Dynamics of Synaptic Transmission and Neural Code

In the light of the latest results concerning the synaptic paired pulse depression, facilitation [Thomson et al., 1993 a,b,c], its effects on long term potentiation (LTP) and depression (LTD) [Markram et al., 1996], and spike frequency adaptation, the question how the neurons communicate and what are meaningful signals in the neural information processing has to be reconsidered. Modeling these phenomena, we could make qualitative estimations on the inputoutput properties of neurons. We examined the transmission of two parameters of the model neurons’ activity: the mean and standard deviation of membrane current. The measured effects of long term potentiation on the dynamics of synaptic transmission show that the transfer of membrane currents mean, and so the transfer of firing rate, can not be considered as synaptic weight change. Other known facts, as the low firing rate and spike frequency adaptation make the simple firing rate code less appropriate for longer period simulation of real neurons, as it is assumed in the majority of artificial neural network models (ANN). Nonetheless, the other examined parameter, the standard deviation of synaptic currents, behaves appropriately as the firing rate in typical ANN models. The formation and operation of this type of "code" is discussed.