Uncovering hidden brain state dynamics that regulate performance and decision-making during cognition

Human cognition is influenced not only by external task demands but also latent mental processes and brain states that change over time. Here, we use novel Bayesian switching dynamical systems algorithm to identify hidden brain states and determine that these states are only weakly aligned with exte...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Nature communications Ročník 9; číslo 1; s. 2505 - 19
Hlavní autori:	Taghia, Jalil, Cai, Weidong, Ryali, Srikanth, Kochalka, John, Nicholas, Jonathan, Chen, Tianwen, Menon, Vinod
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Nature Publishing Group UK 27.06.2018 Nature Publishing Group Nature Portfolio
Predmet:	59/36 631/378/116/1925 631/378/116/2393 631/378/2649/1310 631/378/2649/2150 Adult Algorithms Animals Bayes Theorem Bayesian analysis Brain Brain - diagnostic imaging Brain - physiology Brain Mapping Circuits Cognition Cognition & reasoning Cognition - physiology Computer Simulation Decision making Decision Making - physiology Dynamical systems Female Functional morphology Humanities and Social Sciences Humans Magnetic Resonance Imaging Male Mathematical models Models, Neurological multidisciplinary Nerve Net - physiology Rats Rats, Sprague-Dawley Reconfiguration Science Science (multidisciplinary) Switching Transition probabilities Young Adult
ISSN:	2041-1723, 2041-1723
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Popis
Shrnutí:	Human cognition is influenced not only by external task demands but also latent mental processes and brain states that change over time. Here, we use novel Bayesian switching dynamical systems algorithm to identify hidden brain states and determine that these states are only weakly aligned with external task conditions. We compute state transition probabilities and demonstrate how dynamic transitions between hidden states allow flexible reconfiguration of functional brain circuits. Crucially, we identify latent transient brain states and dynamic functional circuits that are optimal for cognition and show that failure to engage these states in a timely manner is associated with poorer task performance and weaker decision-making dynamics. We replicate findings in a large sample ( N = 122) and reveal a robust link between cognition and flexible latent brain state dynamics. Our study demonstrates the power of switching dynamical systems models for investigating hidden dynamic brain states and functional interactions underlying human cognition. Brain activity is driven, in part, by external stimuli and demands, but internal brain states also change over time. Here, the authors use a novel Bayesian algorithm to track dynamic transitions between hidden neural states in human brain activity and to relate brain dynamics with behavior.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ISSN:	2041-1723 2041-1723
DOI:	10.1038/s41467-018-04723-6