Effects of prediction and attention on tactile precision in somatosensory gating--DATASET

Read full text
Authors: Pierangelo N. D'Onofrio Pacheco
Cited by: 0

Abstract

This repository contains the behavioral data and analysis outputs for the manuscript“Effects of prediction and attention on tactile precision in somatosensory gating” (D’Onofrio Pacheco & Zimmermann, Heinrich-Heine University Düsseldorf). All data are organized in one main folder. Data/ CSV Participant/ Contains the raw data for each participant.Every subfolder Contains the raw data for each participant in each following conditions: Active/ – trials recorded during self-generated movements. Attentional allocation Start & End Passive/ – trials recorded during externally driven movements. Attentional allocation Start & End Control/ – trials recorded at rest (no movement). Attentional allocation Start & End PSE_and_JND/ Contains the fitted psychometric results PSE and JND(based on cumulative Gaussian fits) for all participants in every condition and level. VP,Gender,Age,PSE_Control_end,PSE_Control_start,PSE_Passive_end,PSE_Passive_start,PSE_Active_start,PSE_Active_end,JND_Control_end,JND_Control_start,JND_Passive_end,JND_Passive_start,JND_Active_start,JND_Active_end,Delta_Active_JND,Delta_Passive_JND 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. Three participants were excluded from the final sample: two due to unusable psychometric functions (JD14, HN77), and one because they did not complete the study (JN98). Data can be analyzed using MATLAB, JASP, or any statistical software supporting CSV/XLSX formats.

Fields of Study & Subjects

Tactile and Sensory Interactions Motor Control and Adaptation Multisensory perception and integration

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
5 March 2026
Language
EN
Document type
Dataset