Distinct lifespan trajectories of cortical intrinsic timescales and neural oscillations

The brain integrates information over time through the persistence of neural activity, yet how this persistence changes across the human lifespan and the mechanisms underlying these changes remain unclear. Using resting-state magnetoencephalography from three independent cohorts (n = 1,156; ages 6-88 years), we systematically examined lifespan changes in neural temporal dynamics, focusing on cortical intrinsic timescales and alpha oscillatory frequency. We found that cortical intrinsic timescales shortened from approximately 29 ms in childhood to 9 ms in late adulthood, with the steepest decline occurring before age 30. This compression was reproducible across cohorts and observed in all cortical regions, while the sensory-to-association hierarchy of timescales remained preserved throughout life. By contrast, alpha frequency followed a distinct trajectory, peaking in early adulthood before declining after midlife. Individualized corticothalamic models linked timescale compression to stronger intrathalamic inhibition, whereas increased conduction delays partly accounted for alpha slowing. Further network simulations indicated that intrinsic timescales primarily reflect collective network dynamics rather than single-neuron kinetics. Together, these findings reveal distinct lifespan trajectories of neural persistence and oscillatory rhythms, implicating collective corticothalamic dynamics in the temporal organization of the human brain across development and ageing.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-11-06
DOI
https://doi.org/10.64898/2026.11.04.764097
Primary Topic
Neural dynamics and brain function
Type
preprint

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preprint

Distinct lifespan trajectories of cortical intrinsic timescales and neural oscillations

Tengteng Fan, Brendan Harris, Ruifang Cui, Sanwang Wang et al.
6 links
bioRxiv (Cold Spring Harbor Laboratory)
Neural dynamics and brain function
preprint

Distinct lifespan trajectories of cortical intrinsic timescales and neural oscillations

Tengteng Fan, Brendan Harris, Ruifang Cui, Sanwang Wang, Runhao Lu, Mingyue Zhang, Xinyu Liang, Qiuxuan Yu, Xiaobo Liu
preprint en

Abstract

The brain integrates information over time through the persistence of neural activity, yet how this persistence changes across the human lifespan and the mechanisms underlying these changes remain unclear. Using resting-state magnetoencephalography from three independent cohorts (n = 1,156; ages 6-88 years), we systematically examined lifespan changes in neural temporal dynamics, focusing on cortical intrinsic timescales and alpha oscillatory frequency. We found that cortical intrinsic timescales shortened from approximately 29 ms in childhood to 9 ms in late adulthood, with the steepest decline occurring before age 30. This compression was reproducible across cohorts and observed in all cortical regions, while the sensory-to-association hierarchy of timescales remained preserved throughout life. By contrast, alpha frequency followed a distinct trajectory, peaking in early adulthood before declining after midlife. Individualized corticothalamic models linked timescale compression to stronger intrathalamic inhibition, whereas increased conduction delays partly accounted for alpha slowing. Further network simulations indicated that intrinsic timescales primarily reflect collective network dynamics rather than single-neuron kinetics. Together, these findings reveal distinct lifespan trajectories of neural persistence and oscillatory rhythms, implicating collective corticothalamic dynamics in the temporal organization of the human brain across development and ageing.

bioRxiv (Cold Spring Harbor Laboratory)
The University of Sydney (AU), Fudan University (CN), Huzhou Normal University (CN), Peking University Sixth Hospital (CN), McGill University (CA)
National Natural Science Foundation of China, Beijing Institute of Technology, Peking University
Good health and well-being
Neural dynamics and brain function
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