ArticleFrontiers in neuroinformatics2023
Quantifying evoked responses through information-theoretical measures.
Article in Frontiers in neuroinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
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Who cites it
3 citing papers in PubMed.
- Predictive encoding of auditory sequences in the human prefrontal cortex.bioRxiv : the preprint server for biology · 2025Article
- Direct brain recordings reveal implicit encoding of structure in random auditory streams.Scientific reports · 2025Article
- Beta oscillations predict the envelope sharpness in a rhythmic beat sequence.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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Abstract
Information theory is a viable candidate to advance our understanding of how the brain processes information generated in the internal or external environment. With its universal applicability, information theory enables the analysis of complex data sets, is free of requirements about the data structure, and can help infer the underlying brain mechanisms. Information-theoretical metrics such as Entropy or Mutual Information have been highly beneficial for analyzing neurophysiological recordings. However, a direct comparison of the performance of these methods with well-established metrics, such as the
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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.