Complexity changes in functional state dynamics suggest focal connectivity reductions

Frontiers in Human Neuroscience

Human Neuroscience

David Sutherland Blair¹  Gustavo Deco²  Joana Cabral³  Pedro Morgado⁴  Pedro Moreira⁵  Carles Soriano-Mas⁶ 

[1] Facultad de Comunicación, Universitat Pompeu Fabra, Barcelona, Spain;Facultad de Comunicación, Universitat Pompeu Fabra, Barcelona, Spain;Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain;Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany;School of Psychological Sciences, Monash University, Clayton, VIC, Australia;Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal;Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal;ICVS/3B’s, PT Government Associate Laboratory, Braga, Portugal;Clinical Academic Center—Braga, Braga, Portugal;Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal;ICVS/3B’s, PT Government Associate Laboratory, Braga, Portugal;Psychological Neuroscience Lab, CIPsi, School of Psychology, University of Minho, Braga, Portugal;Psychiatry and Mental Health Group, Neuroscience Program, Institut d’Investigació Biomèdica de Bellvitge, Barcelona, Spain;Network Center for Biomedical Research on Mental Health, Carlos III Health Institute, Madrid, Spain;Department of Social Psychology and Quantitative Psychology, Universitat de Barcelona, Barcelona, Spain;

关键词: LEiDA;    Hopf bifurcation;    whole-brain model;    obsessive-compulsive disorder;    independent component analysis;    eigendecomposition;    Shannon entropy;    network-based statistic;   

DOI  :  10.3389/fnhum.2022.958706

 received in 2022-05-31, accepted in 2022-08-03,  发布年份 2022

来源: Frontiers

【 摘 要 】

The past two decades have seen an explosion in the methods and directions of neuroscience research. Along with many others, complexity research has rapidly gained traction as both an independent research field and a valuable subdiscipline in computational neuroscience. In the past decade alone, several studies have suggested that psychiatric disorders affect the spatiotemporal complexity of both global and region-specific brain activity (Liu et al., 2013; Adhikari et al., 2017; Li et al., 2018). However, many of these studies have not accounted for the distributed nature of cognition in either the global or regional complexity estimates, which may lead to erroneous interpretations of both global and region-specific entropy estimates. To alleviate this concern, we propose a novel method for estimating complexity. This method relies upon projecting dynamic functional connectivity into a low-dimensional space which captures the distributed nature of brain activity. Dimension-specific entropy may be estimated within this space, which in turn allows for a rapid estimate of global signal complexity. Testing this method on a recently acquired obsessive-compulsive disorder dataset reveals substantial increases in the complexity of both global and dimension-specific activity versus healthy controls, suggesting that obsessive-compulsive patients may experience increased disorder in cognition. To probe the potential causes of this alteration, we estimate subject-level effective connectivity via a Hopf oscillator-based model dynamic model, the results of which suggest that obsessive-compulsive patients may experience abnormally high connectivity across a broad network in the cortex. These findings are broadly in line with results from previous studies, suggesting that this method is both robust and sensitive to group-level complexity alterations.

【 授权许可】

Unknown   
Copyright © 2022 Blair, Soriano-Mas, Cabral, Moreira, Morgado and Deco.