Right Hemispheric Broca's Homologue Mediates Pain-Depression Loop: fNIRS Evidence of Language Network Remodeling in Comorbid Chronic Pain and Depression

Right Hemispheric Broca's Homologue Mediates Pain-Depression Loop: fNIRS Evidence of Language Network Remodeling in Comorbid Chronic Pain and Depression | 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 Research Article Right Hemispheric Broca's Homologue Mediates Pain-Depression Loop: fNIRS Evidence of Language Network Remodeling in Comorbid Chronic Pain and Depression Jiaren Zheng, Ning Zhu, Jiaxi Huang, Hongyu Sun, Huimin Lv, Jing Zhang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6998159/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Chronic somatic pain (CSP) modulates the neuropathological mechanisms of depression, but how it reshapes neural circuits remains unclear. This study investigated CSP-specific prefrontal dynamic changes and their mediating role in pain-depression comorbidity. Methods 129 participants were recruited (43 each in Major Depressive Disorder with Chronic Somatic Pain group (MDD + CSP), MDD without Chronic Somatic Pain group (MDD-CSP), and Healthy Control group (HC)). Hemodynamic responses during a Verbal Fluency Task (VFT) and resting state were measured using functional near-infrared spectroscopy (fNIRS). Intergroup comparisons ( Kruskal-Wallis/Mann-Whitney U tests), mediation analysis (FDR-corrected), and Spearman correlation analysis were used to dissect interactions between neural and clinical indices. Results 1. Frontopolar (FP) Functional Abnormalities: Task-state hypofunction: Bilateral FP activation was reduced in all MDD groups (Channels Ch16/22/23/35/36, χ ² >7.287, p < 0.002). Resting-state hyperfunction: Right FP (Ch35/36) activation was higher in MDD + CSP than HC ( p < 0.012). 2. CSP-Specific Language Network Suppression: Compared to MDD-CSP, MDD + CSP showed reduced activation in the right hemispheric Broca's homologue (RH-Broca, Ch51, U = 577.5). Visual Analog Scale (VAS) scores negatively correlated with suppression in Broca's area/RH-Broca (Ch2/49/50/51/53, ρ < -0.5, p < 0.001). 3. Bidirectional Mediation Effect: RH-Broca (Ch53) mediated both the VAS→SDS path ( β = 1.17, 95% CI : 0.66–1.71) and SDS→VAS path ( β = 0.13, 95% CI : 0.08–0.18). 4. Brain Network Reorganization: During task, MDD groups showed increased Connection Density (CP, χ ²=12.268) and Local Efficiency (Gamma, χ ²=9.314). During rest, higher Small-Worldness (Sigma, U = 633) in MDD-CSP predicted treatment resistance. Conclusion CSP exacerbates depression via: ① Selective suppression of the language network (Broca's area/RH-Broca), ② Establishing a bidirectional pain-depression loop via RH-Broca (Ch53), and ③ Driving maladaptive neuroplasticity in prefrontal networks. RH-Broca activation is a potential biomarker for neuromodulation therapy in comorbid depression. Major depressive disorder Chronic pain fNIRS Broca's area homologue Neuroplasticity Mediation analysis Prefrontal cortex Figures Figure 1 Figure 2 Figure 3 Background Major Depressive Disorder (MDD) is a mental illness characterized by persistent low mood as its core symptom, clinically presenting as significant and enduring depressed mood, loss of interest, and anhedonia, often accompanied by cognitive impairment and somatic symptoms (e.g., chronic pain) (Baik et al. 2019; Dong et al. 2021). Epidemiological data indicate high prevalence, recurrence rates, and disability associated with the disease, with over 1 billion patients globally and a trend towards younger onset (Huang et al. 2019; Anna Manelis et al. 2019; Rijavec and Grubic 2012). Notably, approximately 65% of MDD patients also experience chronic somatic pain. This comorbidity not only delays diagnosis but also significantly increases clinical treatment complexity (Rijavec and Grubic 2012; Zhou et al. 2020)。 The pathological mechanisms underlying comorbid MDD and chronic pain involve multisystem interactions, including neurotransmitter (serotonin, norepinephrine, dopamine) system dysfunction (Bonilla-Jaime et al. 2022), prefrontal-amygdala neural circuit imbalance (Wei et al. 2025), neuroinflammatory activation (Kimura et al. 2022), and hypothalamic-pituitary-adrenal (HPA) axis dysregulation (Lee et al. 2024). Neuroimaging studies further confirm significant structural and functional brain alterations in comorbid patients, such as decreased neurotrophic factor levels (Ismail et al. 2024), prefrontal-amygdala emotion regulation dysfunction (Suárez-Pereira et al. 2022), heightened sensitivity in pain-related brain regions like the anterior cingulate cortex (Kashanian et al. 2022), and Default Mode Network (DMN) hyperactivity during rest (Schimmelpfennig et al. 2023)。 Functional near-infrared spectroscopy (fNIRS) has gained widespread use in psychiatric research due to its advantages of non-invasiveness, convenience, and low cost (Yang et al. 2022). Based on the "neurovascular coupling mechanism," it detects changes in oxygenated hemoglobin (HbO) levels to reflect local hemodynamic characteristics in the brain in real-time (Pinti et al. 2020). In clinical studies, fNIRS is often combined with cognitive tasks like working memory, word generation, Trail Making Test (TMT), and Verbal Fluency Test (VFT) to assess cortical function (Ho et al. 2020). Existing research shows that MDD patients commonly exhibit hypoactivation in the frontotemporal cortex during various cognitive tasks (Yeung and Lin 2021) ; weakened functional connectivity (FC) between brain regions during the transition from rest to TMT (Ho et al. 2020) ; and increased HbO levels in the left frontal mid-region in response to threatening stimuli (Nishizawa et al. 2019). Among these, the Verbal Fluency Test (VFT) is the most common paradigm, effectively assessing activation patterns in brain regions related to language and executive function, such as the prefrontal cortex and temporal lobe. This task requires participants to generate as many unique words as possible based on a given rule (e.g., starting with a specific Chinese character) within 30 seconds to 1 minute. Synchronously acquired fNIRS data, through hemodynamic changes, precisely reflect multidimensional cognitive abilities including memory, language expression, attention, and executive control (Tran et al. 2023). Studies consistently report cortical hypoactivation and weakened functional connectivity in MDD (Da et al. 2024; G. Li et al. 2024), significantly reduced HbO change amplitude in the right inferior frontal gyrus, abnormal language lateralization; negative correlations between bilateral frontal HbO responses to cognitive tasks and depression severity (Downey et al. 2019; Lyu et al. 2024) ; decreased hemodynamic response in the left precentral gyrus in suicide attempters, with response intensity in the right middle frontal gyrus negatively correlating with aggression and hopelessness (Ho et al. 2020)。 Despite rich findings using fNIRS in MDD research, studies specifically on MDD comorbid with chronic somatic pain (CSP) remain scarce, especially concerning how CSP modulates the neural circuits and mechanisms of MDD. Key unanswered scientific questions include: 1) The prefrontal dynamic changes during task and rest in comorbid patients and their mediating role in pain-depression comorbidity; 2) Whether these changes can provide neuroimaging evidence for personalized interventions like targeted repetitive transcranial magnetic stimulation (rTMS)? To address these gaps, this study employed a three-group design, enrolling 129 participants divided into: MDD with chronic somatic pain (MDD + CSP, chronic, somatic, VAS ≥ 4), MDD without chronic pain (MDD-CSP), and healthy controls (HC). Using fNIRS, neural activity in frontal and temporal cortices was recorded during a paradigm including a 55-second VFT and an 80-second resting state, while self-report scales assessed mood symptoms. This study aimed to investigate differences in neural activity during task and resting states across depressive subtypes and the role of these differences in the interaction between depressive symptoms (SDS) and pain intensity (VAS). Specifically, mediation analysis tested whether activation levels in specific brain regions mediated the relationship between VAS and SDS. This research aims to deepen the understanding of comorbidity mechanisms and provide a theoretical basis for optimizing clinical intervention strategies. Materials and Methods Subjects Participants and Grouping A case-control design was used, recruiting 129 participants divided into 3 groups (43 per group): The case group ( n = 86) consisted of MDD patients diagnosed by at least two attending physicians from the Neuro-Psychiatric Function Testing & Regulation Center / Center for Mental and Neurological Diseases, West China Xiamen Hospital, Sichuan University, between December 2023 and March 2024. Based on the presence of chronic somatic pain, they were divided into: MDD + CSP: Clear pain persisting/intermittently for ≥ 3 months, Visual Analog Scale (VAS) ≥ 4 (Y. Zhang et al. 2024). MDD-CSP: VAS < 4. The Healthy Control (HC) group ( n = 43) comprised healthy volunteers recruited during the same period, rigorously screened using the Structured Clinical Interview for DSM-IV Axis I Disorders, Non-Patient Edition (SCID-I/NP) to exclude physical illness, substance abuse history, and personal/family history of psychiatric disorders.; Inclusion and Exclusion Criteria Inclusion Criteria (Case Group): ① Met DSM-5 diagnostic criteria for MDD; ② Education level > 6 years; ③ No significant visual or auditory impairment, intact assessment ability; ④ Provided informed consent. Exclusion Criteria: ① Secondary psychiatric disorders (neurological/somatic disease-induced); ② Comorbid bipolar disorder, schizophrenia, or other severe mental disorders; ③ History of severe failure of vital organs (heart, lung, liver, kidney); ④ Uncontrolled hypertension, arrhythmia, severe coronary heart disease, poorly controlled diabetic complications; ⑤ Electroconvulsive therapy (ECT) within the past 6 months; ⑥ Antibiotic/hormone/psychotropic medication use within the past 30 days; ⑦ Pregnant or lactating women; ⑧ Poor compliance preventing study participation. Ethics This study was approved by the Biomedical Huali Review Committee of West China Xiamen Hospital, Sichuan University (Approval No. [2024] Review (004)). It adhered to the principles of the Declaration of Helsinki. The study was registered at the Chinese Clinical Trial Registry (Registration No.: ChiCTR2500098790, Registration date: March 13, 2025). Written informed consent was obtained from all participants or their legal guardians before study commencement. Clinical Assessment Basic Information Collection Demographic data were recorded, including sex (biological), age, illness duration, and nature/impact of somatic pain. Symptom Assessment Depressive Symptoms: Assessed using the Self-Rating Depression Scale (SDS). This 20-item scale uses a 1–4 scoring per item. The standard score cut-off is set at 50: 50–59 indicates mild depression, 60–69 moderate depression, ≥ 70 severe depression (Wu et al. 2024). Pain Symptoms: Assessed using the Visual Analog Scale (VAS). The VAS is a 10 cm horizontal line where 0 indicates "no pain" and 10 indicates "worst imaginable pain." Participants mark their pain intensity on the line. Scores are categorized: 1–3 mild pain, 4–6 moderate pain, 7–10 severe pain (Y. Li et al. 2023). fNIRS Data Acquisition Experimental Procedure Participants sat comfortably for 5 minutes in a dimly lit fNIRS assessment room (25 ± 1°C) to acclimate and reduce tension. They then wore the fNIRS cap. Sound volume was set to 60 dB. Participants were instructed to close their eyes, clear their minds, avoid limb movements, listen attentively to system prompts, and strictly follow task instructions. The assessor turned off room lights and began collecting fNIRS data for 150 seconds. To prevent habituation, each trial was performed only once. Experimental Paradigm A Verbal Fluency Task (VFT) paradigm lasting 150 seconds was used, divided into 3 phases: 1. Resting Period 1 (30 sec): Participants counted sequentially from 1 to 16 following a recorded voice. 