ArticleNeural computation2022
Predicting the Future With a Scale-Invariant Temporal Memory for the Past.
Article in Neural computation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- The anticipation of imminent events is time-scale invariant.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Learning Temporal Relationships Between Symbols with Laplace Neural Manifolds.Computational brain & behavior · 2025Article
- Mesolimbic dopamine release conveys causal associations.Science (New York, N.Y.) · 2022Article
- How do real animals account for the passage of time during associative learning?Behavioral neuroscience · 2022Article
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Authors and funding
3 authors.
Funding
Abstract
In recent years, it has become clear that the brain maintains a temporal memory of recent events stretching far into the past. This letter presents a neurally inspired algorithm to use a scale-invariant temporal representation of the past to predict a scale-invariant future. The result is a scale-invariant estimate of future events as a function of the time at which they are expected to occur. The algorithm is time-local, with credit assigned to the present event by observing how it affects the prediction of the future. To illustrate the potential utility of this approach, we test the model on simultaneous renewal processes with different timescales. The algorithm scales well on these problems despite the fact that the number of states needed to describe them as a Markov process grows exponentially.
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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.