Biological psychiatry. Cognitive neuroscience and neuroimaging最新文献

{"title":"History of Peripartum Depression Moderates the Association Between Estradiol Polygenic Risk Scores and Basal Ganglia Volumes in Major Depressive Disorder.","authors":"Yasmin A Harrington, Marco Paolini, Lidia Fortaner-Uyà, Melania Maccario, Elisa M T Melloni, Sara Poletti, Cristina Lorenzi, Raffaella Zanardi, Cristina Colombo, Francesco Benedetti","doi":"10.1016/j.bpsc.2024.09.011","DOIUrl":"https://doi.org/10.1016/j.bpsc.2024.09.011","url":null,"abstract":"<p><strong>Background: </strong>The neurobiological differences between women who have experienced a peripartum episode and those who have only had episodes outside of this period are not well understood.</p><p><strong>Methods: </strong>64 parous female patients with major depressive disorder that have either a positive (n=30) or negative (n=34) history of peripartum depression (PPD) underwent MRI acquisition to obtain structural brain images. An independent two-sample t-test comparing patients with and without a history of PPD was performed using voxel-based morphometry analysis (VBM). Additionally, polygenic risk scores (PRSs) for estradiol were calculated and a moderation analysis was conducted between 3 estradiol PRSs and PPD history status on extracted cluster volumes using IBM SPSS PROCESS macro.</p><p><strong>Results: </strong>The VBM analysis identified larger grey matter volumes in bilateral clusters encompassing the putamen, pallidum, caudate, and thalamus in patients with PPD history compared to patients without a history. The moderation analysis identified a significant interaction of 2 estradiol PRSs and PPD history on grey matter cluster volumes with a positive effect in PPD women and a negative effect in women with no history of PPD.</p><p><strong>Conclusions: </strong>Our findings demonstrate that women who have experienced a peripartum episode are neurobiologically distinct from women who have no history of PPD in a cluster within the basal ganglia, an area important for motivation, decision-making, and emotional processing. Furthermore, we show that the genetic load for estradiol has a differing effect in this area based on PPD status which supports the claim that PPD is associated with sensitivity to sex steroid hormones.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142373755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Obsessive-Compulsive Disorder Comorbid with or without Obsessive-Compulsive Personality Disorder: Conceptual Implications, Clinical Correlates and Brain Morphometries.","authors":"Chen Zhang, Zongfeng Zhang, Rui Gao, Yongjun Chen, Xuan Cao, Xianghan Yi, Qing Fan","doi":"10.1016/j.bpsc.2024.09.010","DOIUrl":"https://doi.org/10.1016/j.bpsc.2024.09.010","url":null,"abstract":"<p><strong>Background: </strong>Obsessive-compulsive disorder (OCD) is often comorbid with obsessive-compulsive personality disorder (OCPD). The relationship between OCD and OCPD is complex, and the impact of comorbid OCPD on OCD remains underexplored, necessitating further research.. This study aims to investigate the clinical correlates and brain morphometries associated with comorbid OCPD in a large sample of unmedicated OCD patients.</p><p><strong>Methods: </strong>A total of 248 unmedicated patients diagnosed with OCD (45 comorbid with OCPD) were included in this study. All participants were assessed for OCD symptoms, OCPD traits, obsessive beliefs, depression and anxiety. Among them, 145 patients (23 comorbid with OCPD) volunteered to receive magnetic resonance imaging (MRI) brain scans.</p><p><strong>Results: </strong>Approximately 18% (45/248) of OCD patients were comorbid with OCPD. OCD comorbid with OCPD (OCD+OCPD) exhibited more severe OCD symptoms, obsessive beliefs, depression and anxiety than OCD comorbid without OCPD. Additionally, the severity of OCPD was positively correlated with OCD symptoms and obsessive beliefs. Furthermore, OCD+OCPD patients exhibited increased cortical complexity in the left superior parietal lobule and left precuneus, which mediated the relationship between OCPD and OCD symptoms only in OCD patients comorbid without OCPD.</p><p><strong>Conclusions: </strong>The co-occurrence of OCPD may contribute to the heightened severity of psychopathological symptoms and associated brain morphological alterations in OCD patients, indicating distinct but interrelated constructs between these two disorders.