  Working memory (WM) has been intensively used to enable the temporary storing
of information for processing purposes, playing an important role in the
execution of various cognitive tasks. Recent studies have shown that
information in WM is not only maintained through persistent recurrent activity
but also can be stored in activity-silent states such as in short-term synaptic
plasticity (STSP). Motivated by important applications of the STSP mechanisms
in WM, the main focus of the present work is on the analysis of the effects of
random inputs on a leaky integrate-and-fire (LIF) synaptic conductance neuron
under STSP. Furthermore, the irregularity of spike trains can carry the
information about previous stimulation in a neuron. A LIF conductance neuron
with multiple inputs and coefficient of variation (CV) of the
inter-spike-interval (ISI) can bring an output decoded neuron. Our numerical
results show that an increase in the standard deviations in the random input
current and the random refractory period can lead to an increased irregularity
of spike trains of the output neuron.
