Developmental Reinforcement Motor Learning Dataset

Published: 30 June 2025| Version 1 | DOI: 10.17632/g9z67hkyz5.1
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Description

This dataset and code accompanies the eLife publication titled "Age-dependent predictors of effective reinforcement motor learning across childhood" authored by Nayo M. Hill, Haley M. Tripp, Daniel M. Wolpert, Laura A. Malone, and Amy J. Bastian.

Files

Steps to reproduce

As detailed in the Methods section of the associated publication, data for all four tasks were collected using a web-based platform built with Javascript. Participants used a mouse, trackpad, or touchscreen input to control the game object. Movement was sampled at the polling rate of the selected input device and data were uploaded and saved to Google Firebase Realtime Database at the end of each trial. This dataset includes trial by trial endpoint position data from each participant which is used for all metrics reported in the publication. Please consult the Readme.txt file for additional details on utilizing the raw and processed data in this dataset.

Institutions

  • Columbia University
    NY, New York
  • Kennedy Krieger Institute Center for Movement Studies
    MD, Baltimore

Categories

Reinforcement Learning, Child Development, Motor Learning

Funders

Licence