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142334317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opposite-direction spatial working memory biases in people with schizophrenia and healthy controls.","authors":"James M Gold, Sonia Bansal, Benjamin Robinson, Alan Anticevic, Steven J Luck","doi":"10.1016/j.bpsc.2024.09.008","DOIUrl":"10.1016/j.bpsc.2024.09.008","url":null,"abstract":"<p><strong>Background: </strong>People with schizophrenia (PSZ) show Impaired accuracy in spatial working memory (SWM), thought to reflect abnormalities in the sustained firing of feature selective neurons that are critical for successful encoding and maintenance processes. Recent research has documented a new source of variance in the accuracy of SWM: In healthy adults, SWM representations are unconsciously biased by prior trials such that current-trial responses are attracted to previous-trial responses (serial dependence). This opens a new window to examine how schizophrenia impacts both the sustained neural firing representing the current-trial target and longer-term synaptic plasticity that stores previous-trial information.</p><p><strong>Methods: </strong>We examined response accuracy in a single-item SWM test with delay intervals of 0, 2, 4, or 8 seconds in 41 PSZ and 32 demographically similar healthy controls (HCS). Our main dependent variable was the bias index, which quantifies the extent to which the current-trial responses were biased toward or away from the previous-trial target.</p><p><strong>Results: </strong>PSZ showed opposite-direction serial dependence bias effects: HCS showed an attractive bias which increased over increasing delays whereas PSZ showed a repulsion bias that increased over delays. In PSZ, the magnitude of the repulsion bias correlated negatively with broad measures of cognitive ability and WM capacity.</p><p><strong>Conclusions: </strong>PSZ show opposite-direction effects of previous trials on WM. Such qualitatively distinct differences in performance are extremely rare in psychopathology and may index a fundamental alteration in neural processing that could serve as a valuable biomarker for pathophysiology and treatment development research.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142334318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brain age is not a significant predictor of relapse risk in late-life depression.","authors":"Helmet T Karim, Andrew Gerlach, Meryl A Butters, Robert Krafty, Brian D Boyd, Layla Banihashemi, Bennett A Landman, Olusola Ajilore, Warren D Taylor, Carmen Andreescu","doi":"10.1016/j.bpsc.2024.09.009","DOIUrl":"10.1016/j.bpsc.2024.09.009","url":null,"abstract":"<p><strong>Introduction: </strong>Late-life depression (LLD) has been associated cross-sectionally with lower brain structural volumes and accelerated brain aging compared to healthy controls (HC). There are few longitudinal studies on the neurobiological predictors of recurrence in LLD. We tested a machine learning (ML) brain age model and its prospective association with LLD recurrence risk.</p><p><strong>Methods: </strong>We recruited individuals with LLD (n=102) and HC (n=43) into a multi-site 2-yr longitudinal study. Individuals with LLD were enrolled within 4 months of remission. Remitted LLD participants underwent baseline neuroimaging and longitudinal clinical follow-up. Over 2 years, 43 LLD participants relapsed (REL) and 59 stayed in remission (REM). We used a previously developed ML brain age algorithm to compute brain age at baseline and we evaluated brain age group differences (HC vs. LLD and HC vs. REM vs. REL). We conducted a Cox proportional hazards model to evaluate whether baseline brain age predicted time to relapse.</p><p><strong>Results: </strong>We found that brain age did not significantly differ between HC and LLD as well as HC, REM, and REL groups. Brain age did not significantly predict time to relapse.</p><p><strong>Discussion: </strong>In contrast to our hypothesis, we found that brain age did not differ between non-depressed controls and individuals with remitted LLD, and brain age was not associated with subsequent recurrence. This is in contrast to existing literature which has identified baseline brain age differences in late life but in line with work that shows no differences between those who do and do not relapse on gross structural measures.