Title
Analysis of neural interaction during adaptation of reach-to-grasp task under perturbation with Bayesian networks
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.
Year
DOI
Venue
2011
10.1109/BMEI.2011.6098392
2011 4th International Conference on Biomedical Engineering and Informatics (BMEI)
Keywords
Field
DocType
Neural interaction,Adaptation,Perturbation,Reach-to-grasp task,Bayesian Networks
GRASP,Neurophysiology,Computer science,Bayesian network,Complex network,Artificial intelligence,Artificial neural network,Machine learning,Perturbation (astronomy),Bayesian probability
Conference
Volume
Issue
ISSN
2
null
1948-2914
ISBN
Citations 
PageRank 
978-1-4244-9351-7
0
0.34
References 
Authors
3
5
Name
Order
Citations
PageRank
Dong Sang150.75
Bin Lv264.82
Huiguang He311830.75
Fei-Yue Wang45273480.21
Jiping He511017.46