Motivation and pleasure deficits reflect altered network embedding of normal brain deviations in schizophrenia
Year: 2026
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Negative symptoms in schizophrenia are associated with significantly worse outcomes, and their factor structure (i.e., diminished motivation and pleasure [MAP] and diminished expressivity [EXP]) has only recently been clarified. Studies investigating structural imaging correlates of negative symptoms have largely focused on cortical regions involved in motivation, reward processing, affect expression, and language. Structural covariance network modeling provides a framework for examining covariance among these cortical regions in a network-like manner. METHODS: Clinical and imaging data from 203 individuals with schizophrenia were obtained from three independent data sites. Cortical thickness measures based on the Desikan-Killiany atlas were standardized using a normative modeling algorithm developed by the ENIGMA Lifespan Working Group. Structural covariance networks were constructed using a priori cortical regions of interest related to MAP and EXP. Linear regression models tested whether MAP and EXP severity predicted network embeddedness. RESULTS: = 0.3673) were significant. Howerver, only MAP severity predicted network embeddedness within the MAP network (β = 0.085, p = 0.03, 95% CI [0.009, 0.162]). DISCUSSION: Results suggest that MAP is selectively associated with network-level over-coupling of cortical morphology, whereas EXP may reflect more distributed network properties. These findings underscore the potential role of cortical network rigidity in the pathophysiology of negative symptoms.
Source: Schizophrenia Research
Authors: Jacob Holker, Aaron Clouse, Sierra Ann J. Gilday, Jacob Jensen, Delaina Cimmino, Barrett Humble, Jacob Johnston, Kennedy Madrid, Madeleine Reading, Sam Johnson, Braydon Lee, Stefan Ehrlich, Matthew J. Smith, Lei Wang, Derin Cobia
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,910
Awards: A Unified Framework for Flexible Brain Image Analysis, Genetic markers of white matter integrity in schizophrenia: Relationship to clini, Function BIRN, Mapping Abnormal Neurodevelopment in Schizophrenia, Informed Data-Driven Fusion of Behavior, Brain Function, and Genes, Functional Connectivity in Schizophrenia, Neurodegenerative and Neurodevelopmental Subcortical Shape Diffeomorphometry, Brain Glutamate and Outcome in Schizophrenia, Neuromorphometry in Schizophrenia by Computer Algorithm, Schizophrenia Data and Software Tool Federation using BIRN Infrastructure, SchizConnect: Large-Scale Schizophrenia Neuroimaging Data Mediation & Federation, Multivariate methods for identifying multitask/multimodal brain imaging biomarkers
OpenAlex ID: W7162199814