2. Task Period (60 sec): Participants generated words for 4 Chinese characters presented auditorily in a block-randomized order (high-frequency characters from the Modern Chinese Word Frequency Dictionary, e.g., "上/shàng", "时/shí", "说/shuō", "家/jiā"). Each character was played, followed immediately by a 15-second word generation period. Participants generated as many unique words as possible starting with the given character. 3. Resting Period 2 (60 sec): Participants counted sequentially from 1 to 32 following a recorded voice. See Fig. 1. Data Acquisition A BS-3000 fNIRS system (Zilian Hongkang, China) was used, acquiring data at dual wavelengths (690nm/830nm) and a 20Hz sampling rate. The probe array consisted of 16 sources and 16 detectors (3 cm spacing), forming 53 channels. Based on EEG 10–20 system landmarks (F3/F4/Fz), probes were registered to MNI space using NIRSite software (Mir-Moghtadaei et al. 2022), covering: premotor cortex, supplementary motor area, Broca's area, dorsolateral prefrontal cortex. Oxygenated hemoglobin (HbO₂) concentration was calculated using the modified Beer-Lambert law (Scholkmann et al. 2014) with Differential Pathlength Factors (DPF 690 = 5.8, DPF 830 = 4.9). Average HbO₂ concentration (Avg-HbO) was extracted for the task period (35-90s) and resting periods (5-30s pre-task, 95-150s post-task). fNIRS Data Preprocessing Preprocessing was performed in Matlab2013b using Homer2 and SPM toolkits. Steps included: ① Removal of channels with raw light intensity standard deviation > 6% or HbO₂ peak change > 0.5 µM; ② Band-pass filtering (4th order Butterworth filter, 0.008-0.2 Hz); ③ Principal Component Analysis (PCA) on all HbO₂ channels to remove the first principal component (explaining > 95% variance); ④ Segment extraction for task state (35-90s) and resting state (5-30s pre-task, 95-150s post-task) (F. Zhang et al. 2023). Functional Connectivity (FC) Analysis Using FC_NIRS software, HbO₂ concentration time courses were extracted for the task state (35-90s; sliding window 30s, step 1s) (Z. Li et al. 2015) and resting states (pre-task 5-30s, post-task 95-150s). Global signal regression was performed per channel. Pearson correlation coefficients ( r ) were calculated between channels within each window. Fisher Z-transformation was applied: \ $ Z = \frac{1}{2} \ln \left( \frac{1 + r}{1-r} \right)\ $ , with Z-values representing functional connection strength (Wen et al. 2023). Statistical Analysis SPSS 24.0 (IBM, USA) was used. All tests were two-tailed (α = 0.05). Demographic & Clinical Variables: Categorical variables reported as frequency ( n ), compared using χ ² tests. Continuous variables reported as Mean ± SD. Normality assessed via Kolmogorov-Smirnov test and Q-Q plots; homogeneity of variance assessed via Brown-Forsythe test. Age: Normally distributed but heteroscedastic; intergroup comparison used Welch test. SDS & VAS (Case groups): Non-normally distributed and heteroscedastic; compared using Mann-Whitney U test. fNIRS Data (Activation & Network): Non-normally distributed and heteroscedastic. Overall intergroup comparison used Kruskal-Wallis test. Significant channels underwent post-hoc pairwise Mann-Whitney U tests (3 comparisons) with Bonferroni correction (adjusted significance threshold p ≤ 0.0167). Mediation Effect Analysis: Bootstrap -based mediation test (5,000 resamples) examined whether task/rest activation levels and network features mediated the relationship between SDS and VAS. Sex, age, and illness duration (DOI) were covariates. Significance ( p ) of mediation effects was FDR-corrected ( Benjamini-Hochberg , critical q = 0.05). Indirect effect estimates and 95% Bootstrap CI were reported. Correlation Analysis: Spearman rank correlation explored associations between HbO₂ signals (task/rest activation, network features) and demographic/clinical variables. Bonferroni correction applied (adjusted p ≤ 0.01). Visualization: BrainNet Viewer, FC_NIRS, and GraphPad Prism 8 were used. Results Demographic Characteristics and Clinical Variables This study included 129 participants (Case group: 35M, 40.26 ± 17.749y; 51F, 39.86 ± 17.351y; HC group: 19M, 45.21 ± 11.028y; 24F, 38.58 ± 13.351y). No significant differences were found between groups for age ( p = 0.126) or sex distribution ( p = 0.512). Illness duration also showed no significant difference between MDD subgroups ( p = 0.866). SDS scores were significantly higher in MDD-CSP than MDD + CSP ( p < 0.0001). See Table 1. Table 1 Demographic and Clinical Characteristics: Depressive Disorder Subgroups (MDD + CSP, MDD-CSP) vs. Healthy Controls [2024 Cohort] Group n Sex(F/M) Age (y) SDS DOI (y) VAS Pain Intensity (NO/ Mild/ Moderate/ Severe) MMD + CSP 43 20/23 43.35 ± 16.194 71.40 ± 7.271 3.57 ± 3.106 5.58 ± 1.384 0/0/31/12 MDD-CSP 43 15/28 36.70 ± 18.127 61.42 ± 8.547 4.82 ± 5.566 0.63 ± 0.817 23/20/0/0 HC 43 19/24 41.51 ± 12.682 - - - - χ 2 / F / U 1.338 △ 4.145 ◎ 354.50 ●*** 905.000 ● - - Age was analyzed by Welch test (◎). Sex distribution was analyzed by χ ² tests (△). DOI (Duration of Illness) and SDS (Self-Rating Depression Scale) were analyzed by Mann-Whitney U test ( U /●). VAS: Visual Analogue Scale. HC: Healthy control group. MDD + CSP: Depressive disorder with chronic somatic pain. MDD - CSP: Group of pure depressive disorder. ***: p ≤ 0.0001. fNIRS Activation Differences During VFT in MDD Subgroups fNIRS compared neural activity during VFT execution across MDD + CSP, MDD-CSP, and HC. 1. Brain Region Activation Differences: General MDD Feature: All MDD patients showed significantly reduced bilateral FP activation vs HC (Ch16: χ ² = 12.246, p = 0.002; Ch22: χ ² = 15.684, p < 0.0001; Ch23: χ ² = 11.537, p = 0.003; Ch35: χ ² = 15.677, p < 0.0001; Ch36: χ ² = 9.032, p = 0.005). Subgroup-Specific Features: MDD-CSP vs HC: Only R-FP (Ch37, U = 623.00) showed significant hypoactivation. MDD + CSP: Exhibited 1) Widespread bilateral FP hypoactivation (Ch15: U = 575.50; Ch27: U = 617.00; Ch30: U = 574.5; Ch41: U = 563.00; Ch43: U = 621.50); 2) Reduced activation in language-related regions (Broca's area/RH-Broca: Ch08: U = 568.50; Ch44: U = 636.00; Ch49: U = 623.00); 3) Significantly lower activation in RH-Broca (Ch51, U = 577.5) compared to MDD-CSP. 2. Brain Network Feature Differences: All MDD groups showed increased Connection Probability (CP, χ ² = 12.268, p = 0.002), Normalized Clustering Coefficient (Gamma, χ ² = 9.314, p = 0.009), and Local Efficiency (Eloc, χ ² = 11.981, p = 0.003) vs HC. See Fig. 2 for visualization. fNIRS Differences During Resting State in MDD Subgroups fNIRS compared resting-state neural activity across the three groups. 1. Brain Region Activation Differences: General MDD Feature: All MDD patients showed significantly enhanced R-FP activation (Ch35, χ ² = 10.875, p = 0.004) vs HC. Subgroup-Specific Feature: MDD + CSP showed higher activation in R-FP (Ch36, U = 632.00) vs HC. 2. Brain Network Feature Differences: General MDD Feature: All MDD groups showed increased CP ( χ ² = 15.567, p < 0.0001) and Eloc ( χ ² = 14.168, p = 0.001) vs HC. MDD-CSP Feature: Increased Gamma ( U = 519.00), Normalized Path Length (Lambda, U = 573.00), and Small-Worldness (Sigma, U = 633.00) vs HC. See Fig. 2 for visualization. Mediating Effects of Brain Activation and Functional Network Connectivity on Depression and Chronic Somatic Pain Mediation analysis (FDR-corrected) examined the role of task/rest activation and FC between SDS and VAS. Significant Mediation During Task (FDR-corrected): A significant bidirectional mediation effect was observed in RH-Broca (Ch53): Path 1 (VAS → Ch53 → SDS): Increased pain (VAS↑) → Reduced Ch53 activation (a = -0.16, p < 0.0001) → Worsened depression (SDS↑) (b = -7.54, p < 0.0001; Indirect effect = 1.17, 95% CI : 0.66, 1.71, p < 0.0001). Path 2 (SDS → Ch53 → VAS): Worsened depression (SDS↑) → Reduced Ch53 activation (a = -0.06, p < 0.0001) → Increased pain perception (VAS↑) (b = -2.16, p < 0.0001; Indirect effect = 0.13, 95% CI : 0.08, 0.18, p < 0.0001). Other Channels During Task (Uncorrected Significance): Mediation observed in: VAS→Brain Activation→SDS: L-FP (Ch16, p = 0.038), R-FP (Ch41, p = 0.048; Ch43, p = 0.0392), RH-Broca (Ch49, p = 0.0232; Ch50, p = 0.0104); SDS→Brain Activation→VAS: R-FP (Ch43, p = 0.022), RH-Broca (Ch50, p = 0.0028). No Significant Mediation: Found for resting-state activation or FC metrics ( p > 0.05). The bidirectional effect in Ch53 during task indicates: ① Pain sensitivity (VAS) indirectly exacerbates depressive symptoms (SDS) by suppressing this region (large effect: ab ≈ 1.17); ② Depressive symptoms (SDS) indirectly intensify pain perception (VAS) by weakening this region's activity (small effect: ab ≈ 0.13). See Fig. 3. Correlation Analysis of fNIRS-HbO₂ with Demographic/Clinical Variables Spearman correlation examined links between fNIRS-HbO₂ signals and variables. 1. During VFT: Sex: Females showed reduced Broca's area activation (Ch03, p = 0.005) and enhanced left FEF activation (L-FEF, Ch24, p = 0.005). Age: Older age correlated with reduced left DLPFC activation (L-DLPFC, Ch14, p = 0.008). Illness Duration (DOI): Longer DOI correlated with reduced bilateral DLPFC activation (Ch17, p = 0.003; Ch34, p = 0.004). Pain (VAS): Higher VAS correlated with reduced activation in Broca's area/RH-Broca (Ch02, p = 0.002; Ch49, p = 0.006; Ch50, p < 0.0001; Ch51, p < 0.0001; Ch53, p < 0.0001) and R-FP (Ch41, p = 0.002; Ch43, p = 0.005). Depression (SDS): Higher SDS correlated with reduced activation in bilateral SMA + PMC (Ch01, p = 0.007; Ch47, p < 0.0001; Ch52, p = 0.001), R-FP (Ch41, p = 0.01), and RH-Broca (Ch50, p = 0.007; Ch53, p < 0.0001). 