Calcium-based input timing learning

Stimulus-triggered synaptic plasticity is the foundation of learning and crucial cognitive abilities. Although numerous computational models have investigated plasticity within networks of point neurons, dendritic integration provides superior computational capacity compared to these simplistic models, highlighting the significance of dendrites and their spines—small, specialized protrusions that serve as loci for synaptic plasticity. Synaptic plasticity can be categorized into two forms: homosynaptic plasticity, involving changes at directly stimulated synapses, and heterosynaptic plasticity, involving changes at non-stimulated synapses. For homosynaptic plasticity, the Ca ²⁺ -hypothesis identifies the calcium concentration within a stimulated dendritic spine as the key mediator. In contrast, although theoretical studies attribute important roles such as synaptic competition and cooperation to heterosynaptic plasticity, experimental evidence remains ambiguous. By integrating insights from Ca ²⁺ -dependent homosynaptic plasticity with data on dendritic Ca ²⁺ -dynamics, we demonstrate that calcium influx into a stimulated spine can diffuse to neighboring spines, triggering heterosynaptic effects. To investigate this, we developed a mathematical model characterizing the temporal and spatial dynamics of calcium in dendrites in response to different inputs. Our model explains experimental ambiguities and extends the Ca ²⁺ -hypothesis to heterosynaptic plasticity. Notably, it predicts input-timing, distance between spines, and local diffusion properties modulate synaptic changes, revealing a novel mechanism for dendritic computation.