# Recognition of Shape by Vision and Touch

> **NIH NIH R21** · BROWN UNIVERSITY · 2022 · $438,625

## Abstract

Abstract/Summary
The goal of this project is to understand how objects are recognition by vision and touch. While considerable
progress has been made in our understanding how visual information about shape can access higher brain
structures involved in recognizing objects and directing action, circuits by which the same information derived
by touch are not as advanced. This is an important question, because we still do not know how objects are
represented in the brain, and in particular, how a unified representation of these objects can be derived from
multiple senses. The role vision plays in orchestrating this integration is an open question: Do we literally see
with our hands? And is this true even for those without normal vision? The goal of this exploratory project is
to develop a new approach for addressing these questions. In particular, we aim to develop a unique “haptic
display”, built to be MRI safe and capable of presenting novel physical shapes that can be interleaved with
visual stimuli in behavioral studies (Aim 1). In Aim 2, we use this device in a behavioral paradigm to test the
hypothesis that familiarity for specific exemplars can be learned through training and improve behavioral
performance for shape matching, taking advantage of the device’s ability to generate novel exemplars. We
will also establish if learning has equivalent benefits for unimodal and crossmodal identification. These
experiments will clarify the role of familiarity in haptic processing and provide an empirical foundation for Aim
3, which is designed to address an outstanding question about the interaction between haptic exploration
and visual cortical areas, and the conditions under which this form of crossmodal activation is observed.
Together, these studies will both introduce a new paradigm for approaching the understudied problem of
haptic recognition, and attempt to link fields of visual and haptic processing in search of an answer to the
longstanding question of how sensory information about single objects converges to generate impressions
of unified wholes. Successful completion of these aims will provide a key starting point for the first systematic
neurophysiological investigations of multi-modal object recognition at the single neuron level. This has
significant implications for understanding the rich interplay between sensory systems in normal recognition
and the recovery and rehabilitation of sensory function following injury or stroke.

## Key facts

- **NIH application ID:** 10575067
- **Project number:** 1R21NS130475-01
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** DAVID L SHEINBERG
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $438,625
- **Award type:** 1
- **Project period:** 2022-09-15 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10575067

## Citation

> US National Institutes of Health, RePORTER application 10575067, Recognition of Shape by Vision and Touch (1R21NS130475-01). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10575067. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*