DocumentCode
393891
Title
Nonlinear approaches to learning and memory
Author
Lehnertz, Klaus
Author_Institution
Dept. of Epileptology, Bonn Univ. Med. Center, Germany
fYear
2003
fDate
20-22 March 2003
Firstpage
35
Lastpage
38
Abstract
The framework of the theory of nonlinear dynamics provides new concepts and powerful algorithms to analyze complex brain electrical activity. This overview presents a number of applications indicating that nonlinear EEG analyses allow improved characterization of spatially distributed neuronal activity during learning and memory processes.
Keywords
bioelectric potentials; brain models; electroencephalography; neurophysiology; nonlinear dynamical systems; reviews; time series; complex brain electrical activity; learning; memory; nonlinear EEG analyses; nonlinear dynamics; nonlinear time series analysis; overview; spatially distributed neuronal activity; Brain; Data mining; Electroencephalography; Enterprise resource planning; Epilepsy; Information processing; Noise reduction; Signal analysis; Time series analysis; Wavelet analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Engineering, 2003. Conference Proceedings. First International IEEE EMBS Conference on
Print_ISBN
0-7803-7579-3
Type
conf
DOI
10.1109/CNE.2003.1196749
Filename
1196749
Link To Document