Neuronal plasticity is defined as the ability of neuronal systems to modify their connection strength and structure through adjustments at the molecular, cellular, and network levels to enable functional changes.
Synaptic plasticity, particularly long-term potentiation (LTP) and long-term depression (LTD), represents a biochemically mediated modulation of synaptic efficacy induced by Ca2+-dependent signaling pathways in the postsynaptic neuron.
Structural plasticity includes dendritic growth processes, synaptogenesis, and pruning, which adjust neuronal connectivity in the long term.
Formally, synaptic weight adjustment can be described by Hebbian learning rules, where the synaptic strength \( w_{ij} \) between neurons \( i \) and \( j \) is changed as a function of simultaneous activity:
\[ \Delta w_{ij} = \eta \cdot a_i \cdot a_j \]
where \( \eta \) is the learning rate and \( a_i, a_j \) are the activations of the neurons.
Neuronal plasticity is fundamental for cognitive functions and is intensively studied in neuroscience and AI research.
Definition:
“Neuronal plasticity is the ability of the nervous system to adapt its structure and function through activity-dependent changes to enable learning, memory, and adaptation.”
Source:
Citri, A., & Malenka, R. C. (2008). Synaptic Plasticity: Multiple Forms, Functions, and Mechanisms. Neuropsychopharmacology, 33(1), 18–41.