Graph Models of Neurodynamics to Support Oscillatory Associative Memories

Andrade, G.P. and Ruszinkó, Miklós and Kozma, R. (2018) Graph Models of Neurodynamics to Support Oscillatory Associative Memories. In: 2018 International Joint Conference on Neural Networks, IJCNN 2018. IEEE. ISBN 9781509060146


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Recent advances in brain imaging techniques require the development of advanced models of brain networks and graphs. Previous work on percolation on lattices and random graphs demonstrated emergent dynamical regimes, including zero- and non-zero fixed points, and limit cycle oscillations. Here we introduce graph processes using lattices with excitatory and inhibitory nodes, and study conditions leading to spatio-temporal oscillations. Rigorous mathematical analysis provides insights on the possible dynamics and, of particular concern to this work, conditions producing cycles with very long periods. A systematic parameter study demonstrates the presence of phase transitions between various regimes, including oscillations with emergent metastable patterns. We studied the impact of external stimuli on the dynamic patterns, which can be used for encoding and recall in robust associative memories. © 2018 IEEE.

Item Type: Book Section
Uncontrolled Keywords: Brain Mapping; Solvents; PERCOLATION; Graph theory; Graph theory; cellular automata; cellular automata; mathematical analysis; associative memory; associative memory; Percolation (solid state); Associative processing; Parameter studies; Neurodynamics; Neurodynamics; Limit Cycle Oscillation (LCO); External stimulus; Associative storage; Brain imaging techniques; Spatio-temporal oscillations;
Subjects: Q Science / természettudomány > QA Mathematics / matematika > QA166-QA166.245 Graphs theory / gráfelmélet
Depositing User: MTMT SWORD
Date Deposited: 14 Jan 2019 07:32
Last Modified: 16 Jan 2019 07:12

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