Psychiatry Research: Neuroimaging最新文献

{"title":"Differential precuneus and frontal activity associated with facial emotion processing in adolescent depression","authors":"Nazia Jassim ,&nbsp;Cindy Hagan ,&nbsp;Rosemary Holt ,&nbsp;Ian Goodyer ,&nbsp;John Suckling","doi":"10.1016/j.pscychresns.2025.112019","DOIUrl":"10.1016/j.pscychresns.2025.112019","url":null,"abstract":"<div><div>Adolescence is a critical period of vulnerability to mental health issues, yet emotion processing in adolescent depression remains understudied. This task-based functional Magnetic Resonance Imaging (fMRI) study examines emotion processing in depressed adolescents and the effects of Cognitive Behavioural Therapy (CBT). fMRI data were collected during an emotional face processing task from 94 depressed adolescents and 34 healthy controls at baseline. As part of a feasibility study, a longitudinal sub-cohort of 14 depressed adolescents and 33 controls underwent follow-up scans after 24 weeks of CBT. Whole-brain analyses estimated: (a) neural responses to overall facial emotions, and (b) a dynamic range of responses to varying emotion intensities. At baseline, depressed adolescents exhibited greater precuneus activity for positive emotions and hypoactivity in the frontal pole for negative emotions, both correlating with trait anxiety. Although CBT did not significantly alter neural responses in the smaller follow-up sample, behavioural data indicated that depressed adolescents rated high-intensity sad faces as less sad post-treatment. These findings underscore the importance of early interventions targeting emotional biases in adolescent depression. Future studies with larger samples are needed to clarify neural mechanisms of treatment effects.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"351 ","pages":"Article 112019"},"PeriodicalIF":2.1,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144563425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding caffeine’s impact on sustained attention in early phase psychosis: Unveiling cognitive insights through the use of EEG","authors":"Ashley M. Francis ,&nbsp;T-Jay Anderson ,&nbsp;Katelyn J. McKearney ,&nbsp;Bronwen Schryver ,&nbsp;Philip G. Tibbo ,&nbsp;Derek J. Fisher","doi":"10.1016/j.pscychresns.2025.112006","DOIUrl":"10.1016/j.pscychresns.2025.112006","url":null,"abstract":"<div><div>Cognitive impairment, particularly in attention and working memory, is a notable feature of schizophrenia (SZ). Individuals with SZ frequently consume high levels of caffeine, often exceeding 550 mg daily, yet the cognitive effects of this excessive intake – especially in the early stages of the illness – remain unexplored. This study is the first to investigate the acute effects of caffeine on cognition in SZ using a rigorous double-blind, placebo-controlled design. Utilizing electroencephalography (EEG)-derived event-related potentials (ERPs) and the AX-continuous performance task (AX-CPT), we examined behavioural and neurophysiological markers of sustained attention, including P300 amplitude and latency.</div><div>Our sample included individuals within the first five years of their SZ diagnosis (<em>n</em> = 11) and healthy controls (<em>n</em> = 14) aged 20 – 38 (HC: <em>M</em> = 22.5, SZ: <em>M</em> = 28.2).</div><div>Findings revealed that within the caffeine condition, individuals with SZ exhibited enhanced P300 amplitudes and shorter latencies for the priming stimulus compared to controls. Behavioural performance, however, did not support this and found individuals with SZ performed worse than controls, suggesting the enhancement of cognitive resources during the caffeine condition does not significantly improve performance in individuals with SZ. Correlational findings suggest a potential interaction between symptomology and caffeine’s cognitive effects, whereby increased positive symptoms were associated with increased amplitudes, while, negative symptoms were associated with latency findings.</div><div>These findings challenge the assumptions that caffeine consumption enhances cognitive function in SZ, at least at the doses tested. Future research should explore caffeine’s effects at intake levels that are more representative of each individual’s habitual consumption to better determine whether chronic high doses exert differential effects on cognition in this population.