DOI: 10.5061/dryad.70rxwdc6h
title: Surmounting the ceiling effect of motor expertise by novel sensory experience with a hand exoskeleton

description: For trained individuals such as athletes and musicians, learning often
 plateaus after extensive training (i.e., “ceiling effect”). One bottleneck
 to overcome it is no prior physical experience of the skill to be learned.
 Here we challenge this issue through having expert pianists passively
 experience fast and complex finger movements that cannot be performed
 voluntarily, by using a novel hand exoskeleton-robot that can move
 individual fingers fast and independently. Although the skill plateaued
 through weeks of practice, passive exposure to otherwise impossible
 complex finger movements generated by the exoskeleton-robot at a speed
 faster than their fastest one enabled the pianists to play faster. Neither
 a training undergoing fast but simple finger movements nor one undergoing
 slow but complex movements enhanced the overtrained motor skill. Passive
 training with one hand also improved the motor skill of the untrained
 contra-lateral hand, demonstrating the inter-manual transfer effect. The
 training altered patterns of coordinated activities across multiple finger
 muscles during piano playing, but not in general motor and somatosensory
 functions nor in anatomical characteristics of the hand. Patterns of the
 multi-finger movements evoked by transcranial magnetic stimulation over
 the left motor cortex were also changed through passive exposure to fast
 and complex finger movements. The results demonstrate evidence that
 somatosensory exposure to an unexperienced motor skill allows for
 surmounting the ceiling effect in a task-specific but effector-independent
 manner.
description: # Surmounting the ceiling effect of motor expertise by novel sensory
 experience [https://doi.org/10.5061/dryad.70rxwdc6h
 ](https://doi.org/10.5061/dryad.70rxwdc6h) We have submitted our piano
 keystroke data of the experiment 1(**EXO_IKIplot.mat**), piano keystroke
 data before and after five sets of intervention for the experiment 2
 (**IKI_5training_comparison.mat**), tensor decomposition data of the
 finger kinematics of the experiment 3 (**tensordata_righthand.mat**), and
 MATLAB scripts for plotting the keystroke data of the experiment
 1(**plot_ExoIKIdata.m**) and the keystroke data of the experiment 2
 (**plot_ExoIKIdata_after5training.m**). ## Description of the data and
 file structure ### **EXO\_IKIplot.mat** * *Grp_IKI_home*: The average of
 the inter-keystroke interval (sec) across successive piano strikes at five
 different timepoints during the period of practicing at home (i.e. 4 days
 before the day of the intervention and 1 day following it) for each of the
 complex and simple groups (i.e. two training groups). Each group consists
 of fifteen pianists. * *Mean_IKI_value*: The average of the
 inter-keystroke interval (sec) across successive piano strikes at the
 three sessions (i.e. pretest, posttest, and retention) for each of the
 complex and simple groups (i.e. two training groups). Each group consists
 of fifteen pianists. ### **IKI\_5training\_comparison.mat** *
 *AVE_plot_data_MIDI*: The average of the inter-keystroke interval (sec)
 across successive piano strikes with the right hand at the two sessions
 (i.e. pretest and posttest) for five groups undergoing different
 interventions when performing the two different tasks (i.e. complex and
 simple) * *AVE_plot_data_MIDI_L*: The average of the inter-keystroke
 interval (sec) across successive piano strikes with the left hand at the
 two sessions (i.e. pretest and posttest) for five groups undergoing
 different interventions when performing the complex task *
 *SEM_plot_data_MIDI*: The standard error of the inter-keystroke interval
 (sec) across successive piano strikes with the right hand at the two
 sessions (i.e. pretest and posttest) for five groups undergoing different
 interventions when performing the two different tasks (i.e. complex and
 simple) * *SEM_plot_data_MIDI_L*: The standard error of the
 inter-keystroke interval (sec) across successive piano strikes with the
 left hand at the two sessions (i.e. pretest and posttest) for five groups
 undergoing different interventions when performing the complex task ###
 **tensordata\_righthand.mat** * *M1*: a structure variable representing
 the results of the tensor decomposition (a.u.). M1.lambda represents the
 scaling variable, M1.U{1｝and M1.U{2} represents the spatial and temporal
 module, respectively, M1.U{3｝represents the session component. * *X*: a
 structure variable of the input data to the tensor decomposition (a.u.).
 The dimension 1, 2, and 3 represents the joint of the hand, timepoints,
 and stimulus of the transcranial magnetic stimulation, respectively. *
 *maxVAF*: Variance accounted for by the five tensors (%) * *SR*: the
 sampling rate of the data-glove (Hz) * *dataLength*: the number of the
 sampled data for each stimulus (a.u.) * *numTensor*: the number of tensors
 (a.u.) * *myData_size*: the number of data used for each analysis (a.u.).
 The dimension 1, 2, and 3 represents the hand (right, left), session
 (pretest, posttest), and participant (28 pianists), respectively. *
 *hand*: the number 1 represents the right hand. * *count*: the number of
 the total participants + 1 * *contribution*: The average value of the
 M1.U{3} for each participant (a.u.). The dimension 1, 2, and 3 represents
 the tensor (five tensors), session (pretest, posttest), and participant
 (28 pianists). * *IKI*：The averaged inter-keystroke interval at the two
 sessions (pretest and posttest) for all twenty-eight participants
 (millisecond). ## Code/Software MATLAB is required to run
 *plot_ExoIKIdata.m* and *plot_ExoIKIdata_after5training.m*; the script was
 created using version R2020a. Annotations are provided throughout the
 script through 1) dataset loading, 2) analyses, and 3) figure creation.