Larg-scale multimodal fMRI dataset of visual and haptic 3D object category learning.

Authors

Sepideh Tabrik, Sama Rahnemayan, Martin Tegenthoff, Mehdi Behroozi

Published in

Scientific data. Volume 13. Issue 1. Jul 16, 2026. Epub Jul 16, 2026.

Abstract

How do humans recognize objects in their environment using either vision or touch, even when only one sense is available? Humans routinely integrate visual and haptic sensory systems for object recognition, yet the mechanisms behind cross-modal transfer of category information are not fully understood. In this study, we collected behavioral and fMRI data from 134 participants. Fifty participants (25 per group; 13 females each) performed a similarity rating task with novel 3D objects ("digital embryos") using either visual or haptic modalities. The remaining 84 participants completed a 3D object category learning experiment in unimodal (Visual-Visual: n = 19, 11 females; Haptic-Haptic: n = 22, 10 females) or cross-modal (Visual-Haptic: n = 22, 11 females; Haptic-Visual: n = 21, 10 females) conditions. Alongside task-based fMRI, we acquired resting-state fMRI data at four time points: pre-training, post-training, pre-test, and post-test. High-resolution T1-weighted images were also obtained for each MRI session. These data support investigations into visual and haptic representations of the environment, representational similarity across modalities, cross-modal transfer of category information for object recognition, and neural plasticity in brain networks.

PMID:
42463676
Bibliographic data and abstract were imported from PubMed on 17 Jul 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.