The purpose of this study is to investigate how our performance changes after our perceptual system is trained in a certain way ("perceptual learning"). In addition, we are interested in identifying and characterizing relationships between such changes and neuroimaging signals recorded from the human brain.

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 involved in the role that reward plays in the specificity of TIVPL and TRVPL, whereas it is not involved in the role of arousal in the generalizability of TIVPL and TRVPL.

Inclusion Criteria:

• Ages 18 - 60,
• Normal or corrected-to-normal vision

Exclusion Criteria:

• Eye disorders (cataracts, age related macular degeneration, diabetic retinopathy, glaucoma)
• Drug use (psychoactive drugs, neuroleptic medications, prescription medications that might affect cognitive and motor performance)
• Sleep disorders (sleep apnea, insomnia)
• Magnetically or mechanically activated implants (such as cardiac pacemakers)
• clips on blood vessels in the brain
• intrauterine devices
• dentures
• pregnancy

The types of data to be produced in the current project will be behavioral data and participants' demographic information will also be collected. All data will be de-identified before receipt by the repository. Programs for visual stimuli and data analyses will be produced in the project.