Neuronal plasticity refers to the ability of neural networks to change their structure and function in response to internal or external stimuli.
This includes synaptic plasticity, i.e., changes in the strength of synapses, and structural plasticity, where new connections are formed or existing ones are lost.
Long-term potentiation (LTP) and long-term depression (LTD) are central mechanisms that mediate synaptic plasticity and increase or decrease the efficiency of signal transmission through repeated activation.
Neuronal plasticity plays a crucial role in learning processes, memory formation, and recovery after brain injuries.
Modern research also investigates plasticity in artificial neural networks to develop more adaptive AI systems.