Propagation of Synfire Activity in Cortical Networks: a Statistical Approach

Recently it was demonstrated that the activity of frontal cortical neurons in the awake behaving monkey comprises excessive occurrences of highly accurate (~1–3 ms) spatio-temporal firing patterns. Moreover, these patterns can be related to the behavioral state of the animal [l, 10]. On the basis of the characteristic anatomy and physiology of the cortex, it was proposed that syn fire activity, propagating through the sparsely firing cortical neural network, presents a natural explanation for this phenomenon [2, 1]. In order to test this hypothesis, we investigated the dependence of reliable synfire propagation on the structural and the dynamical properties of a model cortical network, using the newly developed simulation tool SYNOD [6].

[1]  M. Abeles Role of the cortical neuron: integrator or coincidence detector? , 1982, Israel journal of medical sciences.

[2]  M Abeles,et al.  Spatio-temporal firing patterns in the frontal cortex of behaving monkeys , 1996, Journal of Physiology-Paris.

[3]  Michael N. Shadlen,et al.  Noise, neural codes and cortical organization , 1994, Current Opinion in Neurobiology.

[4]  Marius Usher,et al.  The Effect of Synchronized Inputs at the Single Neuron Level , 1994, Neural Computation.

[5]  E. Vaadia,et al.  Spatiotemporal firing patterns in the frontal cortex of behaving monkeys. , 1993, Journal of neurophysiology.

[6]  D. Norman Learning and Memory , 1982 .

[7]  Ad Aertsen,et al.  Propagation of Synfire Activity in Cortical Networks - a Dynamical Systems Approach , 1995, SNN Symposium on Neural Networks.

[8]  H. Merskey,et al.  Pain, learning and memory. , 1975, Journal of psychosomatic research.