10.5061/DRYAD.VDNCJSXSW
Blum, Kyle
0000-0002-9760-2053
Northwestern University
Horslen, Brian
University of Waterloo
Campbell, Kenneth
University of Kentucky
Horslen, Brian
University of Waterloo
Nardelli, Paul
Georgia Institute of Technology
Housley, Stephen
Georgia Institute of Technology
Cope, Timothy
Georgia Institute of Technology
Ting, Lena
Emory University
Data from: Diverse and complex muscle spindle afferent firing properties
emerge from multiscale muscle mechanics
Dryad
dataset
2020
2020-12-10T00:00:00Z
2020-12-10T00:00:00Z
en
2304683834 bytes
2
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Despite decades of research, we lack a mechanistic framework capable of
predicting how movement-related signals are transformed into the diversity
of muscle spindle afferent firing patterns observed experimentally,
particularly in naturalistic behaviors. Here, a biophysical model
demonstrates that well-known firing characteristics of mammalian muscle
spindle Ia afferents – including movement history dependence, and
nonlinear scaling with muscle stretch velocity – emerge from first
principles of muscle contractile mechanics. Further, mechanical
interactions of the muscle spindle with muscle-tendon dynamics reveal how
motor commands to the muscle (alpha drive) versus muscle spindle (gamma
drive) can cause highly variable and complex activity during active muscle
contraction and muscle stretch that defy simple explanation. Depending on
the neuromechanical conditions, the muscle spindle model output appears to
“encode” aspects of muscle force, yank, length, stiffness, velocity,
and/or acceleration, providing an extendable, multiscale, biophysical
framework for understanding and predicting proprioceptive sensory signals
in health and disease.