Characterizing the sparseness of neural codes

By Ben D. B. Willmore, David J. Tolhurst. 2001

368 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Electrical and Electronic Engineering

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In Cognitive Neuroscience

In Electrical and Electronic Engineering

Citations in the corpus

Selfless Sequential Learning (2018, methodology): “We also compute Treves–Rolls population sparseness [44] used to measure the sparsity of activity on biological neurons.”
Sparse Representation in the Human Medial Temporal Lobe (2006, background): “Let the sparseness a be the fraction of stimuli a neuron responds to or, alternatively, the probability that a neuron responds to a random stimulus (Treves and Rolls, 1991; Willmore and Tolhurst, 2001; Olshausen and Field, 2004).”
An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data (2016, background): “These principles have been explored in the field of neuroscience [31], [32].”
Unsupervised Learning of Visual Representations using Videos (2015, background): “Willmore and Tolhurst (2001) give a detailed analysis of some of these priors.”
Synaptic and network mechanisms of sparse and reliable visual cortical activity during nonclassical receptive field stimulation. (2010, methodology): “Our experimental observations were replicated with a simple computational model, suggesting that network interactions among neuronal subtypes ultimately sharpen recurrent excitation, producing specific and reliable visual responses.”
Odor representations in olfactory cortex: "sparse" coding, global inhibition, and oscillations. (2009, methodology): “…is proposed to promote the efficient coding of sensory information in the brain by having a relatively small fraction of neurons within a large population active at any given time (Hromadka et al., 2008; Laurent , 2002; Olshausen and Field, 2004; Rolls and Tovee, 1995; Willmore and Tolhurst, 2001).”
Sequential and efficient neural-population coding of complex task information (2019, neutral): “, coding) neuronsmirrors ideas in sparse coding (Olshausen and Field, 1996; Vinje and Gallant, 2000; Willmore and Tolhurst, 2001), unlike previous work on sparse codes, the phenomenon here does not appear optimized to produce particular representations of high-dimensional information such as visual ”
Energy limitation as a selective pressure on the evolution of sensory systems (2008, background): “…to single neurons but can also occur within populations of neurons (Levy and Baxter, 1996; Vinje and Gallant, 2000; Balasubramanian et al., 2001; Willmore and Tolhurst, 2001; De Polavieja, 2002; Perez-Orive et al., 2002; Schreiber et al., 2002; Olshausen and Field, 2004; Hromádka et al., 2008).”
The Packet Switching Brain (2011, neutral): “Although a number of statistics have been developed to gauge sparseness of neural response distributions, (kurtosis, activity fraction, simple threshold measures; see Willmore & Tolhurst, 2001 ), all appear to describe the same property of a system (see Graham & Field, 2006 , for an overview).”
Laminar structure of spontaneous and sensory-evoked population activity in auditory cortex (2009, positive): “Several measures of coding sparseness have been described (Olshausen and Field, 2004; Willmore and Tolhurst , 2001).”