u003e\n\u003cp\u003eThe interactions of segment \u0026times; period (\u003cem\u003eF\u003c/em\u003e(3, 57) = 20.07, \u003cem\u003ep \u0026lt;\u0026nbsp;\u003c/em\u003e0.001,\u0026nbsp;\u0026eta;2 p = 0.28) and segment \u0026times; ER strategy (\u003cem\u003eF\u003c/em\u003e(4, 78) = 3.33, \u003cem\u003ep =\u0026nbsp;\u003c/em\u003e0.015, \u0026eta;2 p = 0.14) were significant. During 1000\u0026ndash;1200ms, the amplitudes of follow-up (-1.89 \u0026plusmn; 0.33\u0026mu;V) were significantly more negative than baseline (-0.54 \u0026plusmn; 0.30\u0026mu;V); the amplitudes in UR (-1.52 \u0026plusmn; 0.24\u0026mu;V) were significantly more negative than in UV (-0.91 \u0026plusmn; 0.22\u0026mu;V) condition.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study aimed to investigate whether iTBS targeting the left DLPFC could improve the ineffective use of ER strategies in HUD patients. We compared the EEG signals of participants between the real and sham iTBS groups while using ER strategies combining ERP, TF, source localization, and connectivity analysis techniques. Results verified our hypothesis that iTBS could significantly improve deficits in the use of ER strategies in HUD patients, particularly for expressive suppression. The increased ER capability was related to the reduced cue-induced heroin use craving. The intervention effect was maintained at the one-month follow-up.\u003c/p\u003e \u003cp\u003eThe most obvious finding is that iTBS could improve the ER capability of HUD patients. Compared to the sham group, the real iTBS group showed a significantly stronger positive DW in the 400\u0026ndash;600ms range when using ER strategies, those altered DW were significantly correlated with reduced cue-induced craving. Compared to the baseline, they had stronger ERS in the delta and theta frequency bands, a reduction in right PCC activity, and lower connectivity between the left DLPFC and right PCC at the post-test while using the expressive suppression strategy. Some ERP indicators were still significant at the one-month late follow-up period. The amplitude of the DW demonstrated may reflect the degree of allocation of cognitive resources [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. The intensity of the ERS correlates with the intensity of cognitive processing and reflects inhibitory processes [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. The PCC is a core region of the default-mode network (DMN) and has been suggested associated with control, inhibition processes, and the use of expressive suppression regulation of negative emotions [\u003cspan additionalcitationids=\"CR71 CR72 CR73\" citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. The current findings may indicate that after the iTBS intervention, HUD patients showed increased cognitive resource recruitment when using ER strategies, especially when using expressive suppression strategy.\u003c/p\u003e \u003cp\u003eIn line with the current study, a recent study found iTBS over the left DLPFC induced decreased theta power while using self-compassion strategies to socially rejected scenarios [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. HF rTMS over the left DLPFC could significantly decrease the level of distress in OCD participants. De Wit et al. (2015) proposed that deficient ER in OCD patients is based on a failure of cognitive control in the DLPFC and rTMS can change the frontal-limbic connectivity thereby affecting their ability to automate ER [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The frontal lobe and how it regulates limbic brain regions has been suggested to play a crucial role in emotion dysregulation among psychiatric disorders [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Alterations in the frontal-limbic systemic interactions have been detected in the current study, which may serve as potential neurophysiological bases for the modulatory role of iTBS.\u003c/p\u003e \u003cp\u003eCompared to reappraisal, iTBS was more effective in enhancing the expressive suppression strategy for HUD patients. One possible reason might be that as a preferred strategy in the Chinese culture [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e], at baseline, the real iTBS group reported more habituated to expressive suppression. However, after controlling the expressive suppression score as a covariate, the results were still significant (see supplement). Another possible explanation is that although reappraisal and expressive suppression may conjointly involve the activation of certain brain regions (e.g., the bilateral DLPFC, dorsomedial prefrontal cortex (DMPFC), inferior parietal cortex (IPC), and anterior insula), the role of the current target, left DLPFC and the specific underlying neural circuits of those two strategies may be different [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Their regulation timing may also differ (reappraisal: 0\u0026ndash;4.5sec, suppression 10.5\u0026ndash;15sec), while the former reduced the activation of the amygdala and insula, the latter enhanced them [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. The characteristics of HUD patients [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], stimulation protocol, choice of target [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], or the duration of the intervention [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e] may also play some roles. One recent review suggested that SUDs more frequently use expressive suppression strategies than HCs [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In healthy participants, HF rTMS over the right ventrolateral prefrontal cortex could significantly reduce the LPP amplitude during the reappraisal of social pain [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Further investigation of the above factors may help to facilitate better intervention protocol for the emotion dysregulation of the HUD population.\u003c/p\u003e \u003cp\u003eOne unanticipated result was that compared to the baseline, there was a significant ERS in the delta/theta band at the post-test of the real iTBS group during free viewing of neutral pictures and the activation in the left supramarginal gyrus was significantly lower at the post-test. These cases were not found while viewing unpleasant pictures. The supramarginal gyrus has been suggested related to attentional processes [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. In our experimental paradigm, to avoid the effect of unpleasant pictures on neutral pictures, the NV condition was presented fixedly first [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Possible explanations might be that iTBS enhanced the cognitive engagement of attentional processes to neutral stimuli or the specificity of the NV condition. Future studies could explore this issue based on our study.