Reaction-diffusion-like formalism for plastic neural networks reveals dissipative solitons at criticality
Autor: | Dmytro Grytskyy, Markus Diesmann, Moritz Helias |
---|---|
Jazyk: | angličtina |
Rok vydání: | 2016 |
Předmět: |
0301 basic medicine
Theoretical computer science Models Neurological FOS: Physical sciences Action Potentials 03 medical and health sciences 0302 clinical medicine Metastability Learning rule Reaction–diffusion system Learning Computer Simulation ddc:530 Statistical physics Mathematics Neuronal Plasticity Artificial neural network Quantitative Biology::Neurons and Cognition Disordered Systems and Neural Networks (cond-mat.dis-nn) Condensed Matter - Disordered Systems and Neural Networks Formalism (philosophy of mathematics) Nonlinear system 030104 developmental biology Criticality FOS: Biological sciences Quantitative Biology - Neurons and Cognition Dissipative system Neurons and Cognition (q-bio.NC) Neural Networks Computer 030217 neurology & neurosurgery |
Zdroj: | Physical review / E 93(6), 062303 (2016). doi:10.1103/PhysRevE.93.062303 Physical Review E |
DOI: | 10.1103/PhysRevE.93.062303 |
Popis: | Self-organized structures in networks with spike-timing dependent synaptic plasticity (STDP) are likely to play a central role for information processing in the brain. In the present study we derive a reaction-diffusion-like formalism for plastic feed-forward networks of nonlinear rate-based model neurons with a correlation sensitive learning rule inspired by and being qualitatively similar to STDP. After obtaining equations that describe the change of the spatial shape of the signal from layer to layer, we derive a criterion for the nonlinearity necessary to obtain stable dynamics for arbitrary input. We classify the possible scenarios of signal evolution and find that close to the transition to the unstable regime metastable solutions appear. The form of these dissipative solitons is determined analytically and the evolution and interaction of several such coexistent objects is investigated. |
Databáze: | OpenAIRE |
Externí odkaz: |