ArticleFrontiers in computational neuroscience2017
Estimating the Information Extracted by a Single Spiking Neuron from a Continuous Input Time Series.
Article in Frontiers in computational neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Neuronal identity is not static: An input-driven perspective.PLoS computational biology · 2025Article
- The tuning of tuning: How adaptation influences single cell information transfer.PLoS computational biology · 2024Article
- Towards Generalizing the Information Theory for Neural Communication.Entropy (Basel, Switzerland) · 2022Article
- A databank for intracellular electrophysiological mapping of the adult somatosensory cortex.GigaScience · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding the relation between (sensory) stimuli and the activity of neurons (i.e., "the neural code") lies at heart of understanding the computational properties of the brain. However, quantifying the information between a stimulus and a spike train has proven to be challenging. We propose a new (
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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.