ArticleProceedings of the National Academy of Sciences of the United States of America2023
Quasiuniversal scaling in mouse-brain neuronal activity stems from edge-of-instability critical dynamics.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Is criticality a unified setpoint of brain function?Neuron · 2025Pooled it
- Population coding under the scale invariance of high-dimensional noise.Science advances · 2026Article
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- Power Laws in Empirical Eigenvalue Spectra.Entropy (Basel, Switzerland) · 2026Article
- Emergent critical oscillations in motor cortex of Parkinson's patients.bioRxiv : the preprint server for biology · 2026Article
- Two views of the brain are reconciled by a unifying principle of maximal information processing.bioRxiv : the preprint server for biology · 2025Article
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- The cortical critical power law balances energy and information in an optimal fashion.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Network Mechanisms Underlying the Regional Diversity of Variance and Time Scales of the Brain's Spontaneous Activity Fluctuations.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Measurement effects on critical scaling in neural systems.Frontiers in computational neuroscience · 2025Article
- Critical dynamics in spontaneous EEG predict anesthetic-induced loss of consciousness and perturbational complexity.Communications biology · 2024Article
- The mechanics of correlated variability in segregated cortical excitatory subnetworks.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Low-dimensional criticality embedded in high-dimensional awake brain dynamics.Science advances · 2024Article
- Article
- Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia.bioRxiv : the preprint server for biology · 2023Article
- Article
- Critical scaling of whole-brain resting-state dynamics.Communications biology · 2023Article
- The mechanics of correlated variability in segregated cortical excitatory subnetworks.bioRxiv : the preprint server for biology · 2023Article
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3 authors.
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Abstract
The brain is in a state of perpetual reverberant neural activity, even in the absence of specific tasks or stimuli. Shedding light on the origin and functional significance of such a dynamical state is essential to understanding how the brain transmits, processes, and stores information. An inspiring, albeit controversial, conjecture proposes that some statistical characteristics of empirically observed neuronal activity can be understood by assuming that brain networks operate in a dynamical regime with features, including the emergence of scale invariance, resembling those seen typically near phase transitions. Here, we present a data-driven analysis based on simultaneous high-throughput recordings of the activity of thousands of individual neurons in various regions of the mouse brain. To analyze these data, we construct a unified theoretical framework that synergistically combines a phenomenological renormalization group approach and techniques that infer the general dynamical state of a neural population, while designing complementary tools. This strategy allows us to uncover strong signatures of scale invariance that are "quasiuniversal" across brain regions and experiments, revealing that all the analyzed areas operate, to a greater or lesser extent, near the edge of instability.
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