Scholars@Duke
Nicolas Brunel

Nicolas Brunel

Adjunct Professor of Neurobiology
Neurobiology
311 Research Drive, Durham, NC 27710

Scholarly Works - Conferences

Rate models with delays and the dynamics of large networks of spiking neurons

Conference Progress of Theoretical Physics Supplement · June 28, 2006 We investigate the dynamics of a one-dimensional network of spiking neurons with spatially modulated excitatory and inhibitory interactions through extensive numerical simulations. We find that the network displays a rich repertoire of dynamical states as ... Full text Cite

Dynamics of the instantaneous firing rate in response to changes in input statistics.

Conference J Comput Neurosci · June 2005 We review and extend recent results on the instantaneous firing rate dynamics of simplified models of spiking neurons in response to noisy current inputs. It has been shown recently that the response of the instantaneous firing rate to small amplitude osci ... Full text Link to item Cite

Phase diagrams of sparsely connected networks of excitatory and inhibitory spiking neurons

Conference Neurocomputing · June 1, 2000 The dynamics of networks of sparsely connected excitatory and inhibitory integrate-and-fire neurons is studied analytically. The 'phase diagrams' of such systems include: synchronous states in which neurons fire regularly; Asynchronous states with stationa ... Full text Cite

Dynamics of networks of randomly connected excitatory and inhibitory spiking neurons.

Conference J Physiol Paris · 2000 Recent advances in the understanding of the dynamics of populations of spiking neurones are reviewed. These studies shed light on how a population of neurones can follow arbitrary variations in input stimuli, how the dynamics of the population depends on t ... Full text Link to item Cite

Modeling memory: what do we learn from attractor neural networks?

Conference C R Acad Sci III · 1998 In this paper we summarize some of the main contributions of models of recurrent neural networks with associative memory properties. We compare the behavior of these attractor neural networks with empirical data from both physiology and psychology. This ty ... Full text Link to item Cite

Cross-correlations in sparsely connected recurrent networks of spiking neurons

Conference Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics · January 1, 1997 We study the dynamics of sparsely connected recurrent networks composed of excitatory and inhibitory integrate-and-fire (IF) neurons firing at low rates, and in particular cross-correlations (CC) between spike times of pairs of neurons using both numerical ... Full text Cite

Learning internal representations in an analog attractor neural network

Conference INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, SUPPLEMENTARY ISSUE, 1995 · January 1, 1995 Link to item Cite

Quantitative modeling of local Hebbian reverberations in primate cortex

Conference INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, SUPPLEMENTARY ISSUE, 1995 · January 1, 1995 Link to item Cite