Biological Psychiatry-Cognitive Neuroscience and Neuroimaging最新文献

{"title":"Rumination and Overrecruitment of Cognitive Control Circuits in Depression","authors":"","doi":"10.1016/j.bpsc.2024.04.013","DOIUrl":"10.1016/j.bpsc.2024.04.013","url":null,"abstract":"<div><h3>Background</h3><p><span>Rumination is associated with greater cognitive dysfunction and treatment resistance in major depressive disorder (MDD), but its underlying neural mechanisms are not well understood. Because rumination is characterized by difficulty in controlling negative thoughts, the current study investigated whether rumination was associated with aberrant cognitive control in the </span>absence of negative emotional information.</p></div><div><h3>Methods</h3><p>Individuals with MDD (<em>n</em> = 176) and healthy control individuals (<em>n</em><span> = 52) completed the stop signal task with varied stop signal difficulty during functional magnetic resonance imaging. In the task, a longer stop signal asynchrony made stopping difficult (hard stop), whereas a shorter stop signal asynchrony allowed more time for stopping (easy stop).</span></p></div><div><h3>Results</h3><p>In participants with MDD, higher rumination intensity was associated with greater neural activity in response to difficult inhibitory control in the frontoparietal regions. Greater activation for difficult inhibitory control associated with rumination was also positively related to state fear. The imaging results provide compelling evidence for the neural basis of inhibitory control difficulties in individuals with MDD with high rumination.</p></div><div><h3>Conclusions</h3><p>The association between higher rumination intensity and greater neural activity in regions involved in difficult inhibitory control tasks may provide treatment targets for interventions aimed at improving inhibitory control and reducing rumination in this population.</p></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"9 8","pages":"Pages 800-808"},"PeriodicalIF":5.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140873834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guide for Authors","authors":"","doi":"10.1016/S2451-9022(24)00180-0","DOIUrl":"10.1016/S2451-9022(24)00180-0","url":null,"abstract":"","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"9 8","pages":"Pages A5-A10"},"PeriodicalIF":5.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2451902224001800/pdfft?md5=9dbbd81f1e7a3188d2323627bea4b992&pid=1-s2.0-S2451902224001800-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141961124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Alterations of Functional Connectivity Dynamics in Affective and Psychotic Disorders","authors":"","doi":"10.1016/j.bpsc.2024.02.013","DOIUrl":"10.1016/j.bpsc.2024.02.013","url":null,"abstract":"<div><h3>Background</h3><p>Patients with psychosis and patients with depression exhibit widespread neurobiological abnormalities. The analysis of dynamic functional connectivity (dFC) allows for the detection of changes in complex brain activity patterns, providing insights into common and unique processes underlying these disorders.</p></div><div><h3>Methods</h3><p>We report the analysis of dFC in a large sample including 127 patients at clinical high risk for psychosis, 142 patients with recent-onset psychosis, 134 patients with recent-onset depression, and 256 healthy control participants. A sliding window–based technique was used to calculate the time-dependent FC in resting-state magnetic resonance imaging data, followed by clustering to reveal recurrent FC states in each diagnostic group.</p></div><div><h3>Results</h3><p>We identified 5 unique FC states, which could be identified in all groups with high consistency (mean <em>r</em> = 0.889 [SD = 0.116]). Analysis of dynamic parameters of these states showed a characteristic increase in the lifetime and frequency of a weakly connected FC state in patients with recent-onset depression (<em>p</em> &lt; .0005) compared with the other groups and a common increase in the lifetime of an FC state characterized by high sensorimotor and cingulo-opercular connectivities in all patient groups compared with the healthy control group (<em>p</em> &lt; .0002). Canonical correlation analysis revealed a mode that exhibited significant correlations between dFC parameters and clinical variables (<em>r</em> = 0.617, <em>p</em> &lt; .0029), which was associated with positive psychosis symptom severity and several dFC parameters.</p></div><div><h3>Conclusions</h3><p>Our findings indicate diagnosis-specific alterations of dFC and underline the potential of dynamic analysis to characterize disorders such as depression and psychosis and clinical risk states.</p></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"9 8","pages":"Pages 765-776"},"PeriodicalIF":5.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S245190222400065X/pdfft?md5=28f00b63ff36cfacb7c88001425c0940&pid=1-s2.0-S245190222400065X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140095322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emotion-Induced Frontal Alpha Asymmetry as a Candidate Predictor of Relapse After Discontinuation of Antidepressant Medication","authors":"","doi":"10.1016/j.bpsc.2024.05.001","DOIUrl":"10.1016/j.bpsc.2024.05.001","url":null,"abstract":"<div><h3>Background</h3><p>One in 3 patients relapse after antidepressant discontinuation. Thus, the prevention of relapse after achieving remission is an important component in the long-term management of major depressive disorder. However, no clinical or other predictors are established. Frontal reactivity to sad mood as measured by functional magnetic resonance imaging has been reported to relate to relapse independently of antidepressant discontinuation and is an interesting candidate predictor.