Neural Mass Model of EEG Responses
Author Information
Author(s): Moran R.J., Kiebel S.J., Stephan K.E., Reilly R.B., Daunizeau J., Friston K.J.
Primary Institution: The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London
Hypothesis
How do neurophysiological parameters influence the spectral response of a neural mass model?
Conclusion
The study establishes a model that shows how neuromodulatory effects can be quantified through EEG spectral density.
Supporting Evidence
- The model incorporates parameters for spike-rate adaptation and recurrent inhibitory connections.
- It demonstrates that the spectral response is influenced by the non-linearity of the firing rate–input curves.
- The model allows for the quantification of pharmacologically induced changes in adaptation currents.
Takeaway
This study created a model to understand how brain signals change with different factors, helping us learn about brain activity.
Methodology
The study used linear systems analysis to explore the spectral response of a neural mass model.
Limitations
The model does not formally map to conventional integrate-and-fire models and lacks explicit representation of receptor subtype gating.
Digital Object Identifier (DOI)
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