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"351 ","pages":"Article 112006"},"PeriodicalIF":2.1,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of retinal neural network parameters of children and adolescents diagnosed with obsessive compulsive disorder with the healthy controls: A cross-sectional study","authors":"Rukiye Çolak Sivri ,&nbsp;Umay Güvenç ,&nbsp;Güner Üney ,&nbsp;Ayşe Nihal Eraslan ,&nbsp;Arzu Yılmaz ,&nbsp;Firdevs Örnek ,&nbsp;Burçin Çolak","doi":"10.1016/j.pscychresns.2025.112017","DOIUrl":"10.1016/j.pscychresns.2025.112017","url":null,"abstract":"<div><div>Obsessive Compulsive Disorder (OCD) is a chronic psychiatric disorder that often begins in childhood or adolescence and is associated with functional abnormalities in cortico-striato-thalamo-cortical circuits. Given the neurodevelopmental basis of OCD and the anatomical and physiological relationship between the retina and the central nervous system, recent studies have focused on investigating retinal changes in neuropsychiatric disorders using Optical Coherence Tomography (OCT). However, data on retinal structural changes in pediatric OCD populations are scant. The aim of this study was to investigate possible retinal structural differences in children and adolescents diagnosed with OCD by comparing OCT-derived measurements with healthy controls. This study compares the Peripapillary Retinal Nerve Fiber Layer (RNFL) thickness, Ganglion Cell Layer (GCL) volume, GCL thickness, Ganglion Cell Complex (GCC) thickness, and Central Macular Thickness (CMT) in pediatric 33 OCD patients and 45 healthy controls. A sociodemographic data form, Maudsley Obsessive Compulsive Questionnaire (MOCI) and Screen for Child Anxiety and Related Disorders (SCARED) were applied. OCT imaging was performed to measure RNFL, GCL volume, GCL thickness, GCC thickness, and CMT. Results showed that the CMT was significantly lower in the OCD group compared to the healthy controls, while the GCC value was lower but not significantly different. No correlation was found between OCT measurements and scale scores. This study is the first to investigate these retinal measurements in pediatric OCD, suggesting a potential relationship that future studies should explore further.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"351 ","pages":"Article 112017"},"PeriodicalIF":2.1,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144365673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does hyperventilation alter the prefrontal hemodynamics of panic disorder during cognitive task? A functional near-infrared spectroscopy (fNIRS) based study","authors":"Pavithra Jayasankar ,&nbsp;Sonika Nichenmetla ,&nbsp;Vanteemar S Sreeraj ,&nbsp;Vijay Kumar ,&nbsp;Harleen Chhabra ,&nbsp;Narayana Manjunatha ,&nbsp;Ganesan Venkatasubramanian ,&nbsp;Y C Janardhan Reddy","doi":"10.1016/j.pscychresns.2025.112018","DOIUrl":"10.1016/j.pscychresns.2025.112018","url":null,"abstract":"<div><h3>Background</h3><div>Cerebral hypofrontality has been implicated in the pathophysiology of panic disorder, (PD). This study examined the effect of symptom provocation on prefrontal cortex activity during a cognitive task in PD patients and healthy controls (HC) using functional near-infrared spectroscopy (fNIRS).</div></div><div><h3>Methods</h3><div>We included 20 drug-naïve PD patients and 20 HC. Participants performed the N-back task before and after hyperventilation, while prefrontal activation was recorded using fNIRS. Two-way repeated-measures ANOVA was used to analyze changes in task performance and brain activation.</div></div><div><h3>Results</h3><div>There was a significant group effect for two-back D′, F(1, 32) = 4.93, <em>p</em> = 0.03, η² = 0.13, indicating that PD participants performed worse than HC. A significant time × group interaction was observed during the zero-back task in LBA8 and right prefrontal regions: RBA10, RBA8, and RBA46 (all <em>p</em> &lt; 0.05), suggesting that the HC group showed greater activation changes after hyperventilation.</div></div><div><h3>Conclusion</h3><div>Our findings highlight working memory deficits and prefrontal hypofunction in PD. The absence of right prefrontal deactivation after hyperventilation in the PD group, compared to HC, suggests altered right-hemisphere involvement in PD pathophysiology.