A layer potential approach to inverse problems in brain imaging

Author:

Asensio Paul1,Badier Jean-Michel2,Leblond Juliette1,Marmorat Jean-Paul3,Nemaire Masimba4

Affiliation:

1. FACTAS , Inria Sophia Antipolis-Méditerranée , 2004 Rte des Lucioles, 06902 Valbonne , France

2. Institut de Neurosciences des Systèmes , Aix-Marseille Université , INS/Inserm, 13005 Marseille , France

3. Center of Applied Mathematics , Ecole des Mines ParisTech , CS 10 207, 06904 Sophia Antipolis Cedex , Paris , France

4. FACTAS , Inria Sophia Antipolis-Méditerranée , 2004 Rte des Lucioles, 06902 Valbonne ; Institut de Mathématiques de Bordeaux UMR 5251, Université de Bordeaux, 351, cours de la Libération, 33405 Talence , France

Abstract

Abstract We study the inverse source localisation problem using the electric potential measured point-wise inside the head with stereo-ElectroEncephaloGraphy (sEEG), the electric potential measured point-wise on the scalp with ElectroEncephaloGraphy (EEG) or the magnetic flux density measured point-wise outside the head with MagnetoEncephaloGraphy (MEG). We present a method that works on a wide range of models of primary currents; in particular, we give details for primary currents that are assumed to be smooth vector fields that are supported on and normally oriented to the grey/white matter interface. Irrespective of the data used, we also solve the transmission problem of the electric potential associated with a recovered source; hence we solve the cortical mapping problem. To ensure that the electric potential and normal currents are continuous in the head, the electric potential is expressed as a linear combination of double layer potentials and the magnetic flux density is expressed as a linear combination of single layer potentials. Numerically, we solve the problems on meshed surfaces of the grey/white matter interface, cortical surface, skull and scalp. A main feature of the numerical approach we take is that, on the meshed surfaces, we can compute the double and single layer potentials exactly and at arbitrary points. Because we explicitly study the transmission of the electric potential in head when using magnetic data, the coupling of electric and magnetic data in the source recovery problem is made explicit and shows the advantage of using simultaneous electric and magnetic data. We provide numerical examples of the source recovery and inverse cortical mapping using synthetic data.

Funder

Agence Nationale de la Recherche

Publisher

Walter de Gruyter GmbH

Subject

Applied Mathematics

Reference39 articles.

1. R. A. Adams, Sobolev Spaces, Pure Appl. Math. 65, Academic Press, New York, 1975.

2. S. Axler, P. Bourdon and W. Ramey, Harmonic Function Theory, Grad. Texts in Math., Springer, New York, 2006.

3. L. Baratchart, C. Villalobos Guillén, D. P. Hardin, M. C. Northington and E. B. Saff, Inverse potential problems for divergence of measures with total variation regularization, Found. Comput. Math. 20 (2020), no. 5, 1273–1307.

4. B. Beauzamy, Introduction to Banach Spaces and Their Geometry, Math. Notes, North-Holland, Amsterdam, 1985.

5. A. Beck, On the convergence of alternating minimization for convex programming with applications to iteratively reweighted least squares and decomposition schemes, SIAM J. Optim. 25 (2015), no. 1, 185–209.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3