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142334315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Utility of a Functional Magnetic Resonance Imaging (fMRI) Cannabis Cue-Reactivity Paradigm in Treatment Seeking Adults with Cannabis Use Disorder.","authors":"Gregory L Sahlem, Logan T Dowdle, Nathaniel L Baker, Brian J Sherman, Kevin M Gray, Aimee L McRae-Clark, Brett Froeliger, Lindsay M Squeglia","doi":"10.1016/j.bpsc.2024.09.006","DOIUrl":"10.1016/j.bpsc.2024.09.006","url":null,"abstract":"<p><strong>Background: </strong>Functional magnetic resonance imaging (fMRI) studies examining cue-reactivity in cannabis use disorder (CUD) have either had small sample sizes or involved non-treatment-seeking participants. As a secondary analysis, we administered an fMRI cue-reactivity task to CUD participants entering two separate clinical trials (varenicline or repetitive Transcranial Magnetic Stimulation-rTMS) to determine the task activation patterns for treatment-seeking participants with CUD. We aimed to determine the activation patterns for the total sample and determined behavioral correlates. We additionally compared studies to determine if patterns were consistent.</p><p><strong>Methods: </strong>Treatment-seeking participants with moderate or severe CUD had behavioral craving measured at baseline via the short form of the Marijuana Craving Questionnaire (MCQ-SF) and completed a visual cannabis cue-reactivity task during fMRI (measuring the Blood-Oxygen-Level-Dependent-BOLD response) following 24-hours of cannabis-abstinence.</p><p><strong>Results: </strong>Sixty-five participants were included (37-varenicline, 28-rTMS; 32% female; mean-age 30.4±9.9SD). When contrasting cannabis-images vs. matched-neutral-images, participants showed greater BOLD response in bilateral ventromedial-prefrontal, dorsolateral-prefrontal, anterior cingulate, and visual cortices, as well as the striatum. There was stronger task-based functional-connectivity (tbFC) between the medial prefrontal cortex and both the amygdala and the visual cortex. Craving negatively correlated with BOLD response in the left ventral striatum (R²=-0.32; p=0.01) in the full sample. There were no significant differences in either activation or tbFC between studies.</p><p><strong>Discussion: </strong>Among two separate treatment-seeking groups with CUD, there was increased cannabis cue-reactivity and tbFC in regions related to executive function and reward processing. Cannabis-craving was negatively associated with cue-reactivity in the left ventral striatum.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142334316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Altered development of the Hurst Exponent in medial prefrontal cortex in preschoolers with autism.","authors":"Annika C Linke, Bosi Chen, Lindsay Olson, Michaela Cordova, Molly Wilkinson, Tiffany Wang, Meagan Herrera, Madison Salmina, Adriana Rios, Judy Mahmalji, Tess Do, Jessica Vu, Michelle Budman, Alexis Walker, Inna Fishman","doi":"10.1016/j.bpsc.2024.09.003","DOIUrl":"10.1016/j.bpsc.2024.09.003","url":null,"abstract":"<p><strong>Background: </strong>Atypical balance of excitation (E) and inhibition (I) in the brain is thought to contribute to the emergence and symptomatology of autism spectrum disorders (ASD). E/I ratio can be estimated from resting state functional magnetic resonance imaging (fMRI) using the Hurst Exponent (H). A recent study reported decreased ventromedial prefrontal cortex (vmPFC) H in male adults with ASD. Part of the default mode network (DMN), vmPFC plays an important role in emotion regulation, decision making, and social cognition. It frequently shows altered function and connectivity in autistic individuals.</p><p><strong>Methods: </strong>The current study presents the first fMRI evidence of altered early development of vmPFC H and its link to DMN functional connectivity (FC) and emotional control in toddlers and preschoolers with ASD. 83 children (n=45 ASD), ages 1½ - 5 years, underwent natural sleep fMRI as part of a longitudinal study.</p><p><strong>Results: </strong>In a cross-sectional analysis, vmPFC H decreased with age in children with ASD, reflecting increasing E/I ratio, but not in typically developing children. This effect remained significant when controlling for gestational age at birth, socioeconomic status, or ethnicity. The same pattern was also observed in a subset of children with longitudinal fMRI data acquired two years apart on average. Lower vmPFC H was further associated with reduced FC within the DMN as well as with higher emotional control deficits (though only significant transdiagnostically).</p><p><strong>Conclusions: </strong>These results suggest an early onset of E/I imbalances in vmPFC in ASD with likely consequences for the maturation of the DMN.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142303305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Symptom Dimensions and Cognitive Impairments in Individuals at Clinical High Risk for Psychosis.","authors":"Tian Hong Zhang, Li Hua Xu, Yan Yan Wei, HuiRu Cui, Xiao Chen Tang, Ye Gang Hu, Hai Chun Liu, Zi Xuan Wang, Tao Chen, Zheng Hui Yi, Chun Bo Li, Ji Jun Wang","doi":"10.1016/j.bpsc.2024.09.002","DOIUrl":"https://doi.org/10.1016/j.bpsc.2024.09.002","url":null,"abstract":"<p><strong>Objective: </strong>Understanding the intricate relationship between symptom dimensions, clusters, and cognitive impairments is crucial for early detection and intervention in individuals at clinical high-risk(CHR) for psychosis. This study delves into this complex interplay within a CHR sample and aims to predict the conversion to psychosis.