ArticleScientific reports2018
Delay-Induced Multistability and Loop Formation in Neuronal Networks with Spike-Timing-Dependent Plasticity.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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25 citing papers in PubMed, 60 citations in OpenAlex.
- Time delays in computational models of neuronal and synaptic dynamics.Frontiers in computational neuroscience · 2025Article
- Synaptic reorganization of synchronized neuronal networks with synaptic weight and structural plasticity.PLoS computational biology · 2024Article
- Synchronization of delayed coupled neurons with multiple synaptic connections.Cognitive neurodynamics · 2024Article
- Dynamics of parkinsonian oscillations mediated by transmission delays in a mean-field model of the basal ganglia.Frontiers in cellular neuroscience · 2024Article
- A Physical Framework to Study the Effect of Magnetic Fields on the Spike-Time Coding.Biomedical engineering and computational biology · 2024Article
- Coordinated reset stimulation of plastic neural networks with spatially dependent synaptic connections.Frontiers in network physiology · 2024Article
- Inhibitory neurons control the consolidation of neural assemblies via adaptation to selective stimuli.Scientific reports · 2023Article
- Delay-dependent transitions of phase synchronization and coupling symmetry between neurons shaped by spike-timing-dependent plasticity.Cognitive neurodynamics · 2023Article
- Decoupling of interacting neuronal populations by time-shifted stimulation through spike-timing-dependent plasticity.PLoS computational biology · 2023Article
- Noise-modulated multistable synapses in a Wilson-Cowan-based model of plasticity.Frontiers in computational neuroscience · 2023Article
- Interplay of different synchronization modes and synaptic plasticity in a system of class I neurons.Scientific reports · 2022Article
- Spike-Timing-Dependent Plasticity Mediated by Dopamine and its Role in Parkinson's Disease Pathophysiology.Frontiers in network physiology · 2022Review
- Inhibitory Spike-Timing-Dependent Plasticity Can Account for Pathological Strengthening of Pallido-Subthalamic Synapses in Parkinson's Disease.Frontiers in physiology · 2022Article
- The Origin of Abnormal Beta Oscillations in the Parkinsonian Corticobasal Ganglia Circuits.Parkinson's disease · 2022Review
- Efficient suppression of parkinsonian beta oscillations in a closed-loop model of deep brain stimulation with amplitude modulation.Frontiers in human neuroscience · 2022Article
- Multistability in a star network of Kuramoto-type oscillators with synaptic plasticity.Scientific reports · 2021Article
- Numerical Simulation: Fluctuation in Background Synaptic Activity Regulates Synaptic Plasticity.Frontiers in systems neuroscience · 2021Article
- Voltage-dependent plasticity of spin-polarized conductance in phenyl-based single-molecule magnetic tunnel junctions.PloS one · 2021Article
- Dopaminergic Neuromodulation of Spike Timing Dependent Plasticity in Mature Adult Rodent and Human Cortical Neurons.Frontiers in cellular neuroscience · 2021Article
- Frequency-Resolved Functional Connectivity: Role of Delay and the Strength of Connections.Frontiers in neural circuits · 2021Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spike-timing-dependent plasticity (STDP) adjusts synaptic strengths according to the precise timing of pre- and postsynaptic spike pairs. Theoretical and computational studies have revealed that STDP may contribute to the emergence of a variety of structural and dynamical states in plastic neuronal populations. In this manuscript, we show that by incorporating dendritic and axonal propagation delays in recurrent networks of oscillatory neurons, the asymptotic connectivity displays multistability, where different structures emerge depending on the initial distribution of the synaptic strengths. In particular, we show that the standard deviation of the initial distribution of synaptic weights, besides its mean, determines the main properties of the emergent structural connectivity such as the mean final synaptic weight, the number of two-neuron loops and the symmetry of the final structure. We also show that the firing rates of the neurons affect the evolution of the network, and a more symmetric configuration of the synapses emerges at higher firing rates. We justify the network results based on a two-neuron framework and show how the results translate to large recurrent networks.
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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.