We compared a range of linear and nonlinear models based on how accurately they could describe resting-state functional magnetic resonance imaging and intracranial electroencephalography dynamics in humans. Linear autoregressive models were the most accurate in all cases. Using numerical simulations, we demonstrated that spatiotemporal averaging has a critical and robust role in this linearity.
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References
Breakspear, M. Dynamic models of large-scale brain activity. Nat. Neurosci. 20, 340–352 (2017). A review article that presents an overview of different classes of linear and nonlinear models most commonly used for modelling large-scale brain dynamics, as well as the theory and assumptions underlying them.
Stam, C. J. Nonlinear dynamical analysis of EEG and MEG: review of an emerging field. Clin. Neurophysiol. 116, 2266–2301 (2005). A review article on various methods for analysis and estimation of nonlinearity in brain signals using indirect measures from nonlinear dynamical systems theory (also known as chaos theory).
Ahmed, S. & Nozari, E. On the linearizing effect of spatial averaging in large-scale populations of homogeneous nonlinear systems. In Proc. 2023 IEEE CDC 641–648 (IEEE, 2023). Follow-up study mathematically proving macroscopic linearity under spatial averaging.
Ahmed, S. & Nozari, E. On the linearizing effect of temporal averaging in nonlinear dynamical systems. In Proc. 2023 ACC 4185–4190 (IEEE, 2023). Follow-up study mathematically proving macroscopic linearity under temporal averaging.
Acharya, G., Davis, K. A. & Nozari, E. Predictive modeling of evoked intracranial EEG response to medial temporal lobe stimulation in patients with epilepsy. Preprint at bioRxiv https://doi.org/10.1101/2023.08.07.552297 (2023). Follow-up study showing that iEEG dynamics become switched-linear under electrical stimulation.
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This is a summary of: Nozari, E. et al. Macroscopic resting-state brain dynamics are best described by linear models. Nat. Biomed. Eng. https://doi.org/10.1038/s41551-023-01117-y (2023).
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Multimodal evidence suggests the linearity of brain dynamics at the macroscale. Nat. Biomed. Eng 8, 7–8 (2024). https://doi.org/10.1038/s41551-023-01127-w
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DOI: https://doi.org/10.1038/s41551-023-01127-w
