ArticleFrontiers in computational neuroscience2022
Approximations of algorithmic and structural complexity validate cognitive-behavioral experimental results.
Article in Frontiers in computational neuroscience, 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
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
5 citing papers in PubMed, 5 citations in OpenAlex.
- SuperARC: a test for artificial superintelligence based on compressed modelling, recursive prediction and problem complexity.Nature communications · 2026Article
- Information Theory Opens New Dimensions in Experimental Studies of Animal Behaviour and Communication.Animals : an open access journal from MDPI · 2023Review
- A Review of Methods for Estimating Algorithmic Complexity: Options, Challenges, and New Directions.Entropy (Basel, Switzerland) · 2020Review
- Algorithmic Entropy and Landauer's Principle Link Microscopic System Behaviour to the Thermodynamic Entropy.Entropy (Basel, Switzerland) · 2018Article
- Inform: Efficient Information-Theoretic Analysis of Collective Behaviors.Frontiers in robotics and AI · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Being able to objectively characterize the intrinsic complexity of behavioral patterns resulting from human or animal decisions is fundamental for deconvolving cognition and designing autonomous artificial intelligence systems. Yet complexity is difficult in practice, particularly when strings are short. By numerically approximating algorithmic (Kolmogorov) complexity (
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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.