2. Resting State: Sex: Females showed reduced bilateral FP (Ch19, p = 0.007; Ch48, p = 0.004) and Broca's area activation (Ch02, p < 0.0001). Age: Older age correlated with enhanced bilateral FP activation (Ch19, p = 0.006; Ch36, p = 0.004). See Table 2. Table 2 Correlation Analysis of Demographic Characteristics and Clinical lndicators with Resting - State/VFT Task fNIRS - HbO2 in Three Groups (HC, MDD-CSP, MDD + CSP) States Factors Sex Age ( y ) DOI ( y ) VAS SDS Task - Based Ch01 0.050 -0.031 -0.138 -0.048 -0.290 * Ch02 -0.006 -0.101 -0.074 -0.326 * -0.217 Ch03 -0.246 * -0.103 -0.128 0.165 -0.13 Ch14 -0.026 -0.232 * -0.254 0.103 -0.091 Ch17 -0.017 -0.059 -0.313 * -0.158 -0.107 Ch24 0.248 * -0.053 0.141 -0.014 -0.154 Ch34 -0.109 -0.151 -0.305 * -0.149 -0.159 Ch41 -0.072 -0.133 -0.115 -0.326 * -0.275 * Ch43 0.002 -0.107 -0.184 -0.298 * -0.214 Ch47 -0.064 0.003 0 -0.067 -0.292 * Ch49 0.017 -0.073 -0.116 -0.295 * -0.156 Ch50 -0.158 -0.048 -0.002 -0.374 *** -0.291 * Ch51 0.073 -0.094 -0.063 -0.390 *** 0.049 Ch52 -0.096 -0.051 -0.125 -0.069 -0.344 ** Ch53 -0.044 -0.077 -0.047 -0.481 *** -0.538 *** Resting State Ch02 -0.329 *** -0.006 -0.122 0.08 -0.109 Ch19 -0.235 * 0.239 * -0.012 -0.042 -0.063 Ch36 -0.176 0.254 * 0.125 0.138 -0.079 Ch48 -0.249 * 0.013 -0.173 -0.029 -0.131 Demographic: full sample ( n = 129). Clinical analysis: patient groups only (MDD-CSP + MDD + CSP, n = 86). Age is counted in years. Sex including male and female. DOI: Duration of Illness, recorded in years. VAS: Visual Analogue Scale. SDS: Self-Rating Depression Scale. HC: Health control group. MDD + CSP: Depressive disorder with chronic somatic pain. MDD - CSP: Group of pure depressive disorder. A Bonferroni -corrected significance threshold of p ≤ 0.01 (0.05 / 5 tests) was adopted. *: 0.01 ≤ p < 0.001, **: 0.001 ≤ p < 0.0001, ***: p ≤ 0.0001. Discussion Using fNIRS, this study systematically characterized neural activity during task (VFT) and resting states in MDD patients with and without chronic somatic pain (CSP), revealing commonalities and differences in neural mechanisms, and elucidating the pivotal hub role of the right hemispheric Broca's homologue (RH-Broca, Ch53) in pain-depression comorbidity. Key findings provide important insights for understanding comorbidity mechanisms and developing targeted interventions. Bidirectional Frontopolar (FP) Dysfunction: A Transdiagnostic Core Mechanism of Depression This study confirmed widespread bilateral FP hypoactivation during VFT in MDD patients (e.g., Ch16, Ch22, Ch23) compared to HC, consistent with prior research (Catalano et al. 2025; Yeung and Lin 2021), supporting prefrontal cortex (PFC, including FP) hypofunction as a core neural mechanism of depression. As a higher cognitive center, PFC dysfunction creates a bidirectional vicious cycle with emotion dysregulation and executive impairment: chronic mood disturbance leads to PFC neurodegeneration, which in turn exacerbates symptoms (Jones and Graff-Radford 2021; Suárez-Pereira et al. 2022). Notably, patients exhibited enhanced R-FP activation (Ch35/36) during rest, contrasting with task hypoactivation. This may reflect impaired DMN suppression (Sun et al. 2024a), promoting rumination and negative self-focus (Katayama et al. 2023; L. Zhang et al. 2025). MDD + CSP showed more extensive task hypoactivation, suggesting CSP may exacerbate prefrontal dysfunction by increasing cognitive load and pain interference, supporting the hypothesis of a unique neural basis for pain-depression comorbidity (Antoniou et al. 2023; Y. Zhang et al. 2024). Neural Modulatory Effect of Chronic Pain (CSP): Language Network Suppression and the Right Broca Hub Language Network Specific Suppression: Beyond more pronounced FP hypoactivation (e.g., Ch15, Ch27, Ch30), MDD + CSP exhibited additional suppression in language-related regions (Broca's area/RH-Broca: Ch08, Ch44, Ch49). This suggests CSP may compete for prefrontal resources via spinothalamocortical pathways, leading to reduced cognitive flexibility and inadequate language processing compensation (e.g., psychomotor retardation, alexithymia). The negative correlation between VAS and RH language activation (da Costa et al. 2025) underscores pain's direct damaging effect on language/prefrontal networks. Ch53 (RH-Broca) in Bidirectional Pain-Depression Mediation: During VFT, RH-Broca (Ch53) activation significantly mediated the bidirectional relationship between VAS and SDS (FDR-corrected): Path 1 (Large Effect): Pain exacerbation → Ch53 suppression → Depression worsening (effect = 1.17). Path 2 (Small Effect): Depression worsening → Ch53 suppression → Pain intensification (effect = 0.13). Ch53 as the "Pain-Depression Circuit" Hub: The RH-Broca homologue (right inferior frontal gyrus, rIFG) integrates emotion and modulates pain: Anterior rIFG regulates DMN and Salience Network (SN), influencing negative emotion processing; posterior rIFG connects to somatosensory cortex, involved in descending pain inhibition. Reduced Ch53 activation may disrupt these functions, creating a vicious cycle of mutual pain-depression amplification (Borst et al. 2024; A. Manelis et al. 2022; Peng et al. 2024; Viellard et al. 2024; Zhu et al. 2018). Asymmetry of Bidirectional Effects: The pain→depression path was stronger (effect 1.17 vs 0.13). Chronic pain, by suppressing rIFG, weakens inhibition of negative emotions and pain perception, significantly worsening depression ("pain-driven depression"). The depression→pain path effect was weaker; depression may indirectly intensify pain via rIFG dysfunction but likely requires co-occurring mechanisms (e.g., inflammatory factors, limbic activation) (Cox et al. 2025; De Ridder, Adhia, and Vanneste 2021; Guida et al. 2022; Jiang et al. 2025; M. Li et al. 2025). Brain Network Reorganization in Depression: Efficiency Compensation and Chronic Pain Interference During task, MDD patients showed enhanced local network function: increased CP, Gamma, and Eloc, suggesting compensatory strengthening of local connections for hypoactivated regions (Mısır, Alıcı, and Kocak 2023; Pan et al. 2020). However, this compensation may impair global information integration efficiency, worsening cognitive resource allocation imbalance. MDD-CSP showed significantly elevated resting-state Small-Worldness (Sigma, U = 633), aligning with the "hyper-optimized network hypothesis" (Jung and Han 2024). Elevated Sigma reflects an imbalance between local clustering and global integration: while local processing efficiency (Gamma) compensatorily increases, rigid network topology limits cross-module information exchange, reducing treatment response (Sun et al. 2024b). For instance, Sun et al. (2024) found patients with baseline Sigma > 1.2 had a 4-fold increased risk (OR = 4.2) of non-response to SSRIs (Sun et al. 2024a), and Saccaro et al. (2024) linked high Sigma to long illness duration and prefrontal-hippocampal circuit plasticity damage (Saccaro et al. 2024). This study extends this model, suggesting MDD patients without pain comorbidity are more prone to developing a treatment-resistant subtype characterized by high Sigma, while CSP may mask this phenotype by disrupting network balance (e.g., unchanged Sigma in MDD + CSP). Correlations Between Neural Activity and Clinical Variables 1. Sex Differences: Task: Reduced Broca's area (Ch03) and enhanced L-FEF (Ch24) activation in females may relate to internalizing symptom (e.g., rumination) propensity. Rest: Reduced bilateral FP (Ch19/48) and Broca's (Ch02) activation in females supports sex-specific depression neurobiology (Bossenbroek et al. 2022; Verhelst et al. 2024). 2. Age & Illness Duration: Age-related reduction in L-DLPFC (Ch14) activation suggests aging exacerbates cognitive control decline. Reduced bilateral DLPFC (Ch17/34) activation with longer DOI reflects neuroplasticity decline from disease chronicity (Saccaro et al. 2024). 3. Depression (SDS): Correlation with reduced activation in motor preparation areas (SMA + PMC, Ch01/47/52) and RH-Broca (Ch50/53) may underlie psychomotor retardation and verbal fluency decline in comorbid patients. 4. Depression Underestimation in Comorbid Group: The "higher depression" in MDD-CSP stems from isolated damage to prefrontal emotion regulation circuits (Oliva et al. 2025), not activating the shared rIFG pain-depression pathway. In MDD + CSP, CSP triggers rIFG-mediated neuroinflammation, "diluting" pure depressive expression with somatic symptoms (Y. Zhang et al. 2024). Research Significance and Clinical Implications This study supports a "Frontal-Language Circuit Dysfunction Model" for pain-depression comorbidity: 1) CSP damages RH language network → emotion processing impairment → depression worsening; 2) DMN hyperactivation (resting FP activity) → weakened cognitive control resources → enhanced pain perception; 3) Network efficiency compensation (increased CP/Eloc) represents early adaptation, potentially failing with disease progression. Clinical Implications: fNIRS can dynamically monitor neural function in MDD subtypes (e.g., Ch36/Ch53), guiding stratified treatment. Neuromodulation (rTMS/tDCS) targeting RH-Broca (Ch53) may simultaneously alleviate pain and depression (Liu et al. 2024). Female patients require focused attention on language region function preservation. Limitations and Future Directions 1. Cross-sectional design cannot establish causal sequence; longitudinal tracking of pain-depression-brain function dynamics needed. 2. Limited fNIRS spatial resolution; deep brain regions (e.g., insula) require validation with fMRI. 3. Pain subtype heterogeneity (neuropathic/nociceptive) not distinguished, potentially affecting mechanism interpretation. 4. Medication carryover effects: Despite ≥ 30-day washout, prior medication history may have residual neuroplasticity effects. Future Directions: Combine multimodal imaging (fMRI-EEG) for longitudinal intervention tracking, controlling for pain subtypes and medication confounders. Conclusion In summary, this fNIRS study revealed characteristic differences in frontopolar function, language network involvement, and global brain network efficiency between MDD with and without CSP. It identified, for the first time, the critical hub role of the right inferior frontal gyrus in a bidirectional pain-depression loop. These findings provide crucial empirical evidence and theoretical foundation for understanding comorbidity mechanisms and developing neuroimaging-based subtyping diagnostics and targeted interventions. Future longitudinal studies incorporating multimodal techniques will help elucidate causal mechanisms and optimize treatment. Declarations Funding: This work was supported by the National Natural Science Foundation of China (Grant No. 81873354). Author Contribution Author Contributions Jiaren Zheng: Conceptualization, Methodology, Writing (First Author) Ning Zhu: Formal Analysis, Investigation, Visualization (Co-First Author) Jiaxi Huang: Investigation, Writing Hongyu Sun, Zhenhua Li: Data Curation Huimin Lü, Jing Zhang, Jing Li, Bo Zheng, Manyu Zhang: Writing–Review & Editing Yibin Xie: Designed the research, Supervision. Zhong Zheng: Designed the research, Supervision, Funding Acquisition Corresponding author: Zhong Zheng Co-corresponding authors: Jiaren Zheng and Yibin XieThis manuscript is original, unpublished, and not under consideration elsewhere. All authors declare no conflicts of interest. Data Availability The datasets generated and analyzed during this study are not publicly available but are available from the corresponding author upon reasonable request. References Antoniou, Georgia, Emilie Lambourg, J. Douglas Steele, and Lesley A. Colvin. 