In neuroscience, homeostatic plasticity refers to the capacity of neurons to regulate their own excitability relative to network activity. The term homeostatic plasticity derives from two opposing concepts: 'homeostatic' (a product of the Greek words for 'same' and 'state' or 'condition') and plasticity (or 'change'), thus homeostatic plasticity means "staying the same through change".
Homeostatic synaptic plasticity is a means of maintaining the synaptic basis for learning, respiration, and locomotion, in contrast to the Hebbian plasticity associated with learning and memory. Although Hebbian forms of plasticity, such as long-term potentiation and long-term depression occur rapidly, homeostatic plasticity (which relies on protein synthesis) can take hours or days. TNF-α and microRNAs are important mediators of homeostatic synaptic plasticity.
Homeostatic plasticity is thought to balance Hebbian plasticity by modulating the activity of the synapse or the properties of ion channels. Homeostatic plasticity in neocortical circuits has been studied in depth by Gina G. Turrigiano and Sacha Nelson of Brandeis University, who first observed compensatory changes in excitatory postsynaptic currents (mEPSCs) after chronic activity manipulations.
Synaptic scaling has been proposed as a potential mechanism of homeostatic plasticity. Homeostatic plasticity can be used to describe a process that maintains the stability of neuronal functions through a coordinated plasticity among subcellular compartments, such as the synapses versus the neurons and the cell bodies versus the axons. Recently, it was proposed that homeostatic synaptic scaling may play a role in establishing the specificity of an associative memory.
Homeostatic plasticity also maintains neuronal excitability in a real-time manner through the coordinated plasticity of threshold and refractory period at voltage-gated sodium channels.
Homeostatic plasticity is also very important in the context of central pattern generators.
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La plasticité synaptique, en neurosciences, désigne la capacité des synapses à moduler, à la suite d'un événement particulier - une augmentation ou une diminution ponctuelle et significative de leur activité - l'efficacité de la transmission du signal électrique d'un neurone à l'autre et à conserver, à plus ou moins long terme, une "trace" de cette modulation. De manière schématique, l'efficacité de la transmission synaptique, voire la synapse elle-même, est maintenue et modulée par l'usage qui en est fait.
In neuroscience, homeostatic plasticity refers to the capacity of neurons to regulate their own excitability relative to network activity. The term homeostatic plasticity derives from two opposing concepts: 'homeostatic' (a product of the Greek words for 'same' and 'state' or 'condition') and plasticity (or 'change'), thus homeostatic plasticity means "staying the same through change". Homeostatic synaptic plasticity is a means of maintaining the synaptic basis for learning, respiration, and locomotion, in contrast to the Hebbian plasticity associated with learning and memory.
vignette|Effets schématiques de la neuroplasticité après entraînement Plasticité neuronale, neuroplasticité ou encore plasticité cérébrale sont des termes génériques qui décrivent les mécanismes par lesquels le cerveau est capable de se modifier lors des processus de neurogenèse dès la phase embryonnaire ou lors d'apprentissages. Elle s’exprime par la capacité du cerveau de créer, défaire ou réorganiser les réseaux de neurones et les connexions de ces neurones. Le cerveau est ainsi qualifié de « plastique » ou de « malléable ».
The course introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies with a focus on the biophysical level.
In this course we study mathematical models of neurons and neuronal networks in the context of biology and establish links to models of cognition. The focus is on brain dynamics approximated by determ
The goal of the course is to increase students' knowledge in the field of Neuroscience, with a particular emphasis on neuronal circuits responsible for sensation, motor control and sensorimotor intera
This course explains the mathematical and computational models that are used in the field of theoretical neuroscience to analyze the collective dynamics of thousands of interacting neurons.
Explore comment les mécanismes de plasticité synaptique conduisent à des neurones étroitement interconnectés et comment les formes des neurones influencent les tendances de la micro-connectivité.
Homeostatic plasticity of intrinsic excitability goes hand in hand with homeostatic plasticity of synaptic transmission. However, the mechanisms linking the two forms of homeostatic regulation have no