| Abstract [eng] |
Plentiful results are coming from advances in single cell recordings. All these data have to be treated in complex ways implementing powerful computational techniques. Goal of this study was to identify the optimal learning rule of feedforward inhibitory interneurons that preserves high temporal precision of input discrimination while excitatory synapses undergo synaptic modifications according to the asymmetric spike-timing dependent plasticity rule. Temporal integration of inputs is enhanced if excitatory synapses undergo long term potentiation. To preserve narrow temporal integration window, feedforward inhibitory synapses must be plastic as well. |
