NDLI: A Unified information flow model of Poisson-type brain neuronal network activity

Content Provider	IEEE Xplore Digital Library
Author	Khaddaj, S.I. Abou-Faycal, I. Karameh, F.N.
Copyright Year	2008
Description	Author affiliation: Dept. of Electr. & Comput. Eng., American Univ. of Beirut, Lebanon (Khaddaj, S.I.; Abou-Faycal, I.; Karameh, F.N.)
Abstract	Understanding information transfer and representation in the brain is one of the most challenging scientific endeavors since neuroscientists are still far from converging to a solution with exact description. The main challenge in deciphering the neural code is the probabilistic nature of the neural codebook which maps stimuli to neural responses and vice versa. With the advent of recording techniques from single and multiple cells, it is becoming plausible to obtain large amount of experimental data against which theoretical models can be tested. In this respect, information theory can potentially provide a powerful framework for analyzing information content and representation in neuronal network activity. In this paper, we develop a simplified neuronal firing model which is mathematically complete and scalable. The model makes use of Poisson processes¿ properties and queuing theory. We also derive theoretical tools to measure, quantify, and set upper limits on information coded by the proposed model based on information theory. The designed measures take into account a general coding scheme in each neuron that combines temporal and rate coding of spike train responses of neurons. The proposed model along with the tools are generalized to quantify information in a population of neurons where correlation among neurons is modeled. The model also incorporates a spatial component which allows studying the amount of information gained from the spatial pattern of responses in a neuron population. Accordingly, the developed model and tools aim at providing a unified view of measuring information quantities and hence giving a better understanding of the neural coding.
Starting Page	2018
Ending Page	2024
File Size	1058126
Page Count	7
File Format	PDF
ISBN	9781424431236
ISSN	01912216
DOI	10.1109/CDC.2008.4738953
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-09
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Brain modeling Biological neural networks Neurons Information theory Encoding Decoding Testing Information analysis Mathematical model Queueing analysis
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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