INVESTIGADORES
MONTANI Fernando Fabian
artículos
Título:
Information theoretic methods for studying population codes
Autor/es:
ROBIN A. A. INCE ; RICCARDO SENATORE; EHSAN ARABZADEHD; FERNANDO MONTANI; MATHEW E. DIAMOND; STEFANO PANZERI
Revista:
NEURAL NETWORKS
Editorial:
PERGAMON-ELSEVIER SCIENCE LTD
Referencias:
Año: 2010 vol. 23 p. 713 - 727
ISSN:
0893-6080
Resumen:
Population coding is the quantitative study of which algorithms or representations are used by thebrain to combine together and evaluate the messages carried by different neurons. Here, we review ani nformation-theoretic approach to population coding. We first discuss how to compute the information carried by simultaneously recorded neural populations, and in particular how to reduce the limitedsampling bias which affects the calculation of information from a limited amount of experimental data.We then discuss how to quantify the contribution of individual members of the population, or theinteraction between them, to the overall information encoded by the considered group of neurons. Wefocus in particular on evaluating what is the contribution of interactions up to any given order to thetotal information. We illustrate this formalism with applications to simulated data with realistic neuronal statistic and to real simultaneous recordings of multiple spike trains.
