Multilayer MEG source modelling enables depth-resolved laminar inference in humans
Abstract Neural dynamics at the laminar level are critical for cortical computation. However, in humans, non-invasive methods to probe such dynamics have been limited to coarse distinctions between deep and superficial layers. Here, we present a multilayer magnetoencephalography source reconstruction framework and evaluate the conditions under which depth-resolved laminar inference may be feasible. Using simulations, we systematically assess the limits of magnetoencephalography depth resolution, showing that laminar discrimination depends on sufficiently high signal-to-noise ratio, precise co-registration, and accurate specification of cortical column orientation. We demonstrate that regional variations in cortical anatomy influence reconstruction fidelity, with lead-field separability emerging as a key determinant. We then apply this framework to empirical data from three independent datasets and find laminar activation patterns that align with canonical feedforward and feedback motifs in visual and sensorimotor circuits, supporting the plausibility of laminar inference under favorable conditions and offering opportunities to bridge invasive electrophysiology and human neuroimaging.
Authors
- Gareth Robert Barnes (ORCID: https://orcid.org/0000-0002-5396-7712)
- Mathilde Bonnefond (ORCID: https://orcid.org/0000-0002-0539-7671)
- Jérémie Mattout (ORCID: https://orcid.org/0000-0003-2659-6984)
- Ishita Agarwal
- Maciej J Szul (ORCID: https://orcid.org/0000-0002-4116-8470)
- Andrew R. Dykstra (ORCID: https://orcid.org/0000-0001-8075-6374)
- James John Bonaiuto (ORCID: https://orcid.org/0000-0001-9165-4082)
- Sébastien Daligault (ORCID: https://orcid.org/0000-0002-8296-238X)
- Maxime Ferez (ORCID: https://orcid.org/0000-0002-8505-2162)
- Carolina Fernandez Pujol (ORCID: https://orcid.org/0009-0003-0611-1270)
- Denis Schwartz (ORCID: https://orcid.org/0000-0002-8557-2934)
- Franck Lamberton (ORCID: https://orcid.org/0000-0002-4655-4397)
- Sven Bestmann (ORCID: https://orcid.org/0000-0002-6867-9545)
- Danila Shelepenkov (ORCID: https://orcid.org/0000-0001-6321-7934)
- Yunkai Zhu
- Solène Gailhard
- Bassem Hiba
- Matteo G. Maspoli (ORCID: https://orcid.org/0009-0004-7222-8802)
- Quentin Moreau
Institutions
- Université Claude Bernard Lyon 1 (FR)
- University of Central Florida (US)
- Centre National de la Recherche Scientifique (FR)
- Institut national de recherche en sciences et technologies du numérique (FR)
- University of Miami (US)
- Inserm (FR)
- Université de Lyon (FR)
- Purdue University West Lafayette (US)
- Brown University (US)
- Centre de Recherche en Neurosciences de Lyon (FR)
- Centre d'Exploration et de Recherche Médicale par Emission de Positons (FR)
- Institut des Sciences Cognitives Marc Jeannerod (FR)
- Structure Fédérative de Recherche Santé Lyon Est (FR)
- Calcul, Cognition et Neurophysiologie (FR)
- UCL Queen Square Institute of Neurology (GB)
- University College London (GB)
- University of Tübingen (DE)
Publication Details
- Journal
- Nature Communications
- Published
- 2026-09-30
- DOI
- https://doi.org/10.1038/s41467-026-77782-9
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00