ArticleScientific reports2023
Cognitive and plastic recurrent neural network clock model for the judgment of time and its variations.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed, 9 citations in OpenAlex.
- A computational framework for epigenetic plasticity in memory.Brain : a journal of neurology · 2026Review
- Time on Their Side: How Visual Timers Affect Anticipatory Anxiety, Performance, and On-Task Behavior in Elementary Math Assessments.European journal of investigation in health, psychology and education · 2025Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
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Abstract
The aim of this study in the field of computational neurosciences was to simulate and predict inter-individual variability in time judgements with different neuropsychological properties. We propose and test a Simple Recurrent Neural Network-based clock model that is able to account for inter-individual variability in time judgment by adding four new components into the clock system: the first relates to the plasticity of the neural system, the second to the attention allocated to time, the third to the memory of duration, and the fourth to the learning of duration by iteration. A simulation with this model explored its fit with participants' time estimates in a temporal reproduction task undertaken by both children and adults, whose varied cognitive abilities were assessed with neuropsychological tests. The simulation successfully predicted 90% of temporal errors. Our Cognitive and Plastic RNN-Clock model (CP-RNN-Clock), that takes into account the interference arising from a clock system grounded in cognition, was thus validated.
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