NDLI: Minimum number of probes for brain dynamics observability

Content Provider	IEEE Xplore Digital Library
Author	Pequito, Sergio Bogdan, Paul Pappas, George J.
Copyright Year	2015
Description	Author affiliation: Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, United States of America (Pequito, Sergio; Pappas, George J.) \|\| USC Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, United States of America (Bogdan, Paul)
Abstract	In this paper, we address the problem of placing sensor probes in the brain such that the system dynamics' are generically observable. The system dynamics whose states can encode for instance the fire-rating of the neurons or their ensemble following a neural-topological (structural) approach, and the sensors are assumed to be dedicated, i.e., can only measure a state at each time. Even though the mathematical description of brain dynamics is (yet) to be discovered, we build on its observed fractal characteristics and assume that the model of the brain activity satisfies fractional-order dynamics. Although the sensor placement explored in this paper is particularly considering the observability of brain dynamics, the proposed methodology applies to any fractional-order linear system. Thus, the main contribution of this paper is to show how to place the minimum number of dedicated sensors, i.e., sensors measuring only a state variable, to ensure generic observability in discrete-time fractional-order systems for a specified finite interval of time. Finally, an illustrative example of the main results is provided using electroencephalogram (EEG) data.
Starting Page	306
Ending Page	311
File Size	711776
Page Count	6
File Format	PDF
e-ISBN	9781479978861
DOI	10.1109/CDC.2015.7402218
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-15
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Observability Neurons Probes Brain modeling Time measurement Yttrium
Content Type	Text
Resource Type	Article

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