Predicting depressed and elevated mood symptomatology in bipolar disorder using brain functional connectomes.

ABSTRACT:

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 [concorda

SUBMITTER: Sankar A 

PROVIDER: S-EPMC10491744 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature