ArticleeLife2024
Neural criticality from effective latent variables.
Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- How the brain dances across critical boundaries.PLoS biology · 2026Article
- Power Laws in Empirical Eigenvalue Spectra.Entropy (Basel, Switzerland) · 2026Article
- Article
- Multiscale Organization of Neural Networks in a 3D Bioprinted Matrix.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Article
- Stereotyped Spatiotemporal Dynamics of Spontaneous Activity in Visual Cortex Prior to Eye Opening.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Structured Dynamics in the Algorithmic Agent.Entropy (Basel, Switzerland) · 2025Article
- Measurement effects on critical scaling in neural systems.Frontiers in computational neuroscience · 2025Article
- The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality.Scientific reports · 2024Article
- The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality.bioRxiv : the preprint server for biology · 2024Article
- Article
- Fluctuating landscapes and heavy tails in animal behavior.bioRxiv : the preprint server for biology · 2023Article
- Article
- Article
Corrections and comments
- Update of
Authors and funding
3 authors.
Funding
Abstract
Observations of power laws in neural activity data have raised the intriguing notion that brains may operate in a critical state. One example of this critical state is 'avalanche criticality', which has been observed in various systems, including cultured neurons, zebrafish, rodent cortex, and human EEG. More recently, power laws were also observed in neural populations in the mouse under an activity coarse-graining procedure, and they were explained as a consequence of the neural activity being coupled to multiple latent dynamical variables. An intriguing possibility is that avalanche criticality emerges due to a similar mechanism. Here, we determine the conditions under which latent dynamical variables give rise to avalanche criticality. We find that populations coupled to multiple latent variables produce critical behavior across a broader parameter range than those coupled to a single, quasi-static latent variable, but in both cases, avalanche criticality is observed without fine-tuning of model parameters. We identify two regimes of avalanches, both critical but differing in the amount of information carried about the latent variable. Our results suggest that avalanche criticality arises in neural systems in which activity is effectively modeled as a population driven by a few dynamical variables and these variables can be inferred from the population activity.
Indexed as
Identifiers
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.