Energy of Functional Brain States Correlates With Cognition in Adolescent‐Onset Schizophrenia and Healthy Persons

Adolescent-onset schizophrenia (AOS) is relatively rare, under-studied, and associated with more severe cognitive impairments and poorer outcomes than adult-onset schizophrenia. Neuroimaging has shown altered regional activations (first-order effects) and functional connectivity (second-order effects) in AOS compared to controls. The pairwise maximum entropy model (MEM) integrates first- and second-order factors into a single quantity called energy, which is inversely related to probability of occurrence of brain activity patterns. We take a combinatorial approach to study multiple brain-wide MEMs of task-associated components; hundreds of independent MEMs for various sub-systems were fit to 7 Tesla functional MRI scans. Acquisitions were collected from 23 AOS individuals and 53 healthy controls while performing the Penn Conditional Exclusion Test (PCET) for executive function, which is known to be impaired in AOS. Accuracy of PCET performance was significantly reduced among AOS compared with controls. A majority of the models showed significant negative correlation between PCET scores and the total energy attained over the fMRI. Severity of psychopathology was correlated positively with energy. Across all instantiations, the AOS group was associated with significantly more frequent occurrence of states of higher energy, assessed with a mixed effects model. An example MEM instance was investigated further using energy landscapes, which visualize high and low energy states on a low-dimensional plane, and trajectory analysis, which quantify the evolution of brain states throughout this landscape. Both supported patient-control differences in the energy profiles. The MEM's integrated representation of energy in task-associated systems can help characterize pathophysiology of AOS, cognitive impairments, and psychopathology.

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Publication Details

Journal
Human Brain Mapping
Published
2025-01-01
DOI
https://doi.org/10.1002/hbm.70129
Citations
6
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
7.16

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article

Energy of Functional Brain States Correlates With Cognition in Adolescent‐Onset Schizophrenia and Healthy Persons

Brendan Muldoon, Jyotika Bahuguna, Konasale M. Prasad, Jonathan E. Rubin et al.
6 citations
Human Brain Mapping
Functional Brain Connectivity Studies
7.16
article

Energy of Functional Brain States Correlates With Cognition in Adolescent‐Onset Schizophrenia and Healthy Persons

Brendan Muldoon, Jyotika Bahuguna, Konasale M. Prasad, Jonathan E. Rubin, Nicholas Theis, Shubha Sankar Banerjee
article en
6 citations

Abstract

Adolescent-onset schizophrenia (AOS) is relatively rare, under-studied, and associated with more severe cognitive impairments and poorer outcomes than adult-onset schizophrenia. Neuroimaging has shown altered regional activations (first-order effects) and functional connectivity (second-order effects) in AOS compared to controls. The pairwise maximum entropy model (MEM) integrates first- and second-order factors into a single quantity called energy, which is inversely related to probability of occurrence of brain activity patterns. We take a combinatorial approach to study multiple brain-wide MEMs of task-associated components; hundreds of independent MEMs for various sub-systems were fit to 7 Tesla functional MRI scans. Acquisitions were collected from 23 AOS individuals and 53 healthy controls while performing the Penn Conditional Exclusion Test (PCET) for executive function, which is known to be impaired in AOS. Accuracy of PCET performance was significantly reduced among AOS compared with controls. A majority of the models showed significant negative correlation between PCET scores and the total energy attained over the fMRI. Severity of psychopathology was correlated positively with energy. Across all instantiations, the AOS group was associated with significantly more frequent occurrence of states of higher energy, assessed with a mixed effects model. An example MEM instance was investigated further using energy landscapes, which visualize high and low energy states on a low-dimensional plane, and trajectory analysis, which quantify the evolution of brain states throughout this landscape. Both supported patient-control differences in the energy profiles. The MEM's integrated representation of energy in task-associated systems can help characterize pathophysiology of AOS, cognitive impairments, and psychopathology.

Human Brain MappingVol. 46(1)
University of Pittsburgh (US), Laboratoire de Neurosciences Cognitives (FR), VA Pittsburgh Healthcare System (US), Université de Strasbourg (FR)
National Institute of Mental Health
Reduced inequalities
Openalex Percentile: Top 4%
Functional Brain Connectivity Studies
7.16
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