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Optimizing information transmission rates drives brain gyrification

Heyden, S. and Ortiz, M. (2018) Optimizing information transmission rates drives brain gyrification. Proceedings of the Royal Society A: Mathematical, physical, and engineering sciences, 474 (2219). Art. No. 20180527. ISSN 1364-5021.

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We investigate the functional optimality of the cerebral cortex of an adult human brain geometry. Unlike most competing models, we postulate that the cerebral cortex formation is driven by the objective of maximizing the total information transmission rate. Starting from a random path model, we show that this optimization problem is related to the Steklov eigenvalue problem. Combining realistic brain geometries with the finite-element method, we calculate the underlying Steklov eigenvalues and eigenfunctions. By comparison to a convex hull approximation, we show that the adult human brain geometry indeed reduces the Steklov eigenvalue spectrum and thus increases the rate at which information is exchanged between points on the cerebral cortex. With a view to possible clinical applications, the leading Steklov eigenfunctions and the resulting induced magnetic fields are computed and reported.

Item Type:Article
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URLURL TypeDescription
Heyden, S.0000-0002-7035-7975
Ortiz, M.0000-0001-5877-4824
Additional Information:© 2018 The Author(s). Published by the Royal Society. Manuscript received 05/08/2018; Manuscript accepted 22/10/2018; Published online 21/11/2018; Published in print 11/2018. Data accessibility: This article has no additional data. Author's contributions: Both authors conceived of and designed this study and drafted the manuscript. Both authors gave final approval for publication. We declare we have no competing interests. S.H. gratefully acknowledges support from the Alexander von Humboldt Stiftung through a Research Fellowship for Postdoctoral Researchers.
Funding AgencyGrant Number
Alexander von Humboldt FoundationUNSPECIFIED
Subject Keywords:Steklov eigenvalue problem; functional optimality; cerebral cortex formation
Issue or Number:2219
Record Number:CaltechAUTHORS:20181212-142046456
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:91737
Deposited By: Tony Diaz
Deposited On:12 Dec 2018 22:27
Last Modified:24 Feb 2020 10:30

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