Movement Enhances Tactile Sensitivity Through Prediction

This repository contains the behavioral data and analysis outputs for the manuscript“Action Refines Tactile Sensitivity Through Prediction” (D’Onofrio Pacheco & Zimmermann, Heinrich-Heine University Düsseldorf). All data are organized in two main folders corresponding to the two experiments. Experiment 1/1. CSV_Participant/ Contains the raw data for each participant in Experiment 1.Each participant has an individual subfolder with the following conditions: Active/ – trials recorded during self-generated movements. Passive/ – trials recorded during externally driven movements. Control/ – trials recorded at rest (no movement). 2. PSE_and_JND/ Contains the fitted psychometric results (based on cumulative Gaussian fits) for all participants in Experiment 1. PSEresults_Cumulative_gaussian.xlsx – Point of Subjective Equality (PSE, sensory bias) values for: Active (overall), Passive (overall), and Control conditions. Active condition divided by timestamps (0, 100, 200, 300 ms). Passive condition divided by movement velocity (Slow, Medium, Fast). JNDresults_Cumulative_gaussian.xlsx – Just Noticeable Difference (JND, sensory precision) values for the same conditions listed above. Experiment 2/ Contains the data from Experiment 2, which examined how spatial and temporal predictability affect tactile sensitivity. 1. Spatial_Predictability/ Includes a single file containing both PSE and JND data.The dataset is divided into three velocity predictability groups: 1v (High Predictability) 2v (Medium Predictability) 3v (Low Predictability) 2. Temporal_Predictability/ Includes a single file containing both PSE and JND data.This dataset compares temporal predictability conditions: 1v (High Predictability) 3t (Low Predictability) Notes All CSV files are comma-separated and include participant ID, condition labels, trial number, and response variables. Excel files contain the averaged and fitted psychometric parameters (PSE and JND) used for group-level analyses. Naming conventions follow the terminology used in the manuscript Methods section. Data can be analyzed using MATLAB, JASP, or any statistical software supporting CSV/XLSX formats.