2023. ‘The Effect of Adverse Childhood Experiences on Chronic Pain and Major Depression in Adulthood: A Systematic Review and Meta-Analysis’. British Journal of Anaesthesia 130 (6): 729–46. https://doi.org/10.1016/j.bja.2023.03.008. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6998159","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":483154027,"identity":"57e2801e-93f6-4031-bda0-6ba71f5c5213","order_by":0,"name":"Jiaren Zheng","email":"","orcid":"","institution":"West China Xiamen Hospital, Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Jiaren","middleName":"","lastName":"Zheng","suffix":""},{"id":483154028,"identity":"da88b61a-7e89-4f3d-befc-4b29cfcf991c","order_by":1,"name":"Ning Zhu","email":"","orcid":"","institution":"West China Hospital of Sichuan 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University","correspondingAuthor":false,"prefix":"","firstName":"Huimin","middleName":"","lastName":"Lv","suffix":""},{"id":483154032,"identity":"d98a1c33-f5be-4b25-9ae1-ff32062d6935","order_by":5,"name":"Jing Zhang","email":"","orcid":"","institution":"West China Xiamen Hospital, Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Zhang","suffix":""},{"id":483154033,"identity":"783817c4-6328-4793-a7bc-d2f54b3c6080","order_by":6,"name":"Zhenhua Li","email":"","orcid":"","institution":"West China Xiamen Hospital, Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Zhenhua","middleName":"","lastName":"Li","suffix":""},{"id":483154034,"identity":"c2a394f4-d3d0-4a2c-975e-73a3406d8c75","order_by":7,"name":"Manyu Zhang","email":"","orcid":"","institution":"West China Xiamen Hospital, Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Manyu","middleName":"","lastName":"Zhang","suffix":""},{"id":483154035,"identity":"38568fb3-2652-4310-8fc8-e2be3a2e05d1","order_by":8,"name":"Jing Li","email":"","orcid":"","institution":"West China Xiamen Hospital, Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Li","suffix":""},{"id":483154036,"identity":"95bbe0c9-04ca-44a7-92e5-75c0affba00d","order_by":9,"name":"Bo Zheng","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Bo","middleName":"","lastName":"Zheng","suffix":""},{"id":483154037,"identity":"37006729-13dd-4d6d-b373-936c40082e15","order_by":10,"name":"Yibin Xie","email":"","orcid":"","institution":"Xiamen Xianyue Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yibin","middleName":"","lastName":"Xie","suffix":""},{"id":483154038,"identity":"a5601d31-fd8b-49da-a659-ec45303594ad","order_by":11,"name":"Zhong Zheng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYDACCTB5AIgZGx98+GHDw8/fQLQW5mbDmT1pMpIzDhCthb1NmoPtsI1BQwJ+HfKzm489/PLnjpw5/8I2aQae8zwGDAcYP3zMwa2Fcc6xdGMZnmfGljMeNlsXWNzmMWduYJacuQ23FmaJHDNpCYnDiRtuHGy8PYPnNo9lwwE2Zl48Wtgk8r9JSxiAtTRI87Cd4zE4kIBfC49EDpvkhwSglvONTUAtBwhrkZBIM5NmOHDY2OAGIyiQk3kkZxxsxusX+RnJzyR//DksZ3D++ENgVNrZ8/M3H/zwEY8WcBDwgO1LgPEZG/CrByn5ASL5DxBUOApGwSgYBSMUAABU0lhptMmExQAAAABJRU5ErkJggg==","orcid":"","institution":"West China Xiamen Hospital, Sichuan University","correspondingAuthor":true,"prefix":"","firstName":"Zhong","middleName":"","lastName":"Zheng","suffix":""}],"badges":[],"createdAt":"2025-06-28 13:38:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6998159/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6998159/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86660313,"identity":"2bb954c8-63b0-4321-bcf1-8bd4e123ca4f","added_by":"auto","created_at":"2025-07-14 10:34:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":23942494,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Channel locations. (b) Verbal Fluency Task.\u003c/p\u003e\n\u003cp\u003eFP: Frontal Pole.\u003c/p\u003e\n\u003cp\u003eFEF: Frontal Eye Fields.\u003c/p\u003e\n\u003cp\u003eDLPFC: Dorsolateral Prefrontal Cortex.\u003c/p\u003e\n\u003cp\u003eBA: Broca's Area.\u003c/p\u003e\n\u003cp\u003ePMC: Premotor Cortex.\u003c/p\u003e\n\u003cp\u003eSMA: Supplementary Motor Area.\u003c/p\u003e","description":"","filename":"Figure.1.png","url":"https://assets-eu.researchsquare.com/files/rs-6998159/v1/ec56d8839b39c100cf4c0b21.png"},{"id":86658630,"identity":"cc6dbb1c-11fa-43a9-88b2-a883f41dd384","added_by":"auto","created_at":"2025-07-14 10:26:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":18520366,"visible":true,"origin":"","legend":"\u003cp\u003e1) Comparison of fNIRS Activation (HbO2) During VFT: (a) HC vs. MMD-CSP. (b) HC vs. MMD+CSP. (c) MMD-CSP vs. MMD+CSP. (d) Comparative Map of Statistcally Significant Channels. 2) Comparison of fNIRS Activation (HbO2) During Rest-state: (e) HC vs. MMD-CSP. (f) HC vs. MMD+CSP. (g) Comparative Map of Statistcally Significant Channels (Ch 27). 3) (h) Comparative analysis of task-based and Resting-State fNIRS functional connectivity across groups.\u003c/p\u003e\n\u003cp\u003eVFT: Verbal Fluency Task.\u003c/p\u003e\n\u003cp\u003eFC: Functional Connectivity.\u003c/p\u003e\n\u003cp\u003eCP: Connection Probability.\u003c/p\u003e\n\u003cp\u003eLP: Link Persistence.\u003c/p\u003e\n\u003cp\u003eGamma: Normalized Clustering Coefficient.\u003c/p\u003e\n\u003cp\u003eLambda: Normalized Path Length.\u003c/p\u003e\n\u003cp\u003eSigma: Small - Worldness.\u003c/p\u003e\n\u003cp\u003eEloc: Local Efficiency.\u003c/p\u003e\n\u003cp\u003eEg: Global Efficiency.\u003c/p\u003e\n\u003cp\u003eHC: Health control group.\u003c/p\u003e\n\u003cp\u003eMDD +CSP: Depressive disorder with chronic somatic pain.\u003c/p\u003e\n\u003cp\u003eMDD - CSP: Group of pure depressive disorder.\u003c/p\u003e\n\u003cp\u003eStatistical Analysis: Intergroup comparisons were performed using the \u003cem\u003eKruskal-Wallis\u003c/em\u003e test, followed by post hoc \u003cem\u003eMann-Whitney U\u003c/em\u003e tests for pairwise comparisons. A Bonferroni correction was applied for multiple comparisons, with the significance threshold set at \u003cem\u003ep\u003c/em\u003e ≤ 0.0167.\u003c/p\u003e","description":"","filename":"Figure.2.png","url":"https://assets-eu.researchsquare.com/files/rs-6998159/v1/b233a2a2f9535609863dce7a.png"},{"id":86662309,"identity":"ec44c48e-6a70-472e-8678-65bda98794a6","added_by":"auto","created_at":"2025-07-14 10:42:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":10439540,"visible":true,"origin":"","legend":"\u003cp\u003eMediation effect analysis of VAS on SDS via multi-channel activation during VFT:\u003c/p\u003e\n\u003cp\u003e(a) VAS→Channel Activation→SDS.\u003c/p\u003e\n\u003cp\u003e(b) SDS→Channel Activation→VAS.\u003c/p\u003e\n\u003cp\u003e(c) Channel 53 Localization(MNI).\u003c/p\u003e\n\u003cp\u003e(d) SDS→RH-Broca (Ch53) →VAS.\u003c/p\u003e\n\u003cp\u003e(e) VAS→RH-Broca (Ch53) →SDS.\u003c/p\u003e\n\u003cp\u003e(f) SDS→VAS Bootstrap Distribution.\u003c/p\u003e\n\u003cp\u003e(g) VAS→SDS Bootstrap Distribution.\u003c/p\u003e\n\u003cp\u003eVAS: Visual Analogue Scale.\u003c/p\u003e\n\u003cp\u003eSDS: Self-Rating Depression Scale.\u003c/p\u003e\n\u003cp\u003eVFT: Verbal Fluency Task.\u003c/p\u003e\n\u003cp\u003eAge is counted in years.\u003cbr\u003e\nSex including male and female.\u003cbr\u003e\nDOI: Duration of Illness, recorded in years.\u003c/p\u003e\n\u003cp\u003eFDR: False Discovery Rate.\u003c/p\u003e\n\u003cp\u003eMNI: Montreal Neurological Institute.\u003c/p\u003e\n\u003cp\u003eStatistical Analysis: \u003cem\u003eBootstrap-based\u003c/em\u003e mediation analysis (5,000 resamples) was employed to examine the mediating roles of task-/resting-state activation levels and brain network features in the relationship between \u003cem\u003eSDS\u003c/em\u003e and \u003cem\u003eVAS\u003c/em\u003e, with Sex, Age, and DOI as covariates. The significance \u003cem\u003ep\u003c/em\u003e-values of the mediation effects were adjusted via the Benjamini-Hochberg False Discovery Rate (FDR) method (critical value \u003cem\u003eq\u003c/em\u003e = 0.05). We reported the estimate of the indirect effect along with its 95% \u003cem\u003eCI\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"Figure.3.png","url":"https://assets-eu.researchsquare.com/files/rs-6998159/v1/dacfa43b6d88e31b79e77f16.png"},{"id":86665100,"identity":"e03e7d8a-29f5-4cb5-8534-da37fd78cde1","added_by":"auto","created_at":"2025-07-14 10:59:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":41053985,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6998159/v1/2403438c-c7ca-4984-99db-1dc226fdb72c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Right Hemispheric Broca's Homologue Mediates Pain-Depression Loop: fNIRS Evidence of Language Network Remodeling in Comorbid Chronic Pain and Depression","fulltext":[{"header":"Background","content":"\u003cp\u003eMajor Depressive Disorder (MDD) is a mental illness characterized by persistent low mood as its core symptom, clinically presenting as significant and enduring depressed mood, loss of interest, and anhedonia, often accompanied by cognitive impairment and somatic symptoms (e.g., chronic pain) (Baik et al. 2019; Dong et al. 2021). Epidemiological data indicate high prevalence, recurrence rates, and disability associated with the disease, with over 1\u0026nbsp;billion patients globally and a trend towards younger onset (Huang et al. 2019; Anna Manelis et al. 2019; Rijavec and Grubic 2012). Notably, approximately 65% of MDD patients also experience chronic somatic pain. This comorbidity not only delays diagnosis but also significantly increases clinical treatment complexity (Rijavec and Grubic 2012; Zhou et al. 2020)。\u003c/p\u003e\u003cp\u003eThe pathological mechanisms underlying comorbid MDD and chronic pain involve multisystem interactions, including neurotransmitter (serotonin, norepinephrine, dopamine) system dysfunction (Bonilla-Jaime et al. 2022), prefrontal-amygdala neural circuit imbalance (Wei et al. 2025), neuroinflammatory activation (Kimura et al. 2022), and hypothalamic-pituitary-adrenal (HPA) axis dysregulation (Lee et al. 2024). Neuroimaging studies further confirm significant structural and functional brain alterations in comorbid patients, such as decreased neurotrophic factor levels (Ismail et al. 2024), prefrontal-amygdala emotion regulation dysfunction (Su\u0026aacute;rez-Pereira et al. 2022), heightened sensitivity in pain-related brain regions like the anterior cingulate cortex (Kashanian et al. 2022), and Default Mode Network (DMN) hyperactivity during rest (Schimmelpfennig et al. 2023)。