  We are interested in understanding the neural correlates of attentional
processes using first principles. Here we apply a recently developed first
principles approach that uses transmitted information in bits per joule to
quantify the energy efficiency of information transmission for an
inter-spike-interval (ISI) code that can be modulated by means of the synchrony
in the presynaptic population. We simulate a single compartment
conductance-based model neuron driven by excitatory and inhibitory spikes from
a presynaptic population, where the rate and synchrony in the presynaptic
excitatory population may vary independently from the average rate. We find
that for a fixed input rate, the ISI distribution of the post synaptic neuron
depends on the level of synchrony and is well-described by a Gamma distribution
for synchrony levels less than 50%. For levels of synchrony between 15% and 50%
(restricted for technical reasons), we compute the optimum input distribution
that maximizes the mutual information per unit energy. This optimum
distribution shows that an increased level of synchrony, as it has been
reported experimentally in attention-demanding conditions, reduces the mode of
the input distribution and the excitability threshold of post synaptic neuron.
This facilitates a more energy efficient neuronal communication.
