Computational models of spinal sensorimotor pathways under epidural electrical stimulation

Spinal cord injury (SCI) disrupts neuromuscular control, leading to motor impairments such as spasticity and abnormal reflex modulation, posing significant challenges for rehabilitation. This thesis presents a computational modeling framework, developed through a systematic reimplementation and refinement of existing methodologies described in literature, which integrates biomechanical modeling, spiking neural networks, and muscle activation dynamics to investigate spinal sensorimotor pathways and neuromuscular function. The core modeling approach involves the integration of a musculoskeletal model, responsible for generating movement and estimating sensory feedback, a spiking neural network, simulating spinal circuits that regulate motor output, and muscle activation dynamics modeling. This framework enables the study of afferent-driven motoneuron activation, proprioceptive feedback mechanisms, and neuromuscular dynamics under both physiological and pathological conditions, such as spasticity and clonus. Additionally, it serves as a promising tool for investigating neuromuscular function and rehabilitation, with the potential to integrate EES simulations and explore its modulation of spinal circuits and motor control, advancing neuromechanical research and neuromodulation-based interventions for SCI rehabilitation.

Publication Details

Journal
Electronic Theses and Dissertations Repository (University of Pisa)
Published
2025-04-03
Primary Topic
Magnetic confinement fusion research
Type
article
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article

Computational models of spinal sensorimotor pathways under epidural electrical stimulation

Electronic Theses and Dissertations Repository (University of Pisa)
Magnetic confinement fusion research
article

Computational models of spinal sensorimotor pathways under epidural electrical stimulation

article en

Abstract

Spinal cord injury (SCI) disrupts neuromuscular control, leading to motor impairments such as spasticity and abnormal reflex modulation, posing significant challenges for rehabilitation. This thesis presents a computational modeling framework, developed through a systematic reimplementation and refinement of existing methodologies described in literature, which integrates biomechanical modeling, spiking neural networks, and muscle activation dynamics to investigate spinal sensorimotor pathways and neuromuscular function. The core modeling approach involves the integration of a musculoskeletal model, responsible for generating movement and estimating sensory feedback, a spiking neural network, simulating spinal circuits that regulate motor output, and muscle activation dynamics modeling. This framework enables the study of afferent-driven motoneuron activation, proprioceptive feedback mechanisms, and neuromuscular dynamics under both physiological and pathological conditions, such as spasticity and clonus. Additionally, it serves as a promising tool for investigating neuromuscular function and rehabilitation, with the potential to integrate EES simulations and explore its modulation of spinal circuits and motor control, advancing neuromechanical research and neuromodulation-based interventions for SCI rehabilitation.

Electronic Theses and Dissertations Repository (University of Pisa)
Good health and well-being
Openalex Percentile: Top 71%
Magnetic confinement fusion research
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