Linking brain entropy to molecular and cellular architecture in psychosis

Brain entropy reflects the complexity of intrinsic activity and has been linked to both cognitive function and psychiatric disorders. Yet its connection to the brain's neurochemical and cellular architecture remains poorly understood. By integrating molecular imaging with neuroimaging datasets, we show that the spatial distribution of cell types, neurotransmitter systems, and mitochondrial phenotypes is systematically related to brain entropy. We observed significant differences in entropy correlations: between healthy controls and individuals with schizophrenia for the mu-opioid and dopamine D1 receptors, and between controls and individuals with bipolar disorder for the norepinephrine transporter (NAT) and N-methyl-D-aspartate (NMDA) receptor. No significant differences emerged between schizophrenia and bipolar disorder in the neurotransmitter domain. At the cellular and metabolic level, both control-schizophrenia and control-bipolar comparisons revealed widespread alterations involving most mitochondrial markers, glial cells, and inhibitory neurons. These patterns point to disruptions in energy metabolism, neuroinflammatory processes, and inhibitory regulation within the clinical groups. Overall, the findings indicate that brain entropy is not randomly distributed but is closely tied to specific neurochemical systems and cellular features. This systems-level view helps explain how the complexity of brain activity arises from molecular architecture, and how it is altered in psychiatric disorders. It also provides a biological foundation for understanding brain entropy in the context of psychosis.

Authors

Institutions

Publication Details

Journal
NeuroImage
Published
2025-10-27
DOI
https://doi.org/10.1016/j.neuroimage.2025.121537
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Linking brain entropy to molecular and cellular architecture in psychosis

Vince D. Calhoun, Jingyu Liu, Qiang Li
NeuroImage
Functional Brain Connectivity Studies
article

Linking brain entropy to molecular and cellular architecture in psychosis

Vince D. Calhoun, Jingyu Liu, Qiang Li
article en

Abstract

Brain entropy reflects the complexity of intrinsic activity and has been linked to both cognitive function and psychiatric disorders. Yet its connection to the brain's neurochemical and cellular architecture remains poorly understood. By integrating molecular imaging with neuroimaging datasets, we show that the spatial distribution of cell types, neurotransmitter systems, and mitochondrial phenotypes is systematically related to brain entropy. We observed significant differences in entropy correlations: between healthy controls and individuals with schizophrenia for the mu-opioid and dopamine D1 receptors, and between controls and individuals with bipolar disorder for the norepinephrine transporter (NAT) and N-methyl-D-aspartate (NMDA) receptor. No significant differences emerged between schizophrenia and bipolar disorder in the neurotransmitter domain. At the cellular and metabolic level, both control-schizophrenia and control-bipolar comparisons revealed widespread alterations involving most mitochondrial markers, glial cells, and inhibitory neurons. These patterns point to disruptions in energy metabolism, neuroinflammatory processes, and inhibitory regulation within the clinical groups. Overall, the findings indicate that brain entropy is not randomly distributed but is closely tied to specific neurochemical systems and cellular features. This systems-level view helps explain how the complexity of brain activity arises from molecular architecture, and how it is altered in psychiatric disorders. It also provides a biological foundation for understanding brain entropy in the context of psychosis.

NeuroImageVol. 322
Center for Translational Research in Neuroimaging and Data Science (US)
Openalex Percentile: Top 69%
Functional Brain Connectivity Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.