Results 31 to 40 of about 188,649 (338)

Associative properties of structural plasticity based on firing rate homeostasis in recurrent neuronal networks [PDF]

open access: yes, 2017
Correlation-based Hebbian plasticity is thought to shape neuronal connectivity during development and learning, whereas homeostatic plasticity would stabilize network activity. Here we investigate another, new aspect of this dichotomy: Can Hebbian associative properties also emerge as a network effect from a plasticity rule based on homeostatic ...
arxiv   +1 more source

Neuronal Plasticity and Function

open access: yesClinical Neuropharmacology, 1993
Neuronal plasticity is a key issue in neuroscience. It is defined as the capability of the neuron to adapt to a changing internal or external environment, to previous experience or to trauma. It appears that during all phases of the individual life span in the nervous system, changes take place that relate to development, degeneration, and regeneration.
openaire   +4 more sources

Soluble Ectodomain of Neuroligin 1 Decreases Synaptic Activity by Activating Metabotropic Glutamate Receptor 2

open access: yesFrontiers in Molecular Neuroscience, 2017
Synaptic cell adhesion molecules represent important targets for neuronal activity-dependent proteolysis. Postsynaptic neuroligins (NLs) form trans-synaptic complexes with presynaptic neurexins (NXs). Both NXs and NLs are cleaved from the cell surface by
Michelle D. Gjørlund   +9 more
doaj   +1 more source

Astrocytes: orchestrating synaptic plasticity? [PDF]

open access: yes, 2015
Synaptic plasticity is the capacity of a preexisting connection between two neurons to change in strength as a function of neural activity. Because synaptic plasticity is the major candidate mechanism for learning and memory, the elucidation of its constituting mechanisms is of crucial importance in many aspects of normal and pathological brain ...
arxiv   +1 more source

Neuron–glia metabolic coupling and plasticity [PDF]

open access: yesJournal of Experimental Biology, 2006
SUMMARY The coupling between synaptic activity and glucose utilization(neurometabolic coupling) is a central physiological principle of brain function that has provided the basis for 2-deoxyglucose-based functional imaging with positron emission tomography (PET).
openaire   +9 more sources

Serum Amyloid A1/Toll-Like Receptor-4 Axis, an Important Link between Inflammation and Outcome of TBI Patients

open access: yesBiomedicines, 2021
Traumatic brain injury (TBI) is one of the leading causes of mortality and disability worldwide without any validated biomarker or set of biomarkers to help the diagnosis and evaluation of the evolution/prognosis of TBI patients.
Víctor Farré-Alins   +20 more
doaj   +1 more source

Dis-inhibitory neuronal circuits can control the sign of synaptic plasticity [PDF]

open access: yesarXiv, 2023
How neuronal circuits achieve credit assignment remains a central unsolved question in systems neuroscience. Various studies have suggested plausible solutions for back-propagating error signals through multi-layer networks. These purely functionally motivated models assume distinct neuronal compartments to represent local error signals that determine ...
arxiv  

THE FUNDAMENTS OF NEURONAL PLASTICITY

open access: yesAnnals of the Russian academy of medical sciences, 2012
 Plasticity of the nervous system  is determined by the modification of efficacy of synaptic transmission: long- term potentiation and long- term depression. Different modern technical approaches such as: registration of ionic currents in single neuron, molecular- genetic analysis, neurovisualization, and others reveal the molecular mechanisms of ...
M. B. Shtark, V. G. Skrebitskii
openaire   +3 more sources

Foldscope as an Innovative Teaching Tool

open access: yesEducation Sciences, 2022
This study deals with the descriptive analysis of the opinion of a pilot group of students at the University of Salamanca about the use of an innovative origami microscope: the Foldscope.
Carlos Hernández-Pérez   +1 more
doaj   +1 more source

A Spiking Neuron Synaptic Plasticity Model Optimized for Unsupervised Learning [PDF]

open access: yesarXiv, 2021
Spiking neural networks (SNN) are considered as a perspective basis for performing all kinds of learning tasks - unsupervised, supervised and reinforcement learning. Learning in SNN is implemented through synaptic plasticity - the rules which determine dynamics of synaptic weights depending usually on activity of the pre- and post-synaptic neurons ...
arxiv  

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