</p><p><strong>Methods: </strong>A comprehensive cognitive assessment was performed among 744 CHR individuals. The study included a three-year follow-up period to assess conversion to psychosis. Symptom profiles were determined using the Structured Interview for Prodromal Syndromes. By applying factor analysis, symptom dimensions were categorized as dominant negative symptoms(NS), positive symptoms-stressful(PS-S), and positive symptoms-odd(PS-O). The factor scores were used to define three dominant symptom groups. Latent class analysis(LCA) and factor mixture model(FMM) were employed to identify discrete clusters based on symptom patterns. The three-class solution was chosen for the LCA and FMM analysis.</p><p><strong>Results: </strong>Individuals in the dominant NS group exhibited significantly higher conversion rates to psychosis than those in the other groups. Specific cognitive variables, including performance in the Brief Visuospatial Memory Test-Revised(Odd ratio, OR=0.702, p=0.001) and Neuropsychological Assessment Battery mazes(OR=0.776, p=0.024), significantly predicted conversion to psychosis. Notably, cognitive impairments associated with NS and PS-S affected different cognitive domains. LCA- and FMM-Cluster 1, characterized by severe NS and PS-O, exhibited more impairments in cognitive domains than other clusters. No significant difference in the conversion rate was observed among LCA and FMM clusters.</p><p><strong>Conclusions: </strong>These findings highlight the importance of NS in the development of psychosis and suggest specific cognitive domains that are affected by symptom dimensions.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142303310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neural Basis of Pain Empathy Dysregulations in Mental Disorders: A Preregistered Neuroimaging Meta-Analysis.","authors":"Jingxian He, Mercy Chepngetich Bore, Heng Jiang, Xianyang Gan, Junjie Wang, Jialin Li, Xiaolei Xu, Lan Wang, Kun Fu, Liyuan Li, Bo Zhou, Keith Kendrick, Benjamin Becker","doi":"10.1016/j.bpsc.2024.08.019","DOIUrl":"10.1016/j.bpsc.2024.08.019","url":null,"abstract":"<p><strong>Background: </strong>Pain empathy represents a fundamental building block of several social functions, which have been demonstrated to be impaired across various mental disorders by accumulating evidence from case-control functional magnetic resonance imaging studies. However, it remains unclear whether the dysregulations are underpinned by robust neural alterations across mental disorders.</p><p><strong>Methods: </strong>This study utilized coordinate-based meta-analyses to quantitatively determine robust markers of altered pain empathy across mental disorders. To support the interpretation of the findings, exploratory network-level and behavioral meta-analyses were conducted.</p><p><strong>Results: </strong>Quantitative analysis of 11 case-control functional magnetic resonance imaging studies with data from 296 patients and 229 control participants revealed that patients with mental disorders exhibited increased pain empathic reactivity in the left anterior cingulate gyrus, adjacent medial prefrontal cortex, and right middle temporal gyrus but decreased activity in the left cerebellum IV/V and left middle occipital gyrus compared with control participants. The hyperactive regions showed network-level interactions with the core default mode network and were associated with affective and social cognitive domains.</p><p><strong>Conclusions: </strong>The findings suggest that pain empathic alterations across mental disorders are underpinned by excessive empathic reactivity in brain systems involved in empathic distress and social processes, highlighting a shared therapeutic target to normalize basal social dysfunctions in mental disorders.