Predicting depressed and elevated mood symptomatology in bipolar disorder using brain functional connectomes
| العنوان: | Predicting depressed and elevated mood symptomatology in bipolar disorder using brain functional connectomes |
|---|---|
| المؤلفون: | Anjali Sankar, Xilin Shen, Lejla Colic, Danielle A. Goldman, Luca M. Villa, Jihoon A. Kim, Brian Pittman, Dustin Scheinost, R. Todd Constable, Hilary P. Blumberg |
| المصدر: | Psychological Medicine. :1-10 |
| بيانات النشر: | Cambridge University Press (CUP), 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Psychiatry and Mental health, Applied Psychology |
| الوصف: | Background The study is aimed to identify brain functional connectomes predictive of depressed and elevated mood symptomatology in individuals with bipolar disorder (BD) using the machine learning approach Connectome-based Predictive Modeling (CPM). Methods Functional magnetic resonance imaging data were obtained from 81 adults with BD while they performed an emotion processing task. CPM with 5000 permutations of leave-one-out cross-validation was applied to identify functional connectomes predictive of depressed and elevated mood symptom scores on the Hamilton Depression and Young Mania rating scales. The predictive ability of the identified connectomes was tested in an independent sample of 43 adults with BD. Results CPM predicted the severity of depressed [concordance between actual and predicted values (r = 0.23, pperm (permutation test) = 0.031) and elevated (r = 0.27, pperm = 0.01) mood. Functional connectivity of left dorsolateral prefrontal cortex and supplementary motor area nodes, with inter- and intra-hemispheric connections to other anterior and posterior cortical, limbic, motor, and cerebellar regions, predicted depressed mood severity. Connectivity of left fusiform and right visual association area nodes with inter- and intra-hemispheric connections to the motor, insular, limbic, and posterior cortices predicted elevated mood severity. These networks were predictive of mood symptomatology in the independent sample (r ⩾ 0.45, p = 0.002). Conclusions This study identified distributed functional connectomes predictive of depressed and elevated mood severity in BD. Connectomes subserving emotional, cognitive, and psychomotor control predicted depressed mood severity, while those subserving emotional and social perceptual functions predicted elevated mood severity. Identification of these connectome networks may help inform the development of targeted treatments for mood symptoms. |
| تدمد: | 1469-8978 0033-2917 |
| DOI: | 10.1017/s003329172300003x |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::1d771987b8c18855d18f44f074e8de48 https://doi.org/10.1017/s003329172300003x |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi...........1d771987b8c18855d18f44f074e8de48 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 14698978 00332917 |
|---|---|
| DOI: | 10.1017/s003329172300003x |