Internal KCN - Functional electrical stimulation-therapy

Modeling Long-term Plasticity for Optimizing Functional Electrical Stimulation-Therapy 

Michael Howard, Kei Masani, Milad Lankarany 

Abstract: 

Functional Electrical Stimulation (FES)-therapy is a rehabilitation technology that restores motor function and improves quality of life in individuals with neurological impairments, by applying FES to target muscles during voluntary contraction. Tuning FES parameters significantly impacts clinical outcomes; however, traditional Hebbian plasticity frameworks fail to capture the nuanced and heterogeneous spiking dynamics of FES-therapy, limiting their utility in modeling and optimization. To address this, we developed a computational model of activity-dependent plasticity tailored to FES-therapy, incorporating voltage-dependent synaptic dynamics and high-order spiking interactions to simulate long-term potentiation (LTP) and long-term depression (LTD) during FES. Unlike previous models, ours replicates complex spiking protocols. 

Using this model, we evaluated synaptic weight distributions and plasticity outcomes under varied stimulation protocols, to show how parameters—such as FES frequency, heterogeneity, and timing—affect the balance of LTP and LTD. 

Our model integrates stimulation heterogeneity, demonstrating a relationship between interspike interval (ISI) variability and plasticity outcomes. Our findings show that ISI heterogeneity significantly influences synaptic weight distributions and plasticity. Reducing ISI heterogeneity biases the system towards LTD, suggesting a novel path for targeted synaptic weakening in rehabilitation protocols. 

Our work provides a platform to study plasticity in FES-therapy, paving the way for improved FES design and clinical translation.