Evidence map›Paper›PMID 39901043›Full record

ArticleCommunications biology2025

Mapping and modeling age-related changes in intrinsic neural timescales.

Kaichao Wu, Leonardo L Gollo

Abstract read
In one paragraph

Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Temporal and Spatial Scales of Human Resting-State Cortical Activity across the Lifespan.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  8. Article
  9. Criticality and increased intrinsic neural timescales in stroke.NPJ systems biology and applications · 2025
    Article
  10. Aging and the Spectral Properties of Brain Hemodynamics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  11. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Kaichao WuBrain Networks and Modelling Laboratory and The Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia.ORCID http://orcid.org/0000-0001-6988-624X
Leonardo L GolloBrain Networks and Modelling Laboratory and The Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia. leonardo.gollo@monash.edu.ORCID http://orcid.org/0000-0003-3505-9259

Funding

Department of Education and Training | Australian Research Council (ARC) FT200100942Rebecca L. Cooper Medical Research Foundation PG2019402
6 · The paper itself

Abstract

Intrinsic timescales of brain regions exhibit heterogeneity, escalating with hierarchical levels, and are crucial for the temporal integration of external stimuli. Aging, often associated with cognitive decline, involves progressive neuronal and synaptic loss, reshaping brain structure and dynamics. However, the impact of these structural changes on temporal coding in the aging brain remains unclear. We mapped intrinsic timescales and gray matter volume (GMV) using magnetic resonance imaging (MRI) in young and elderly adults. We found shorter intrinsic timescales across multiple large-scale functional networks in the elderly cohort, and a significant positive association between intrinsic timescales and GMV. Additionally, age-related decline in performance on visual discrimination tasks was linked to a reduction in intrinsic timescales in the cuneus. To explain these age-related shifts, we developed an age-dependent spiking neuron network model. In younger subjects, brain regions were near a critical branching regime, while regions in elderly subjects had fewer neurons and synapses, pushing the dynamics toward a subcritical regime. The model accurately reproduced the empirical results, showing longer intrinsic timescales in young adults due to critical slowing down. Our findings reveal how age-related structural brain changes may drive alterations in brain dynamics, offering testable predictions and informing possible interventions targeting cognitive decline.

Indexed as

AgingBrainBrain MappingModels, NeurologicalAdultAgedAged, 80 and overFemaleGray MatterHumansMagnetic Resonance ImagingMaleMiddle AgedNeuronsYoung Adult

Identifiers

PMID39901043
PMCPMC11791184

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.