ArticlePLoS computational biology2015
Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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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.
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Who cites it
47 citing papers in PubMed, 88 citations in OpenAlex.
- Strong and localized recurrence controls the dimensionality of neural activity across brain areas.Nature neuroscience · 2026Article
- Homeostatic Plasticity Enables Stable yet Tunable Neuronal Assemblies.bioRxiv : the preprint server for biology · 2026Article
- A complex network perspective on brain disease.Biological reviews of the Cambridge Philosophical Society · 2026Review
- Deriving connectivity from spiking activity in detailed models of large-scale cortical microcircuits.iScience · 2026Article
- Behavioral Timescale Synaptic Plasticity: A Burst in the Field of Learning and Memory.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Review
- Synaptic Synchronization-Based Learning of Pattern Separation in Self-Organizing Probabilistic Spiking Neural Networks.bioRxiv : the preprint server for biology · 2025Article
- Extending Mathematical Frameworks to Investigate Neuronal Dynamics in the Presence of Microglial Ensheathment.Bulletin of mathematical biology · 2025Article
- Balancing complexity, performance and plausibility to meta learn plasticity rules in recurrent spiking networks.PLoS computational biology · 2025Article
- Multistable Synaptic Plasticity Induces Memory Effects and Cohabitation of Chimera and Bump States in Leaky Integrate-and-Fire Networks.Entropy (Basel, Switzerland) · 2025Article
- Maintenance of delay-period activity in working memory task is modulated by local network structure.PLoS computational biology · 2024Article
- Spiking attractor model of motor cortex explains modulation of neural and behavioral variability by prior target information.Nature communications · 2024Article
- Stimulus type shapes the topology of cellular functional networks in mouse visual cortex.Nature communications · 2024Article
- Simulated dataset on coordinated reset stimulation of homogeneous and inhomogeneous networks of excitatory leaky integrate-and-fire neurons with spike-timing-dependent plasticity.Data in brief · 2024Article
- Mean-Field Approximations With Adaptive Coupling for Networks With Spike-Timing-Dependent Plasticity.Neural computation · 2023Article
- Stimulus-dependent functional network topology in mouse visual cortex.bioRxiv : the preprint server for biology · 2023Article
- Purely STDP-based assembly dynamics: Stability, learning, overlaps, drift and aging.PLoS computational biology · 2023Article
- Synaptic reshaping of plastic neuronal networks by periodic multichannel stimulation with single-pulse and burst stimuli.PLoS computational biology · 2022Article
- Dynamics of phase oscillator networks with synaptic weight and structural plasticity.Scientific reports · 2022Article
- Microcircuits for spatial coding in the medial entorhinal cortex.Physiological reviews · 2022Review
- Metastable dynamics of neural circuits and networks.Applied physics reviews · 2022Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure.
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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.