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

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,...

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Autores principales: He, Xiaosong, Caciagli, Lorenzo, Parkes, Linden, Stiso, Jennifer, Karrer, Teresa M., Kim, Jason Z., Lu, Zhixin, Menara, Tommaso, Pasqualetti, Fabio, Sperling, Michael R., Tracy, Joseph I., Bassett, Dani S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9645718/
https://www.ncbi.nlm.nih.gov/pubmed/36351015
http://dx.doi.org/10.1126/sciadv.abn2293
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author He, Xiaosong
Caciagli, Lorenzo
Parkes, Linden
Stiso, Jennifer
Karrer, Teresa M.
Kim, Jason Z.
Lu, Zhixin
Menara, Tommaso
Pasqualetti, Fabio
Sperling, Michael R.
Tracy, Joseph I.
Bassett, Dani S.
author_facet He, Xiaosong
Caciagli, Lorenzo
Parkes, Linden
Stiso, Jennifer
Karrer, Teresa M.
Kim, Jason Z.
Lu, Zhixin
Menara, Tommaso
Pasqualetti, Fabio
Sperling, Michael R.
Tracy, Joseph I.
Bassett, Dani S.
author_sort He, Xiaosong
collection PubMed
description 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.
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spelling pubmed-96457182022-11-21 Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy He, Xiaosong Caciagli, Lorenzo Parkes, Linden Stiso, Jennifer Karrer, Teresa M. Kim, Jason Z. Lu, Zhixin Menara, Tommaso Pasqualetti, Fabio Sperling, Michael R. Tracy, Joseph I. Bassett, Dani S. Sci Adv Neuroscience 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. American Association for the Advancement of Science 2022-11-09 /pmc/articles/PMC9645718/ /pubmed/36351015 http://dx.doi.org/10.1126/sciadv.abn2293 Text en 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). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , 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.
spellingShingle Neuroscience
He, Xiaosong
Caciagli, Lorenzo
Parkes, Linden
Stiso, Jennifer
Karrer, Teresa M.
Kim, Jason Z.
Lu, Zhixin
Menara, Tommaso
Pasqualetti, Fabio
Sperling, Michael R.
Tracy, Joseph I.
Bassett, Dani S.
Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy
title Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy
title_full Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy
title_fullStr Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy
title_full_unstemmed Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy
title_short Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy
title_sort uncovering the biological basis of control energy: structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9645718/
https://www.ncbi.nlm.nih.gov/pubmed/36351015
http://dx.doi.org/10.1126/sciadv.abn2293
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