Abstract: We develop a linkage between the mathematical analysis of a single neuron and the statistical connection of that neuron to the rest of the brain.
Jun 11, 2015 · Neuronal information processing is energetically costly. Energy supply restrictions on information processing have resulted in the evolution ...
We develop a linkage between the mathematical analysis of a single neuron and the statistical connection of that neuron to the rest of the brain.
Toby Berger, William B. Levy, Jie Xing: Energy efficient neurons with generalized inverse Gaussian interspike interval durations. Allerton 2011: 1737-1742.
Energy efficient neurons with generalized inverse Gaussian conditional and marginal hitting times ; IEEE Transactions on Information Theory ◽. 10.1109/tit.
Neuronal information processing is energetically costly. Energy supply restrictions on information processing have resulted in the evolution of brains to ...
Accordingly, we model the interspike interval. (ISI) random variable T as the time it takes a certain diffusion of ionic particles that possesses an average ...
A Berger-Levy energy efficient neuron model with unequal synaptic weights · A Mathematical Theory of Energy Efficient Neural Computation and Communication.
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Dec 2, 2019 · In this paper we investigate the rate coding capabilities of neurons whose input signal are alterations of the base state of balanced ...
Arguments for Generalized Inverse. Gaussian ISI Durations of Cortical Neurons ... interspike interval (ISI). We seek to maximize ... ENERGY-EFFICIENT ...