Impacts of background synaptic bombardment on the weak signal coding performance of morris-lecar Type-I neurons

Signal processing, coding, and transmission in the nervous system are quite complex and highly dependent on the environmental conditions of the neuronal environment. Also, neurons carry out the signals they process through unique junctions called synapses. In this context, it is a known fact that a neuron can make synaptic connections from a single connection to thousands of connections, depending on the network in which it is located. Pre-synaptic random inputs from these connections cause fluctuations in the neuron membrane potential. This noise source is called background synaptic activity. On the other hand, it is known that noise makes positive contributions to neuron dynamics. In this thesis study, the possible contributions of background synaptic activity to the information processing mechanism of Morris–Lecar Type I neurons are discussed. Our results show that, at appropriate synaptic conductance values, the signal processing capacity of Morris–Lecar Type I neurons exhibits stochastic resonance behavior depending on the frequency of the background synaptic inputs. It has also been found that Morris–Lecar Type I neurons perceive signals within a certain frequency range. It has been numerically demonstrated that this frequency range is significantly affected by pre-synaptic inputs. Moreover, it has been observed that Type I neurons can only benefit from background synaptic input when encoding weak signals in a certain frequency range In conclusion, in this study, the contributions of background synaptic activity to the weak signal coding capacity of Morris–Lecar Type I neurons is analyzed in detail. Our numerical results show that neurons can increase their subthreshold signal encoding capacity by exploiting background synaptic noise at appropriate weak signal frequencies.