Version 1
: Received: 30 April 2024 / Approved: 1 May 2024 / Online: 1 May 2024 (09:18:11 CEST)
How to cite:
Blair, D. S.; Miller, R. L.; Calhoun, V. D. A Dynamic Entropy Approach Reveals Reduced Functional Network Connectivity Trajectory Complexity in Schizophrenia. Preprints2024, 2024050068. https://doi.org/10.20944/preprints202405.0068.v1
Blair, D. S.; Miller, R. L.; Calhoun, V. D. A Dynamic Entropy Approach Reveals Reduced Functional Network Connectivity Trajectory Complexity in Schizophrenia. Preprints 2024, 2024050068. https://doi.org/10.20944/preprints202405.0068.v1
Blair, D. S.; Miller, R. L.; Calhoun, V. D. A Dynamic Entropy Approach Reveals Reduced Functional Network Connectivity Trajectory Complexity in Schizophrenia. Preprints2024, 2024050068. https://doi.org/10.20944/preprints202405.0068.v1
APA Style
Blair, D. S., Miller, R. L., & Calhoun, V. D. (2024). A Dynamic Entropy Approach Reveals Reduced Functional Network Connectivity Trajectory Complexity in Schizophrenia. Preprints. https://doi.org/10.20944/preprints202405.0068.v1
Chicago/Turabian Style
Blair, D. S., Robyn L. Miller and Vince D. Calhoun. 2024 "A Dynamic Entropy Approach Reveals Reduced Functional Network Connectivity Trajectory Complexity in Schizophrenia" Preprints. https://doi.org/10.20944/preprints202405.0068.v1
Abstract
Over the past decade and a half, dynamic functional imaging has revolutionized the neuroimaging field. Since 2009, it has revealed low dimensional brain connectivity measures, has identified potential common human spatial connectivity states, has tracked the transition patterns of these states, and has demonstrated meaningful alterations in these transition and spatial patterns in neurological disorders, psychiatric disorders, and over the course of development. Recently, researchers have begun to analyze this data from the perspective of dynamic system and information theory in the hopes of understanding how these dynamics support less easily quantified processes, such as information processing, cortical hierarchy, and consciousness. Consciousness, in particular, appears to be strongly linked to entropy production in the brain. Little attention has been paid to the effects of psychiatric disease on entropy production in the human brain, however. Even disorders characterized by substantial changes in conscious experience have not been widely analyzed from this perspective. We begin to rectify this by examining the complexity of subject trajectories in state space through the lens of information theory. Specifically, we identify a basis for the dynamic functional connectivity state space and track subject trajectories through this space over the course of the scan. The dynamic complexity of these trajectories is assessed along each dimension of the proposed basis space. Using these estimates, we demonstrate that schizophrenia patients display substantially simpler trajectories than demographically matched healthy controls, and that this drop in complexity concentrates along specific dimensions. We also demonstrate that entropy generation in at least one of these dimensions is linked to cognitive performance. Overall, results suggest great value in applying dynamic systems theory to problems of neuroimaging and reveal a substantial drop in the complexity of schizophrenia patients’ brain function.
Biology and Life Sciences, Neuroscience and Neurology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