\u003c/p\u003e\u003cp\u003eFunctional near-infrared spectroscopy (fNIRS) has gained widespread use in psychiatric research due to its advantages of non-invasiveness, convenience, and low cost (Yang et al. 2022). Based on the \"neurovascular coupling mechanism,\" it detects changes in oxygenated hemoglobin (HbO) levels to reflect local hemodynamic characteristics in the brain in real-time (Pinti et al. 2020). In clinical studies, fNIRS is often combined with cognitive tasks like working memory, word generation, Trail Making Test (TMT), and Verbal Fluency Test (VFT) to assess cortical function (Ho et al. 2020). Existing research shows that MDD patients commonly exhibit hypoactivation in the frontotemporal cortex during various cognitive tasks (Yeung and Lin 2021) ; weakened functional connectivity (FC) between brain regions during the transition from rest to TMT (Ho et al. 2020) ; and increased HbO levels in the left frontal mid-region in response to threatening stimuli (Nishizawa et al. 2019). Among these, the Verbal Fluency Test (VFT) is the most common paradigm, effectively assessing activation patterns in brain regions related to language and executive function, such as the prefrontal cortex and temporal lobe. This task requires participants to generate as many unique words as possible based on a given rule (e.g., starting with a specific Chinese character) within 30 seconds to 1 minute. Synchronously acquired fNIRS data, through hemodynamic changes, precisely reflect multidimensional cognitive abilities including memory, language expression, attention, and executive control (Tran et al. 2023). Studies consistently report cortical hypoactivation and weakened functional connectivity in MDD (Da et al. 2024; G. Li et al. 2024), significantly reduced HbO change amplitude in the right inferior frontal gyrus, abnormal language lateralization; negative correlations between bilateral frontal HbO responses to cognitive tasks and depression severity (Downey et al. 2019; Lyu et al. 2024) ; decreased hemodynamic response in the left precentral gyrus in suicide attempters, with response intensity in the right middle frontal gyrus negatively correlating with aggression and hopelessness (Ho et al. 2020)。\u003c/p\u003e\u003cp\u003eDespite rich findings using fNIRS in MDD research, studies specifically on MDD comorbid with chronic somatic pain (CSP) remain scarce, especially concerning how CSP modulates the neural circuits and mechanisms of MDD. Key unanswered scientific questions include: 1) The prefrontal dynamic changes during task and rest in comorbid patients and their mediating role in pain-depression comorbidity; 2) Whether these changes can provide neuroimaging evidence for personalized interventions like targeted repetitive transcranial magnetic stimulation (rTMS)?\u003c/p\u003e\u003cp\u003eTo address these gaps, this study employed a three-group design, enrolling 129 participants divided into: MDD with chronic somatic pain (MDD\u0026thinsp;+\u0026thinsp;CSP, chronic, somatic, VAS\u0026thinsp;\u0026ge;\u0026thinsp;4), MDD without chronic pain (MDD-CSP), and healthy controls (HC). Using fNIRS, neural activity in frontal and temporal cortices was recorded during a paradigm including a 55-second VFT and an 80-second resting state, while self-report scales assessed mood symptoms. This study aimed to investigate differences in neural activity during task and resting states across depressive subtypes and the role of these differences in the interaction between depressive symptoms (SDS) and pain intensity (VAS). Specifically, mediation analysis tested whether activation levels in specific brain regions mediated the relationship between VAS and SDS. This research aims to deepen the understanding of comorbidity mechanisms and provide a theoretical basis for optimizing clinical intervention strategies.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eSubjects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants and Grouping\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA case-control design was used, recruiting 129 participants divided into 3 groups (43 per group): The case group (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;86) consisted of MDD patients diagnosed by at least two attending physicians from the Neuro-Psychiatric Function Testing \u0026amp; Regulation Center / Center for Mental and Neurological Diseases, West China Xiamen Hospital, Sichuan University, between December 2023 and March 2024. Based on the presence of chronic somatic pain, they were divided into: MDD\u0026thinsp;+\u0026thinsp;CSP: Clear pain persisting/intermittently for \u0026ge;\u0026thinsp;3 months, Visual Analog Scale (VAS)\u0026thinsp;\u0026ge;\u0026thinsp;4 (Y. Zhang et al. 2024). MDD-CSP: VAS\u0026thinsp;\u0026lt;\u0026thinsp;4. The Healthy Control (HC) group (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;43) comprised healthy volunteers recruited during the same period, rigorously screened using the Structured Clinical Interview for DSM-IV Axis I Disorders, Non-Patient Edition (SCID-I/NP) to exclude physical illness, substance abuse history, and personal/family history of psychiatric disorders.;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion and Exclusion Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInclusion Criteria (Case Group): ① Met DSM-5 diagnostic criteria for MDD; ② Education level\u0026thinsp;\u0026gt;\u0026thinsp;6 years; ③ No significant visual or auditory impairment, intact assessment ability; ④ Provided informed consent. Exclusion Criteria: ① Secondary psychiatric disorders (neurological/somatic disease-induced); ② Comorbid bipolar disorder, schizophrenia, or other severe mental disorders; ③ History of severe failure of vital organs (heart, lung, liver, kidney); ④ Uncontrolled hypertension, arrhythmia, severe coronary heart disease, poorly controlled diabetic complications; ⑤ Electroconvulsive therapy (ECT) within the past 6 months; ⑥ Antibiotic/hormone/psychotropic medication use within the past 30 days; ⑦ Pregnant or lactating women; ⑧ Poor compliance preventing study participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Biomedical Huali Review Committee of West China Xiamen Hospital, Sichuan University (Approval No. [2024] Review (004)). It adhered to the principles of the Declaration of Helsinki. The study was registered at the Chinese Clinical Trial Registry (Registration No.: ChiCTR2500098790, Registration date: March 13, 2025). Written informed consent was obtained from all participants or their legal guardians before study commencement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBasic Information Collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDemographic data were recorded, including sex (biological), age, illness duration, and nature/impact of somatic pain.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSymptom Assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepressive Symptoms: Assessed using the Self-Rating Depression Scale (SDS). This 20-item scale uses a 1\u0026ndash;4 scoring per item. The standard score cut-off is set at 50: 50\u0026ndash;59 indicates mild depression, 60\u0026ndash;69 moderate depression, \u0026ge;\u0026thinsp;70 severe depression (Wu et al. 2024).\u003c/p\u003e\n\u003cp\u003ePain Symptoms: Assessed using the Visual Analog Scale (VAS). The VAS is a 10 cm horizontal line where 0 indicates \u0026quot;no pain\u0026quot; and 10 indicates \u0026quot;worst imaginable pain.\u0026quot; Participants mark their pain intensity on the line. Scores are categorized: 1\u0026ndash;3 mild pain, 4\u0026ndash;6 moderate pain, 7\u0026ndash;10 severe pain (Y. Li et al. 2023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003efNIRS Data Acquisition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExperimental Procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants sat comfortably for 5 minutes in a dimly lit fNIRS assessment room (25\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C) to acclimate and reduce tension. They then wore the fNIRS cap. Sound volume was set to 60 dB. Participants were instructed to close their eyes, clear their minds, avoid limb movements, listen attentively to system prompts, and strictly follow task instructions. The assessor turned off room lights and began collecting fNIRS data for 150 seconds. To prevent habituation, each trial was performed only once.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExperimental Paradigm\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA Verbal Fluency Task (VFT) paradigm lasting 150 seconds was used, divided into 3 phases: 1. Resting Period 1 (30 sec): Participants counted sequentially from 1 to 16 following a recorded voice. 2. Task Period (60 sec): Participants generated words for 4 Chinese characters presented auditorily in a block-randomized order (high-frequency characters from the Modern Chinese Word Frequency Dictionary, e.g., \u0026quot;上/sh\u0026agrave;ng\u0026quot;, \u0026quot;时/sh\u0026iacute;\u0026quot;, \u0026quot;说/shuō\u0026quot;, \u0026quot;家/jiā\u0026quot;). Each character was played, followed immediately by a 15-second word generation period. Participants generated as many unique words as possible starting with the given character. 3. Resting Period 2 (60 sec): Participants counted sequentially from 1 to 32 following a recorded voice. See Fig. 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Acquisition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA BS-3000 fNIRS system (Zilian Hongkang, China) was used, acquiring data at dual wavelengths (690nm/830nm) and a 20Hz sampling rate. The probe array consisted of 16 sources and 16 detectors (3 cm spacing), forming 53 channels. Based on EEG 10\u0026ndash;20 system landmarks (F3/F4/Fz), probes were registered to MNI space using NIRSite software (Mir-Moghtadaei et al. 2022), covering: premotor cortex, supplementary motor area, Broca\u0026apos;s area, dorsolateral prefrontal cortex. Oxygenated hemoglobin (HbO₂) concentration was calculated using the modified Beer-Lambert law (Scholkmann et al. 2014) with Differential Pathlength Factors (DPF\u0026thinsp;\u0026lt;\u0026thinsp;sub\u0026thinsp;\u0026gt;\u0026thinsp;690\u0026lt;/sub\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;5.8, DPF\u0026thinsp;\u0026lt;\u0026thinsp;sub\u0026thinsp;\u0026gt;\u0026thinsp;830\u0026lt;/sub\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;4.9). Average HbO₂ concentration (Avg-HbO) was extracted for the task period (35-90s) and resting periods (5-30s pre-task, 95-150s post-task).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003efNIRS Data Preprocessing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePreprocessing was performed in Matlab2013b using Homer2 and SPM toolkits. Steps included: ① Removal of channels with raw light intensity standard deviation\u0026thinsp;\u0026gt;\u0026thinsp;6% or HbO₂ peak change\u0026thinsp;\u0026gt;\u0026thinsp;0.5 \u0026micro;M; ② Band-pass filtering (4th order Butterworth filter, 0.008-0.2 Hz); ③ Principal Component Analysis (PCA) on all HbO₂ channels to remove the first principal component (explaining\u0026thinsp;\u0026gt;\u0026thinsp;95% variance); ④ Segment extraction for task state (35-90s) and resting state (5-30s pre-task, 95-150s post-task) (F. Zhang et al. 2023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional Connectivity (FC) Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing FC_NIRS software, HbO₂ concentration time courses were extracted for the task state (35-90s; sliding window 30s, step 1s) (Z. Li et al. 2015) and resting states (pre-task 5-30s, post-task 95-150s). Global signal regression was performed per channel. \u003cem\u003ePearson\u003c/em\u003e correlation coefficients (\u003cem\u003er\u003c/em\u003e) were calculated between channels within each window. Fisher Z-transformation was applied: \\\u003cspan\u003e$\u003c/span\u003eZ = \\frac{1}{2} \\ln \\left( \\frac{1\u0026thinsp;+\u0026thinsp;r}{1-r} \\right)\\\u003cspan\u003e$\u003c/span\u003e, with Z-values representing functional connection strength (Wen et al. 2023).