ArticleJournal of neurophysiology2010
The h current is a candidate mechanism for regulating the sliding modification threshold in a BCM-like synaptic learning rule.
Article in Journal of neurophysiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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Who cites it
59 citing papers in PubMed.
- Reopening Motor Learning Windows: Targeted Re-Engagement of Latent Pathways via Non-Invasive Neuromodulation.Life (Basel, Switzerland) · 2026Review
- Resonant hierarchies: a multiscale framework for oscillatory dynamics in the brain.Frontiers in psychology · 2026Article
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- Intrinsic calcium resonance and its modulation: insights from computational modeling.Frontiers in computational neuroscience · 2025Article
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- Astrocytes enhance plasticity response during reversal learning.Communications biology · 2024Article
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- Alteration of hyperpolarization-activated cation current-mediated metaplasticity contributes to electroconvulsive shock-induced learning and memory impairment in depressed rats.Frontiers in psychiatry · 2024Article
- Ion-channel degeneracy and heterogeneities in the emergence of complex spike bursts in CA3 pyramidal neurons.The Journal of physiology · 2023Article
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- Heterogeneous off-target impact of ion-channel deletion on intrinsic properties of hippocampal model neurons that self-regulate calcium.Frontiers in cellular neuroscience · 2023Article
- Synergies between synaptic and HCN channel plasticity dictates firing rate homeostasis and mutual information transfer in hippocampal model neuron.Frontiers in cellular neuroscience · 2023Article
- Dominant role of adult neurogenesis-induced structural heterogeneities in driving plasticity heterogeneity in dentate gyrus granule cells.Hippocampus · 2022Article
- Conjunctive changes in multiple ion channels mediate activity-dependent intrinsic plasticity in hippocampal granule cells.iScience · 2022Article
- Metaplasticity framework for cross-modal synaptic plasticity in adults.Frontiers in synaptic neuroscience · 2022Review
- Voltage-Gated Ion Channels and the Variability in Information Transfer.Frontiers in cellular neuroscience · 2022Article
- Stable continual learning through structured multiscale plasticity manifolds.Current opinion in neurobiology · 2021Review
- Spatial information transfer in hippocampal place cells depends on trial-to-trial variability, symmetry of place-field firing, and biophysical heterogeneities.Neural networks : the official journal of the International Neural Network Society · 2021Article
- Ion-channel degeneracy: Multiple ion channels heterogeneously regulate intrinsic physiology of rat hippocampal granule cells.Physiological reports · 2021Article
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2 authors.
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Abstract
Hebbian synaptic plasticity acts as a positive feedback mechanism and can destabilize a neuronal network unless concomitant homeostatic processes that counterbalance this instability are activated. Within a Bienenstock-Cooper-Munro (BCM)-like plasticity framework, such compensation is achieved through a modification threshold that slides in an activity-dependent fashion. Although the BCM-like plasticity framework has been a useful formulation to understand synaptic plasticity and metaplasticity, a mechanism for the activity-dependent regulation of this modification threshold has remained an open question. In this simulation study based on CA1 pyramidal cells, we use a modification of the calcium-dependent hypothesis proposed elsewhere and show that a change in the hyperpolarization-activated, nonspecific-cation h current is capable of shifting the modification threshold. Based on the direction of such a shift in relation to changes in the h current, and supported by previous experimental results, we argue that the h current fits the requirements for an activity-dependent regulator of this modification threshold. Additionally, using the same framework, we show that multiple voltage- and ligand-gated ion channels present in a neuronal compartment can regulate the modification threshold through complex interactions among themselves. Our results underscore the heavy mutual interdependence of synaptic and intrinsic properties/plasticity in regulating learning and homeostasis in single neurons and their networks under both physiological and pathological brain states.
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