Effects of Neuromodulation in a Cortical Network Model of Object Working Memory Dominated by Recurrent Inhibition

By Nicolas J.-B. Brunel, Xiao-Jing Wang. Journal of Computational Neuroscience, 2004

608 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/0dd3703bd7f9ed2f7ef146d5551550129f12cf68

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In Cellular and Molecular Neuroscience

In Cognitive Neuroscience

Citations in the corpus

A Neuronal Model of Predictive Coding Accounting for the Mismatch Negativity (2012, methodology): “AMPA, NMDA, and GABA synaptic currents are modeled according to Brunel and Wang (2001) as follows: Isyn t IAMPA t INMDA t IGABA t Iext t with IAMPA t gAMPA v t VE j 1 CE wj AMPAsj AMPA t INMDA t gNMDA v t VE 1 Mg2 ]exp 0.062v t /3.57 j 1 CE wj NMDAsj NMDA t IGABA t gGABA v t Vi j 1 CI wj GABAsj…”
One-dimensional dynamics of attention and decision making in LIP. (2008, background): “Although attractor models exist that are capable of ignoring distractors to some extent (Brunel and Wang, 2001), they rely on a suppression of the transient response to the distractor by the active attractor.”
Intrinsically motivated action-outcome learning and goal-based action recall: a system-level bio-constrained computational model. (2013, background): “on the reciprocal influence of BG and cortex, rather than on the fast time scale reactions happening at the level of single neurons (Wilson and Cowan, 1972; Brunel and Wang, 2001; Bojak et al., 2003).”
Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons (2014, methodology): “The stability of the equilibrium state of the Poisson network to slow heterogeneous perturbations is specified by the eigenvalues of the same stability matrix as the LIF network (Online Methods equation (12)).”
The Noisy Brain: Stochastic Dynamics as a Principle of Brain Function (2010, unknown): “Consequently , we choose a weaker value w − = 1 − r ( w + − 1 ) / ( 1 − r ) , so that the over - all recurrent excitatory synaptic drive in the spontaneous state remains constant as w + is varied ( Brunel and Wang 2001 ) .”
The Dynamics of Legged Locomotion: Models, Analyses, and Challenges (2006, background): “This assumes spatial homogeneity of membrane voltage within the cell and treats the distributed membrane transport processes collectively as ionic currents, determined via gating variables that describe the fraction of open channels.”
The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields (2008, background): “For example, an extended mean-field framework, which is consistent with the IF and realistic synaptic equations that considers both the fast and slow glutamatergic excitatory synaptic dynamics (AMPA and NMDA) and the dynamics of GABA inhibitory synapses, can be found in [10].”
Neurodynamics of biased competition and cooperation for attention: a model with spiking neurons. (2005, methodology): “The mean-field study ensures that the dynamics will converge to a stationary attractor that is consistent with what we were looking for (Brunel and Wang 2001; Del Giudice et al. 2003).”
A Recurrent Network Mechanism of Time Integration in Perceptual Decisions (2006, methodology): “…the population firing rate of each population can be described by the Wilson–Cowan type of equations (Wilson and Cowan, 1972, 1973) with a fast time constant (␶ r ϭ 2 ms) in noisy networks (van Vreeswijk and Sompolinsky, 1998; Brunel et al., 2001; Fourcaud and Brunel, 2002; Renart et al., 2003).”
The Catechol-O-Methyltransferase Polymorphism: Relations to the Tonic–Phasic Dopamine Hypothesis and Neuropsychiatric Phenotypes (2004, methodology): “Detailed biophysical models of PFC neuronal architecture support the validity of the proposed complementary roles of tonic and phasic DA in neuronal ensembles (Brunel and Wang, 2001; Durstewitz et al, 1999, 2000a, b).”
The Brain's Router: A Cortical Network Model of Serial Processing in the Primate Brain (2010, background): “In sensory and routing areas these homogeneous populations were grouped into larger groups, forming local modules as used in previous studies [36,37].”
The Virtual Brain: a simulator of primate brain network dynamics (2013, methodology): “The BrunelWang model (Brunel and Wang, 2001, 2003) is a mean field model derived from integrate-and-fire spiking neurons and makes the approximation of randomly distributed interspike intervals.”