ArticleNature communications2025
Computational memory capacity predicts aging and cognitive decline.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The efficacy of reminiscence therapy on the cognition of older patients with cognitive impairment or dementia: a meta-analysis based on regulatory factors.Aging clinical and experimental research · 2026Pooled it
- BOLD fMRI activations and LC contrast associated with successful episodic memory in healthy older adults and MCI.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Neuromorphic hierarchical modular reservoirs.Nature communications · 2026Article
- Competitive interactions shape mammalian brain network dynamics and computation.Nature neuroscience · 2026Article
- Fifteen years on: a review of the Cam-CAN study of the cognitive neuroscience of ageing.GeroScience · 2026Review
- Electromechanically induced membrane restructuring enables learning and memory.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Cancer and Aging Biomarkers: Classification, Early Detection Technologies and Emerging Research Trends.Biosensors · 2025Review
- The locus coeruleus, a blue spot for early diagnosis and prognosis of Alzheimer's disease.Frontiers in aging neuroscience · 2025Review
Corrections and comments
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Authors and funding
21 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Memory is a crucial cognitive function that deteriorates with age. However, this ability is normally assessed using cognitive tests instead of the architecture of brain networks. Here, we use reservoir computing, a recurrent neural network computing paradigm, to assess the linear memory capacities of neural-network reservoirs extracted from brain anatomical connectivity data in a lifespan cohort of 636 individuals. The computational memory capacity emerges as a robust marker of aging, being associated with resting-state functional activity, white matter integrity, locus coeruleus signal intensity, and cognitive performance. We replicate our findings in an independent cohort of 154 young and 72 old individuals. By linking the computational memory capacity of the brain network with cognition, brain function and integrity, our findings open new pathways to employ reservoir computing to investigate aging and age-related disorders.
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Registered trials
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.