A Mathematical Model for Neuronal Activity and Brain Information Processing Capacity
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)(2023)
摘要
Neurophysiological measurements suggest that human information processing is evinced by neuronal activity. However, the quantitative relationship between the activity of a brain region and its information processing capacity remains unclear. In this paper, we introduce an information conservation law for regional brain activation, and establish a mathematical model to quantify the relationship between the information processing capacity, input storage capacity, the arrival rate of exogenous information, and the neuronal activity of a brain region—referred to as the brain information processing capacity (IPC) model. We apply the IPC model to event related fMRI data from a flanker test, designed to determine age-related differences in brain activation. Our analysis demonstrates the predictive validity of the model in terms of providing accurate account of fMRI responses, and shows that for a given cognitive task, higher information processing capacity leads to lower neuronal activity level and faster response. Relying solely on the information conservation law, the IPC model provides a framework for modeling distributed neuronal processing—and can be applied to different data types and scales: i.e., single neurons, brain regions, and networks.
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关键词
brain information processing capacity model,brain region-referred,exogenous information,higher information processing capacity,human information processing,information conservation law,input storage capacity,IPC model,mathematical model,neuronal activity level,regional brain activation,single neurons
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