\u003c/p\u003e"},{"header":"5. Limitations and Prospects","content":"\u003cp\u003eSeveral limitations be considered. First, female participants were missing due to the hospital only admitted male patients. Gender differences were previously found in ER processing and the effectiveness of TMS intervention [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan additionalcitationids=\"CR85\" citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. Future studies could investigate whether the present results generalize to women with HUD. Second, the follow-up period didn\u0026rsquo;t include a sham iTBS group. Although numerous studies demonstrated the transdiagnostically long-term post-intervention effect of iTBS across multiple disorders [\u003cspan additionalcitationids=\"CR88 CR89\" citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e], and the pattern of ERP amplitudes during the follow-up period are very similar to the post-test phase, sham-controlled follow-up studies with different tracking intervals to explore the dynamic process of iTBS post-effectiveness merit further investigation. Third, the low signal-to-noise ratio of the DW may have some influence on the current results [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Although the results of our analysis have relatively satisfactory effect sizes, future studies could validate our findings by including more participants. Moreover, it is also merited to use higher spatial resolution techniques, e.g., fMRI, to explore the important role of frontal-limbic connectivity in TMS interventions for ER capability in patients with HUD or other SUDs.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis study demonstrates that iTBS could significantly improve the capability of HUD patients to use ER strategies with long-term effects, especially for expressive suppression. Effects on frontal-limbic connectivity might be a potential therapeutic mechanism of action. Improving the ER capability of HUD patients was related to reduced craving, merits further exploration in their withdrawal treatment and relapse prevention.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Regional Project of the National Natural Science Foundation of China (31960181, 32360213) and the scientific and technological innovation 2030 - the major project of the Brain Science and Brain-Inspired Intelligence Technology (2021ZD0200500).\u003c/p\u003e\n\u003cp\u003eThe authors would like to sincerely thank all the patients in the Lanzhou Drug Rehabilitation Hospital who participated in the current study; Wenwen Gao, Shaoqiong Wang, Yanyun Lu, Limei Xie, and other staff for their assistance; all the healthy control participants for their participation; and strong support from Prof. Tifei Yuan and his team from Shanghai Jiaotong University School of Medicine.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work\u0026nbsp;was conducted without any commercial or financial relationship that could be considered a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eUnited Nations publication. 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Inter-individual differences in the habitual use of cognitive reappraisal and expressive suppression are associated with variations in prefrontal cognitive control for emotional information: An event related fMRI study. Biol Psychol. 2013;92:433\u0026ndash;439.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi S, Xie H, Zheng Z, Chen W, Xu F, Hu X, et al. The causal role of the bilateral ventrolateral prefrontal cortices on emotion regulation of social feedback. Hum Brain Mapp. 2022;43:2898\u0026ndash;2910.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQiu X, He Z, Cao X, Zhang D. Transcranial magnetic stimulation and transcranial direct current stimulation affect explicit but not implicit emotion regulation: a meta-analysis. Behav Brain Funct. 2023;19:15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCulham JC, Kanwisher NG. Neuroimaging of cognitive functions in human parietal cortex. 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Psychother Psychosom. 2022;91:94\u0026ndash;106.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePhilip NS, Barredo J, Aiken E, Larson V, Jones RN, Shea MT, et al. Theta-Burst Transcranial Magnetic Stimulation for Posttraumatic Stress Disorder. Am J Psychiatry. 2019;176:939\u0026ndash;948.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"heroin use disorder, emotion regulation, expressive suppression, cognitive reappraisal, event-related synchronization, LORETA","lastPublishedDoi":"10.21203/rs.3.rs-6301058/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6301058/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDysfunctional Emotion regulation (ER) strategies may represent a promising treatment target for heroin use disorder (HUD). The therapeutic potential of transcranial magnetic stimulation to improve ER in HUD remains to be evaluated.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe present randomized sham-controlled pre-registered clinical trial determined the therapeutic efficacy of intermittent theta-burst transcranial magnetic stimulation (iTBS) over the left dorsolateral prefrontal cortex (DLPFC) for 10 days in 39 HUD patients (21 real iTBS; 18 sham). The ER performance-associated electroencephalographic indices obtained by event-related potential, time-frequency, source localization, and connectivity analysis techniques served as outcomes and were assessed pre- and post-intervention, and one month later follow-up for real iTBS group.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCompared to the sham iTBS group, the intervention group exhibited significantly more positive difference waves (DW) at 400\u0026ndash;600ms, which was significantly related to reduced craving. The real iTBS group specifically showed changes over the intervention, with enhanced event-related synchronization in the delta/theta band during viewing neutral pictures and expressing suppression of unpleasant pictures (US); lower activation in the left supramarginal gyrus and right posterior cingulate cortex (PCC) in the above conditions, separately; and lower connectivity between left DLPFC and right PCC under US condition. During 1000\u0026ndash;1200ms, their DW amplitudes at the follow-up period were significantly more negative than baseline.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe iTBS can improve the ER ability of HUD patients to use ER strategies, particularly expressive suppression, which are maintained following the intervention. Improved ER capability is associated with reduced craving, possibly due to enhanced frontal regulatory control.\u003c/p\u003e","manuscriptTitle":"Modulation of Emotion Regulation Deficits in Patients with Heroin Use Disorder by Intermittent Theta-Burst Transcranial Magnetic Stimulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-16 07:00:45","doi":"10.21203/rs.3.rs-6301058/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":"063326d4-1947-438f-bd70-66ff2255d3df","owner":[],"postedDate":"June 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":46235468,"name":"Health sciences/Diseases/Psychiatric disorders/Addiction"},{"id":46235469,"name":"Biological sciences/Psychology"}],"tags":[],"updatedAt":"2025-08-01T05:00:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-16 07:00:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6301058","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6301058","identity":"rs-6301058","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}