NDLI: Information Capacity of Brain Machine Interfaces

Content Provider	IEEE Xplore Digital Library
Author	Gage, G.J. Ionides, E.L. Kipke, D.R.
Copyright Year	2005
Description	Author affiliation: Dept. of Biomed. Eng., Michigan Univ., Ann Arbor, MI (Gage, G.J.)
Abstract	Brain machine interfaces (BMIs) are emerging as an important research area in clinical therapy. A large range of potential BMI control signals can be found in the brain. In increasing order of volume of brain tissue being sampled, these signal includes recordings of electric discharges from multi unit activity (MUA), summed population activity of thousands of neurons via local field potentials (LFPs), and electrical activity recorded from either the surface of the brain via electrocorticograms (ECoGs) or the surface of the scalp via electroencephalograms (EEGs). While each of these signals have been studied separately, it has been difficult to compare the potential that each signal has for general prosthetic control across studies. Information theory has been proposed as an abstract measurement to bridge this gap, however the maximum information rates of any experiment is limited by the parameters defined by that experiment (e.g. inter-trial interval length, number of targets). Here we propose a different measure of information, which we call information capacity, which measures the maximum possible information rate that a signal can provide. An advantage of measuring information capacity is that it can readily be compared between different signals and different tasks. We show how to calculate information capacity making linear Gaussian assumptions, and we discuss more general possibilities. We present a case study involving a rat BMI task involving either MUA or LFP signals
Starting Page	2110
Ending Page	2113
File Size	195518
Page Count	4
File Format	PDF
ISBN	0780387414
DOI	10.1109/IEMBS.2005.1616876
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-01-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Brain Surface discharges Information rates Medical treatment Disk recording Neurons Electric potential Scalp Electroencephalography Prosthetics
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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