Dynamic Synapses and Synaptic Strength

generic.intelligence at gmail.com generic.intelligence at gmail.com
Fri Mar 11 12:49:12 EST 2005

I think Markram, among others, has done some research on the dynamic
response of synapses to spike trains, and according to him synapses
have several modes of response.  The post-synaptic potential patterns
can be variable, such as increasing / decreasing / peaking in amplitude
as the presynaptic train passes through.  This type of experimental
results throw into question the validity of the concept of a fixed
"synaptic strength".

I'm working on some artificial neuron networks for vision and I found
that the use of a "Gaussian" synapse may be more useful than the
traditional "perceptron" type of synapses.  I suspect that in real
neurons the "synaptic strength" may be encoded not as the single
response to a spike but as the collective response to spike trains
within a longer time window.

For each synpase there should be an internal "peak" frequency and when
the incoming spike train is of that frequency the synpase will respond
most positively (ie exhibit facilitation).  Therefore, the strength of
the synapse is encoded as the frequency of peak response.

I'm not sure if Markram actually proposed this mechanism in his papers.
 Also I'm wondering if this idea can be refuted by other known facts.
Any thoughts?


================ Reference ===================
Neural Networks with Dynamic Synapses
Authors: Tsodyks M. 1; Pawelzik K. 2; Markram H. 1

Source: Neural Computation, 1 May 1998, vol. 10, no. 4, pp. 821-835(15)


Transmission across neocortical synapses depends on the frequency of
presynaptic activity (Thomson & Deuchars, 1994). Interpyramidal
synapses in layer V exhibit fast depression of synaptic transmission,
while other types of synapses exhibit facilitation of transmission. To
study the role of dynamic synapses in network computation, we propose a
unified phenomenological model that allows computation of the
postsynaptic current generated by both types of synapses when driven by
an arbitrary pattern of action potential (AP) activity in a presynaptic
population. Using this formalism, we analyze different regimes of
synaptic transmission and demonstrate that dynamic synapses transmit
different aspects of the presynaptic activity depending on the average
presynaptic frequency. The model also allows for derivation of
mean-field equations, which govern the activity of large,
interconnected networks. We show that the dynamics of synaptic
transmission results in complex sets of regular and irregular regimes
of network activity.

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