Title
Analyzing Neural Interaction Characteristics in a Monkey's Motor Cortex during Reach-to-Grasp Tasks
Abstract
Applying a dynamic Bayesian network model can help detect neural interactions and analyze the characteristics of a monkey's motor cortex during reach-to-grasp tasks.
Year
DOI
Venue
2011
10.1109/MIS.2011.62
IEEE Intelligent Systems
Keywords
Field
DocType
neurophysiology,neural interaction,dynamic bayesian network model,bayes methods,brain informatics,intelligent systems,computational neuroscience,motor cortex,analyzing neural interaction characteristics,dynamic bayesian networks,reach-to-grasp tasks,monkey motor cortex,medical computing,reach-to-grasp task,neural interaction characteristic,brain models,neural nets,bayesian methods,bayesian method,markov process,neural networks,neuroscience,markov processes,dynamic bayesian network,bioinformatics,neural network,informatics
Computational neuroscience,GRASP,Intelligent decision support system,Neurophysiology,Computer science,Motor cortex,Artificial intelligence,Artificial neural network,Dynamic Bayesian network,Bayesian probability
Journal
Volume
Issue
ISSN
26
5
1541-1672
Citations 
PageRank 
References 
5
0.42
4
Authors
5
Name
Order
Citations
PageRank
Dong Sang150.75
Bin Lv264.82
Huiguang He311830.75
Fei-Yue Wang45273480.21
Jiping He511017.46