Literature DB >> 16764504

Correlation and independence in the neural code.

Shun-ichi Amari1, Hiroyuki Nakahara.   

Abstract

The decoding scheme of a stimulus can be different from the stochastic encoding scheme in the neural population coding. The stochastic fluctuations are not independent in general, but an independent version could be used for the ease of decoding. How much information is lost by using this unfaithful model for decoding? There are discussions concerning loss of information (Nirenberg & Latham, 2003; Schneidman, Bialek, & Berry, 2003). We elucidate the Nirenberg-Latham loss from the point of view of information geometry.

Mesh:

Year:  2006        PMID: 16764504     DOI: 10.1162/neco.2006.18.6.1259

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  4 in total

1.  Computational role of large receptive fields in the primary somatosensory cortex.

Authors:  Guglielmo Foffani; John K Chapin; Karen A Moxon
Journal:  J Neurophysiol       Date:  2008-04-09       Impact factor: 2.714

2.  Information loss associated with imperfect observation and mismatched decoding.

Authors:  Masafumi Oizumi; Masato Okada; Shun-Ichi Amari
Journal:  Front Comput Neurosci       Date:  2011-03-02       Impact factor: 2.380

3.  A Measure of Information Available for Inference.

Authors:  Takuya Isomura
Journal:  Entropy (Basel)       Date:  2018-07-07       Impact factor: 2.524

4.  Algorithms for the analysis of ensemble neural spiking activity using simultaneous-event multivariate point-process models.

Authors:  Demba Ba; Simona Temereanca; Emery N Brown
Journal:  Front Comput Neurosci       Date:  2014-02-10       Impact factor: 2.380

  4 in total

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