It's a Catastrophe! Testing dynamics between competing cognitive states using mixture and hidden Markov models
Year: 2014
Type: conference-paper
Abstract: Dual or multiple systems approaches are ubiquitous in cognitive science, with examples in memory, perception, categorization, cognitive development, and many other fields.Dynamical systems models with multiple stable states or modes of behavior are also increasingly used in explaining cognitive phenomena.Catastrophe theory provides a formal framework for studying the dynamics of switching between two qualitatively distinct modes of behavior.Here we present a parametric approach to testing specific predictions about the dynamics of such switches that follow from catastrophe theory.These socalled catastrophe flags are bimodality, divergence, and hysteresis.We show how these three flags can be tested using (constrained) mixture and hidden Markov models and provide an example of each using three different data sets.
Authors: Visser, I., Speekenbrink, M., Bello, P., Guarini, M., McShane, M., Scassellati, B.
Institutions: University College London, University of Amsterdam
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2223364956