Literature DB >> 15321069

Sparse coding of sensory inputs.

Bruno A Olshausen1, David J Field.   

Abstract

Several theoretical, computational, and experimental studies suggest that neurons encode sensory information using a small number of active neurons at any given point in time. This strategy, referred to as 'sparse coding', could possibly confer several advantages. First, it allows for increased storage capacity in associative memories; second, it makes the structure in natural signals explicit; third, it represents complex data in a way that is easier to read out at subsequent levels of processing; and fourth, it saves energy. Recent physiological recordings from sensory neurons have indicated that sparse coding could be a ubiquitous strategy employed in several different modalities across different organisms.

Mesh:

Year:  2004        PMID: 15321069     DOI: 10.1016/j.conb.2004.07.007

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  357 in total

1.  Decorrelation and efficient coding by retinal ganglion cells.

Authors:  Xaq Pitkow; Markus Meister
Journal:  Nat Neurosci       Date:  2012-03-11       Impact factor: 24.884

2.  Sparse and dense coding of natural stimuli by distinct midbrain neuron subpopulations in weakly electric fish.

Authors:  Katrin Vonderschen; Maurice J Chacron
Journal:  J Neurophysiol       Date:  2011-09-21       Impact factor: 2.714

3.  Calling song recognition in female crickets: temporal tuning of identified brain neurons matches behavior.

Authors:  Konstantinos Kostarakos; Berthold Hedwig
Journal:  J Neurosci       Date:  2012-07-11       Impact factor: 6.167

4.  Local non-linear interactions in the visual cortex may reflect global decorrelation.

Authors:  Simo Vanni; Tom Rosenström
Journal:  J Comput Neurosci       Date:  2010-04-27       Impact factor: 1.621

5.  Capacity analysis in multi-state synaptic models: a retrieval probability perspective.

Authors:  Yibi Huang; Yali Amit
Journal:  J Comput Neurosci       Date:  2010-10-27       Impact factor: 1.621

6.  Precise feature based time scales and frequency decorrelation lead to a sparse auditory code.

Authors:  Chen Chen; Heather L Read; Monty A Escabí
Journal:  J Neurosci       Date:  2012-06-20       Impact factor: 6.167

7.  Parallel sparse and dense information coding streams in the electrosensory midbrain.

Authors:  Michael K J Sproule; Michael G Metzen; Maurice J Chacron
Journal:  Neurosci Lett       Date:  2015-09-12       Impact factor: 3.046

Review 8.  What single-cell stimulation has told us about neural coding.

Authors:  Guy Doron; Michael Brecht
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2015-09-19       Impact factor: 6.237

9.  Origin of information-limiting noise correlations.

Authors:  Ingmar Kanitscheider; Ruben Coen-Cagli; Alexandre Pouget
Journal:  Proc Natl Acad Sci U S A       Date:  2015-11-30       Impact factor: 11.205

10.  Sample skewness as a statistical measurement of neuronal tuning sharpness.

Authors:  Jason M Samonds; Brian R Potetz; Tai Sing Lee
Journal:  Neural Comput       Date:  2014-02-20       Impact factor: 2.026

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.