Closer to critical resting-state neural dynamics in individuals with higher fluid intelligence

Autor: Takahiro Ezaki, Naoki Masuda, Elohim Fonseca dos Reis, Michiko Sakaki, Takamitsu Watanabe
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Computer science
Rest
Computation
Intelligence
Models
Neurological
Medicine (miscellaneous)
Boundary (topology)
01 natural sciences
General Biochemistry
Genetics and Molecular Biology
Article
03 medical and health sciences
0302 clinical medicine
Models of neural computation
Critical point (thermodynamics)
0103 physical sciences
medicine
Humans
010306 general physics
Link (knot theory)
lcsh:QH301-705.5
Quotient
030304 developmental biology
0303 health sciences
Brain Mapping
Network models
Quantitative Biology::Neurons and Cognition
Resting state fMRI
medicine.diagnostic_test
business.industry
Brain
Magnetic Resonance Imaging
Criticality
lcsh:Biology (General)
Computational neuroscience
Artificial intelligence
General Agricultural and Biological Sciences
Functional magnetic resonance imaging
business
Algorithms
030217 neurology & neurosurgery
Zdroj: Communications Biology, Vol 3, Iss 1, Pp 1-9 (2020)
Ezaki, T, Fonseca dos Reis, E, Watanabe, T, Sakaki, M & Masuda, N 2020, ' Closer to critical resting-state neural dynamics in individuals with higher fluid intelligence ', Communications Biology, vol. 3, 52 (2020) . https://doi.org/10.1038/s42003-020-0774-y
Communications Biology
ISSN: 2399-3642
DOI: 10.1038/s42003-020-0774-y
Popis: According to the critical brain hypothesis, the brain is considered to operate near criticality and realize efficient neural computations. Despite the prior theoretical and empirical evidence in favor of the hypothesis, no direct link has been provided between human cognitive performance and the neural criticality. Here we provide such a key link by analyzing resting-state dynamics of functional magnetic resonance imaging (fMRI) networks at a whole-brain level. We develop a data-driven analysis method, inspired from statistical physics theory of spin systems, to map out the whole-brain neural dynamics onto a phase diagram. Using this tool, we show evidence that neural dynamics of human participants with higher fluid intelligence quotient scores are closer to a critical state, i.e., the boundary between the paramagnetic phase and the spin-glass (SG) phase. The present results are consistent with the notion of “edge-of-chaos” neural computation.
Ezaki et al. develop a computational tool to analyze neural resting-state dynamics of functional magnetic resonance imaging data. Their data from adult humans suggest that the ability to think logically and find solutions improves with the brain located closer to criticality.
Databáze: OpenAIRE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje