ArticlePLoS computational biology2016
Shaping Neural Circuits by High Order Synaptic Interactions.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Synaptic-state-dependent plasticity routes learning signals in recurrent circuits.bioRxiv : the preprint server for biology · 2026Article
- Homeostatic Plasticity Enables Stable yet Tunable Neuronal Assemblies.bioRxiv : the preprint server for biology · 2026Article
- Dynamic control of sequential retrieval speed in networks with heterogeneous learning rules.eLife · 2024Article
- Learning what matters: Synaptic plasticity with invariance to second-order input correlations.PLoS computational biology · 2024Article
- Purely STDP-based assembly dynamics: Stability, learning, overlaps, drift and aging.PLoS computational biology · 2023Article
- Drifting assemblies for persistent memory: Neuron transitions and unsupervised compensation.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- From synapse to network: models of information storage and retrieval in neural circuits.Current opinion in neurobiology · 2021Review
- Balanced networks under spike-time dependent plasticity.PLoS computational biology · 2021Article
- Characteristics of sequential activity in networks with temporally asymmetric Hebbian learning.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Autonomous emergence of connectivity assemblies via spike triplet interactions.PLoS computational biology · 2020Article
- Training and Spontaneous Reinforcement of Neuronal Assemblies by Spike Timing Plasticity.Cerebral cortex (New York, N.Y. : 1991) · 2019Article
- Topological reinforcement as a principle of modularity emergence in brain networks.Network neuroscience (Cambridge, Mass.) · 2019Article
- A Theoretical Framework to Derive Simple, Firing-Rate-Dependent Mathematical Models of Synaptic Plasticity.Frontiers in computational neuroscience · 2019Article
- Rhythmogenesis evolves as a consequence of long-term plasticity of inhibitory synapses.Scientific reports · 2018Article
- Interplay of multiple pathways and activity-dependent rules in STDP.PLoS computational biology · 2018Article
- Effects of Firing Variability on Network Structures with Spike-Timing-Dependent Plasticity.Frontiers in computational neuroscience · 2018Article
- From the statistics of connectivity to the statistics of spike times in neuronal networks.Current opinion in neurobiology · 2017Review
- Linking structure and activity in nonlinear spiking networks.PLoS computational biology · 2017Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Spike timing dependent plasticity (STDP) is believed to play an important role in shaping the structure of neural circuits. Here we show that STDP generates effective interactions between synapses of different neurons, which were neglected in previous theoretical treatments, and can be described as a sum over contributions from structural motifs. These interactions can have a pivotal influence on the connectivity patterns that emerge under the influence of STDP. In particular, we consider two highly ordered forms of structure: wide synfire chains, in which groups of neurons project to each other sequentially, and self connected assemblies. We show that high order synaptic interactions can enable the formation of both structures, depending on the form of the STDP function and the time course of synaptic currents. Furthermore, within a certain regime of biophysical parameters, emergence of the ordered connectivity occurs robustly and autonomously in a stochastic network of spiking neurons, without a need to expose the neural network to structured inputs during learning.
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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.