Evaluating in-vivo spontaneous firing rate in the brain based on neuronal noise modeling

基于神经元噪声模型评估大脑体内自发放电率

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Abstract

Even without external stimuli, neurons produce spontaneous bursts of activities. Theoretical and practical clinical considerations, suggest the importance of determining the in-vivo statistical profile of those spontaneous spikes bursts, however this task has not been accomplished yet. Currently, it is only accepted that the in-vivo value of the mean firing rate (λ) of those spontaneous bursts is below 0.1Hz, without knowing its specific value and its population distribution. Here we propose a framework to evaluate the neurons' λ during rest of a given subject, using stochastic signal processing analysis of in-vivo brain fMRI and EEG. Our main hypothesis is that during rest the input to the neurons is mostly formed by a random neuronal noise, and although it fluctuates with zero mean, it affects the neurons' signal output characteristics. Our results based on in-vivo human fMRI and EEG databases, suggest that different people have different and stable characteristic λ values, and that λ of different functional systems of the same subject correlate in their values. Moreover, we find here that the λ values of subjects correlate with their brain task performances, in particular for tasks which are known to be affected by changes in neuronal noise or neuronal excitability threshold.

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