Neural facilitation, also known as paired-pulse facilitation (PPF), is a phenomenon in neuroscience in which postsynaptic potentials (PSPs) (EPPs, EPSPs or IPSPs) evoked by an impulse are increased when that impulse closely follows a prior impulse. PPF is thus a form of short-term synaptic plasticity. The mechanisms underlying neural facilitation are exclusively pre-synaptic; broadly speaking, PPF arises due to increased presynaptic Ca2+ concentration leading to a greater release of neurotransmitter-containing synaptic vesicles.[1] Neural facilitation may be involved in several neuronal tasks, including simple learning, information processing,[2] and sound-source localization.[3]
^Zucker, Robert S.; Regehr, Wade G. (2002). "Short-Term Synaptic Plasticity". Annu. Rev. Physiol. 64: 355–405. doi:10.1146/annurev.physiol.64.092501.114547. PMID 11826273. S2CID 7980969.
^Fortune, Eric S.; Rose, Gary J. (2001). "Short-term synaptic plasticity as a temporal filter". Trends in Neurosciences. 24 (7): 381–5. doi:10.1016/s0166-2236(00)01835-x. PMID 11410267. S2CID 14642561.
Neuralfacilitation, also known as paired-pulse facilitation (PPF), is a phenomenon in neuroscience in which postsynaptic potentials (PSPs) (EPPs, EPSPs...
Look up facilitation or facilitator in Wiktionary, the free dictionary. Facilitation may refer to: Facilitation (organisational), the designing and running...
observed it has been speculated that it changes to facilitation in adult brains. An example of a neural circuit is the trisynaptic circuit in the hippocampus...
Deep learning is the subset of machine learning methods based on neural networks with representation learning. The adjective "deep" refers to the use of...
neuralfacilitation rather than by probability summation. These effects can be ascribed to the convergence of tactile and visual inputs onto neural centers...
Neural oscillations, or brainwaves, are rhythmic or repetitive patterns of neural activity in the central nervous system. Neural tissue can generate oscillatory...
A residual neural network (also referred to as a residual network or ResNet) is a seminal deep learning model in which the weight layers learn residual...
replace, or enhance neural systems. Neural engineers are uniquely qualified to solve design problems at the interface of living neural tissue and non-living...
scales over which it acts synaptic enhancement is classified as neuralfacilitation, synaptic augmentation or post-tetanic potentiation. Synaptic fatigue...
A neural radiance field (NeRF) is a method based on deep learning for reconstructing a three-dimensional representation of a scene from sparse two-dimensional...
An AI accelerator, deep learning processor, or neural processing unit (NPU) is a class of specialized hardware accelerator or computer system designed...
many types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used...
Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks. Their creation was inspired by neural circuitry...
Nervous tissue, also called neural tissue, is the main tissue component of the nervous system. The nervous system regulates and controls body functions...
Brain implants, often referred to as neural implants, are technological devices that connect directly to a biological subject's brain – usually placed...
created by Google engineer Alexander Mordvintsev that uses a convolutional neural network to find and enhance patterns in images via algorithmic pareidolia...
repeated stimuli. Another possible explanation of facilitation is synaptic potentiation within an attractor neural network model where repetition decreases the...
and experience-induced facilitation of sexual performance. Animals with DeltaFosB overexpression displayed enhanced facilitation of sexual performance...
Neuroprosthetics (also called neural prosthetics) is a discipline related to neuroscience and biomedical engineering concerned with developing neural prostheses. They...
of nervous system cells (or cultured neurons) involved in a particular neural computation. The concept of neuronal ensemble dates back to the work of...
gradient problem, thus leading to easier to optimize neural networks. The gating mechanisms facilitate information flow across many layers ("information...
Gemini is also multimodal. A Boltzmann machine is a type of stochastic neural network invented by Geoffrey Hinton and Terry Sejnowski in 1985. Boltzmann...