Acetylcholine-modulated plasticity in reward-driven navigation: a computational study

TL;DR

This study explores how acetylcholine influences synaptic plasticity and navigation learning, showing that neuromodulation enables flexible, reward-driven behavior adaptation in computational models.

Contribution

It introduces a sequential neuromodulation rule for STDP, demonstrating its effectiveness in flexible learning and exploration in navigation tasks.

Findings

Acetylcholine biases hippocampal plasticity towards depression.

Dopamine can convert depression into potentiation retroactively.

Sequential neuromodulated STDP outperforms other plasticity rules in learning efficiency.

Abstract

Neuromodulation plays a fundamental role in the acquisition of new behaviours. Our experimental findings show that, whereas acetylcholine biases hippocampal synaptic plasticity towards depression, the subsequent application of dopamine can retroactively convert depression into potentiation. We previously demonstrated that incorporating this sequentially neuromodulated Spike-Timing-Dependent Plasticity (STDP) rule in a network model of navigation yields effective learning of changing reward locations. Here, we further characterize the effects of cholinergic depression on behaviour. We find that acetylcholine, by allowing learning from negative outcomes, influences exploration in a non-trivial manner that highly depends on the specifics of the model, the environment and the task. Interestingly, sequentially neuromodulated STDP also yields flexible learning, surpassing the performance of other reward-modulated plasticity rules.