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"351 ","pages":"Article 112018"},"PeriodicalIF":2.1,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144480898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Redefining parameter-efficiency in ADHD diagnosis: A lightweight attention-driven kolmogorov-arnold network with reduced parameter complexity and a novel activation function","authors":"Deepika,&nbsp;Meghna Sharma,&nbsp;Shaveta Arora","doi":"10.1016/j.pscychresns.2025.112016","DOIUrl":"10.1016/j.pscychresns.2025.112016","url":null,"abstract":"<div><div>As deep learning continues to advance in medical analysis, the increasing complexity of models, particularly Convolutional Neural Networks (CNNs), presents significant challenges related to interpretability, computational costs, and real-world applicability. These issues are critical in the medical domain, e.g., Attention Deficit Hyperactivity Disorder (ADHD) diagnosis, where model efficiency and interpretability are paramount. This paper proposes a novel parameter-efficient framework based on the Kolmogorov-Arnold Network (KAN) to overcome these challenges. Unlike CNNs, KAN restructures feature transformations, significantly reducing parameter overhead while preserving high classification accuracy. An attention-driven feature selection mechanism dynamically prioritizes the most significant features, minimizing irrelevant features and unnecessary computational load. Recognizing the complex and diverse nature of ADHD- related brain connectivity features, a novel activation function with learnable coefficients is introduced, enabling adaptive transformation based on specific data patterns. To further enhance model generalization, an advanced sliding window-based data augmentation technique is incorporated to meet substantial data requirements for training. Extensive experimentation on the benchmark ADHD-200 dataset demonstrates the model's superiority, achieving an accuracy of 79.25 %, an F1-score of 78. 75 % and a precision of 78.23 %, surpassing many state-of-the-art ADHD studies. Remarkably, these results are achieved using only a few thousand parameters compared to the millions required by many existing approaches, making it valuable for various resource-constrained researchers and organizations. The proposed framework, seamlessly fusing KAN, attention-driven feature selection, adaptive activation, and robust data augmentation, achieves substantial parameter reduction with enhanced performance. This lightweight architecture, combined with superior performance and interpretability, makes the proposed model highly promising for ADHD diagnosis and other complex medical applications.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"351 ","pages":"Article 112016"},"PeriodicalIF":2.1,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144514215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Causal Discovery Analysis Reveals Insights into Psychosis Proneness, Brain Function, and Environmental Factors among Young Individuals","authors":"Tuba Sahin-Ilikoglu ,&nbsp;Sisi Ma ,&nbsp;Erich Kummerfeld ,&nbsp;Eric Rawls ,&nbsp;Hao Yang Tan ,&nbsp;Timothea Toulopoulou","doi":"10.1016/j.pscychresns.2025.112015","DOIUrl":"10.1016/j.pscychresns.2025.112015","url":null,"abstract":"<div><div>Experiencing mild symptoms of psychosis, like delusions and hallucinations, occurs sometimes in general, nonclinical populations, often termed psychosis proneness (PP), potentially part of the psychosis continuum. Understanding the neural and environmental factors contributing to PP in young individuals during critical developmental periods remains unclear. We aimed to explore these directional relationships using causal discovery analysis (CDA). Participants were 194 healthy adolescent and young adult twin and sibling pairs aged between 14–24 years. They completed comprehensive assessments evaluating sociodemographic status, environmental risk, general intelligence, self-schema, psychosis proneness score (PPS), and working memory (WM) performance during fMRI (37 variables). CDA, a novel machine learning algorithm, was applied to understand the causal relationships of PPS<strong>.</strong> The analysis identified negative self-schema as having the largest potential causal effect among all assessments in PPS. Secondly, experiencing low levels of social cohesion and trust had a potential causal effect on PPS. Although our analysis could not exclude the possibility that other unmeasured factors may confound these relationships, the effect sizes (ES) were substantial, negative self-schema &amp; PPS (ES= 0.54) and social cohesion and trust &amp; PPS (ES= -0.18). PPS, on the other hand, was identified as a direct cause of greater activation in DLPFC (ES= 0.12). CDA provided simultaneous directionality for 37 variables collected on the same individuals. The findings highlight the significance of negative self-schema and social cohesion and trust in the general population with PP, emphasizing the potential for preventive interventions targeting these factors. These findings also suggest a role for DLPFC as a potential target in this regard. This study represents the first data-driven analysis to model causal mechanisms in PP in the general population.