In neuroscience and computer science, synaptic weight refers to the strength or amplitude of a connection between two nodes, corresponding in biology...

In neuroscience, synaptic plasticity is the ability of synapses to strengthen or weaken over time, in response to increases or decreases in their activity...

synaptic efficacy arises from a presynaptic cell's repeated and persistent stimulation of a postsynaptic cell. It is an attempt to explain synaptic plasticity...

postsynaptic potentials at neural dendrites, or activation, its weights are analogous to synaptic weight, and its output is analogous to a neuron's action potential...

Synaptic plasticity refers to a chemical synapse's ability to undergo changes in strength. Synaptic plasticity is typically input-specific (i. e. homosynaptic...

are "embedded" into the synaptic weights of the network. Although including the optimization constraints into the synaptic weights in the best possible way...

plasticity mechanisms modify neural synaptic connections selectively, synaptic scaling normalizes all neural synaptic connections by decreasing the strength...

the product of each input and its synaptic weight to the power of p-1, which in the case of p=2 is synaptic weight itself, or y ( x )   =   ∑ j = 1 m...

catastrophic forgetting in spiking neural networks by forming a joint synaptic weight representation". PLOS Computational Biology. 18 (11): e1010628. Bibcode:2022PLSCB...

Bienenstock–Cooper–Munro (BCM) theory, BCM synaptic modification, or the BCM rule, named after Elie Bienenstock, Leon Cooper, and Paul Munro, is a physical...