Short-Term Synaptic Plasticity Stabilizes Goal-Conditioned Dynamics in a PFC-Inspired Reservoir Model for Multistep Goal-Directed Action Planning
2026-06-02 • Neural and Evolutionary Computing
Neural and Evolutionary Computing
AI summaryⓘ
The authors studied how the brain’s prefrontal cortex keeps goal information ready for action over time. They tested a model that includes short-term synaptic plasticity (STP), which lets connections between neurons change briefly, to see if this helps keep goal info usable. Their results showed that while goal info can be detected without STP, having STP makes the system much more stable and reliable, especially when there’s noise or distraction. The authors conclude that STP helps maintain goal-related brain activity by adjusting neuron connections dynamically during the delay before action.
prefrontal cortexshort-term synaptic plasticityreservoir computinggoal-directed behaviortemporal-difference learningeffective connectivityneural dynamicsaction planningstate noisefacilitation time constants
Authors
Jin Nakamura, Yuichi Katori
Abstract
The prefrontal cortex (PFC) maintains goal information for action planning, but how recurrent circuits preserve it in an action-usable form over behavioral timescales remains unclear. Here we ask whether short-term synaptic plasticity (STP) can stabilize goal information as action-usable, goal-conditioned dynamics. We incorporated STP into a PFC-inspired reservoir computing model with basal-ganglia-inspired temporal-difference readout learning, and evaluated paired models with and without STP across 100 independently generated networks in a multistep goal-directed action-selection task with delayed execution. Goal identity was highly decodable during the delay even without STP, so STP was not required to form a linearly readable goal representation. Under state noise, however, success without STP fell from 75.8% to 49.5%, whereas the model with STP remained essentially unchanged (91.8% without noise versus 89.2% under noise; paired Cohen's dz=1.31). Time-resolved decoding, state-space separability, and action-value-difference analyses showed that STP preserved goal information as action-relevant goal-conditioned dynamics available at later action opportunities. Gain-matched and STP-state perturbation controls argued against a simple fixed recurrent-scaling explanation and supported online, history-dependent synaptic modulation. Effective-connectivity analyses showed delay-period goal-specific patterning that increased toward the later part of the trial with STP, where it should be read as goal- and task-state-conditioned patterning; effective connectivity without STP was time-invariant. A grid search identified a facilitation-dominant range of STP time constants associated with high success rates. These results suggest that STP supports robust goal-conditioned dynamics through dynamic modulation of goal-dependent effective recurrent connectivity.