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"351 ","pages":"Article 112015"},"PeriodicalIF":2.1,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144365674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The thalamus network seems responsible for the depression and anxiety affecting risk-taking","authors":"Maede Bahri ,&nbsp;Hassan Farrahi ,&nbsp;Hami Mahdavinataj ,&nbsp;Seyed Amir Hossein Batouli","doi":"10.1016/j.pscychresns.2025.112003","DOIUrl":"10.1016/j.pscychresns.2025.112003","url":null,"abstract":"<div><div>Risk-taking refers to making decisions in risky situations that involve both high risk and high payoff. Previous studies have found that depressed and anxious individuals often exhibit impaired function in risk-taking. However, the neural mechanisms responsible for how depression and anxiety affect individuals' risk-taking are still unknown.</div><div>Using a sample of 245 participants, functional and structural brain scanning using a 3T MRI machine was performed, along with the depression anxiety stress scale (DASS) test, as well as the balloon analog risk task (BART) test.</div><div>The results showed that depression and anxiety symptoms were negatively associated with risk-taking. Also, the GM volumes in the left pallidum and the right cerebellum were negatively correlated with depression, and the GM of the left and right cerebellum were negatively correlated with anxiety. In addition, the resting state networks results indicated that depression and anxiety were positively correlated with the thalamus network. In the analysis on the causality between the scores, depression and anxiety mediated the relationship between the thalamic network and risk-taking behavior through an indirect effect.</div><div>In general, our research showed that the thalamic network affects risk-taking by mediating depression and anxiety, and this finding could be a help in the subthreshold mental health disorders.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"351 ","pages":"Article 112003"},"PeriodicalIF":2.1,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144255011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Selection, visualization, and explanation of deep features from resting-state fMRI for Alzheimer’s disease diagnosis","authors":"Mahda Nasrolahzadeh ,&nbsp;Azizeh Akbari","doi":"10.1016/j.pscychresns.2025.112005","DOIUrl":"10.1016/j.pscychresns.2025.112005","url":null,"abstract":"<div><div>Despite the remarkable achievements of deep learning networks in analyzing neuroimaging data for various tasks linked to brain functions and disorders, the opaque nature of these models and their interpretability challenges pose significant barriers to their broader use in clinical settings. This research scrutinizes the visualization of deep features from resting-state functional magnetic resonance imaging (rs-fMRI) images to discriminate individuals who are cognitively normal from those with different stages of Alzheimer's disease. Rs-fMRI data are obtained from the ADNI database. This research indicates the presence of a specific subset of deep features capable of effectively identifying Alzheimer's, termed \"informative deep features.\" By visualizing the distinct deep features, we gain better insights into the pathological patterns present at each level of the entire rs-fMRI volume, despite the challenges posed by closely resembling patterns of brain atrophy and image intensities. These deep features were visualized across the whole slide image level using deep feature-specific heatmaps and activation maps. Furthermore, the findings imply that these significant deep features may hold diagnostic potential for other central nervous system disorders beyond Alzheimer's. This framework could act as a basis for assessing the interpretability of any deep learning model in the context of diagnostic decision-making.