In neuroscience and computer science, synaptic weight refers to the strength or amplitude of a connection between two nodes, corresponding in biology to the amount of influence the firing of one neuron has on another.
, or pre- and post-synaptic neurons respectively, are interconnected with synaptic weights represented by the matrix
For biological networks, the effect of synaptic weights is not as simple as for linear neurons or Hebbian learning.
In the mammalian central nervous system, signal transmission is carried out by interconnected networks of nerve cells, or neurons.
For the basic pyramidal neuron, the input signal is carried by the axon, which releases neurotransmitter chemicals into the synapse which is picked up by the dendrites of the next neuron, which can then generate an action potential which is analogous to the output signal in the computational case.