ArticleScientific reports2022
Neuromodulator-dependent synaptic tagging and capture retroactively controls neural coding in spiking neural networks.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 21 citations in OpenAlex.
- Neuromodulatory Gating of Synaptic Plasticity: Mechanisms, Motivation, and Clinical Dysfunction Across Scales.Synapse (New York, N.Y.) · 2026Review
- Two-factor synaptic plasticity enables memory consolidation during neuronal burst firing.PNAS nexus · 2026Article
- Plastic Arbor: A modern simulation framework for synaptic plasticity-From single synapses to networks of morphological neurons.PLoS computational biology · 2026Article
- Competition and cooperation of assembly sequences in recurrent neural networks.PLoS computational biology · 2025Article
- Synapses tagged, memories kept: synaptic tagging and capture hypothesis in brain health and disease.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- Learning with filopodia and spines: Complementary strong and weak competition lead to specialized, graded, and protected receptive fields.PLoS computational biology · 2024Article
- Unsupervised learning of perceptual feature combinations.PLoS computational biology · 2024Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Events that are important to an individual's life trigger neuromodulator release in brain areas responsible for cognitive and behavioral function. While it is well known that the presence of neuromodulators such as dopamine and norepinephrine is required for memory consolidation, the impact of neuromodulator concentration is, however, less understood. In a recurrent spiking neural network model featuring neuromodulator-dependent synaptic tagging and capture, we study how synaptic memory consolidation depends on the amount of neuromodulator present in the minutes to hours after learning. We find that the storage of rate-based and spike timing-based information is controlled by the level of neuromodulation. Specifically, we find better recall of temporal information for high levels of neuromodulation, while we find better recall of rate-coded spatial patterns for lower neuromodulation, mediated by the selection of different groups of synapses for consolidation. Hence, our results indicate that in minutes to hours after learning, the level of neuromodulation may alter the process of synaptic consolidation to ultimately control which type of information becomes consolidated in the recurrent neural network.
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