Literature DB >> 9097477

How well can we estimate the information carried in neuronal responses from limited samples?

D Golomb1, J Hertz, S Panzeri, A Treves, B Richmond.   

Abstract

It is difficult to extract the information carried by neuronal responses about a set of stimuli because limited data samples result in biased estimates. Recently two improved procedures have been developed to calculate information from experimental results: a binning-and-correcting procedure and a neural network procedure. We have used data produced from a model of the spatiotemporal receptive fields of parvocellular and magnocellular lateral geniculate neurons to study the performance of these methods as a function of the number of trials used. Both procedures yield accurate results for one-dimensional neuronal codes. They can also be used to produce a reasonable estimate of the extra information in a three-dimensional code, in this instance, within 0.05-0.1 bit of the asymptotically calculated value--about 10% of the total transmitted information. We believe that this performance is much more accurate than previous procedures.

Mesh:

Year:  1997        PMID: 9097477     DOI: 10.1162/neco.1997.9.3.649

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


  17 in total

1.  Neuronal interactions improve cortical population coding of movement direction.

Authors:  E M Maynard; N G Hatsopoulos; C L Ojakangas; B D Acuna; J N Sanes; R A Normann; J P Donoghue
Journal:  J Neurosci       Date:  1999-09-15       Impact factor: 6.167

2.  Consistency of encoding in monkey visual cortex.

Authors:  M C Wiener; M W Oram; Z Liu; B J Richmond
Journal:  J Neurosci       Date:  2001-10-15       Impact factor: 6.167

3.  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
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4.  Decoding spike trains instant by instant using order statistics and the mixture-of-Poissons model.

Authors:  Matthew C Wiener; Barry J Richmond
Journal:  J Neurosci       Date:  2003-03-15       Impact factor: 6.167

5.  Assessing the encoding of stimulus attributes with rapid sequences of stimulus events.

Authors:  M Eger; R Eckhorn
Journal:  J Comput Neurosci       Date:  2002 Nov-Dec       Impact factor: 1.621

6.  Neural encoding schemes of tactile information in afferent activity of the vibrissal system.

Authors:  Fernando D Farfán; Ana L Albarracín; Carmelo J Felice
Journal:  J Comput Neurosci       Date:  2012-06-22       Impact factor: 1.621

7.  Spike count, spike timing and temporal information in the cortex of awake, freely moving rats.

Authors:  Alessandro Scaglione; Guglielmo Foffani; Karen A Moxon
Journal:  J Neural Eng       Date:  2014-07-15       Impact factor: 5.379

8.  Neuronal signals in the monkey ventral striatum related to progress through a predictable series of trials.

Authors:  M Shidara; T G Aigner; B J Richmond
Journal:  J Neurosci       Date:  1998-04-01       Impact factor: 6.167

9.  Information in the neuronal representation of individual stimuli in the primate temporal visual cortex.

Authors:  E T Rolls; A Treves; M J Tovee; S Panzeri
Journal:  J Comput Neurosci       Date:  1997-11       Impact factor: 1.621

10.  Neurons responsive to face-view in the primate ventrolateral prefrontal cortex.

Authors:  L M Romanski; M M Diehl
Journal:  Neuroscience       Date:  2011-05-13       Impact factor: 3.590

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