DocumentCode :
1749209
Title :
Sequence learning and timing in hippocampus, prefrontal cortex, and accumbens
Author :
Banquet, Jean Paul ; Gaussier, Philippe ; Revel, Arnaud ; Moga, S. ; Burnod, Yves
Author_Institution :
Neurosci. et Modelisation, UPMC, Paris, France
Volume :
2
fYear :
2001
fDate :
2001
Firstpage :
1053
Abstract :
A basic architecture inspired from dentate gyrus and CA3-CA1 hippocampal fields combines a spectral timing module and an association network learning event transitions. According to the type of input the system can learn and replay: purely temporal sequences of aperiodic events; place-field chains as building blocks of graphs and maps, by combining visual and path-integration inputs; imitated sequences of movements by combining optic flow and movement-related proprioceptive feedback. The model is part of a triptych featuring also place cell computation and planning. The integrated architecture is used as a control system for robot navigation, sequence learning, prediction and novelty detection
Keywords :
brain models; learning (artificial intelligence); mechanoception; mobile robots; neural nets; neurophysiology; path planning; physiological models; CA3-CA1 hippocampal fields; accumbens; aperiodic events; association network; dentate gyrus; event transitions; hippocampus; imitated movement sequences; movement-related proprioceptive feedback; novelty detection; optic flow; path-integration inputs; place cell computation; place-field chains; planning; prediction; prefrontal cortex; purely temporal sequences; robot navigation; sequence learning; spectral timing module; visual inputs; Animals; Biomedical optical imaging; Gaussian processes; Hippocampus; Image motion analysis; Lesions; Navigation; Optical feedback; Optical sensors; Timing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-7044-9
Type :
conf
DOI :
10.1109/IJCNN.2001.939506
Filename :
939506
Link To Document :
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