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(Reference retrieved automatically from SciELO through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Information theory applications in neuroscience

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Author(s):
Vinícius Lima Cordeiro [1] ; Rodrigo Felipe de Oliveira Pena [2] ; Cesar Augusto Celis Ceballos ; Renan Oliveira Shimoura [4] ; Antonio Carlos Roque [5]
Total Authors: 5
Affiliation:
[1] Universidade de São Paulo. Departamento de Física. Laboratório de Sistemas Neurais - Brasil
[2] Universidade de São Paulo. Departamento de Física. Laboratório de Sistemas Neurais - Brasil
[4] Universidade de São Paulo. Departamento de Física. Laboratório de Sistemas Neurais - Brasil
[5] Universidade de São Paulo. Departamento de Física. Laboratório de Sistemas Neurais - Brasil
Total Affiliations: 5
Document type: Journal article
Source: Revista Brasileira de Ensino de Física; v. 41, n. 2 2018-11-29.
Abstract

Abstract Neurons respond to external stimuli by emitting sequences of action potentials (spike trains). In this way, one can say that the spike train is the neuronal response to an input stimulus. Action potentials are “all-or-none” phenomena, which means that a spike train can be represented by a sequence of zeros and ones. In the context of information theory, one can then ask: how much information about a given stimulus the spike train conveys? Or rather, what aspects of the stimulus are encoded by the neuronal response? In this article, an introduction to information theory is presented which consists of historical aspects, fundamental concepts of the theory, and applications to neuroscience. The connection to neuroscience is made with the use of demonstrations and discussions of different methods of the theory of information. Examples are given through computer simulations of two neuron models, the Poisson neuron and the integrate-and-fire neuron, and a cellular automata network model. In the latter case, it is shown how one can use information theory measures to retrieve the connectivity matrix of a network. All codes used in the simulations were made publicly available at the GitHub platform and are accessible trough the url: github.com/ViniciusLima94/ticodigoneural. (AU)

FAPESP's process: 13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat
Grantee:Oswaldo Baffa Filho
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 17/05874-0 - Models of neural networks with stochastic neurons and different topologies: construction and analysis
Grantee:Vinícius Lima Cordeiro
Support Opportunities: Scholarships in Brazil - Master
FAPESP's process: 15/50122-0 - Dynamic phenomena in complex networks: basics and applications
Grantee:Elbert Einstein Nehrer Macau
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 13/25667-8 - Mechanisms of propagation of epileptiform activity in a large-scale cortical model
Grantee:Rodrigo Felipe de Oliveira Pena
Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
FAPESP's process: 17/07688-9 - Computational study of hippocampal-cortical-thalamic interactions: simulating patterns of synaptic plasticity and oscillatory activity
Grantee:Renan Oliveira Shimoura
Support Opportunities: Scholarships in Brazil - Doctorate