PT  - JOURNAL ARTICLE
AU  - Veronika Vilgis
AU  - Debbie Yee
AU  - Tim J. Silk
AU  - Alasdair Vance
TI  - Multivariate Pattern Analysis (MVPA) Reveals Distinct Neural Profiles of Frontoparietal Networks in Boys with Attention-Deficit/Hyperactivity Disorder and Boys with Persistent Depressive Disorder
AID  - 10.1101/2021.03.09.434662
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.03.09.434662
4099  - http://biorxiv.org/content/early/2021/07/16/2021.03.09.434662.short
4100  - http://biorxiv.org/content/early/2021/07/16/2021.03.09.434662.full
AB  - Working memory deficits are common in attention-deficit/hyperactivity disorder (ADHD) and depression, two common neurodevelopmental disorders with overlapping cognitive profiles but distinct clinical presentation. Multivariate techniques have previously been utilized to understand working memory processes in functional brain networks in healthy adults, but have not yet been applied to investigate how working memory processes within the same networks differ within typical and atypical developing populations. We used multivariate pattern analysis (MVPA) to identify whether brain networks discriminated between spatial vs. verbal working memory processes in ADHD and Persistent Depressive Disorder (PDD). 36 male clinical participants and 19 typically developing (TD) boys participated in a fMRI scan while completing a verbal and a spatial working memory task. Within a priori functional brain networks (frontoparietal, default mode, salience) the TD group demonstrated differential response patterns to verbal and spatial working memory. Both clinical groups show less differentiation than TD, with lower classification accuracies observed in primarily the salience network in the ADHD group and in left frontoparietal and default mode networks in the PDD group. Whereas the TD group’s neural profile indicates network response patterns that are sensitive to task demands, the neural profiles of the ADHD and PDD group suggest less specificity in neural representations of spatial and verbal working memory. We highlight within-group classification as innovative tool for understanding the neural mechanisms of how cognitive processes may deviate in clinical disorders, an important intermediary step towards improving translational psychiatry to inform clinical diagnoses and treatment.Competing Interest StatementThe authors have declared no competing interest.