Quantitative modeling of multiscale neural activity

Peter A. Robinson; Christopher J. Rennie

doi:10.1117/12.694598

3 January 2007 Quantitative modeling of multiscale neural activity

Peter A. Robinson, Christopher J. Rennie

Proceedings Volume 6417, Complexity and Nonlinear Dynamics; 64170F (2007) https://doi.org/10.1117/12.694598
Event: SPIE Smart Materials, Nano- and Micro-Smart Systems, 2006, Adelaide, Australia

Abstract

The electrical activity of the brain has been observed for over a century and is widely used to probe brain function and disorders, chiefly through the electroencephalogram (EEG) recorded by electrodes on the scalp. However, the connections between physiology and EEGs have been chiefly qualitative until recently, and most uses of the EEG have been based on phenomenological correlations. A quantitative mean-field model of brain electrical activity is described that spans the range of physiological and anatomical scales from microscopic synapses to the whole brain. Its parameters measure quantities such as synaptic strengths, signal delays, cellular time constants, and neural ranges, and are all constrained by independent physiological measurements. Application of standard techniques from wave physics allows successful predictions to be made of a wide range of EEG phenomena, including time series and spectra, evoked responses to stimuli, dependence on arousal state, seizure dynamics, and relationships to functional magnetic resonance imaging (fMRI). Fitting to experimental data also enables physiological parameters to be infered, giving a new noninvasive window into brain function, especially when referenced to a standardized database of subjects. Modifications of the core model to treat mm-scale patchy interconnections in the visual cortex are also described, and it is shown that resulting waves obey the Schroedinger equation. This opens the possibility of classical cortical analogs of quantum phenomena.

Citation Download Citation

Peter A. Robinson and Christopher J. Rennie "Quantitative modeling of multiscale neural activity", Proc. SPIE 6417, Complexity and Nonlinear Dynamics, 64170F (3 January 2007); https://doi.org/10.1117/12.694598

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