NDLI: Embedding global physiological data in an artificial neural network

Content Provider	IEEE Xplore Digital Library
Author	Kilis, D. Ackerman, E. Slagle, J.R.
Copyright Year	1996
Description	Author affiliation: Dept. of Comput., Hong Kong Polytech. Univ., Hung Hom, Hong Kong (Kilis, D.)
Abstract	The goal of creating a realistic neural network model for studying biological processing has constantly piqued the interest of many researchers (Grossberg, 1995). One reason for the lack of realism in many existing artificial neural network models is that the dynamics of the human brain have not been captured. The difficulty partially arises from the lack of mathematical representation that can more easily express the dynamics of the brain. This paper introduces a network model that can be used to incorporate the global dynamic data of the brain. In particular, this project has incorporated into a Fukushima (1984) based network a set of data that has been obtained from a true recording of electroencephalographic (EEG) potential of the human subject, who was in a light sleep condition. The incorporation of the EEG data into an artificial neural network is important, since biological neurons never achieve a stable state, unless they are dead or in deep anesthesia. In addition, some physiological findings have suggested that neurons in different parts of the brain might communicate with each other through oscillation of synchronous electrical activity at 40 hertz (Barinaga, 1990). This study has shown that the new network model is able to achieve the pattern associative capabilities of the original model.
Starting Page	92
Ending Page	95
File Size	622437
Page Count	4
File Format	PDF
ISBN	0780336674
DOI	10.1109/ANZIIS.1996.573897
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-11-18
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent networks Artificial neural networks Neurons Biological system modeling Brain modeling Electroencephalography Biological neural networks Computer science Biology computing Information science
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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