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Topic: Structural instability

ePoster
2 ePosters
Seminar
1 seminar

In Computational Neuroscience and Dynamical Systems

Seminar · Computational Neuroscience

Back to the Continuous Attractor

Memming Park · Champalimaud Foundation

Wed, Nov 27, 2024 · 16:00 UTC

Continuous attractors offer a unique class of solutions for storing continuous-valued variables in recurrent system states for indefinitely long time intervals. Unfortunately, continuous attractors suffer from severe structural instability in general---they are destroyed by most infinitesimal changes of the dynamical law that defines them. This fragility limits their utility especially in biological systems as their recurrent dynamics are subject to constant perturbations. We observe that the bifurcations from continuous attractors in theoretical neuroscience models display various structurall

ePoster · Neuroscience

Slow Manifold Dynamics for Working Memory are near Continuous Attractors

Ábel Ságodi, Guillermo Martin, Piotr Sokół, Il Park · Bernstein Conference 2024

Continuous attractors offer a unique class of solutions for storing continuous-valued variables in recurrent system states for arbitrarily long time intervals. Unfortunately, because continuous attractors are not structurally stable, they suffer from severe structural instability in general---they are destroyed by most infinitesimal changes of the dynamical law that defines them. This fragility limits their utility especially in biological systems as their recurrent dynamics are subject to constant perturbations. We observe that bifurcations from and approximations of continuous attractors i

ePoster · Neuroscience

Approximate continuous attractor theory

Abel Sagodi, Guillermo Martin-Sanchez, Piotr Sokoł, Il Memming Park · COSYNE 2025

Continuous attractors offer a unique class of dynamical systems solutions for storing continuous-valued variables in recurrent neural states for indefinitely long time intervals. Unfortunately, continuous attractors suffer from severe structural instability in general---they are destroyed by most infinitesimal changes of the dynamical law that defines them. This fragility may limit their utility especially in biological systems as their recurrent dynamics are subject to constant perturbations. We indeed observe that the bifurcations from continuous attractors in theoretical neuroscience models

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