Data from: Tuning of feedforward control enables stable muscle force-length dynamics after loss of autogenic proprioceptive feedback
Daley, Monica A; Gordon, Joanne C; Biewener, Andrew A; Holt, Natalie C (2020), Data from: Tuning of feedforward control enables stable muscle force-length dynamics after loss of autogenic proprioceptive feedback, Dryad, Dataset, https://doi.org/10.7280/D11H49
Animals must integrate feedforward, feedback and intrinsic mechanical control mechanisms to maintain stable locomotion. Recent studies of guinea fowl (Numida meleagris) revealed that the distal leg muscles rapidly modulate force and work output to minimize perturbations in uneven terrain. Here we probe the role of reflexes in the rapid perturbation responses of muscle by studying the effects of proprioceptive loss. We induced bilateral loss of autogenic proprioception in the lateral gastrocnemius muscle (LG) using self-reinnervation. We compared in vivo muscle dynamics and ankle kinematics in birds with reinnervated and intact LG. Reinnervated and intact LG exhibit similar steady state mechanical function and similar work modulation in response to obstacle encounters. Reinnervated LG exhibits 23ms earlier steady-state activation, consistent with feedforward tuning of activation phase to compensate for lost proprioception. Modulation of activity duration is impaired in rLG, confirming the role of reflex feedback in regulating force duration in intact muscle.
See description in associated paper: doi:10.7554/eLife.53908
The file ‘morphologySummaryData.csv’ contains:
Body mass, total gastrocnemius muscle mass, lateral gastrocnemius (LG) muscle mass, LG fascicle length and LG pennation angle for the ‘intact’ and ‘reinnervated’ cohorts of individuals.
The file ‘metaDataTable.csv’ contains:
1) Names of individual data files,
2) ‘Treatment’ condition indicating whether the individual was from the ‘intact’ cohort (Daley and Biewener 2011) or the ‘reinnervated cohort’ (Gordon et al. 2020)
3) Individual number: arbitrary number assigned for individual identification in data processing
4) Speed in ms-1
5) Terrain condition number: 1 indicates level terrain, 5 indicates 5cm obstacle terrain (see methods within papers above).
6) Subject body mass in kg
7) Total gastrocnemius muscle mass
8) Lateral gastrocnemius (LG) fascicle length
9) Lateral gastrocnemius (LG) pennation angle
10) Recording sample frequency
The folders ‘Intact’ and ‘Reinnervated’ each contain three files per trial:
‘fileName.csv’: (File names in metaDataTable.csv, above)
Continuous recordings of muscle data in text format, with the following columns:
1) Time: time in seconds relative to the original video trigger.
2) muscleLength_mm: fascicle length in mm
3) muscleLength_FL: fascicle length as a fraction of rest length
4) velocity_FL: fascicle velocity in lengths per second
5) tendonForceN: muscle-tendon force of gastrocnemius, in Newtons
6) totPower_EMG: total muscle electromyographic intensity calculated by summing across wavelet frequencies that span the physiological range of frequencies for vertebrate skeletal muscle, units mV^2
7) mV_EMG: raw muscle electromyographic signal
‘fileName _Cal.mat’: Contains the structure ‘data’ with the continuous recordings, as above, ‘params’ with the associated trial metadata, and ‘strideInfo’ with stride cycle times. These are provided to allow users to recreate the statistical processing and statistics reported in the paper using the Matlab scripts.
‘fileName _StrideTimesWCats.csv’: Text file containing the data points, time (in seconds from video post-trigger’ for identified strides in the data file, with the stride category in the 3rd column. Level strides are arbitrarily designated the number ‘10’ in these files, which is changed in the Matlab processing scripts to ‘-10’ so that level strides are always first in plots and pairwise comparisons.
The folder ‘matFiles’ contains the Matlab data processing scripts used to generate the main statistical results and findings presented in Gordon et al 2020.
‘InVivoMuscleProcessingScripts_Intact_v_Reinn.m’ is the main script to run the data processing steps and statistical analysis from the data contained within the ‘Intact’ and ‘Reinnervated’ folders. See comments within. To run the script, the user must have a valid Matlab install, include the downloaded functions on Matlabs filepaths, and update the directory location of the intact and reinnervated data folders within this script. Please contact author Monica Daley with any questions about these Matlab files.
The data spreadsheet, 'Gordon_etal_Daley_LG_MuscleData.csv' contains the datafile used for the statistical results presented in the paper.
Grouping variables for statistics are found in the first 4 columns:
Individual ID number ('ind')
Terrain condition ('terrain') 1= level, 5 = terrain with repeated 5cm obstacles
Self-reinnervation treatment ('treatment'): 1 = intact, 2 = self-reinnervated
Stride category ('str_ID') has 5 possible values: -10 = level terrain strides, stride prior to an obstacle contact (-1), obstacle contact strides (0), stride following obstacle contact (+1), and 'mid-flat' strides within the level region between obstacles (S +2). The mid-flat strides are grouped together because there is a variable number of strides between obstacle encounters.
NIH, Award: NIAMS 5R01AR055648
Biotechnology and Biological Sciences Research Council, Award: BB/H005838/1
National Institutes of Health, Award: NIAMS 5R01AR055648