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Dynamical systems theory in cognitive science and neuroscience
Author(s) -
Favela Luis H.
Publication year - 2020
Publication title -
philosophy compass
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.973
H-Index - 25
ISSN - 1747-9991
DOI - 10.1111/phc3.12695
Subject(s) - cognition , cognitive science , cognitive neuroscience , dynamical systems theory , representation (politics) , rational analysis , psychology , computer science , cognitive systems , systems neuroscience , neuroscience , epistemology , cognitive psychology , physics , politics , philosophy , myelin , quantum mechanics , political science , law , oligodendrocyte , central nervous system
Dynamical systems theory (DST) is a branch of mathematics that assesses abstract or physical systems that change over time. It has a quantitative part (mathematical equations) and a related qualitative part (plotting equations in a state space). Nonlinear dynamical systems theory applies the same tools in research involving phenomena such as chaos and hysteresis. These approaches have provided different ways of investigating and understanding cognitive systems in cognitive science and neuroscience. The ‘dynamical hypothesis’ claims that cognition is and can be understood as dynamical systems. Common consequences for such an approach include rejecting understanding cognition as information processing in nature, including eschewing explanatory roles for computation or representation. Contemporary applications of DST include mouse‐tracking studies in cognitive science and nonrepresentational perspectives on motor control in neuroscience. Such work has philosophical implications concerning the boundaries of cognition, explanation, and representations. DST offers powerful methodology and theories that raise many topics of philosophical significance.