Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy

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Abstract

Network control theory is increasingly used to profile the brain’s energy landscape via simulations of neural dynamics. This approach estimates the control energy required to simulate the activation of brain circuits based on structural connectome measured using diffusion magnetic resonance imaging, thereby quantifying those circuits’ energetic efficiency. The biological basis of control energy, however, remains unknown, hampering its further application. To fill this gap, investigating temporal lobe epilepsy as a lesion model, we show that patients require higher control energy to activate the limbic network than healthy volunteers, especially ipsilateral to the seizure focus. The energetic imbalance between ipsilateral and contralateral temporolimbic regions is tracked by asymmetric patterns of glucose metabolism measured using positron emission tomography, which, in turn, may be selectively explained by asymmetric gray matter loss as evidenced in the hippocampus. Our investigation provides the first theoretical framework unifying gray matter integrity, metabolism, and energetic generation of neural dynamics.

Abstract

The structural and metabolic basis of control energy in the brain is uncovered by leveraging epilepsy as a human lesion model.

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Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.

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Author and article information

Contributors

Xiaosong He:

ORCID: https://orcid.org/0000-0002-7941-2918

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: SoftwareRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Lorenzo Caciagli:

ORCID: https://orcid.org/0000-0001-7189-9699

Role: ConceptualizationRole: Formal analysisRole: ResourcesRole: Writing - original draftRole: Writing - review & editing

Linden Parkes:

ORCID: https://orcid.org/0000-0002-9329-7207

Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Supervision

Jennifer Stiso: Role: ConceptualizationRole: MethodologyRole: Writing - review & editing

Teresa M. Karrer: Role: SoftwareRole: Writing - review & editing

Jason Z. Kim:

ORCID: https://orcid.org/0000-0002-3970-4561

Role: MethodologyRole: Software

Zhixin Lu: Role: Conceptualization

Tommaso Menara:

ORCID: https://orcid.org/0000-0002-5523-2170

Role: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: Writing - review & editing

Fabio Pasqualetti: Role: ConceptualizationRole: SoftwareRole: Supervision

Michael R. Sperling:

ORCID: https://orcid.org/0000-0003-0708-6006

Role: ConceptualizationRole: ResourcesRole: SupervisionRole: Writing - review & editing

Joseph I. Tracy: Role: ConceptualizationRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing - review & editing

Dani S. Bassett:

ORCID: https://orcid.org/0000-0002-6183-4493

Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing - original draft

Journal

Journal ID (nlm-ta): Sci Adv

Journal ID (iso-abbrev): Sci Adv

Journal ID (publisher-id): sciadv

Journal ID (hwp): advances

Title: Science Advances

Publisher: American Association for the Advancement of Science

ISSN (Electronic): 2375-2548

Publication date Collection: November 2022

Publication date (Electronic, pub): 09 November 2022

Volume: 8

Issue: 45

Electronic Location Identifier: eabn2293

Affiliations

[ ¹ ]Department of Psychology, School of Humanities and Social Sciences, University of Science and Technology of China, Hefei, Anhui, China.

[ ² ]Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.

[ ³ ]UCL Queen Square Institute of Neurology, Queen Square, London, UK.

[ ⁴ ]MRI Unit, Epilepsy Society, Chesham Lane, Chalfont St Peter, Buckinghamshire, UK.

[ ⁵ ]Personalized Health Care, Product Development, F. Hoffmann-La Roche Ltd., Basel, Switzerland.

[ ⁶ ]Department of Mechanical and Aerospace Engineering, University of California, San Diego, San Diego, CA, USA.

[ ⁷ ]Department of Mechanical Engineering, University of California, Riverside, Riverside, CA, USA.

[ ⁸ ]Department of Neurology, Thomas Jefferson University, Philadelphia, PA, USA.

[ ⁹ ]Departments of Electrical and Systems Engineering, Physics and Astronomy, Psychiatry, and Neurology, University of Pennsylvania, Philadelphia, PA, USA.

[ ¹⁰ ]Santa Fe Institute, Santa Fe, NM, USA.

Author notes

[* ]Corresponding author. Email: hexs@ 123456ustc.edu.cn (X.H.); dsb@ 123456seas.upenn.edu (D.S.B.)

Author information

Xiaosong He https://orcid.org/0000-0002-7941-2918

Lorenzo Caciagli https://orcid.org/0000-0001-7189-9699

Linden Parkes https://orcid.org/0000-0002-9329-7207

Jason Z. Kim https://orcid.org/0000-0002-3970-4561

Tommaso Menara https://orcid.org/0000-0002-5523-2170

Michael R. Sperling https://orcid.org/0000-0003-0708-6006

Dani S. Bassett https://orcid.org/0000-0002-6183-4493

Article

Publisher ID: abn2293

DOI: 10.1126/sciadv.abn2293

PMC ID: 9645718

PubMed ID: 36351015

SO-VID: 83ac67a7-37b8-4e72-bf12-4841a9e007cc

Copyright © Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

History

Date received : 16 November 2021

Date accepted : 22 September 2022

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;

Award ID: BCS-1631550

Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;

Award ID: IIS-1926757