\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n \u003cp\u003eSPSS 24.0 (IBM, USA) was used. All tests were two-tailed (\u0026alpha;\u0026thinsp;=\u0026thinsp;0.05). Demographic \u0026amp; Clinical Variables: Categorical variables reported as frequency (\u003cem\u003en\u003c/em\u003e), compared using \u003cem\u003e\u0026chi;\u003c/em\u003e\u0026sup2; tests. Continuous variables reported as Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Normality assessed via \u003cem\u003eKolmogorov-Smirnov\u003c/em\u003e test and Q-Q plots; homogeneity of variance assessed via \u003cem\u003eBrown-Forsythe\u003c/em\u003e test. Age: Normally distributed but heteroscedastic; intergroup comparison used \u003cem\u003eWelch\u003c/em\u003e test. SDS \u0026amp; VAS (Case groups): Non-normally distributed and heteroscedastic; compared using \u003cem\u003eMann-Whitney U\u003c/em\u003e test. fNIRS Data (Activation \u0026amp; Network): Non-normally distributed and heteroscedastic. Overall intergroup comparison used \u003cem\u003eKruskal-Wallis\u003c/em\u003e test. Significant channels underwent post-hoc pairwise \u003cem\u003eMann-Whitney U\u003c/em\u003e tests (3 comparisons) with \u003cem\u003eBonferroni\u003c/em\u003e correction (adjusted significance threshold \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.0167). Mediation Effect Analysis: \u003cem\u003eBootstrap\u003c/em\u003e-based mediation test (5,000 resamples) examined whether task/rest activation levels and network features mediated the relationship between SDS and VAS. Sex, age, and illness duration (DOI) were covariates. Significance (\u003cem\u003ep\u003c/em\u003e) of mediation effects was FDR-corrected (\u003cem\u003eBenjamini-Hochberg\u003c/em\u003e, critical \u003cem\u003eq\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05). Indirect effect estimates and 95% Bootstrap \u003cem\u003eCI\u003c/em\u003e were reported. Correlation Analysis: \u003cem\u003eSpearman\u003c/em\u003e rank correlation explored associations between HbO₂ signals (task/rest activation, network features) and demographic/clinical variables. \u003cem\u003eBonferroni\u003c/em\u003e correction applied (adjusted \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.01). Visualization: BrainNet Viewer, FC_NIRS, and GraphPad Prism 8 were used.\u003c/p\u003e\n\u003c/div\u003e\n"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDemographic Characteristics and Clinical Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study included 129 participants (Case group: 35M, 40.26 ± 17.749y; 51F, 39.86 ± 17.351y; HC group: 19M, 45.21 ± 11.028y; 24F, 38.58 ± 13.351y). No significant differences were found between groups for age (\u003cem\u003ep\u003c/em\u003e = 0.126) or sex distribution (\u003cem\u003ep\u003c/em\u003e = 0.512). Illness duration also showed no significant difference between MDD subgroups (\u003cem\u003ep\u003c/em\u003e = 0.866). SDS scores were significantly higher in MDD-CSP than MDD + CSP (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001). See Table 1.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eDemographic and Clinical Characteristics: Depressive Disorder Subgroups (MDD + CSP, MDD-CSP) vs. Healthy Controls [2024 Cohort]\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSex(F/M)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAge (y)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSDS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDOI (y)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVAS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePain Intensity\u003c/p\u003e\n \u003cp\u003e(NO/ Mild/ Moderate/ Severe)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMMD + CSP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20/23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.35 ± 16.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71.40 ± 7.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.57 ± 3.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.58 ± 1.384\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0/0/31/12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMDD-CSP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15/28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.70 ± 18.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61.42 ± 8.547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.82 ± 5.566\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63 ± 0.817\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23/20/0/0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19/24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.51 ± 12.682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e/\u003cem\u003eF\u003c/em\u003e/\u003cem\u003eU\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.338\u003csup\u003e△\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.145\u003csup\u003e◎\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e354.50\u003csup\u003e●***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e905.000\u003csup\u003e●\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAge was analyzed by \u003cem\u003eWelch\u003c/em\u003e test (◎).\u003c/p\u003e\n\u003cp\u003eSex distribution was analyzed by \u003cem\u003eχ\u003c/em\u003e² tests (△).\u003c/p\u003e\n\u003cp\u003eDOI (Duration of Illness) and SDS (Self-Rating Depression Scale) were analyzed by \u003cem\u003eMann-Whitney U\u003c/em\u003e test (\u003cem\u003eU\u003c/em\u003e/●).\u003c/p\u003e\n\u003cp\u003eVAS: Visual Analogue Scale.\u003c/p\u003e\n\u003cp\u003eHC: Healthy control group.\u003c/p\u003e\n\u003cp\u003eMDD + CSP: Depressive disorder with chronic somatic pain.\u003c/p\u003e\n\u003cp\u003eMDD - CSP: Group of pure depressive disorder.\u003c/p\u003e\n\u003cp\u003e***: \u003cem\u003ep\u003c/em\u003e ≤ 0.0001.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003efNIRS Activation Differences During VFT in MDD Subgroups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003efNIRS compared neural activity during VFT execution across MDD + CSP, MDD-CSP, and HC. 1. Brain Region Activation Differences: General MDD Feature: All MDD patients showed significantly reduced bilateral FP activation vs HC (Ch16: \u003cem\u003eχ\u003c/em\u003e² = 12.246, \u003cem\u003ep\u003c/em\u003e = 0.002; Ch22: \u003cem\u003eχ\u003c/em\u003e² = 15.684, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001; Ch23: \u003cem\u003eχ\u003c/em\u003e² = 11.537, \u003cem\u003ep\u003c/em\u003e = 0.003; Ch35: \u003cem\u003eχ\u003c/em\u003e² = 15.677, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001; Ch36: \u003cem\u003eχ\u003c/em\u003e² = 9.032, \u003cem\u003ep\u003c/em\u003e = 0.005). Subgroup-Specific Features: MDD-CSP vs HC: Only R-FP (Ch37, \u003cem\u003eU\u003c/em\u003e = 623.00) showed significant hypoactivation. MDD + CSP: Exhibited 1) Widespread bilateral FP hypoactivation (Ch15: \u003cem\u003eU\u003c/em\u003e = 575.50; Ch27: \u003cem\u003eU\u003c/em\u003e = 617.00; Ch30: \u003cem\u003eU\u003c/em\u003e = 574.5; Ch41: \u003cem\u003eU\u003c/em\u003e = 563.00; Ch43: \u003cem\u003eU\u003c/em\u003e = 621.50); 2) Reduced activation in language-related regions (Broca's area/RH-Broca: Ch08: \u003cem\u003eU\u003c/em\u003e = 568.50; Ch44: \u003cem\u003eU\u003c/em\u003e = 636.00; Ch49: \u003cem\u003eU\u003c/em\u003e = 623.00); 3) Significantly lower activation in RH-Broca (Ch51, \u003cem\u003eU\u003c/em\u003e = 577.5) compared to MDD-CSP. 2. Brain Network Feature Differences: All MDD groups showed increased Connection Probability (CP, \u003cem\u003eχ\u003c/em\u003e² = 12.268, \u003cem\u003ep\u003c/em\u003e = 0.002), Normalized Clustering Coefficient (Gamma, \u003cem\u003eχ\u003c/em\u003e² = 9.314, \u003cem\u003ep\u003c/em\u003e = 0.009), and Local Efficiency (Eloc, \u003cem\u003eχ\u003c/em\u003e² = 11.981, \u003cem\u003ep\u003c/em\u003e = 0.003) vs HC. See Fig.\u0026nbsp;2 for visualization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003efNIRS Differences During Resting State in MDD Subgroups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003efNIRS compared resting-state neural activity across the three groups. 1. Brain Region Activation Differences: General MDD Feature: All MDD patients showed significantly enhanced R-FP activation (Ch35, \u003cem\u003eχ\u003c/em\u003e² = 10.875, \u003cem\u003ep\u003c/em\u003e = 0.004) vs HC. Subgroup-Specific Feature: MDD + CSP showed higher activation in R-FP (Ch36, \u003cem\u003eU\u003c/em\u003e = 632.00) vs HC. 2. Brain Network Feature Differences: General MDD Feature: All MDD groups showed increased CP (\u003cem\u003eχ\u003c/em\u003e² = 15.567, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001) and Eloc (\u003cem\u003eχ\u003c/em\u003e² = 14.168, \u003cem\u003ep\u003c/em\u003e = 0.001) vs HC. MDD-CSP Feature: Increased Gamma (\u003cem\u003eU\u003c/em\u003e = 519.00), Normalized Path Length (Lambda, \u003cem\u003eU\u003c/em\u003e = 573.00), and Small-Worldness (Sigma, \u003cem\u003eU\u003c/em\u003e = 633.00) vs HC. See Fig.\u0026nbsp;2 for visualization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMediating Effects of Brain Activation and Functional Network Connectivity on Depression and Chronic Somatic Pain\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMediation analysis (FDR-corrected) examined the role of task/rest activation and FC between SDS and VAS. Significant Mediation During Task (FDR-corrected): A significant bidirectional mediation effect was observed in RH-Broca (Ch53): Path 1 (VAS → Ch53 → SDS): Increased pain (VAS↑) → Reduced Ch53 activation (a = -0.16, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001) → Worsened depression (SDS↑) (b = -7.54, p \u0026lt; 0.0001; Indirect effect = 1.17, 95% \u003cem\u003eCI\u003c/em\u003e: 0.66, 1.71, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001). Path 2 (SDS → Ch53 → VAS): Worsened depression (SDS↑) → Reduced Ch53 activation (a = -0.06, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001) → Increased pain perception (VAS↑) (b = -2.16, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001; Indirect effect = 0.13, 95% \u003cem\u003eCI\u003c/em\u003e: 0.08, 0.18, p \u0026lt; 0.0001). Other Channels During Task (Uncorrected Significance): Mediation observed in: VAS→Brain Activation→SDS: L-FP (Ch16, \u003cem\u003ep\u003c/em\u003e = 0.038), R-FP (Ch41, p = 0.048; Ch43, \u003cem\u003ep\u003c/em\u003e = 0.0392), RH-Broca (Ch49, \u003cem\u003ep\u003c/em\u003e = 0.0232; Ch50, \u003cem\u003ep\u003c/em\u003e = 0.0104); SDS→Brain Activation→VAS: R-FP (Ch43, \u003cem\u003ep\u003c/em\u003e = 0.022), RH-Broca (Ch50, \u003cem\u003ep\u003c/em\u003e = 0.0028). No Significant Mediation: Found for resting-state activation or FC metrics (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05). The bidirectional effect in Ch53 during task indicates: ① Pain sensitivity (VAS) indirectly exacerbates depressive symptoms (SDS) by suppressing this region (large effect: ab ≈ 1.17); ② Depressive symptoms (SDS) indirectly intensify pain perception (VAS) by weakening this region's activity (small effect: ab ≈ 0.13). See Fig.