ArticleFrontiers in neural circuits2020
Subsampled Directed-Percolation Models Explain Scaling Relations Experimentally Observed in the Brain.
Article in Frontiers in neural circuits, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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23 citing papers in PubMed.
- Hippocampal criticality tracks cognitive demand and shifts with memory impairment.Communications biology · 2026Article
- Symmetry breaking and avalanche shapes in modular neural networks.Frontiers in computational neuroscience · 2026Article
- Inferring global exponents in subsampled neural systems.iScience · 2025Article
- Article
- The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality.Scientific reports · 2024Article
- Existence of multiple transitions of the critical state due to anesthetics.Nature communications · 2024Article
- The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality.bioRxiv : the preprint server for biology · 2024Article
- Low-dimensional criticality embedded in high-dimensional awake brain dynamics.Science advances · 2024Article
- Criticality of neuronal avalanches in human sleep and their relationship with sleep macro- and micro-architecture.iScience · 2023Article
- Parabolic avalanche scaling in the synchronization of cortical cell assemblies.Nature communications · 2023Article
- Structural Modularity Tunes Mesoscale Criticality in Biological Neuronal Networks.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Scale free avalanches in excitatory-inhibitory populations of spiking neurons with conductance based synaptic currents.Journal of computational neuroscience · 2023Article
- Article
- Power spectrum and critical exponents in the 2D stochastic Wilson-Cowan model.Scientific reports · 2022Article
- Sampling effects and measurement overlap can bias the inference of neuronal avalanches.PLoS computational biology · 2022Article
- Percolation may explain efficiency, robustness, and economy of the brain.Network neuroscience (Cambridge, Mass.) · 2022Article
- Disentangling the critical signatures of neural activity.Scientific reports · 2022Article
- Theoretical foundations of studying criticality in the brain.Network neuroscience (Cambridge, Mass.) · 2022Review
- Addressing skepticism of the critical brain hypothesis.Frontiers in computational neuroscience · 2022Review
- Toward a Unified Analysis of the Brain Criticality Hypothesis: Reviewing Several Available Tools.Frontiers in neural circuits · 2022Review
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9 authors.
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Abstract
Recent experimental results on spike avalanches measured in the urethane-anesthetized rat cortex have revealed scaling relations that indicate a phase transition at a specific level of cortical firing rate variability. The scaling relations point to critical exponents whose values differ from those of a branching process, which has been the canonical model employed to understand brain criticality. This suggested that a different model, with a different phase transition, might be required to explain the data. Here we show that this is not necessarily the case. By employing two different models belonging to the same universality class as the branching process (mean-field directed percolation) and treating the simulation data exactly like experimental data, we reproduce most of the experimental results. We find that subsampling the model and adjusting the time bin used to define avalanches (as done with experimental data) are sufficient ingredients to change the apparent exponents of the critical point. Moreover, experimental data is only reproduced within a very narrow range in parameter space around the phase transition.
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