</p></div><div><h3>Methods</h3><p>Patients (<em>n</em><span> = 56) who had remitted from a depressive episode while taking antidepressants underwent electroencephalography (EEG) recording during a sad mood induction procedure prior to gradually discontinuing their medication. Relapse was assessed over a 6-month follow-up period. Thirty five healthy control participants were also tested. Current source density of the EEG power in the alpha band (8–13 Hz) was extracted and alpha asymmetry was computed by comparing the power across 2 hemispheres at frontal electrodes (F5 and F6).</span></p></div><div><h3>Results</h3><p>Sad mood induction was robust across all groups. Reactivity of alpha asymmetry to sad mood did not distinguish healthy control participants from patients with remitted major depressive disorder on medication. However, the 14 (25%) patients who relapsed during the follow-up period after discontinuing medication showed significantly reduced reactivity in alpha asymmetry compared with patients who remained well. This EEG signal provided predictive power (69% out-of-sample balanced accuracy and a positive predictive value of 0.75).</p></div><div><h3>Conclusions</h3><p>A simple EEG-based measure of emotional reactivity may have potential to contribute to clinical prediction models of antidepressant discontinuation. Given the very small sample size, this finding must be interpreted with caution and requires replication in a larger study.</p></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"9 8","pages":"Pages 809-818"},"PeriodicalIF":5.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140913542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emerging Outlook on Personalized Neuromodulation for Depression: Insights From Tractography-Based Targeting","authors":"","doi":"10.1016/j.bpsc.2024.04.007","DOIUrl":"10.1016/j.bpsc.2024.04.007","url":null,"abstract":"<div><h3>Background</h3><p>Deep brain stimulation<span> has shown promise in treating individual patients with treatment-resistant depression, but larger-scale trials have been less successful. Here, we created what is, to our knowledge, the largest meta-analysis with individual patient data to date to explore whether the use of tractography enhances the efficacy of deep brain stimulation for treatment-resistant depression.</span></p></div><div><h3>Methods</h3><p>We systematically reviewed 1823 articles, selecting 32 that contributed data from 366 patients. We stratified the individual patient data based on stimulation target and use of tractography. Using 2-way type III analysis of variance, Welch’s 2-sample <em>t</em> tests, and mixed-effects linear regression models, we evaluated changes in depression severity 1 year (9–15 months) postoperatively and at last follow-up (4 weeks to 8 years) as assessed by depression scales.</p></div><div><h3>Results</h3><p><span>Tractography was used for medial forebrain bundle (MFB) (</span><em>n</em> = 17 tractography/32 total), subcallosal cingulate (SCC) (<em>n</em> = 39 tractography/241 total), and ventral capsule/ventral striatum (<em>n</em><span> = 3 tractography/41 total) targets; it was not used for bed nucleus of stria terminalis (</span><em>n</em><span> = 11), lateral habenula (</span><em>n</em> = 10), and inferior thalamic peduncle (<em>n</em> = 1). Across all patients, tractography significantly improved mean depression scores at 1 year (<em>p</em> &lt; .001) and last follow-up (<em>p</em><span> = .009). Within the target cohorts, tractography improved depression scores at 1 year for both MFB and SCC, though significance was met only at the α = 0.1 level (SCC: β = 15.8%, </span><em>p</em> = .09; MFB: β = 52.4%, <em>p</em> = .10). Within the tractography cohort, patients with MFB tractography showed greater improvement than patients with SCC tractography (72.42 ± 7.17% vs. 54.78 ± 4.08%) at 1 year (<em>p</em> = .044).</p></div><div><h3>Conclusions</h3><p>Our findings underscore the promise of tractography in deep brain stimulation for treatment-resistant depression as a method for personalization of therapy, supporting its inclusion in future trials.</p></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"9 8","pages":"Pages 754-764"},"PeriodicalIF":5.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140873758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial Board Page","authors":"","doi":"10.1016/S2451-9022(24)00176-9","DOIUrl":"10.1016/S2451-9022(24)00176-9","url":null,"abstract":"","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"9 8","pages":"Page A1"},"PeriodicalIF":5.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2451902224001769/pdfft?md5=da33030b8bbfce95ce6553dfde6c41dc&pid=1-s2.0-S2451902224001769-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141961122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Subscribers' Page","authors":"","doi":"10.1016/S2451-9022(24)00177-0","DOIUrl":"10.1016/S2451-9022(24)00177-0","url":null,"abstract":"","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"9 8","pages":"Page A2"},"PeriodicalIF":5.