\u0026nbsp;3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation Analysis of fNIRS-HbO₂ with Demographic/Clinical Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSpearman\u003c/em\u003e correlation examined links between fNIRS-HbO₂ signals and variables. 1. During VFT: Sex: Females showed reduced Broca's area activation (Ch03, \u003cem\u003ep\u003c/em\u003e = 0.005) and enhanced left FEF activation (L-FEF, Ch24, \u003cem\u003ep\u003c/em\u003e = 0.005). Age: Older age correlated with reduced left DLPFC activation (L-DLPFC, Ch14, \u003cem\u003ep\u003c/em\u003e = 0.008). Illness Duration (DOI): Longer DOI correlated with reduced bilateral DLPFC activation (Ch17, \u003cem\u003ep\u003c/em\u003e = 0.003; Ch34, \u003cem\u003ep\u003c/em\u003e = 0.004). Pain (VAS): Higher VAS correlated with reduced activation in Broca's area/RH-Broca (Ch02, \u003cem\u003ep\u003c/em\u003e = 0.002; Ch49, \u003cem\u003ep\u003c/em\u003e = 0.006; Ch50, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001; Ch51, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001; Ch53, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001) and R-FP (Ch41, \u003cem\u003ep\u003c/em\u003e = 0.002; Ch43, \u003cem\u003ep\u003c/em\u003e = 0.005). Depression (SDS): Higher SDS correlated with reduced activation in bilateral SMA + PMC (Ch01, \u003cem\u003ep\u003c/em\u003e = 0.007; Ch47, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001; Ch52, \u003cem\u003ep\u003c/em\u003e = 0.001), R-FP (Ch41, \u003cem\u003ep\u003c/em\u003e = 0.01), and RH-Broca (Ch50, \u003cem\u003ep\u003c/em\u003e = 0.007; Ch53, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001). 2. Resting State: Sex: Females showed reduced bilateral FP (Ch19, \u003cem\u003ep\u003c/em\u003e = 0.007; Ch48, \u003cem\u003ep\u003c/em\u003e = 0.004) and Broca's area activation (Ch02, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001). Age: Older age correlated with enhanced bilateral FP activation (Ch19, \u003cem\u003ep\u003c/em\u003e = 0.006; Ch36, \u003cem\u003ep\u003c/em\u003e = 0.004). See Table 2.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eCorrelation Analysis of Demographic Characteristics and Clinical lndicators with Resting - State/VFT Task fNIRS - HbO2 in Three Groups (HC, MDD-CSP, MDD + CSP)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStates\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFactors\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAge\u003cem\u003e(\u003c/em\u003ey\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDOI\u003cem\u003e(\u003c/em\u003ey\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVAS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSDS\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"15\"\u003e\n \u003cp\u003eTask - Based\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.290\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.326\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.246\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.232\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.313\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.248\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.305\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.326\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.275\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.298\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.214\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.292\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.295\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.374\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.291\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.390\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.344\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.481\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.538\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eResting State\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.329\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.235\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.239\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.254\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCh48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.249\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eDemographic: full sample (\u003cem\u003en\u003c/em\u003e = 129).\u003c/p\u003e\n\u003cp\u003eClinical analysis: patient groups only (MDD-CSP + MDD + CSP, \u003cem\u003en\u003c/em\u003e = 86).\u003c/p\u003e\n\u003cp\u003eAge is counted in years.\u003c/p\u003e\n\u003cp\u003eSex including male and female.\u003c/p\u003e\n\u003cp\u003eDOI: Duration of Illness, recorded in years.\u003c/p\u003e\n\u003cp\u003eVAS: Visual Analogue Scale.\u003c/p\u003e\n\u003cp\u003eSDS: Self-Rating Depression Scale.\u003c/p\u003e\n\u003cp\u003eHC: Health control group.\u003c/p\u003e\n\u003cp\u003eMDD + CSP: Depressive disorder with chronic somatic pain.\u003c/p\u003e\n\u003cp\u003eMDD - CSP: Group of pure depressive disorder.\u003c/p\u003e\n\u003cp\u003eA \u003cem\u003eBonferroni\u003c/em\u003e-corrected significance threshold of \u003cem\u003ep\u003c/em\u003e ≤ 0.01 (0.05 / 5 tests) was adopted.\u003c/p\u003e\n\u003cp\u003e*: 0.01 ≤ \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, **: 0.001 ≤ \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001, ***: \u003cem\u003ep\u003c/em\u003e ≤ 0.0001.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eUsing fNIRS, this study systematically characterized neural activity during task (VFT) and resting states in MDD patients with and without chronic somatic pain (CSP), revealing commonalities and differences in neural mechanisms, and elucidating the pivotal hub role of the right hemispheric Broca's homologue (RH-Broca, Ch53) in pain-depression comorbidity. Key findings provide important insights for understanding comorbidity mechanisms and developing targeted interventions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eBidirectional Frontopolar (FP) Dysfunction: A Transdiagnostic Core Mechanism of Depression\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study confirmed widespread bilateral FP hypoactivation during VFT in MDD patients (e.g., Ch16, Ch22, Ch23) compared to HC, consistent with prior research (Catalano et al. 2025; Yeung and Lin 2021), supporting prefrontal cortex (PFC, including FP) hypofunction as a core neural mechanism of depression. As a higher cognitive center, PFC dysfunction creates a bidirectional vicious cycle with emotion dysregulation and executive impairment: chronic mood disturbance leads to PFC neurodegeneration, which in turn exacerbates symptoms (Jones and Graff-Radford 2021; Su\u0026aacute;rez-Pereira et al. 2022). Notably, patients exhibited enhanced R-FP activation (Ch35/36) during rest, contrasting with task hypoactivation. This may reflect impaired DMN suppression (Sun et al. 2024a), promoting rumination and negative self-focus (Katayama et al. 2023; L. Zhang et al. 2025). MDD\u0026thinsp;+\u0026thinsp;CSP showed more extensive task hypoactivation, suggesting CSP may exacerbate prefrontal dysfunction by increasing cognitive load and pain interference, supporting the hypothesis of a unique neural basis for pain-depression comorbidity (Antoniou et al. 2023; Y. Zhang et al. 2024).\u003c/p\u003e\u003cp\u003e\u003cb\u003eNeural Modulatory Effect of Chronic Pain (CSP): Language Network Suppression and the Right Broca Hub\u003c/b\u003e\u003c/p\u003e\u003cp\u003eLanguage Network Specific Suppression: Beyond more pronounced FP hypoactivation (e.g., Ch15, Ch27, Ch30), MDD\u0026thinsp;+\u0026thinsp;CSP exhibited additional suppression in language-related regions (Broca's area/RH-Broca: Ch08, Ch44, Ch49). This suggests CSP may compete for prefrontal resources via spinothalamocortical pathways, leading to reduced cognitive flexibility and inadequate language processing compensation (e.g., psychomotor retardation, alexithymia). The negative correlation between VAS and RH language activation (da Costa et al. 2025) underscores pain's direct damaging effect on language/prefrontal networks.\u003c/p\u003e\u003cp\u003eCh53 (RH-Broca) in Bidirectional Pain-Depression Mediation: During VFT, RH-Broca (Ch53) activation significantly mediated the bidirectional relationship between VAS and SDS (FDR-corrected): Path 1 (Large Effect): Pain exacerbation \u0026rarr; Ch53 suppression \u0026rarr; Depression worsening (effect\u0026thinsp;=\u0026thinsp;1.17). Path 2 (Small Effect): Depression worsening \u0026rarr; Ch53 suppression \u0026rarr; Pain intensification (effect\u0026thinsp;=\u0026thinsp;0.13). Ch53 as the \"Pain-Depression Circuit\" Hub: The RH-Broca homologue (right inferior frontal gyrus, rIFG) integrates emotion and modulates pain: Anterior rIFG regulates DMN and Salience Network (SN), influencing negative emotion processing; posterior rIFG connects to somatosensory cortex, involved in descending pain inhibition. Reduced Ch53 activation may disrupt these functions, creating a vicious cycle of mutual pain-depression amplification (Borst et al. 2024; A. Manelis et al. 2022; Peng et al. 2024; Viellard et al. 2024; Zhu et al. 2018). Asymmetry of Bidirectional Effects: The pain\u0026rarr;depression path was stronger (effect 1.17 vs 0.13). Chronic pain, by suppressing rIFG, weakens inhibition of negative emotions and pain perception, significantly worsening depression (\"pain-driven depression\"). The depression\u0026rarr;pain path effect was weaker; depression may indirectly intensify pain via rIFG dysfunction but likely requires co-occurring mechanisms (e.g., inflammatory factors, limbic activation) (Cox et al. 2025; De Ridder, Adhia, and Vanneste 2021; Guida et al. 2022; Jiang et al. 2025; M. Li et al. 2025).