Information transmission and recovery in neural communication channels revisited - art. no. 012901

Nerve cells in the brain generate all-or-none electric events-spikes-that a re transmitted to other nerve cells via chemical synapses. An important iss ue in neuroscience is how neurons encode and transmit information using spi ke trains. Recently, signal transduction through two neurons connected by a n excitatory chemical synapse was studied by Eguia et al. [Phys. Rev. E 62, 7111 (2000)]. They reported an apparent Violation of the data processing i nequality: The mutual information between the input signal and the output o f the first neuron can be lower than the mutual information between the inp ut signal and the output of the second neuron, that only receives input fro m the first neuron. We investigate whether it is possible, using a differen t method, to retrieve, from the first neuron's spike train, all the informa tion about the input that is present in the second neurons output. We find that single interspike intervals (ISI's) from the first neuron, at a resolu tion of 0.5 time units. contain more information about the input signal tha n those of the second neuron. Using a classification procedure based on the ISI return map, we recover 71% of the input entropy using the first neuron 's spike train, and only 42% using the second neuron's spike train. Hence f or these spike-train observables the data processing inequality is not viol ated.