Synapse models

Synapse models are mathematical or conceptual representations of the connections between neurons in the brain or artificial neural networks. They describe how signals (electrical or data) pass from one neuron to another, including how strong the connection is and how it changes over time. These models help us understand learning, memory, and processing by simulating synaptic behavior—like strengthening or weakening connections based on activity—mirroring how actual biological synapses work or enabling efficient machine learning algorithms.