\u003c/p\u003e\u003cp\u003e\u003cb\u003eBrain Network Reorganization in Depression: Efficiency Compensation and Chronic Pain Interference\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDuring task, MDD patients showed enhanced local network function: increased CP, Gamma, and Eloc, suggesting compensatory strengthening of local connections for hypoactivated regions (Mısır, Alıcı, and Kocak 2023; Pan et al. 2020). However, this compensation may impair global information integration efficiency, worsening cognitive resource allocation imbalance. MDD-CSP showed significantly elevated resting-state Small-Worldness (Sigma, \u003cem\u003eU\u003c/em\u003e\u0026thinsp;=\u0026thinsp;633), aligning with the \"hyper-optimized network hypothesis\" (Jung and Han 2024). Elevated Sigma reflects an imbalance between local clustering and global integration: while local processing efficiency (Gamma) compensatorily increases, rigid network topology limits cross-module information exchange, reducing treatment response (Sun et al. 2024b). For instance, Sun et al. (2024) found patients with baseline Sigma\u0026thinsp;\u0026gt;\u0026thinsp;1.2 had a 4-fold increased risk (OR\u0026thinsp;=\u0026thinsp;4.2) of non-response to SSRIs (Sun et al. 2024a), and Saccaro et al. (2024) linked high Sigma to long illness duration and prefrontal-hippocampal circuit plasticity damage (Saccaro et al. 2024). This study extends this model, suggesting MDD patients without pain comorbidity are more prone to developing a treatment-resistant subtype characterized by high Sigma, while CSP may mask this phenotype by disrupting network balance (e.g., unchanged Sigma in MDD\u0026thinsp;+\u0026thinsp;CSP).\u003c/p\u003e\u003cp\u003e\u003cb\u003eCorrelations Between Neural Activity and Clinical Variables\u003c/b\u003e\u003c/p\u003e\u003cp\u003e1. Sex Differences: Task: Reduced Broca's area (Ch03) and enhanced L-FEF (Ch24) activation in females may relate to internalizing symptom (e.g., rumination) propensity. Rest: Reduced bilateral FP (Ch19/48) and Broca's (Ch02) activation in females supports sex-specific depression neurobiology (Bossenbroek et al. 2022; Verhelst et al. 2024). 2. Age \u0026amp; Illness Duration: Age-related reduction in L-DLPFC (Ch14) activation suggests aging exacerbates cognitive control decline. Reduced bilateral DLPFC (Ch17/34) activation with longer DOI reflects neuroplasticity decline from disease chronicity (Saccaro et al. 2024). 3. Depression (SDS): Correlation with reduced activation in motor preparation areas (SMA\u0026thinsp;+\u0026thinsp;PMC, Ch01/47/52) and RH-Broca (Ch50/53) may underlie psychomotor retardation and verbal fluency decline in comorbid patients. 4. Depression Underestimation in Comorbid Group: The \"higher depression\" in MDD-CSP stems from isolated damage to prefrontal emotion regulation circuits (Oliva et al. 2025), not activating the shared rIFG pain-depression pathway. In MDD\u0026thinsp;+\u0026thinsp;CSP, CSP triggers rIFG-mediated neuroinflammation, \"diluting\" pure depressive expression with somatic symptoms (Y. Zhang et al. 2024).\u003c/p\u003e\u003cp\u003e\u003cb\u003eResearch Significance and Clinical Implications\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study supports a \"Frontal-Language Circuit Dysfunction Model\" for pain-depression comorbidity: 1) CSP damages RH language network \u0026rarr; emotion processing impairment \u0026rarr; depression worsening; 2) DMN hyperactivation (resting FP activity) \u0026rarr; weakened cognitive control resources \u0026rarr; enhanced pain perception; 3) Network efficiency compensation (increased CP/Eloc) represents early adaptation, potentially failing with disease progression.\u003c/p\u003e\u003cp\u003eClinical Implications: fNIRS can dynamically monitor neural function in MDD subtypes (e.g., Ch36/Ch53), guiding stratified treatment. Neuromodulation (rTMS/tDCS) targeting RH-Broca (Ch53) may simultaneously alleviate pain and depression (Liu et al. 2024). Female patients require focused attention on language region function preservation.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations and Future Directions\u003c/b\u003e\u003c/p\u003e\u003cp\u003e1. Cross-sectional design cannot establish causal sequence; longitudinal tracking of pain-depression-brain function dynamics needed. 2. Limited fNIRS spatial resolution; deep brain regions (e.g., insula) require validation with fMRI. 3. Pain subtype heterogeneity (neuropathic/nociceptive) not distinguished, potentially affecting mechanism interpretation. 4. Medication carryover effects: Despite \u0026ge;\u0026thinsp;30-day washout, prior medication history may have residual neuroplasticity effects. Future Directions: Combine multimodal imaging (fMRI-EEG) for longitudinal intervention tracking, controlling for pain subtypes and medication confounders.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, this fNIRS study revealed characteristic differences in frontopolar function, language network involvement, and global brain network efficiency between MDD with and without CSP. It identified, for the first time, the critical hub role of the right inferior frontal gyrus in a bidirectional pain-depression loop. These findings provide crucial empirical evidence and theoretical foundation for understanding comorbidity mechanisms and developing neuroimaging-based subtyping diagnostics and targeted interventions. Future longitudinal studies incorporating multimodal techniques will help elucidate causal mechanisms and optimize treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (Grant No. 81873354).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor Contributions Jiaren Zheng: Conceptualization, Methodology, Writing (First Author) Ning Zhu: Formal Analysis, Investigation, Visualization (Co-First Author) Jiaxi Huang: Investigation, Writing Hongyu Sun, Zhenhua Li: Data Curation Huimin L\u0026uuml;, Jing Zhang, Jing Li, Bo Zheng, Manyu Zhang: Writing\u0026ndash;Review \u0026amp; Editing Yibin Xie: Designed the research, Supervision. Zhong Zheng: Designed the research, Supervision, Funding Acquisition Corresponding author: Zhong Zheng Co-corresponding authors: Jiaren Zheng and Yibin XieThis manuscript is original, unpublished, and not under consideration elsewhere. All authors declare no conflicts of interest.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed during this study are not publicly available but are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAntoniou, Georgia, Emilie Lambourg, J. Douglas Steele, and Lesley A. 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Emotional Conflict Processing in Major Depression: ERPs and Source Localization Analysis on the N450 and P300 Components\u0026rsquo;. \u003cem\u003eFrontiers in Human Neuroscience\u003c/em\u003e 12:214. https://doi.org/10.3389/fnhum.2018.00214.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Major depressive disorder, Chronic pain, fNIRS, Broca's area homologue, Neuroplasticity, Mediation analysis, Prefrontal cortex","lastPublishedDoi":"10.21203/rs.3.rs-6998159/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6998159/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eChronic somatic pain (CSP) modulates the neuropathological mechanisms of depression, but how it reshapes neural circuits remains unclear. This study investigated CSP-specific prefrontal dynamic changes and their mediating role in pain-depression comorbidity.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003e129 participants were recruited (43 each in Major Depressive Disorder with Chronic Somatic Pain group (MDD\u0026thinsp;+\u0026thinsp;CSP), MDD without Chronic Somatic Pain group (MDD-CSP), and Healthy Control group (HC)). Hemodynamic responses during a Verbal Fluency Task (VFT) and resting state were measured using functional near-infrared spectroscopy (fNIRS). Intergroup comparisons (\u003cem\u003eKruskal-Wallis/Mann-Whitney U\u003c/em\u003e tests), mediation analysis (FDR-corrected), and \u003cem\u003eSpearman\u003c/em\u003e correlation analysis were used to dissect interactions between neural and clinical indices.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003e1. Frontopolar (FP) Functional Abnormalities: Task-state hypofunction: Bilateral FP activation was reduced in all MDD groups (Channels Ch16/22/23/35/36, \u003cem\u003eχ\u003c/em\u003e\u0026sup2; \u0026gt;7.287, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.002). Resting-state hyperfunction: Right FP (Ch35/36) activation was higher in MDD\u0026thinsp;+\u0026thinsp;CSP than HC (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.012). 2. CSP-Specific Language Network Suppression: Compared to MDD-CSP, MDD\u0026thinsp;+\u0026thinsp;CSP showed reduced activation in the right hemispheric Broca's homologue (RH-Broca, Ch51, \u003cem\u003eU\u003c/em\u003e\u0026thinsp;=\u0026thinsp;577.5). Visual Analog Scale (VAS) scores negatively correlated with suppression in Broca's area/RH-Broca (Ch2/49/50/51/53, \u003cem\u003eρ\u003c/em\u003e \u0026lt; -0.5, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). 3. Bidirectional Mediation Effect: RH-Broca (Ch53) mediated both the VAS\u0026rarr;SDS path (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.17, 95% \u003cem\u003eCI\u003c/em\u003e: 0.66\u0026ndash;1.71) and SDS\u0026rarr;VAS path (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.13, 95% \u003cem\u003eCI\u003c/em\u003e: 0.08\u0026ndash;0.18). 4. Brain Network Reorganization: During task, MDD groups showed increased Connection Density (CP, \u003cem\u003eχ\u003c/em\u003e\u0026sup2;=12.268) and Local Efficiency (Gamma, \u003cem\u003eχ\u003c/em\u003e\u0026sup2;=9.314). During rest, higher Small-Worldness (Sigma, \u003cem\u003eU\u003c/em\u003e\u0026thinsp;=\u0026thinsp;633) in MDD-CSP predicted treatment resistance.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eCSP exacerbates depression via: ① Selective suppression of the language network (Broca's area/RH-Broca), ② Establishing a bidirectional pain-depression loop via RH-Broca (Ch53), and ③ Driving maladaptive neuroplasticity in prefrontal networks. RH-Broca activation is a potential biomarker for neuromodulation therapy in comorbid depression.\u003c/p\u003e","manuscriptTitle":"Right Hemispheric Broca's Homologue Mediates Pain-Depression Loop: fNIRS Evidence of Language Network Remodeling in Comorbid Chronic Pain and Depression","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-14 10:26:28","doi":"10.21203/rs.3.rs-6998159/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-05T17:59:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-22T23:09:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"331174358192642523375021521827263319947","date":"2025-09-09T01:05:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-13T00:28:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"36044475337663113482656598341218865120","date":"2025-07-22T21:49:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"90406115692095576495835870827961126001","date":"2025-07-17T17:20:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-08T19:26:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-04T15:15:32+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-04T15:14:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2025-06-28T13:30:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8bed2b97-cce7-4835-99a1-16577b432a44","owner":[],"postedDate":"July 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-27T17:24:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-14 10:26:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6998159","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6998159","identity":"rs-6998159","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}