ArticleFrontiers in behavioral neuroscience2026
Behavioral phenotypes in aging: structured exploratory computational analysis of multi-assay behavioral data.
Article in Frontiers in behavioral neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Aging is associated with progressive alterations in behavioral function, yet majority of the studies interpret behavioral outcomes on an assay-by-assay basis, limiting understanding of how behavioral domains are organized. Our previously published study used a mouse cohort to report assay-specific behavioral effects. In this study, we examined whether aging-related behavioral signals remain localized to individual assays or can be summarized as coordinated domain-level patterns. Methods: A structured rule-based workflow was implemented for feature engineering, direction harmonization, z-score standardization, and domain-level composite construction across locomotion/exploration, anxiety/avoidance, depression/passive coping, cognition/learning, memory, and sociability domains. Outcomes were analyzed using parametric or non-parametric models following assumption screening, with effect sizes reported. Results: Domain-level composite scores did not show significant age- or sex-related effects, indicating limited broad behavioral separation. In contrast, refined feature-level analysis identified modest locomotor differences (core locomotion distance; Kruskal-Wallis Conclusion: Aging-related behavioral changes in this dataset were concentrated in specific assay-level measures rather than broadly distributed across domains. Domain-level aggregation reduced separation of effects, indicating that the present composites should be interpreted as heuristic summaries rather than validated behavioral dimensions. The main added value of this reanalysis is therefore interpretive, showing that the strongest signals remain most evident in selected measures, particularly Barnes Maze outcomes.
Indexed as
Identifiers
What OpenQuestion holds
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.