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142303309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multitrait analysis to decipher the intertwined genetic architecture of neuroanatomical phenotypes and psychiatric disorders.","authors":"Antoine Auvergne, Nicolas Traut, Léo Henches, Lucie Troubat, Arthur Frouin, Christophe Boetto, Sayeh Kazem, Hanna Julienne, Roberto Toro, Hugues Aschard","doi":"10.1016/j.bpsc.2024.08.018","DOIUrl":"https://doi.org/10.1016/j.bpsc.2024.08.018","url":null,"abstract":"<p><strong>Background: </strong>There is increasing evidence of shared genetic factors between psychiatric disorders and brain magnetic resonance imaging (MRI) phenotypes. However, deciphering the joint genetic architecture of these outcomes has proven challenging, and new approaches are needed to infer potential genetic structure underlying those phenotypes. Multivariate analyses is arising as a meaningful approach to reveal links between MRI phenotypes and psychiatric disorders missed by univariate approaches.</p><p><strong>Methods: </strong>We first conducted univariate and multivariate genome-wide association studies (GWAS) for nine MRI-derived brain volume phenotypes in 20K UK Biobank participants. We next performed various complementary enrichment analyses to assess whether and how univariate and multitrait approaches can distinguish disorder-associated and non-disorder-associated variants from six psychiatric disorders: bipolarity, attention-deficit/hyperactivity disorder (ADHD), autism, schizophrenia, obsessive-compulsive disorder, and major depressive disorder. Finally, we conducted a clustering analysis of top associated variants based on their MRI multitrait association using an optimized k-medoids approach.</p><p><strong>Results: </strong>Univariate MRI GWAS displayed only negligible genetic correlation with psychiatric disorders, while multitrait GWAS identified multiple new associations and showed significant enrichment for variants related to both ADHD and schizophrenia. Clustering analyses further detected two clusters displaying not only enrichment for association with ADHD and schizophrenia, but also consistent direction of effects. Functional annotation analyses of those clusters pointed to multiple potential mechanisms, suggesting in particular a role of neurotrophins pathways on both MRI and schizophrenia.</p><p><strong>Conclusions: </strong>Our results show that multitrait association signature can be used to infer genetically-driven latent MRI variables associated with psychiatric disorders, opening paths for future biomarker development.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142303307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multivariate Association between Functional Connectivity Gradients and Cognition in Schizophrenia Spectrum Disorders.","authors":"Ju-Chi Yu, Colin Hawco, Lucy Bassman, Lindsay D Oliver, Miklos Argyelan, James M Gold, Sunny X Tang, George Foussias, Robert W Buchanan, Anil K Malhotra, Stephanie H Ameis, Aristotle N Voineskos, Erin W Dickie","doi":"10.1016/j.bpsc.2024.09.001","DOIUrl":"https://doi.org/10.1016/j.bpsc.2024.09.001","url":null,"abstract":"<p><strong>Background: </strong>Schizophrenia Spectrum Disorders (SSDs), which are characterized by social cognitive deficits, have been associated with dysconnectivity in \"unimodal\" (e.g., visual, auditory) and \"multimodal\" (e.g., default-mode and frontoparietal) cortical networks. However, little is known regarding how such dysconnectivity relates to social and non-social cognition, and how such brain-behavioral relationships associate with clinical outcomes of SSDs.</p><p><strong>Methods: </strong>We analyzed cognitive (non-social and social) measures and resting-state functional magnetic resonance imaging data from the 'Social Processes Initiative in Neurobiology of the Schizophrenia(s) (SPINS)' study (247 stable participants with SSDs and 172 healthy controls, ages 18-55). We extracted gradients from parcellated connectomes and examined the association between the first 3 gradients and the cognitive measures using partial least squares correlation (PLSC). We then correlated the PLSC dimensions with functioning and symptoms in the SSDs group.</p><p><strong>Results: </strong>The SSDs group showed significantly lower differentiation on all three gradients. The first PLSC dimension explained 68.53% (p<.001) of the covariance and showed a significant difference between SSDs and Controls (bootstrap p<.05). PLSC showed that all cognitive measures were associated with gradient scores of unimodal and multimodal networks (Gradient 1), auditory, sensorimotor, and visual networks (Gradient 2), and perceptual networks and striatum (Gradient 3), which were less differentiated in SSDs. Furthermore, the first dimension was positively correlated with negative symptoms and functioning in the SSDs group.</p><p><strong>Conclusions: </strong>These results suggest a potential role of lower differentiation of brain networks in cognitive and functional impairments in SSDs.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142303308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}