Table of Contents

Temporal Irreversibility of Large-Scale Brain Dynamics in Alzheimer’s Disease

  1. Agustín Ibañez1,4,5,7,16
  1. 1Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
  2. 2Fundación para el Estudio de la Conciencia Humana (ECoH), 7550000, Santiago, Chile
  3. 3Department of Physics, University of Buenos Aires, C1428EGA, Buenos Aires, Argentina
  4. 4National Scientific and Technical Research Council (CONICET), C1033AAJ, Buenos Aires, Argentina
  5. 5Cognitive Neuroscience Center (CNC), Universidad de San Andrés, C116ABJ, Buenos Aires, Argentina
  6. 6Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, 08005 Barcelona, Spain
  7. 7Global Brain Health Institute, University of California, San Francisco, San Francisco, California 94143
  8. 8Global Brain Health Institute, Trinity College, Dublin 2, Ireland
  9. 9Department of Psychiatry, University of Oxford, Oxford OX3 7JX, United Kingdom
  10. 10Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, 8000 Århus, Denmark
  11. 11Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford OX3 9BX, United Kingdom
  12. 12Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08018 Barcelona, Spain
  13. 13Institució Catalana de la Recerca i Estudis Avancats (ICREA), 08010 Barcelona, Spain
  14. 14Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, D-04303 Leipzig, Germany
  15. 15School of Psychological Sciences, Monash University, Melbourne 3168, Australia
  16. 16Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
  17. 17Escuela de Fonoaudiología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago, Chile
  1. Author contributions: J.C. and A.I. designed research; R.H., R.G.-G., S.M., and A.I. performed research; J.C., M.L.K., G.D., E.T., and A.I. contributed unpublished reagents/analytic tools; J.C., R.H., P.P., Y.S.-P., R.G.-G., and S.M. analyzed data; J.C., P.P., M.L.K., and A.I. wrote the paper.

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.

SIGNIFICANCE STATEMENT By assessing the irreversibility of large-scale dynamics across multiple brain signals, we provide a precise signature capable of distinguishing Alzheimer’s disease (AD) at the global, local, and network levels and different oscillatory regimes. Irreversibility of limbic, frontoparietal, default-mode, and salience networks was the most compromised by AD compared with more sensory–motor networks. Moreover, the time-irreversibility properties associated with cognitive decline and atrophy outperformed and complemented classical neurocognitive markers of AD in predictive classification performance. Findings were generalized and replicated with an out-of-sample validation procedure. We provide novel multilevel evidence of reduced irreversibility in AD brain dynamics that has the potential to open new avenues for understating neurodegeneration in terms of the temporal asymmetry of brain dynamics.

  • Received July 4, 2022.
  • Revision received December 12, 2022.
  • Accepted December 25, 2022.

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.

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