Academic
Publications
Sparse coding of sensory inputs

Sparse coding of sensory inputs,10.1016/j.conb.2004.07.007,Current Opinion in Neurobiology,Bruno A Olshausen,David J Field

Sparse coding of sensory inputs   (Citations: 241)
BibTex | RIS | RefWorks Download
Journal: Current Opinion in Neurobiology - CURR OPIN NEUROBIOL , vol. 14, no. 4, pp. 481-487, 2004
Cumulative Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.
    • ...As an alternative to the whitening hypothesis mentioned above, theoretical studies suggest that a common underlying principle of sensory processing is that the representation of information becomes more efficient in higher brain centers because neurons in these areas respond more selectively to specific features of natural sensory stimuli. This principle, commonly referred to as “sparse coding,” has been investigated in different sensory systems (see ...

    Corentin Massotet al. The Vestibular System Implements a Linear–Nonlinear Transformation In ...

    • ...The importance of sparse representations has been long recognized in applied mathematics (Baraniuk, 2007; Chen, Donoho, & Saunders, 1998) and in neuroscience, where electrophysiological recordings (DeWeese, Wehr, & Zador, 2003) and theoretical arguments (Attwell & Laughlin, 2001; Lennie, 2003) demonstrate that most neurons are silent at any given moment (Gallant & Vinje, 2000; Olshausen & Field, 1996, 2004)...

    Tao Huet al. A Network of Spiking Neurons for Computing Sparse Representations in a...

    • ...Distributed sparse neural codes have several potential benefits over dense linear codes, including explicit information representation and easy decodability at higher processing stages (Olshausen & Field, 2004), metabolic efficiency (due to the the significant cost of producing and transmitting action potentials; Lennie, 2003), and increased capacity of associativeandsequencememorymodels(Baum,Moody,&Wilczek,1988;Charles, Yap, & ...

    Adam S. Charleset al. A Common Network Architecture Efficiently Implements a Variety of Spar...

    • ...Kurtosis (Field, 1994; Lehky, Sejnowski, & Desimone, 2005; Olshausen & Field, 2004; Willmore & Tolhurst, 2001):
    M. W. Spratling. Unsupervised Learning of Generative and Discriminative Weights Encodin...
    • ..., but instead are consistent with the idea that optimal motor solutions could be refined over the course of motor learning and adaptation. Such refined solutions could be encoded within the nervous system in sparse representations that use small number of neurons at any given time. Sparse representations have been hypothesized to increased storage capacity in associative memories and increased energy efficiency ...

    J. Lucas McKayet al. Optimization of Muscle Activity for Task-Level Goals Predicts Complex ...

  • Sort by: