
doi: 10.3934/mbe.2016004
pmid: 27106184
Recently, it has been suggested that certain neurons with Poissonian spiking statistics may communicate by discontinuously switching between two levels of firing intensity. Such a situation resembles in many ways the optimal information transmission protocol for the continuous-time Poisson channel known from information theory. In this contribution we employ the classical information-theoretic results to analyze the efficiency of such a transmission from different perspectives, emphasising the neurobiological viewpoint. We address both the ultimate limits, in terms of the information capacity under metabolic cost constraints, and the achievable bounds on performance at rates below capacity with fixed decoding error probability. In doing so we discuss optimal values of experimentally measurable quantities that can be compared with the actual neuronal recordings in a future effort.
Neurons, poisson neuron, Poisson neuron, Models, Neurological, Statistical aspects of information-theoretic topics, information capacity, Synaptic Transmission, Applications of statistics to biology and medical sciences; meta analysis, metabolic cost, QA1-939, decoding error., Point processes (e.g., Poisson, Cox, Hawkes processes), decoding error, TP248.13-248.65, Mathematics, Biotechnology, Probability
Neurons, poisson neuron, Poisson neuron, Models, Neurological, Statistical aspects of information-theoretic topics, information capacity, Synaptic Transmission, Applications of statistics to biology and medical sciences; meta analysis, metabolic cost, QA1-939, decoding error., Point processes (e.g., Poisson, Cox, Hawkes processes), decoding error, TP248.13-248.65, Mathematics, Biotechnology, Probability
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