Literature DB >> 26520084

Sequential memory: Binding dynamics.

Valentin Afraimovich1, Xue Gong2, Mikhail Rabinovich3.   

Abstract

Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories-episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.

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Year:  2015        PMID: 26520084     DOI: 10.1063/1.4932563

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  3 in total

1.  Itinerant complexity in networks of intrinsically bursting neurons.

Authors:  Siva Venkadesh; Ernest Barreto; Giorgio A Ascoli
Journal:  Chaos       Date:  2020-06       Impact factor: 3.642

Review 2.  Itinerancy between attractor states in neural systems.

Authors:  Paul Miller
Journal:  Curr Opin Neurobiol       Date:  2016-06-16       Impact factor: 6.627

3.  Discrete Sequential Information Coding: Heteroclinic Cognitive Dynamics.

Authors:  Mikhail I Rabinovich; Pablo Varona
Journal:  Front Comput Neurosci       Date:  2018-09-07       Impact factor: 2.380

  3 in total

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