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141961126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transdiagnostic Mood, Anxiety, and Trauma Symptom Factors in Alcohol Use Disorder: Neural Correlates Across 3 Brain Networks","authors":"","doi":"10.1016/j.bpsc.2024.01.013","DOIUrl":"10.1016/j.bpsc.2024.01.013","url":null,"abstract":"<div><h3>Background</h3><p>Alcohol use disorder (AUD) is associated with high rates of trauma, mood, and anxiety disorders. Across these diagnoses, individual symptoms substantially overlap, highlighting the need for a transdiagnostic approach. Furthermore, there is limited research on how transdiagnostic psychopathology impacts the neural correlates of AUD. Thus, we aimed to identify symptom factors spanning diagnoses and examine how they relate to the neurocircuitry of addiction.</p></div><div><h3>Methods</h3><p><span>Eighty-six veterans with AUD completed self-report measures and reward, incentive salience, and cognitive control functional magnetic resonance imaging tasks. Factor analysis was performed on self-reported trauma, depression, anxiety, and stress symptoms to obtain transdiagnostic symptom compositions. Neural correlates of a priori–defined regions of interest in the 3 networks were assessed. Independent sample </span><em>t</em> tests were used to compare the same nodes by DSM-5 diagnosis.</p></div><div><h3>Results</h3><p>Four symptom factors were identified: Trauma distress, Negative affect, Hyperarousal<span><span>, and Somatic<span> anxiety. Trauma distress score was associated with increased cognitive control activity during response inhibition (dorsal anterior cingulate cortex). Negative affect was related to lower activation in reward regions (right caudate) but higher activation in cognitive control regions during response inhibition (left dorsolateral prefrontal cortex). Hyperarousal was related to lower reward activity during monetary reward anticipation (left caudate, right caudate). Somatic anxiety was not significantly associated with </span></span>brain activation<span><span>. No difference in neural activity was found by posttraumatic stress disorder, major depressive disorder, or </span>generalized anxiety disorder diagnosis.</span></span></p></div><div><h3>Conclusions</h3><p>These hypothesis-generating findings offer transdiagnostic symptom factors that are differentially associated with neural function and could guide us toward a brain-based classification of psychiatric dysfunction in AUD. Results warrant further investigation of transdiagnostic approaches in addiction.</p></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"9 8","pages":"Pages 837-845"},"PeriodicalIF":5.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140023651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Repetitive Negative Thoughts and the Brain as a Resource-Limited Machine","authors":"Helmet T. Karim","doi":"10.1016/j.bpsc.2024.06.011","DOIUrl":"10.1016/j.bpsc.2024.06.011","url":null,"abstract":"","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"9 8","pages":"Pages 742-743"},"PeriodicalIF":5.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141903936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Atypical Brain Aging and Its Association With Working Memory Performance in Major Depressive Disorder","authors":"","doi":"10.1016/j.bpsc.2024.04.008","DOIUrl":"10.1016/j.bpsc.2024.04.008","url":null,"abstract":"<div><h3>Background</h3><p>Patients with major depressive disorder (MDD) can present with altered brain structure and deficits in cognitive function similar to those seen in aging. However, the interaction between age-related brain changes and brain development in MDD remains understudied. In a cohort of adolescents and adults with and without MDD, we assessed brain aging differences and associations through a newly developed tool that quantifies normative neurodevelopmental trajectories.</p></div><div><h3>Methods</h3><p>A total of 304 participants with MDD and 236 control participants without depression were recruited and scanned from 3 studies under the Canadian Biomarker Integration Network for Depression. Volumetric data were used to generate brain centile scores, which were examined for 1) differences between participants with MDD and control participants; 2) differences between individuals with versus without severe childhood maltreatment; and 3) correlations with depressive symptom severity, neurocognitive assessment domains, and escitalopram treatment response.</p></div><div><h3>Results</h3><p>Brain centiles were significantly lower in the MDD group than in the control group. Brain centile was also significantly correlated with working memory in the control group but not the MDD group. No significant associations were observed between depression severity or antidepressant treatment response and brain centiles. Likewise, childhood maltreatment history did not significantly affect brain centiles.</p></div><div><h3>Conclusions</h3><p>Consistent with previous work on machine learning models that predict brain age, brain centile scores differed in people diagnosed with MDD, and MDD was associated with differential relationships between centile scores and working memory. The results support the notion of atypical development and aging in MDD, with implications for neurocognitive deficits associated with aging-related cognitive function.</p></div>","PeriodicalId":54231,"journal":{"name":"Biological Psychiatry-Cognitive Neuroscience and Neuroimaging","volume":"9 8","pages":"Pages 786-799"},"PeriodicalIF":5.7,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140854706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}