ReviewFrontiers in computational neuroscience2015
Models of Metaplasticity: A Review of Concepts.
Review in Frontiers in computational neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 35 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
35 citing papers in PubMed.
- Transcranial Magnetic Stimulation in Parkinson's Disease and Parkinsonian Syndromes: A Narrative Expert Review.Life (Basel, Switzerland) · 2026Review
- Churning Better Transcranial Direct Current Stimulation Outcome with Accelerated Protocols: Understanding the Non-linear Dynamics through Metaplasticity.Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology · 2025Review
- Synapses learn to utilize stochastic pre-synaptic release for the prediction of postsynaptic dynamics.PLoS computational biology · 2024Article
- Synaptic weight dynamics underlying memory consolidation: Implications for learning rules, circuit organization, and circuit function.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Article
- Systemic pharmacological suppression of neural activity reverses learning impairment in a mouse model of Fragile X syndrome.bioRxiv : the preprint server for biology · 2024Article
- Stability and learning in excitatory synapses by nonlinear inhibitory plasticity.PLoS computational biology · 2022Article
- Homeostatic control of synaptic rewiring in recurrent networks induces the formation of stable memory engrams.PLoS computational biology · 2022Article
- A comprehensive review of transcranial magnetic stimulation in secondary dementia.Frontiers in aging neuroscience · 2022Review
- Metaplasticity in the human swallowing system: clinical implications for dysphagia rehabilitation.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2022Review
- Metaplastic Reinforcement of Long-Term Potentiation in Hippocampal Area CA2 by Cholinergic Receptor Activation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- Article
- Unsupervised Learning and Clustered Connectivity Enhance Reinforcement Learning in Spiking Neural Networks.Frontiers in computational neuroscience · 2021Article
- Nonlinear Dendritic Coincidence Detection for Supervised Learning.Frontiers in computational neuroscience · 2021Article
- Review
- Neuroregeneration and plasticity: a review of the physiological mechanisms for achieving functional recovery postinjury.Military Medical Research · 2020Review
- The self-organized learning of noisy environmental stimuli requires distinct phases of plasticity.Network neuroscience (Cambridge, Mass.) · 2020Article
- The Interplay of Synaptic Plasticity and Scaling Enables Self-Organized Formation and Allocation of Multiple Memory Representations.Frontiers in neural circuits · 2020Article
- Evaluation and Treatment of Vascular Cognitive Impairment by Transcranial Magnetic Stimulation.Neural plasticity · 2020Review
- The BDNF Val66Met Polymorphism Promotes Changes in the Neuronal Integrity and Alters the Time Perception.Journal of molecular neuroscience : MN · 2019Review
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Part of hippocampal and cortical plasticity is characterized by synaptic modifications that depend on the joint activity of the pre- and post-synaptic neurons. To which extent those changes are determined by the exact timing and the average firing rates is still a matter of debate; this may vary from brain area to brain area, as well as across neuron types. However, it has been robustly observed both in vitro and in vivo that plasticity itself slowly adapts as a function of the dynamical context, a phenomena commonly referred to as metaplasticity. An alternative concept considers the regulation of groups of synapses with an objective at the neuronal level, for example, maintaining a given average firing rate. In that case, the change in the strength of a particular synapse of the group (e.g., due to Hebbian learning) affects others' strengths, which has been coined as heterosynaptic plasticity. Classically, Hebbian synaptic plasticity is paired in neuron network models with such mechanisms in order to stabilize the activity and/or the weight structure. Here, we present an oriented review that brings together various concepts from heterosynaptic plasticity to metaplasticity, and show how they interact with Hebbian-type learning. We focus on approaches that are nowadays used to incorporate those mechanisms to state-of-the-art models of spiking plasticity inspired by experimental observations in the hippocampus and cortex. Making the point that metaplasticity is an ubiquitous mechanism acting on top of classical Hebbian learning and promoting the stability of neural function over multiple timescales, we stress the need for incorporating it as a key element in the framework of plasticity models. Bridging theoretical and experimental results suggests a more functional role for metaplasticity mechanisms than simply stabilizing neural activity.
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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.