NDLI: Analysis of neural interaction during adaptation of reach-to-grasp task under perturbation with Bayesian networks

Content Provider	IEEE Xplore Digital Library
Author	Dong Sang Bin Lv Huiguang He Feiyue Wang Jiping He
Copyright Year	2011
Description	Author affiliation: The Harrington Departemnt of Bioengineering and the, Center for Neural Interface Design, Arizona State University, Tempe, USA (Jiping He) \|\| The State Key Laboratory of Intelligent Control and Management of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China (Dong Sang; Bin Lv; Huiguang He; Feiyue Wang)
Abstract	In this work, we took the analysis of neural interactions change in M1 of a monkey during the adaptation process for it to complete reach-to-grasp tasks with external perturbation across days. BN model was applied to model and evaluate neural interaction networks from recorded neural spike trains data of each set. Our results showed that for delay period across sets, interaction level of neural network tended to be higher during later stage of adaptation than during begin stage, which indicated the monkey performed more fully preparation through adaptation. In addition, for both delay period and peri-movement period, the neural interaction networks tended to change more stably from one set to the next as the monkey adapted to the perturbation experiment better.
Starting Page	625
Ending Page	629
File Size	671100
Page Count	5
File Format	PDF
ISBN	9781424493517
e-ISBN	9781424493524
DOI	10.1109/BMEI.2011.6098392
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bayesian Networks Adaptation models Neuroscience Bayesian methods Neurons Reach-to-grasp task Neural interaction Perturbation Delay Biological neural networks Adaptation
Content Type	Text
Resource Type	Article

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