Literature DB >> 9950723

Narrow versus wide tuning curves: What's best for a population code?

A Pouget1, S Deneve, J C Ducom, P E Latham.   

Abstract

Neurophysiologists are often faced with the problem of evaluating the quality of a code for a sensory or motor variable, either to relate it to the performance of the animal in a simple discrimination task or to compare the codes at various stages along the neuronal pathway. One common belief that has emerged from such studies is that sharpening of tuning curves improves the quality of the code, although only to a certain point; sharpening beyond that is believed to be harmful. We show that this belief relies on either problematic technical analysis or improper assumptions about the noise. We conclude that one cannot tell, in the general case, whether narrow tuning curves are better than wide ones; the answer depends critically on the covariance of the noise. The same conclusion applies to other manipulations of the tuning curve profiles such as gain increase.

Entities:  

Mesh:

Year:  1999        PMID: 9950723     DOI: 10.1162/089976699300016818

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


  38 in total

1.  Neural activity in prefrontal cortex during copying geometrical shapes. II. Decoding shape segments from neural ensembles.

Authors:  Bruno B Averbeck; David A Crowe; Matthew V Chafee; Apostolos P Georgopoulos
Journal:  Exp Brain Res       Date:  2003-04-01       Impact factor: 1.972

2.  Evidence and Counterevidence in Motion Perception.

Authors:  Jacob Duijnhouwer; Bart Krekelberg
Journal:  Cereb Cortex       Date:  2015-10-03       Impact factor: 5.357

3.  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

Review 4.  Circuits for Action and Cognition: A View from the Superior Colliculus.

Authors:  Michele A Basso; Paul J May
Journal:  Annu Rev Vis Sci       Date:  2017-06-15       Impact factor: 6.422

5.  Cues to move increased information in superior colliculus tuning curves.

Authors:  Xiaobing Li; Michele A Basso
Journal:  J Neurophysiol       Date:  2011-05-18       Impact factor: 2.714

6.  Adaptive shaping of cortical response selectivity in the vibrissa pathway.

Authors:  He J V Zheng; Qi Wang; Garrett B Stanley
Journal:  J Neurophysiol       Date:  2015-03-18       Impact factor: 2.714

Review 7.  Visual attention mitigates information loss in small- and large-scale neural codes.

Authors:  Thomas C Sprague; Sameer Saproo; John T Serences
Journal:  Trends Cogn Sci       Date:  2015-03-11       Impact factor: 20.229

8.  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

9.  Error-based analysis of optimal tuning functions explains phenomena observed in sensory neurons.

Authors:  Steve Yaeli; Ron Meir
Journal:  Front Comput Neurosci       Date:  2010-10-14       Impact factor: 2.380

10.  Neural representations that support invariant object recognition.

Authors:  Robbe L T Goris; Hans P Op de Beeck
Journal:  Front Comput Neurosci       Date:  2009-02-17       Impact factor: 2.380

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.