- Title
- Geometric constraints on human brain function
- Creator
- Pang, James C.; Aquino, Kevin M.; Oldehinkel, Marianne; Robinson, Peter A.; Fulcher, Ben D.; Breakspear, Michael; Fornito, Alex
- Relation
- Nature Vol. 618, Issue 7965, p. 566-574
- Publisher Link
- http://dx.doi.org/10.1038/s41586-023-06098-1
- Publisher
- Nature Publishing Group
- Resource Type
- journal article
- Date
- 2023
- Description
- The anatomy of the brain necessarily constrains its function, but precisely how remains unclear. The classical and dominant paradigm in neuroscience is that neuronal dynamics are driven by interactions between discrete, functionally specialized cell populations connected by a complex array of axonal fibres1–3. However, predictions from neural field theory, an established mathematical framework for modelling large-scale brain activity4–6, suggest that the geometry of the brain may represent a more fundamental constraint on dynamics than complex interregional connectivity7,8. Here, we confirm these theoretical predictions by analysing human magnetic resonance imaging data acquired under spontaneous and diverse task-evoked conditions. Specifically, we show that cortical and subcortical activity can be parsimoniously understood as resulting from excitations of fundamental, resonant modes of the brain’s geometry (that is, its shape) rather than from modes of complex interregional connectivity, as classically assumed. We then use these geometric modes to show that task-evoked activations across over 10,000 brain maps are not confined to focal areas, as widely believed, but instead excite brain-wide modes with wavelengths spanning over 60 mm. Finally, we confirm predictions that the close link between geometry and function is explained by a dominant role for wave-like activity, showing that wave dynamics can reproduce numerous canonical spatiotemporal properties of spontaneous and evoked recordings. Our findings challenge prevailing views and identify a previously underappreciated role of geometry in shaping function, as predicted by a unifying and physically principled model of brain-wide dynamics.
- Subject
- anatomy; neuroscience; brain geometry; wave-like activity
- Identifier
- http://hdl.handle.net/1959.13/1482829
- Identifier
- uon:51037
- Identifier
- ISSN:0028-0836
- Rights
- This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Language
- eng
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