Temporal irreversibility of large-scale brain dynamics in Alzheimer’s disease

Mostra el registre complet Registre parcial de l'ítem

• dc.contributor.author Cruzat Grand, Josefina, 1983-
• dc.contributor.author Herzog, Rubén
• dc.contributor.author Prado, Pavel
• dc.contributor.author Sanz Perl, Yonatan
• dc.contributor.author Gonzalez-Gomez, Raul
• dc.contributor.author Moguilner, Sebastián
• dc.contributor.author Kringelbach, Morten L.
• dc.contributor.author Deco, Gustavo
• dc.contributor.author Tagliazucchi, Enzo
• dc.contributor.author Ibañez, Agustin
• dc.date.accessioned 2023-07-12T07:27:00Z
• dc.date.available 2023-07-12T07:27:00Z
• dc.date.issued 2023
• dc.description.abstract Healthy brain dynamics can be understood as the emergence of a complex system far from thermodynamic equilibrium. Brain dynamics are temporally irreversible and thus establish a preferred direction in time (i.e., arrow of time). However, little is known about how the time-reversal symmetry of spontaneous brain activity is affected by Alzheimer's disease (AD). We hypothesized that the level of irreversibility would be compromised in AD, signaling a fundamental shift in the collective properties of brain activity toward equilibrium dynamics. We investigated the irreversibility from resting-state fMRI and EEG data in male and female human patients with AD and elderly healthy control subjects (HCs). We quantified the level of irreversibility and, thus, proximity to nonequilibrium dynamics by comparing forward and backward time series through time-shifted correlations. AD was associated with a breakdown of temporal irreversibility at the global, local, and network levels, and at multiple oscillatory frequency bands. At the local level, temporoparietal and frontal regions were affected by AD. The limbic, frontoparietal, default mode, and salience networks were the most compromised at the network level. The temporal reversibility was associated with cognitive decline in AD and gray matter volume in HCs. The irreversibility of brain dynamics provided higher accuracy and more distinctive information than classical neurocognitive measures when differentiating AD from control subjects. Findings were validated using an out-of-sample cohort. Present results offer new evidence regarding pathophysiological links between the entropy generation rate of brain dynamics and the clinical presentation of AD, opening new avenues for dementia characterization at different levels.
• dc.description.sponsorship A.I. was supported by Takeda Grant CW2680521; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET); Fondo para la Investigación Científica y Tecnológica (FONCYT)-Proyectos de Investigación Científica y Tecnológica (PICT) Grants 2017-1818 and 2017-1820; Agencia Nacional de Investigación y Desarrollo (ANID)/Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica (FONDECYT) Regular Grants 1210195, 1210176, and 1220995); ANID/Fondo de Financiamiento de Centros de Investigación en Áreas Prioritarias (FONDAP) Grant 15150012; ANID-PIA ANILLOS Grant ACT210096; ANID/Fondo Nacional de la Defensa Argentino (FONDEF) Grants ID20I10152 and ID22I10029; and the Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat), funded by the National Institutes of Aging of the National Institutes of Health under Grant R01-AG-057234, Alzheimer's Association Grant SG-20-725707-ReDLat, the Rainwater Foundation, and the Global Brain Health Institute. J.C. was supported by BrainLat Postdoctoral Fellowship. Y.S.-P. is supported by European Union's Horizon 2020 Research And Innovation Program under Marie Sklodowska-Curie Grant 896354. E.T. is supported by Grants PICT-2018-03103 and PICT-2019-02294 funded by Agencia I+D+I (Argentina), a Mercator fellowship granted by the German Research Foundation, and by ANID/FONDECYT Regular Grant 1220995 (Chile). G.D. was supported by the Human Brain Project Specific Grant Agreement 3 Grant 945539 and by the Spanish Research Project AWAKENING: Using Whole-Brain Models Perturbational Approaches for Predicting External Stimulation to Force Transitions between Different Brain States (reference PID2019-105772GB-I00/AEI/10.13039/501100011033), financed by the Spanish Ministry of Science, Innovation, and Universities (MCIU) and State Research Agency (AEI). M.L.K. is supported by the Center for Music in the Brain, funded by the Danish National Research Foundation (Grant DNRF117); and the Center for Eudaimonia and Human Flourishing at Linacre College, funded by the Pettit and Carlsberg Foundations.
• dc.format.mimetype application/pdf
• dc.identifier.citation Cruzat J, Herzog R, Prado P, Sanz-Perl Y, Gonzalez-Gomez R, Moguilner S, Kringelbach ML, Deco G, Tagliazucchi E, Ibañez A. Temporal irreversibility of large-scale brain dynamics in Alzheimer’s disease. J Neurosci. 2023;43(9):1643-56. DOI: 10.1523/JNEUROSCI.1312-22.2022
• dc.identifier.doi http://dx.doi.org/10.1523/JNEUROSCI.1312-22.2022
• dc.identifier.issn 0270-6474
• dc.identifier.uri http://hdl.handle.net/10230/57554
• dc.language.iso eng
• dc.publisher Society for Neuroscience
• dc.relation.ispartof Journal of Neuroscience. 2023;43(9):1643-56.
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/896354
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-105772GB-I00
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/945539
• dc.rights © 2023 Cruzat et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Alzheimer’s disease
• dc.subject.keyword dynamic networks
• dc.subject.keyword EEG
• dc.subject.keyword fMRI
• dc.subject.keyword irreversibility dynamics
• dc.subject.keyword machine learning
• dc.title Temporal irreversibility of large-scale brain dynamics in Alzheimer’s disease
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion