Dynamic synapses in neural information processing : Examining the influence of short-term synaptic plasticity on neural coding

Abstract: Short-term synaptic plasticity (STP) is a phenomenon that has been closely associated with how neurons communicate with each other. I study communication between neurons tied to synapses endowed with short-term plasticity (dynamic synapses). This is achieved by using mathematical models of neural phenomena that align with those found in real neurons. In addition to dynamic synapses, a model of static synapses is created, on which control experiments are performed. The response of postsynaptic neurons, to spiking-sequences from presynaptic neurons, is examined in order to infer how information is transmitted across cells. During these computational experiments, it was found that the range of firing rates to which postsynaptic neurons responded, depends heavily on certain parameters of STP-processes. These parameters are the time constants for short-term synaptic depression and facilitation: the two time-dependent processes that define STP. Some results confirm those of the existing literature, while this work places an added emphasis on the sensitivity of the propagation of rate codes to the aforementioned parameters of synapses. This is relevant because it has been found that real synapses display a wide range of time constants in the nervous system. Hence, understanding how this variation carries a significant impact on rate-coding schemes is vital when engaging in further studies of neural rate codes.