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

Davide Momi (), Zheng Wang, Sara Parmigiani, Ezequiel Mikulan, Sorenza P. Bastiaens, Mohammad P. Oveisi, Kevin Kadak, Gianluca Gaglioti, Allison C. Waters, Sean Hill, Andrea Pigorini, Corey J. Keller and John D. Griffiths
Additional contact information
Davide Momi: Centre for Addiction and Mental Health (CAMH)
Zheng Wang: Centre for Addiction and Mental Health (CAMH)
Sara Parmigiani: Stanford University Medical Center
Ezequiel Mikulan: Università degli studi di Milano
Sorenza P. Bastiaens: Centre for Addiction and Mental Health (CAMH)
Mohammad P. Oveisi: Centre for Addiction and Mental Health (CAMH)
Kevin Kadak: Centre for Addiction and Mental Health (CAMH)
Gianluca Gaglioti: Università degli Studi di Milano
Allison C. Waters: Icahn School of Medicine at Mount Sinai
Sean Hill: Centre for Addiction and Mental Health (CAMH)
Andrea Pigorini: Università degli Studi di Milano
Corey J. Keller: Stanford University Medical Center
John D. Griffiths: Centre for Addiction and Mental Health (CAMH)

Nature Communications, 2025, vol. 16, issue 1, 1-12

Abstract: Abstract The human brain exhibits a modular and hierarchical structure, spanning low-order sensorimotor to high-order cognitive/affective systems. What is the mechanistic significance of this organization for brain dynamics and information processing properties? We investigated this question using rare simultaneous multimodal electrophysiology (stereotactic and scalp electroencephalography - EEG) recordings in 36 patients with drug-resistant focal epilepsy during presurgical intracerebral electrical stimulation (iES) (323 stimulation sessions). 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 on 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 an activity pattern characterized by more inter-network functional integration 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. These findings offer new insights into how hierarchical brain organization influences cognitive functions and could inform strategies for targeted neuromodulation therapies.

Date: 2025
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DOI: 10.1038/s41467-025-58187-6

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