CLOSED-LOOP PROPRIOCEPTIVE FEEDBACK IN A SPINAL CIRCUIT MODEL OF ALS

Spinal-onset amyotrophic lateral sclerosis (ALS) is characterized by early disruption of inhibitory V1 interneuron synapses within locomotor central pattern generators (CPGs), spinal circuits that generate rhythmic movement. This V1 synaptic loss is followed by inhibitory V1 interneuron dysregulation, then excitatory V2a interneuron dysregulation and ultimately motoneuron loss. Experimental stabilization of V1 synapses restores locomotor function by sparing V1 inhibitory interneurons and motoneurons, and recent work from our lab suggests that such interventions can also spare excitatory V2a interneurons, highlighting circuit-level mechanisms beyond motoneuron degeneration. However, how degeneration of sensorimotor feedback pathways between muscles, interneurons, and motoneurons contributes to circuit failure and shapes the efficacy of therapeutic interventions remains unknown. In this study, we build a computational model of a CPG with proprioceptive feedback provided by muscle models with Hill-type dynamics. The biophysical component is constructed as a pendulum model representing a simplified single hindlimb joint, actuated by antagonist muscles to produce flexion and extension. The muscle models provide proprioceptive feedback that modulates the stretch reflex, a pathway that is known to degenerate during ALS. This study implements stage-dependent degeneration of this feedback pathway in addition to progressive cell and synaptic death to understand the role of feedback in circuit degeneration and the potential impact on treatment. The findings from this work aim to generate testable predictions about how feedback impairment interacts with circuit degeneration and candidate intervention strategies.