ArticlePloS one2013
Neural avalanches at the critical point between replay and non-replay of spatiotemporal patterns.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 49 citations in OpenAlex.
- Symmetry breaking and avalanche shapes in modular neural networks.Frontiers in computational neuroscience · 2026Article
- Self-organized criticality in a mesoscopic model of excitatory-inhibitory neuronal populations by short-term and long-term synaptic plasticity.Frontiers in computational neuroscience · 2022Article
- Flexible brain dynamics underpins complex behaviours as observed in Parkinson's disease.Scientific reports · 2021Article
- Scale-Free Dynamics in Animal Groups and Brain Networks.Frontiers in systems neuroscience · 2020Article
- Single-Cell Membrane Potential Fluctuations Evince Network Scale-Freeness and Quasicriticality.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2019Article
- Fast and flexible sequence induction in spiking neural networks via rapid excitability changes.eLife · 2019Article
- Spike-Timing-Dependent Plasticity With Axonal Delay Tunes Networks of Izhikevich Neurons to the Edge of Synchronization Transition With Scale-Free Avalanches.Frontiers in systems neuroscience · 2019Article
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- Repertoires of Spike Avalanches Are Modulated by Behavior and Novelty.Frontiers in neural circuits · 2016Article
- Avalanches in self-organized critical neural networks: a minimal model for the neural SOC universality class.PloS one · 2014Article
- Spike avalanches in vivo suggest a driven, slightly subcritical brain state.Frontiers in systems neuroscience · 2014Article
- Alternation of up and down states at a dynamical phase-transition of a neural network with spatiotemporal attractors.Frontiers in systems neuroscience · 2014Article
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We model spontaneous cortical activity with a network of coupled spiking units, in which multiple spatio-temporal patterns are stored as dynamical attractors. We introduce an order parameter, which measures the overlap (similarity) between the activity of the network and the stored patterns. We find that, depending on the excitability of the network, different working regimes are possible. For high excitability, the dynamical attractors are stable, and a collective activity that replays one of the stored patterns emerges spontaneously, while for low excitability, no replay is induced. Between these two regimes, there is a critical region in which the dynamical attractors are unstable, and intermittent short replays are induced by noise. At the critical spiking threshold, the order parameter goes from zero to one, and its fluctuations are maximized, as expected for a phase transition (and as observed in recent experimental results in the brain). Notably, in this critical region, the avalanche size and duration distributions follow power laws. Critical exponents are consistent with a scaling relationship observed recently in neural avalanches measurements. In conclusion, our simple model suggests that avalanche power laws in cortical spontaneous activity may be the effect of a network at the critical point between the replay and non-replay of spatio-temporal patterns.
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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.