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"351 ","pages":"Article 112005"},"PeriodicalIF":2.1,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144240847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EEG vigilance and response to oral prolonged-release ketamine in treatment-resistant depression – A double-blind randomized validation study","authors":"Anna Monn ,&nbsp;Corinne Eicher ,&nbsp;Annia Rüesch ,&nbsp;Golo Kronenberg ,&nbsp;Benjamin Offenhammer ,&nbsp;Atalìa Adank ,&nbsp;Mateo de Bardeci ,&nbsp;Cheng-Teng Ip ,&nbsp;Hanne Scherer ,&nbsp;Linda Schaekel ,&nbsp;Michael Colla ,&nbsp;Annette B. Brühl ,&nbsp;Erich Seifritz ,&nbsp;Sebastian Olbrich","doi":"10.1016/j.pscychresns.2025.112001","DOIUrl":"10.1016/j.pscychresns.2025.112001","url":null,"abstract":"<div><div>Treatment-resistant depression (TRD) is associated with reduced quality of life and elevated mortality, posing a major challenge to psychiatric care. After non-response to conventional treatments, next-level interventions such as (es)ketamine are recommended, though remission rates remain variable. Identifying reliable markers of treatment response is therefore critical. Recent evidence suggests that a higher percentage of electroencephalography (EEG) vigilance stage A1 is associated with response to intravenous ketamine in major depression. We aimed to corroborate this finding in TRD patients from a recent phase-2 randomized controlled trial of oral prolonged-release ketamine. An algorithm classified vigilance stages in 21 10-minute resting-state EEG recordings. While no significant response <span><math><mo>×</mo></math></span> treatment interaction emerged for percentage of vigilance stage A1, a small-scale meta-analysis showed a significant pooled mean difference between ketamine responders and non-responders. Applying a previously proposed A1 cutoff (43 %) yielded chance-level prediction accuracy in the combined ketamine group, but 75 % accuracy in the 240 mg subgroup. Moreover, responders to 240 mg ketamine exhibited a significantly more stable vigilance over time compared to non-responders. Although further validation in a larger sample is warranted, these findings support the clinical value of EEG vigilance as a predictive biomarker for treatment outcomes in depression.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"350 ","pages":"Article 112001"},"PeriodicalIF":2.1,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144167061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cortical gyrification patterns associated with neuroticism in panic disorder and healthy individuals","authors":"Yeong-Geon Hwang ,&nbsp;Geonseop Lee ,&nbsp;Hyun-Ju Kim","doi":"10.1016/j.pscychresns.2025.112002","DOIUrl":"10.1016/j.pscychresns.2025.112002","url":null,"abstract":"<div><h3>Background</h3><div>Several studies have demonstrated an association between neuroticism and alterations in cortical folding. However, few studies have investigated the relation between neuroticism and gyrification in panic disorder (PD) patients and healthy controls (HC).</div></div><div><h3>Methods</h3><div>This study included 102 PD patients and 128 HC. Neuroticism, anxiety symptomatology, ways of coping strategies, and health-related quality of life was evaluated. Voxel-wise correlation analyses using FreeSurfer were conducted to determine the neural correlates of neuroticism related to cortical gyrification.</div></div><div><h3>Results</h3><div>As neuroticism increased, cortical gyrification of the lingual gyrus decreased significantly in HC, whereas postcentral gyrus gyrification increased while lingual gyrus gyrification decreased in PD patients. Although lingual gyrus gyrification in HC was significantly correlated with social phobia, interoception, and agoraphobia, lingual gyrus gyrification in PD patients revealed significant correlations with emotional coping, physical functioning, and emotional role. The gyrification patterns in the postcentral gyrus was significantly correlated with excessive worry scores.</div></div><div><h3>Conclusions</h3><div>Our study suggests that increased neuroticism is associated with decreased gyrification patterns in the lingual gyrus in both HC and PD group and increased postcentral gyrus gyrification only in PD group. These gyrification alterations may influence perceived quality of life as well as high levels of anxiety in PD patients.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"350 ","pages":"Article 112002"},"PeriodicalIF":2.1,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144138222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}