Estimating the energy of dissipative neural systems

J 2024

Estimating the energy of dissipative neural systems

FAGERHOLM, Erik Daniel, Robert LEECH, Federico E TURKHEIMER, Gregory SCOTT, Milan BRÁZDIL et. al.

Základní údaje

Originální název

Estimating the energy of dissipative neural systems

Autoři

FAGERHOLM, Erik Daniel, Robert LEECH, Federico E TURKHEIMER, Gregory SCOTT a Milan BRÁZDIL

Vydání

COGNITIVE NEURODYNAMICS, DORDRECHT, SPRINGER, 2024, 1871-4080

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30210 Clinical neurology

Stát vydavatele

Nizozemské království

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 3.700 v roce 2022

Organizační jednotka

Lékařská fakulta

DOI

http://dx.doi.org/10.1007/s11571-024-10166-1

UT WoS

001302327300001

Klíčová slova anglicky

Computational neuroscience; Neural energy

Štítky

14110127

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 23. 9. 2024 13:42, Mgr. Tereza Miškechová

Anotace

V originále

There is, at present, a lack of consensus regarding precisely what is meant by the term 'energy' across the sub-disciplines of neuroscience. Definitions range from deficits in the rate of glucose metabolism in consciousness research to regional changes in neuronal activity in cognitive neuroscience. In computational neuroscience virtually all models define the energy of neuronal regions as a quantity that is in a continual process of dissipation to its surroundings. This, however, is at odds with the definition of energy used across all sub-disciplines of physics: a quantity that does not change as a dynamical system evolves in time. Here, we bridge this gap between the dissipative models used in computational neuroscience and the energy-conserving models of physics using a mathematical technique first proposed in the context of fluid dynamics. We go on to derive an expression for the energy of the linear time-invariant (LTI) state space equation. We then use resting-state fMRI data obtained from the human connectome project to show that LTI energy is associated with glucose uptake metabolism. Our hope is that this work paves the way for an increased understanding of energy in the brain, from both a theoretical as well as an experimental perspective.

Citovat

FAGERHOLM, Erik Daniel, Robert LEECH, Federico E TURKHEIMER, Gregory SCOTT a Milan BRÁZDIL. Estimating the energy of dissipative neural systems. COGNITIVE NEURODYNAMICS. DORDRECHT: SPRINGER, 2024, 8 s. ISSN 1871-4080. Dostupné z: https://dx.doi.org/10.1007/s11571-024-10166-1.

@article{2436118,
   author = {Fagerholm, Erik Daniel and Leech, Robert and Turkheimer, Federico E and Scott, Gregory and Brázdil, Milan},
   article_location = {DORDRECHT},
   doi = {http://dx.doi.org/10.1007/s11571-024-10166-1},
   keywords = {Computational neuroscience; Neural energy},
   language = {eng},
   issn = {1871-4080},
   journal = {COGNITIVE NEURODYNAMICS},
   title = {Estimating the energy of dissipative neural systems},
   url = {https://link.springer.com/article/10.1007/s11571-024-10166-1},
   year = {2024}
}

TY  - JOUR
ID  - 2436118
AU  - Fagerholm, Erik Daniel - Leech, Robert - Turkheimer, Federico E - Scott, Gregory - Brázdil, Milan
PY  - 2024
TI  - Estimating the energy of dissipative neural systems
JF  - COGNITIVE NEURODYNAMICS
PB  - SPRINGER
SN  - 18714080
KW  - Computational neuroscience
KW  - Neural energy
UR  - https://link.springer.com/article/10.1007/s11571-024-10166-1
N2  - There is, at present, a lack of consensus regarding precisely what is meant by the term 'energy' across the sub-disciplines of neuroscience. Definitions range from deficits in the rate of glucose metabolism in consciousness research to regional changes in neuronal activity in cognitive neuroscience. In computational neuroscience virtually all models define the energy of neuronal regions as a quantity that is in a continual process of dissipation to its surroundings. This, however, is at odds with the definition of energy used across all sub-disciplines of physics: a quantity that does not change as a dynamical system evolves in time. Here, we bridge this gap between the dissipative models used in computational neuroscience and the energy-conserving models of physics using a mathematical technique first proposed in the context of fluid dynamics. We go on to derive an expression for the energy of the linear time-invariant (LTI) state space equation. We then use resting-state fMRI data obtained from the human connectome project to show that LTI energy is associated with glucose uptake metabolism. Our hope is that this work paves the way for an increased understanding of energy in the brain, from both a theoretical as well as an experimental perspective.
ER  -

FAGERHOLM, Erik Daniel, Robert LEECH, Federico E TURKHEIMER, Gregory SCOTT a Milan BRÁZDIL. Estimating the energy of dissipative neural systems. \textit{COGNITIVE NEURODYNAMICS}. DORDRECHT: SPRINGER, 2024, 8 s. ISSN~1871-4080. Dostupné z: https://dx.doi.org/10.1007/s11571-024-10166-1.

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