Coordinate invariance as a fundamental constraint on the form of stimulus-specific information measures
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985823%3A_____%2F18%3A00489787" target="_blank" >RIV/67985823:_____/18:00489787 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/s00422-017-0729-7" target="_blank" >http://dx.doi.org/10.1007/s00422-017-0729-7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00422-017-0729-7" target="_blank" >10.1007/s00422-017-0729-7</a>
Alternative languages
Result language
angličtina
Original language name
Coordinate invariance as a fundamental constraint on the form of stimulus-specific information measures
Original language description
The value of Shannon's mutual information is commonly used to describe the total amount of information that the neural code transfers between the ensemble of stimuli and the ensemble of neural responses. In addition, it is often desirable to know which features of the stimulus or response are most informative. The literature offers several different decompositions of the mutual information into its stimulus or response-specific components, such as the specific surprise or the uncertainty reduction, but the number of mutually distinct measures is in fact infinite. We resolve this ambiguity by requiring the specific information measures to be invariant under invertible coordinate transformations of the stimulus and the response ensembles. We prove that the Kullback-Leibler divergence is then the only suitable measure of the specific information. On a more general level, we discuss the necessity and the fundamental aspects of the coordinate invariance as a selection principle. We believe that our results will encourage further research into invariant statistical methods for the analysis of neural coding.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
<a href="/en/project/GA17-06943S" target="_blank" >GA17-06943S: Neural coding precision and its adaptation to the stimulus statistics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Biological Cybernetics
ISSN
0340-1200
e-ISSN
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Volume of the periodical
112
Issue of the periodical within the volume
1-2
Country of publishing house
DE - GERMANY
Number of pages
11
Pages from-to
13-23
UT code for WoS article
000430460400003
EID of the result in the Scopus database
2-s2.0-85028607049