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Noise in the central nervous system

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Noise — random disturbances of signals — pose a fundamental problem for information processing and affects all aspects of nervous-system function. However, the nature, amount and impact of noise in the central nervous system have only recently been addressed in a quantitative manner by the use of stochastic models and simulations.

Here, I will focus on action potentials, the fundamental signal used by neurons to transmit information rapidly and reliably to other neurons along nerve fibers (axons).

I will show how conduction along such axons of our brains is affected by the probabilistic nature of voltage-gated ion channels, “protein transitors” mediating the signal. The key finding is that fluctuations in these signalling proteins set a general lower limit to cell size. This limit operates above other biophysical limits to axon diameter and matches anatomical data across the animal kingdom.

Axons operating close to this limit, as in our brains, are affected by these molecular noise sources, as signals get corrupted in distance-dependent ways and modify information transmission at synapses. The combined effect of stochastically behaving ion channels produces two counterintuitive side-effects: First, the effect of noise decreases with increasing temperature. Second, noise effects become dependent on the history of previous signalling events.

While, these findings have direct implication to neuroscience, the general nature of these mechanisms should apply to all cellular signalling systems using noisy protein switches to propagate signals, such as Ca++ waves.

This talk is part of the Inference Group series.

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