Abstract: Statistical analysis of electrophysiological recordings
obtained under, e.g. tactile, stimulation frequently suggests participation
in the network dynamics of experimentally unobserved “hidden"
neurons. Such interneurons making synapses to experimentally
recorded neurons may strongly alter their dynamical responses to
the stimuli. We propose a mathematical method that formalizes this
possibility and provides an algorithm for inferring on the presence
and dynamics of hidden neurons based on fitting of the experimental
data to spike trains generated by the network model. The model
makes use of Integrate and Fire neurons “chemically" coupled
through exponentially decaying synaptic currents. We test the method
on simulated data and also provide an example of its application to
the experimental recording from the Dorsal Column Nuclei neurons
of the rat under tactile stimulation of a hind limb.