Multivariate Association Between Functional Connectivity Gradients and Cognition in Schizophrenia Spectrum Disorders

Background: 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 about how such dysconnectivity is related to social and nonsocial cognition and how such brain-behavior relationships associate with clinical outcomes of SSDs.

Methods: We analyzed cognitive (nonsocial and social) measures and resting-state functional magnetic resonance imaging data from the SPINS [Social Processes Initiative in Neurobiology of the Schizophrenia(s)] study (247 stable participants with SSDs and 172 healthy control participants, ages 18-55 years). 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 SSD group.

Results: The SSD group showed significantly lower differentiation on all 3 gradients. The first PLSC dimension explained 68.53% (p < .001) of the covariance and showed a significant difference between the SSD and the control group (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 the striatum (gradient 3), which were less differentiated in SSDs. Furthermore, the first dimension was positively correlated with negative symptoms and functioning in the SSD group.

Conclusions: These results suggest a potential role of lower differentiation of brain networks in cognitive and functional impairments in SSDs.