activity
19982018
most citedSynchronous Behavior of Two Coupled Biological Neurons

369 citations · 827 across the 11 of their papers we have counts for

collaborators

11 papers

nlin.CD2018★ 13 cited

Mind-to-mind heteroclinic coordination: model of sequential episodic memory initiation

Valentin S. Afraimovich, Michael A. Zaks, Mikhail I. Rabinovich

Retrieval of episodic memory is a dynamical process in the large scale brain networks. In social groups, the neural patterns, associated to specific events directly experienced by…

nlin.AO2009★ 2 cited

Mutual Emotion-Cognition Dynamics

Mikhail I. Rabinovich, Mehmet K. Muezzinoglu

We present a new paradigm in the study of brain mental dynamics on the basis of the stable transient activity neural networks observed in experiments. This new approach is in contr…

q-bio.QM2005★ 23 cited

Synaptic Plasticity with Discrete state synapses

H. D. Abarbanel, S. S. Talathi, L. Gibb +1

Experimental observations on synaptic plasticity at individual glutamatergic synapses from the CA3 Shaffer collateral pathway onto CA1 pyramidal cells in the hippocampus suggest th…

q-bio.NC2003★ 4 cited

Sensory Coding with Dynamically Competitive Networks

M. I. Rabinovich, R. Huerta, A. Volkovskii +2

Studies of insect olfactory processing indicate that odors are represented by rich spatio-temporal patterns of neural activity. These patterns are very difficult to predict a prior…

nlin.CD2003★ 129 cited

Heteroclinic Contours in Neural Ensembles and the Winnerless Competition Principle

Valentin S. Afraimovich, Mikhail I. Rabinovich, Pablo Varona

The ability of nonlinear dynamical systems to process incoming information is a key problem of many fundamental and applied sciences. Information processing by computation with att…

nlin.AO2002★ 19 cited

Spatial representation of temporal information through spike timing dependent plasticity

Thomas Nowotny, Misha I. Rabinovich, Henry D. I. Abarbanel

We suggest a mechanism based on spike time dependent plasticity (STDP) of synapses to store, retrieve and predict temporal sequences. The mechanism is demonstrated in a model syste…