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Stimulation mapping and whole-brain modeling reveal gradients of excitability and recurrence in cortical networks

Momi, D.; Wang, Z.; Parmigiani, S.; Mikulan, E.; Bastiaens, S.; Oveisi, M.; Kadak, K.; Gaglioti, G.; Waters, A.; Hill, S.; Pigorini, A.; Keller, C.; Griffiths, J. D.

2024-02-28 neuroscience
10.1101/2024.02.26.581277 bioRxiv
Show abstract

The human brain exhibits a modular and hierarchical structure, spanning low-order sensorimotor to high-order cognitive/affective systems. What is the causal significance of this organization for brain dynamics and information processing properties? We investigated this question using rare simultaneous multimodal electrophysiology (stereotactic and scalp EEG) recordings in patients during presurgical intracerebral electrical stimulation (iES). Our analyses revealed an anatomical gradient of excitability across the cortex, with stronger iES-evoked EEG responses in high-order compared to low-order regions. Mathematical modeling further showed that this variation in excitability levels results from a differential dependence of recurrent feedback from non-stimulated regions across the anatomical hierarchy, and could be extinguished by suppressing those connections in-silico. High-order brain regions/networks thus show a more functionally integrated processing style than low-order ones, which manifests as a spatial gradient of excitability that is emergent from, and causally dependent on, the underlying hierarchical network structure.

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