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Relating alpha power and phase to population firing and hemodynamic activity using a thalamo-cortical neural mass model

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Ritter,  Petra
Minerva Research Group Brain Modes, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Department of Neurology, Charité University Medicine Berlin, Germany;
Bernstein Center for Computational Neuroscience, Berlin, Germany;
Berlin School of Mind and Brain, Humboldt University Berlin, Germany;

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Citation

Becker, R., Knock, S., Ritter, P., & Jirsa, V. (2015). Relating alpha power and phase to population firing and hemodynamic activity using a thalamo-cortical neural mass model. PLoS Computational Biology, 11(9): e1004352. doi:10.1371/journal.pcbi.1004352.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0027-76AB-0
Abstract
Oscillations are ubiquitous phenomena in the animal and human brain. Among them, the alpha rhythm in human EEG is one of the most prominent examples. However, its precise mechanisms of generation are still poorly understood. It was mainly this lack of knowledge that motivated a number of simultaneous electroencephalography (EEG) – functional magnetic resonance imaging (fMRI) studies. This approach revealed how oscillatory neuronal signatures such as the alpha rhythm are paralleled by changes of the blood oxygenation level dependent (BOLD) signal. Several such studies revealed a negative correlation between the alpha rhythm and the hemodynamic BOLD signal in visual cortex and a positive correlation in the thalamus. In this study we explore the potential generative mechanisms that lead to those observations. We use a bursting capable Stefanescu-Jirsa 3D (SJ3D) neural-mass model that reproduces a wide repertoire of prominent features of local neuronal-population dynamics. We construct a thalamo-cortical network of coupled SJ3D nodes considering excitatory and inhibitory directed connections. The model suggests that an inverse correlation between cortical multi-unit activity, i.e. the firing of neuronal populations, and narrow band local field potential oscillations in the alpha band underlies the empirically observed negative correlation between alpha-rhythm power and fMRI signal in visual cortex. Furthermore the model suggests that the interplay between tonic and bursting mode in thalamus and cortex is critical for this relation. This demonstrates how biophysically meaningful modelling can generate precise and testable hypotheses about the underpinnings of large-scale neuroimaging signals.