Results 1 to 10 of about 8,597 (225)

Synaptic metaplasticity underlies tetanic potentiation in Lymnaea: a novel paradigm [PDF]

open access: yesPLoS ONE 8(10): e78056 (2013), 2013
We present a mathematical model which explains and interprets a novel form of short-term potentiation, which was found to be use-, but not time-dependent, in experiments done on Lymnaea neurons.
Luck, Jean-Marc   +3 more
core   +4 more sources

Effects of TrkB-related induced metaplasticity within the BLA on anxiety, extinction learning, and plasticity in BLA-modulated brain regions [PDF]

open access: yesBehavioral and Brain Functions
Background Neuronal plasticity within the basolateral amygdala (BLA) is fundamental for fear learning. Metaplasticity, the regulation of plasticity states, has emerged as a key mechanism mediating the subsequent impact of emotional and stressful ...
Joyeeta Dutta Hazra   +10 more
doaj   +2 more sources

Synaptic Variability Introduces State-Dependent Modulation of Excitatory Spinal Cord Synapses [PDF]

open access: yesNeural Plasticity, 2015
The relevance of neuronal and synaptic variability remains unclear. Cellular and synaptic plasticity and neuromodulation are also variable. This could reflect state-dependent effects caused by the variable initial cellular or synaptic properties or ...
Parker, David
core   +4 more sources

Multiple forms of metaplasticity at a single hippocampal synapse during late postnatal development [PDF]

open access: yesDevelopmental Cognitive Neuroscience, 2015
Metaplasticity refers to adjustment in the requirements for induction of synaptic plasticity based on the prior history of activity. Numerous forms of developmental metaplasticity are observed at Schaffer collateral synapses in the rat hippocampus at the
Dumas, Theodore C., McHail, Daniel G.
core   +4 more sources

Synaptic metaplasticity with multi-level memristive devices [PDF]

open access: yes, 2023
Deep learning has made remarkable progress in various tasks, surpassing human performance in some cases. However, one drawback of neural networks is catastrophic forgetting, where a network trained on one task forgets the solution when learning a new one.
Arcamone, J   +7 more
core   +2 more sources

Regulation of hippocampal synaptic plasticity thresholds and changes in exploratory and learning behavior in dominant negative NPR-B mutant rats [PDF]

open access: yesFrontiers in Molecular Neuroscience, 2014
The second messenger cyclic GMP affects synaptic transmission and modulates synaptic plasticity and certain types of learning and memory processes. The impact of the natriuretic peptide receptor B (NPR-B) and its ligand C-type natriuretic peptide (CNP ...
Bader, Michael   +6 more
core   +7 more sources

Probabilistic metaplasticity for continual learning with memristors in spiking networks [PDF]

open access: yesScientific Reports
Edge devices operating in dynamic environments critically need the ability to continually learn without catastrophic forgetting. The strict resource constraints in these devices pose a major challenge to achieve this, as continual learning entails memory
Fatima Tuz Zohora   +3 more
doaj   +2 more sources

Systemic pharmacological suppression of neural activity reverses learning impairment in a mouse model of Fragile X syndrome [PDF]

open access: yeseLife
The enhancement of associative synaptic plasticity often results in impaired rather than enhanced learning. Previously, we proposed that such learning impairments can result from saturation of the plasticity mechanism (Nguyen-Vu et al., 2017), or, more ...
Amin MD Shakhawat   +4 more
doaj   +2 more sources

Pathway-specific TNF-mediated metaplasticity in hippocampal area CA1

open access: yesScientific Reports, 2022
Long-term potentiation (LTP) is regulated in part by metaplasticity, the activity-dependent alterations in neural state that coordinate the direction, amplitude, and persistence of future synaptic plasticity.
Anurag Singh   +3 more
doaj   +1 more source

Synaptic metaplasticity in binarized neural networks [PDF]

open access: yesComputational and Systems Neuroscience (Cosyne) 2021, 2021
Unlike the brain, artificial neural networks, including state-of-the-art deep neural networks for computer vision, are subject to "catastrophic forgetting": they rapidly forget the previous task when trained on a new one. Neuroscience suggests that biological synapses avoid this issue through the process of synaptic consolidation and metaplasticity ...
arxiv   +1 more source

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