ArticlePloS one2014
Emergence of connectivity motifs in networks of model neurons with short- and long-term plastic synapses.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- A unified model of short- and long-term plasticity: Effects on network connectivity and information capacity.PLoS computational biology · 2026Article
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- A computational theory of short-term synaptic plasticity: synapses learn to tell time.Research square · 2026Article
- Modelling novelty detection in the thalamocortical loop.PLoS computational biology · 2023Article
- A robust model of Stimulus-Specific Adaptation validated on neuromorphic hardware.Scientific reports · 2021Article
- Embodied working memory during ongoing input streams.PloS one · 2021Article
- Autonomous emergence of connectivity assemblies via spike triplet interactions.PLoS computational biology · 2020Article
- Computational geometry for modeling neural populations: From visualization to simulation.PLoS computational biology · 2019Article
- Discrimination of Motion Direction in a Robot Using a Phenomenological Model of Synaptic Plasticity.Computational intelligence and neuroscience · 2019Article
- Abstract concept learning in a simple neural network inspired by the insect brain.PLoS computational biology · 2018Article
- Article
- Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks.PLoS computational biology · 2017Article
- Functional consequences of pre- and postsynaptic expression of synaptic plasticity.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017Review
- Effects of local network topology on the functional reconstruction of spiking neural network models.Applied network science · 2017Article
- Emulating short-term synaptic dynamics with memristive devices.Scientific reports · 2016Article
- Article
- Adaptation of short-term plasticity parameters via error-driven learning may explain the correlation between activity-dependent synaptic properties, connectivity motifs and target specificity.Frontiers in computational neuroscience · 2014Article
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2 authors.
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Abstract
Recent experimental data from the rodent cerebral cortex and olfactory bulb indicate that specific connectivity motifs are correlated with short-term dynamics of excitatory synaptic transmission. It was observed that neurons with short-term facilitating synapses form predominantly reciprocal pairwise connections, while neurons with short-term depressing synapses form predominantly unidirectional pairwise connections. The cause of these structural differences in excitatory synaptic microcircuits is unknown. We show that these connectivity motifs emerge in networks of model neurons, from the interactions between short-term synaptic dynamics (SD) and long-term spike-timing dependent plasticity (STDP). While the impact of STDP on SD was shown in simultaneous neuronal pair recordings in vitro, the mutual interactions between STDP and SD in large networks are still the subject of intense research. Our approach combines an SD phenomenological model with an STDP model that faithfully captures long-term plasticity dependence on both spike times and frequency. As a proof of concept, we first simulate and analyze recurrent networks of spiking neurons with random initial connection efficacies and where synapses are either all short-term facilitating or all depressing. For identical external inputs to the network, and as a direct consequence of internally generated activity, we find that networks with depressing synapses evolve unidirectional connectivity motifs, while networks with facilitating synapses evolve reciprocal connectivity motifs. We then show that the same results hold for heterogeneous networks, including both facilitating and depressing synapses. This does not contradict a recent theory that proposes that motifs are shaped by external inputs, but rather complements it by examining the role of both the external inputs and the internally generated network activity. Our study highlights the conditions under which SD-STDP might explain the correlation between facilitation and reciprocal connectivity motifs, as well as between depression and unidirectional motifs.
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