Optimal information storage and the distribution of synaptic weights: perceptron versus Purkinje cell.

By Nicolas J.-B. Brunel, Vincent Hakim, P. Isope, Jean-Pierre Nadal, Boris Barbour. 2004

302 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Electrical and Electronic Engineering

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Citations in the corpus

Re-evaluating circuit mechanisms underlying pattern separation (2019, neutral): “In the cerebellar cortex such supervised learning is thought to occur largely in Purkinje cells (Brunel et al., 2004; Ito, 2006; Gao et al., 2012; Ohmae and Medina, 2015; Herzfeld et al, 2018; Raymond and Medina, 2018), where precise sensorimotor associations are”
The excitatory neuronal network of the C2 barrel column in mouse primary somatosensory cortex. (2009, background): “In general, we found few largeamplitude synaptic connections but many small synaptic connections, giving rise to a highly skewed distribution of uEPSP amplitudes (Brunel et al., 2004; Feldmeyer et al., 1999, 2002, 2006; Frick et al., 2008; Song et al., 2005) (Figure 6C).”
Sparseness constrains the prolongation of memory lifetime via synaptic metaplasticity. (2008, background): “We are presently only beginning to understand how learning with discrete synapses affects functional and computational properties of neural systems (e.g., Brunel et al. 2004; Fusi and Abbott 2007).”
Statistical mechanics of complex neural systems and high dimensional data (2013, background): “However, the authors of [81] took an even more elegant approach that did not depend on even positing any particular learning rule.”
Synaptic Integration in Cerebellar Granule Cells (2008, background): “The large number of “silent” parallel fiber synapses on Purkinje cells secures a high learning capacity [ 11 ].”
The tempotron: a neuron that learns spike timing–based decisions (2006, background): “By contrast, an example of rate coding could be implemented through spike patterns in each of which a randomly chosen half of the afferents do not spike while the other half fire synchronousl”
Compressed sensing, sparsity, and dimensionality in neuronal information processing and data analysis. (2012, background): “A remarkable theoretical result is that if synapses are constrained to be either excitatory or inhibitory, then near capacity, the optimal solution is sparse, with most of the synapses silent (Brunel et al. 2004), even if the input patterns themselves show no obvious sparse structure.”
Highly Nonrandom Features of Synaptic Connectivity in Local Cortical Circuits (2005, background): “For example, in the feedforward projection from granule to Purkinje cells in the cerebellum, the distribution was fitted by a truncated Gaussian distribution, argued to be optimal for information storage [40].”
Somatosensory integration controlled by dynamic thalamocortical feed-forward inhibition. (2005, unknown): “…in the brain (Shepherd, 1998) and have been shown to control neuronal excitability in time (Berger and Luscher, 2003; Blitz and Regehr, 2005; Brunel et al., 2004; Mittmann et al., 2005; Pouille and Scanziani, 2001; Wehr and Zador, 2003) and space (Laaris et al., 2000; Lavallee and…”