Crucial to controlling movements is our bodies' sense of limb state arising from mechanically gated neurons located within the musculotendon, called proprioceptors. Understanding the mechanical encoding of proprioceptors is critical to understanding their roles in sensorimotor behaviors such as balance control. Proprioceptive loss due to aging, diabetes, as well as chemotherapy-induced peripheral neuropathy (CIPN) and other disorders can increase the risk for falls, which is the leading cause of morbidity and mortality in older adults. Neuromechanical models are essential for predicting the impact of sensory loss on movement because proprioceptors are difficult to access and measure from during actual movements. Here, the goal is to develop a parsimonious model of proprioceptive function appropriate for predictive modeling of sensorimotor control in healthy and neuropathic conditions. Specifically, this work aims to directly test what information is encoded in the instantaneous firing rates and aggregate firing activity of proprioceptors in healthy cat (Specific Aim 1) and in healthy and CIPN rat (Specific Aim 2). Preliminary data suggest that group Ia proprioceptors encode information related to musculotendon kinetics (i.e. passive tension and its first time derivative), but not kinematics (i.e. length and velocity) as previously thought. Usng a combination of previously collected and new datasets with simple musculotendon and spiking neuron model, the proposed work will explicitly test hypotheses about the relationship between firing rates and aggregate activity of group Ia, Ib, and II proprioceptors and musculotendon kinetics in anesthetized cat (healthy) and rat (healthy and neuropathic).

Public Health Relevance

The objective of this study is to gain a deeper understanding of what sensory information is provided to the central nervous system by movement-sensitive neurons in the musculotendon. A more complete understanding of how mechanical information is encoded in neural impulses would provide an explanation for specific changes in neural coding after chemotherapy. This could have multiple clinical applications including improved sensation in neural prostheses, and could help develop treatments for individuals with chemotherapy-induced peripheral neuropathy.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Predoctoral Individual National Research Service Award (F31)
Project #
1F31NS093855-01
Application #
8982884
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Chen, Daofen
Project Start
2015-08-17
Project End
2018-08-16
Budget Start
2015-08-17
Budget End
2016-08-16
Support Year
1
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Georgia Institute of Technology
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
097394084
City
Atlanta
State
GA
Country
United States
Zip Code
30318
Blum, Kyle P; Lamotte D'Incamps, Boris; Zytnicki, Daniel et al. (2017) Force encoding in muscle spindles during stretch of passive muscle. PLoS Comput Biol 13:e1005767