Modelling studies on the computational function of fast temporal structure in cortical circuit activity

被引:12
作者
Sommer, FT [1 ]
Wennekers, T
机构
[1] Univ Ulm, Dept Neural Informat Proc, D-89069 Ulm, Germany
[2] Max Planck Inst Math Sci, D-04103 Leipzig, Germany
关键词
D O I
10.1016/S0928-4257(00)01098-6
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
The interplay between modelling and experimental studies can support the exploration of the function of neuronal circuits in the cortex. We exemplify such an approach with a study on the role of spike timing and gamma-oscillations in associative memory in strongly connected circuits of cortical neurones. It is demonstrated how associative memory studies on different levels of abstraction can specify the functionality to be expected in real cortical neuronal circuits. In our model overlapping random configurations of sparse cell populations correspond to memory items that are stored by simple Hebbian coincidence learning. This associative memory task will be implemented with biophysically well tested compartmental neurones developed by Pinsky and Rinzel [58]. We ran simulation experiments to study memory recall in two network architectures: one interconnected pool of cells, and two reciprocally connected pools. When recalling a memory by stimulating a spatially overlapping set of cells, the completed pattern is coded by an event of synchronized single spikes occurring after 25-60 ms. These fast associations are performed even at a memory load corresponding to the memory capacity of optimally tuned formal associative networks (> 0.1 bit/synapse). With tonic stimulation or feedback loops in the network the neurones fire periodically in the gamma-frequency range (20-80 Hz). With fast changing inputs memory recall can be switched between items within a single gamma cycle. Thus, oscillation is nor a primary coding feature necessary for associative memory. However, it accompanies reverberatory feedback providing an improved iterative memory recall completed after a few gamma cycles (60-260 ms). In the bidirectional architecture reverberations do not express in a rigid phase locking between the pools. For small stimulation sets bursting occurred in these cells acting as a supportive mechanism for associative memory. (C) 2000 Elsevier Science Ltd. Published by Editions scientifiques et medicales Elsevier SAS.
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收藏
页码:473 / 488
页数:16
相关论文
共 90 条
[1]  
Abbott L.F., 1999, NEURAL CODES DISTRIB
[2]  
Abeles M., 1991, CORTICONICS
[3]  
ALBUS J S, 1971, Mathematical Biosciences, V10, P25, DOI 10.1016/0025-5564(71)90051-4
[4]   MATHEMATICAL FOUNDATION FOR STATISTICAL NEURODYNAMICS [J].
AMARI, SI ;
YOSHIDA, K ;
KANATANI, KI .
SIAM JOURNAL ON APPLIED MATHEMATICS, 1977, 33 (01) :95-126
[6]  
Amit D., 1989, Modelling Brain Function: the World of Attractor Neural Networks
[7]   STATISTICAL-MECHANICS OF NEURAL NETWORKS NEAR SATURATION [J].
AMIT, DJ ;
GUTFREUND, H ;
SOMPOLINSKY, H .
ANNALS OF PHYSICS, 1987, 173 (01) :30-67
[8]  
AMIT DJ, 1995, BEHAV BRAIN SCI, V18, P617, DOI 10.1017/S0140525X00040164
[9]  
ANDERSON J A, 1972, Mathematical Biosciences, V14, P197, DOI 10.1016/0025-5564(72)90075-2
[10]   A MEMORY STORAGE MODEL UTILIZING SPATIAL CORRELATION FUNCTIONS [J].
ANDERSON, JA .
KYBERNETIK, 1968, 5 (03) :113-&