ArticleScientific reports2016
Phase transitions and self-organized criticality in networks of stochastic spiking neurons.
Article in Scientific reports, 2016. 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, 100 citations in OpenAlex.
- Two views of the brain are reconciled by a unifying principle of maximal information processing.bioRxiv : the preprint server for biology · 2025Article
- A mean-field approach to criticality in spiking neural networks for reservoir computing.Scientific reports · 2025Article
- Sequence processing with quantum-inspired tensor networks.Scientific reports · 2025Article
- Emergent functions of noise-driven spontaneous activity: homeostatic maintenance of criticality and memory consolidation.Frontiers in neural circuits · 2025Article
- Network structure influences self-organized criticality in neural networks with dynamical synapses.Frontiers in systems neuroscience · 2025Article
- Collective dynamics and long-range order in thermal neuristor networks.Nature communications · 2024Article
- Network state transitions during cortical development.Nature reviews. Neuroscience · 2024Review
- Scale free avalanches in excitatory-inhibitory populations of spiking neurons with conductance based synaptic currents.Journal of computational neuroscience · 2023Article
- Topological data analysis of the firings of a network of stochastic spiking neurons.Frontiers in neural circuits · 2023Article
- 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
- Article
- Neural field theory of neural avalanche exponents.Biological cybernetics · 2021Article
- Criticality, Connectivity, and Neural Disorder: A Multifaceted Approach to Neural Computation.Frontiers in computational neuroscience · 2021Review
- Time-dependent branching processes: a model of oscillating neuronal avalanches.Scientific reports · 2020Article
- Higher-Order Cumulants Drive Neuronal Activity Patterns, Inducing UP-DOWN States in Neural Populations.Entropy (Basel, Switzerland) · 2020Article
- The Emergence of Integrated Information, Complexity, and 'Consciousness' at Criticality.Entropy (Basel, Switzerland) · 2020Article
- Subsampled Directed-Percolation Models Explain Scaling Relations Experimentally Observed in the Brain.Frontiers in neural circuits · 2020Article
- Stochastic oscillations and dragon king avalanches in self-organized quasi-critical systems.Scientific reports · 2019Article
- Heterogeneity and Delayed Activation as Hallmarks of Self-Organization and Criticality in Excitable Tissue.Frontiers in physiology · 2019Article
- Dynamics of spontaneous activity in random networks with multiple neuron subtypes and synaptic noise : Spontaneous activity in networks with synaptic noise.Journal of computational neuroscience · 2018Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phase transitions and critical behavior are crucial issues both in theoretical and experimental neuroscience. We report analytic and computational results about phase transitions and self-organized criticality (SOC) in networks with general stochastic neurons. The stochastic neuron has a firing probability given by a smooth monotonic function Φ(V) of the membrane potential V, rather than a sharp firing threshold. We find that such networks can operate in several dynamic regimes (phases) depending on the average synaptic weight and the shape of the firing function Φ. In particular, we encounter both continuous and discontinuous phase transitions to absorbing states. At the continuous transition critical boundary, neuronal avalanches occur whose distributions of size and duration are given by power laws, as observed in biological neural networks. We also propose and test a new mechanism to produce SOC: the use of dynamic neuronal gains - a form of short-term plasticity probably located at the axon initial segment (AIS) - instead of depressing synapses at the dendrites (as previously studied in the literature). The new self-organization mechanism produces a slightly supercritical state, that we called SOSC, in accord to some intuitions of Alan Turing.
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