DocumentCode :
3232741
Title :
Neural encoding based on frequency states using multi-spike train data
Author :
Hu, Fanxing ; Wei, Hui
Author_Institution :
Lab. of Algorithm for Cognitive Model, Fudan Univ., Shanghai, China
fYear :
2010
fDate :
23-26 Sept. 2010
Firstpage :
123
Lastpage :
126
Abstract :
Understanding the way how the neural networks encode outer stimulus and inner decision-making process is a key problem in neuroscience as well as in artificial intelligence. Although researchers have proposed several assumptions and related models, the supporting biological evidences are rarely provided. Our task involves finding an encoding method based on neuron firing frequency states and its transformation model under certain stimulus. Besides, a new method to analyze spikes train data is also proposed which is proved effective here. Then, the results by analyzing multi-microelectrodes simultaneous recorded spike train from temporal cortex and hippocampus of mouse experiment is shown, supporting and validating this model.
Keywords :
neural nets; neurophysiology; artificial intelligence; decision making; hippocampus; multi-spike train data; neural encoding; neuron firing frequency states; neuroscience; temporal cortex; Systematics; DTW; Multi-spike train; Neural encoding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-6437-1
Type :
conf
DOI :
10.1109/BICTA.2010.5645340
Filename :
5645340
Link To Document :
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