Reconfigurations of cortical manifold structure during reward-based motor learning

Adaptive motor behavior depends on the coordinated activity of multiple neural systems distributed across the brain. While the role of sensorimotor cortex in motor learning has been well-established, how higher-order brain systems interact with sensorimotor cortex to guide learning is less well understood. Using functional MRI, we examined human brain activity during a reward-based motor task where subjects learned to shape their hand trajectories through reinforcement feedback. We projected patterns of cortical and striatal functional connectivity onto a low-dimensional manifold space and examined how regions expanded and contracted along the manifold during learning. During early learning, we found that several sensorimotor areas in the Dorsal Attention Network exhibited increased covariance with areas of the salience/ventral attention network and reduced covariance with areas of the default mode network (DMN). During late learning, these effects reversed, with sensorimotor areas now ..., Description of the reward-based motor learning task
In this task, subjects (N=36) used their right finger on an MRI-compatible touchpad to trace, without visual feedback of their finger, a rightward-curved path displayed on a screen (see Fig. 1A,B in the paper). Participants began the MRI study by performing a *Baseline *block of 70 trials, wherein they did not receive any feedback about their performance. Following this, subjects began a separate *Learning *block of 200 trials in which they were told that they would now receive score feedback (from 0 to 100 points), presented at the end of each trial, based on how accurately they traced the visual path displayed on the screen. However, unbeknownst to subjects, the score they actually received was based on how well they traced a *hidden *mirror-image path (the ‘reward’ path, which was reflected across the vertical axis; see Fig. 1C in the paper). Importantly, because subjects received no visual feedback about their actual finger traject..., , # Reconfigurations of cortical manifold structure during reward-based motor learning

[https://doi.org/10.5061/dryad.7sqv9s512](https://doi.org/10.5061/dryad.7sqv9s512)

Welcome to the data repository for the paper by Nick et al., (2024), published in eLife. This repository contains the behavioural and preprocessed fMRI timeseries data used in the paper.

## Description of the data and file structure

There are two main sets of data files included in this repository:

**(1) fMRI Timeseries data.**

This includes a .csv file for each task epoch (Baseline, Early and Late learning) and each subject (N=36). E.g., the file \"ts_1_baseline.csv\" includes the timeseries data for subject # 1 for 1000 Schaefer cortical brain regions and 14 subcortical regions from the Harvard-Oxford parcellation (left and right Thalamus, Putamen, Pallidum, Hippocampus, Amygdala, Accumbens). Each timeseries is 216 imaging volumes long (see Methods details above) and the column headers denote the name of individual ...