# Comprehensive frameworks of perceptual learning

> **NIH NIH R01** · BROWN UNIVERSITY · 2024 · $398,750

## Abstract

Summary
This is a resubmission of the competitive renewal of the ongoing R01 grant. Visual perceptual learning (VPL) is
an important tool that can be used to better understand visual plasticity. The long-term goal is to comprehensively
understand the mechanisms of VPL and their underlying plasticity, which may provide important information for
the development of training and rehabilitation tools and programs for improving and restoring damaged, declining
or degraded vision. This proposal aims to examine the roles of global processing, such as reward and arousal,
in the specificity of VPL, which is one of the most important characteristics of VPL. VPL is generally characterized
as specific to the trained feature and the retinal location in which the feature is presented, minimally transferring
to other features or locations. The specificity of VPL may impose serious restrictions on the use of VPL in clinical
applications that require generalized effects in everyday life. Early studies suggested that the specificity of VPL
comes from properties of neurons in early visual areas. However, later studies indicate that the specificity is
greatly influenced by global processing that does not originate in early visual areas. The current proposal aims
to examine the roles of global processing such as reward and arousal in the generalizability and specificity of
VPL. No research has ever been conducted to test whether and how reward and arousal each influence the
generalizability/specificity of VPL. There are two types of VPL. Task-irrelevant VPL (TIVPL) refers to the learning
resulting from passive exposure to a task-irrelevant feature or object, whereas task-relevant VPL (TRVPL) refers
to the learning of a task-relevant feature or object through a given task. Significantly different mechanisms may
underlie these two types of VPL. Thus, the abovementioned questions will be addressed for TIVPL and TRVPL
in Specific Aims 1 and 2, respectively. Our preliminary results consistently suggest the following aspects: (1)
Arousal plays a role in generalizing the trained feature or object to untrained features or untrained objects within
the same category of the trained object, whereas reward is not involved in the generalization of VPL and rather
plays a role in inducing the specificity of VPL. (2) Generalization due to arousal is not involved in reinforcement
processing, which may play an important role in the specificity of VPL due to reward. The information that will be
obtained from the research results is expected to be important for the development of a clinical training method,
for which the generalization of VPL is crucial. We will test the following hypotheses by psychophysics.
Hypothesis (H)1: Reward plays a role in increasing the specificity of TIVPL and TRVPL. H2: Arousal plays a
role in increasing the generalizability of TIVPL and TRVPL. H3: H1 and H2 are valid for both VPL of a primitive
feature and VPL of an object. H4: Reinforcement processing is inv...

## Key facts

- **NIH application ID:** 10798782
- **Project number:** 2R01EY027841-05A1
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Takeo Watanabe
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $398,750
- **Award type:** 2
- **Project period:** 2018-06-01 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10798782

## Citation

> US National Institutes of Health, RePORTER application 10798782, Comprehensive frameworks of perceptual learning (2R01EY027841-05A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10798782. Licensed CC0.

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