Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons.

By Alain Destexhe, Michael Rudolph, Jean-Marc Fellous, Terrence J. Sejnowski. Neuroscience, 2001

699 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/743c245176a2536ee501008cf316eee4045be99f

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Citations in the corpus

A Review of the Integrate-and-fire Neuron Model: I. Homogeneous Synaptic Input (2006, methodology): “Recent studies have made use of largescale numerical simulations (Destexhe and Paré 1999) and whole-cell recordings using the dynamic-clamp technique, in which the response of a neuron to an injected stochastic current with parameters (µ, σ ) is observed (Destexhe et al. 2001).”
Generalized integrate-and-fire models of neuronal activity approximate spike trains of a detailed model to a high degree of accuracy. (2004, methodology): “At each time step, N ៮ independent random variables are generated and distributed among the N Ͼ N ៮ synapses to generate slightly correlated spike trains (Destexhe and Paré 1999).”
Pyramidal Neuron Conductance State Gates Spike-Timing-Dependent Plasticity (2010, methodology): “We used rapidly fluctuating excitatory and inhibitory conductance trains that recreated several of the electrophysiological conditions neocortical neurons experience in vivo (Destexhe et al., 2001; Desai and Walcott, 2006; Haider and McCormick, 2009).”
Gain modulation from background synaptic input. (2002, background): “inhibitory presynaptic neurons (Figure al., 1992; Borg-Graham et al., 1998; Hirsch et al., 1998; Destexhe and Paré , 1999), and the associated fluctua- 1B) (see also Destexhe et al., 2001).”
Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting (2006, methodology): “…(t) (Fig.8.17b), were generated using the Ornstein-Uhlenbeck stochastic process (Uhlenbeck and Ornstein 1930), which was originally developed to describe Brownian motion, but can equally well describe in vivo-like fluctuating synaptic conductances produced by random firings (Destexhe et al. 2001).”
A Recurrent Network Mechanism of Time Integration in Perceptual Decisions (2006, neutral): “This is thus described by an Ornstein–Uhlenbeck process (Uhlenbeck and Ornstein, 1930) (for example, see Destexhe et al., 2001): ␶ AMPA dI noise ͑t͒ dt ϭ ϪI noise ͑t͒ ϩ ␩͑t͒ ͱ␶ AMPA ␴ noise 2 , where ␴ noise 2 is the variance of the noise, and ␩ is a Gaussian white noise with zero mean and unit…”
Supplementary Information for the article ‘ Correlation between neural spike trains increases with firing rate ’ (2007, neutral): “The common terms ξ c (t), and the independent terms ξ i (t), were low-pass filtered Gaussian currents with a time constant 5 ms, zero mean and unit variance [1].”
Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. (2005, methodology): “75 mV), described by Ornstein-Uhlenbeck processes with respective time constants e (cid:2) 2.728 ms and i (cid:2) 10.49 ms (Destexhe et al. 2001).”
A review of the integrate-and-fire neuron model: II. Inhomogeneous synaptic input and network properties (2006, result): “…study was extended to a sparsely connected network with conductance synapses (Mefﬁn et al. 2004), which gave results consistent with both experimental data and numerical simulations of a Hodgkin–Huxley model for quantities characterizing in vivo data (Destexhe and Paré 1999; Destexhe et al. 2001).”
Inhibitory postsynaptic potentials carry synchronized frequency information in active cortical networks. (2005, neutral): “Noisy conductances were constructed according to an Ornstein-Uhlenbeck (colored noise) model ( Destexhe et al., 2001 ).”
Pyramidal cell communication within local networks in layer 2/3 of rat neocortex (2003, methodology): “Using the dynamic clamp technique (Sharp et al. 1993) and a ‘point conductance’ model, Destexhe et al. (2001) recreated in vivo-like activity in slices.”
Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity (2013, methodology): “(3) are firing already on their own - even without any excitatory drive from the input neuron y (due to assumed background synaptic inputs; modeled in our simulations by an Ornstein-Uhlenbeck process, as suggested by in-vivo data [110]).”
Noise in the nervous system (2008, background): “, which is often referred to as 'synaptic background noise' (Ref”