DOI: 10.5061/dryad.79cnp5hx8
title: Reward-dependent selection of feedback gains impact rapid motor decisions

description: Target reward influences motor planning strategies through modulation of
 movement vigor. Considering current theories of sensorimotor control
 suggesting that movement planning consists in selecting a goal-directed
 control strategy, we sought to investigate the influence of reward on
 feedback control. Here we explored this question in three human reaching
 experiments. First, we altered the explicit reward associated with the
 goal target and found an overall increase in feedback gains for higher
 target rewards, highlighted by larger velocities, feedback responses to
 external loads, and background muscle activity. Then, we investigated
 whether the differences in target rewards across multiple goals impacted
 rapid motor decisions during movement. We observed idiosyncratic switching
 strategies dependent on both target rewards and, surprisingly, the
 feedback gains at perturbation onset: the more vigorous movements were
 less likely to switch to a new goal following perturbations. To gain
 further insight into a causal influence of the feedback gains on rapid
 motor decisions, we demonstrated that biasing the baseline activity and
 reflex gains by means of a background load evoked a larger proportion of
 target switches in the direction opposite to the background load
 associated with lower muscle activity. Together, our results demonstrate
 an impact of target reward on feedback control and highlight the
 competition between movement vigor and flexibility.
description: This dataset was collected on a Kinarm end-point robot. EMG data
 were collected with Delsys surface EMGs. More details about the methods
 and the experimental paradigms are detailed in the manuscript.
   Kinematics data were sampled at 1kHz and
 low-pass filtered (4th order butterworth, double pass) with a cutoff
 frequency of 20Hz. EMG data were sampled at 1kHz and
 band-pass filtered (4th order butterworth, double pass) with cutoff
 frequencies of 20-250Hz. EMG data were normalized for each participant to
 the average activity collected when they maintained postural control
 against a constant force of 9N at the starting position.
description: Datasets structure : DSExpe1.mat
 - Contains 14 fields (one for each participant) each composed
 of     - "id" : anonymised subject
 identifier     - "matrix_timing" : Timing of
 the triggered events     - "array_timing" :
 Name of the triggered events     -
 "vector_TP" : Type of trials     -
 "matrix_kinematics" : Individual kinematics (position and
 velocity of the end point)     - "matrix_EMG"
 : Individual EMG data (along the third dimension, 1st and 2nd entries are
 for Pectoralis Major and Posterior Deltoid)     -
 "mean_kine" : Individual mean kinematics trace
     - "std_kine": Individual standard deviation of the
 kinematics     - "time_matrix": Individual
 time vector     -"mean_EMG": Individual mean
 EMG trace     -"std_EMG": Individual standard
 deviation of the EMG  
 DSExpe2.mat -Contains 20 fields (one for each
 participant) see DSExpe1.mat for the different fields
 DSExpe3.mat -Contains 19 fields (one for each
 participant) see DSExpe1.mat for the different fields