The code provided models a form of synaptic plasticity known as Spike-Timing-Dependent Plasticity (STDP). STDP is a well-described neurobiological mechanism that alters the strength of synapses based on the precise timing of spikes between pre-synaptic and post-synaptic neurons. This dynamic process allows neurons to adjust synaptic weights, promoting learning and memory formation within neural networks. Here are the key biological aspects modeled in the code:
STDP Mechanism: The code is structured to simulate STDP by adjusting synaptic weights based on the timing difference between pre- and post-synaptic spikes. The code calculates separate traces for pre-synaptic and post-synaptic activities (denoted by conv1_pre and conv1_post, respectively) and uses these to compute the synaptic weight changes (W).
Hebbian Learning: The core principle of STDP mirrors Hebbian learning theories, often summarized as "cells that fire together, wire together." If a pre-synaptic spike precedes a post-synaptic spike within a certain time window, the synaptic strength increases (LTP - Long-Term Potentiation); if the order is reversed, the strength decreases (LTD - Long-Term Depression).
Time Constants: The parameters tau_plus and tau_minus represent time constants for the decay of pre- and post-synaptic traces. These constants model the rate at which synaptic influences wane over time, capturing the temporal dynamics of synaptic interactions.
A+, A- parameters: These represent the amplitudes for the modification of the synaptic strengths due to STDP. A_plus is applied when the pre neuron spikes shortly before the post neuron, and A_minus is applied when the post neuron spikes shortly before the pre neuron.
Trace and Tot_conv: The code uses an eligibility trace (trace) to modulate synaptic changes in response to neuronal activity, reflecting the concept that not all spike events can immediately alter synapse strengths. The eligibility trace is shaped by the spikes and weighted changes (W), emphasizing that relevant plasticity effects are contingent on concurrent neuronal activity and previous synaptic changes.
Biological Interpretation: The concept of eligibility traces is analogous to real neural mechanisms where internal biochemical signals bridge the gap between activity patterns and synaptic modification, resulting in potent learning effects only under suitable conditions, such as neuromodulator presence.
Overall, this code embodies neuroscientific principles encapsulating how dynamic synaptic strengths, influenced by the precise timing of neuronal spikes, contribute to the plastic architecture of neural circuitry, ultimately supporting learning and adaptive behavior.