Effects of autapse on weak signal detection in FFL network motifs

Complex network models which are used in order to explain information processing and transmission mechanisms in nervous system, are frequently used to modeling the complex network topologies. It is known that in these complex network structures there are small groups which are relatively simple in structure and repeating themselves. These structures, which are called "network motifs", are considered as the basic building blocks of complex networks. In this thesis, the detection of weak signal, applied to the input neuron, by the output neuron in Feed Forward Loop (FFL) motifs has been investigated. FFL network motifs are constructed depending on whether the chemical synapse between neurons is excitatory or inhibitory. In addition, the presence of an electrical autapse of the output neuron has been considered and the effects of this autapse have been investigated. It has been observed that FFL-T3 and FFL-T7 motif structure is the most reliable and suitable motif structure for weak signal detection in network motifs in case of without autapse. In this case, to detect the weak signal by the output neuron, it has been determined that either the synapse between the input neuron and the output neuron must be excitatory or the synapses through which the weak signal is transmitted to output must be excitatory. In the motif structures with autapse, it has been observed that the weak signal detection performance of the output neuron is increased in all motifs regardless of the motif structure. It has been found that the reason for this increase was due to the matching between the time scale of the autapse and the period of weak signal which is applied to input neuron. In addition, multiple coherence resonances have been obtained at integer multiples of the period of the weak signal depending on autaptic time delay.