A Predictive Coding Account for Chaotic Itinerancy
Neural and Evolutionary Computing
2021-06-17 v1 Machine Learning
Chaotic Dynamics
Abstract
As a phenomenon in dynamical systems allowing autonomous switching between stable behaviors, chaotic itinerancy has gained interest in neurorobotics research. In this study, we draw a connection between this phenomenon and the predictive coding theory by showing how a recurrent neural network implementing predictive coding can generate neural trajectories similar to chaotic itinerancy in the presence of input noise. We propose two scenarios generating random and past-independent attractor switching trajectories using our model.
Cite
@article{arxiv.2106.08937,
title = {A Predictive Coding Account for Chaotic Itinerancy},
author = {Louis Annabi and Alexandre Pitti and Mathias Quoy},
journal= {arXiv preprint arXiv:2106.08937},
year = {2021}
}