Applying information theory to cellular ion concentration gradients, these authors derive a principle where cells optimally code responses to environmental perturbations -- incl input from other cells -- by minimizing the cross entropy (Kullback-Leibler divergence) between intracellular and extracellular ion concentrations.
"We demonstrate the ion dynamics in neuronal action potentials described by Hodgkin and Huxley (including the equations themselves) represent a special case of these general information principles."
The greater the KL-divergence, the longer the codeword of Shannon information, the longer the response time. Natural selection would choose rapid responses, so the KL-divergence is minimized: the probability density of the fluctuating intracellular ion concentration is kept as close to the mostly-constant probability density of the extracellular concentration as possible.
The huge range of different perturbations leading to intracellular ion concentration changes would increase the evolutionary pressure for complex and diverse ion channels under this principle
All cells process information, but nerves/neurons are specialized to do so extremely fast in order to respond accurately, in chain reactions, in real time to inputs from perception and memory. Spikes should be really good at this, they're both very short codewords and strong electrical perturbations for neighboring neurons, but they aren't the sole information carriers that would fit the digital computer metaphor. Analog abounds
"transmembrane ion gradients potentially may encode in excess of 10^14 bits of
Shannon information"
@axoaxonic
I mean when you consider how those ion gradients are actively and passively manipulated and computed on across the entire arborizaton of a neuron, hell ya they encode a shitload of information
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