Title :
Learning and recall of temporal sequences in the network of CA3 pyramidal cells and a basket cell
Abstract :
A new recurrent network model of pyramidal cells and a basket cell in Field CA3 of the hippocampus is proposed. We assume that temporal sequences are processed in the CA3 network, and bursts are used as elements of the temporal sequences in synchronization with the theta rhythm. Besides ordinary synaptic connections between the pyramidal cells, delayed connections are assumed to connect the consecutive elements of temporal sequences. In learning mode, LTP of these connections are caused by burst inputs of theta rhythm. In recalling mode, the cooperative of a cue input, excitatory feedback, inhibitory feedback via the basket cell, and delayed excitatory feedback leads to the successful recall of the learned temporal sequence. The memory capacity of the network strongly depends on the number of firing sites in the spatial patterns
Keywords :
bioelectric potentials; biology computing; brain models; learning systems; recurrent neural nets; temporal logic; CA3 network; CA3 pyramidal cell network; Field CA3; LTP; basket cell; burst inputs; cue input; delayed connections; delayed excitatory feedback; excitatory feedback; firing sites; hippocampus; inhibitory feedback; learned temporal sequence; learning mode; long term potentiation; memory capacity; recalling mode; recurrent network model; spatial patterns; synaptic connections; temporal sequence learning; temporal sequence recall; theta rhythm; Computer science; Delay; Feedback; Hippocampus; Indium tin oxide; Intelligent networks; Physics; Rats; Rhythm; Telephony;
Conference_Titel :
Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-5871-6
DOI :
10.1109/ICONIP.1999.843954