Systematic Psychophysical (Visuallearning)

Brown University

Status

Enrolling

Conditions

Perceptual Learning

Treatments

Behavioral: Visual Training

Study type

Interventional

Funder types

Other

NIH

Identifiers

NCT06965478

R01EY019466 (U.S. NIH Grant/Contract)

1203000582-02

Details and patient eligibility

About

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, investigators are interested in identifying and characterizing relationships between such changes and neuroimaging signals recorded from the human brain.

Full description

The long-term goal of the proposed project is to elucidate the underlying mechanisms of visual perceptual learning (VPL) for artificial and natural stimuli, which will be instrumental in developing rehabilitation programs aimed at enhancing damaged or deteriorating vision. The specificity of VPL to the feature and location of the trained visual stimulus is a fundamental characteristic of VPL. To investigate the specificity, one effective way is to use an artificial stimulus such as a Gabor patch as the trained stimulus, as it has been widely used to investigate basic visual processing. Simultaneously, to create an impactful rehabilitation program, the resulting improvements must be generalized to untrained features and locations in visual stimuli encountered in everyday life, including natural scenes (NS). However, it remains uncertain whether the same mechanisms underlie the generalization and specificity in VPL for artificial and NS stimuli. In Specific Aim (SA) 1, investigators aim to examine basic mechanism of the specificity using a Gabor patch. According to a prevailing theory, early visual processing (e.g., 0 to 150ms after the stimulus onset) primarily involves input-level feedforward signals. In contrast, late processing (e.g.,150-300ms after the stimulus onset) involves recurrent processing. To better understand the mechanism of the specificity of VPL it is crucial to clarify whether early or late processing is involved. Additionally, it remains unclear whether the specificity of VPL involves excitation on the trained feature and location or inhibition on untrained features and locations. Therefore, investigators will test Hypothesis 1 (H1): Late processing (H1-a) or early processing (H1-b) plays a role in the specificity of VPL, and H2: Excitatory signals (H2-a) or inhibitory signals (H2-b) are involved in inducing the specificity of VPL. investigators will employ two methods. The backward masking (BM) is used to disrupts and reveal roles of late processing. In preliminary results, BM applied to the trained orientation eliminated the orientation specificity in VPL, supporting H1-a. A Rhythmic Synchronization Orientation Decoding Change (RSDC) method is a novel method that examines at which band(s) of rhythmic synchronization from electroencephalogram (EEG) the decoding performances of trained and untrained features and locations change after VPL training. Preliminary results suggest that trained orientation signals are enhanced at both trained and untrained locations during early processing, while those at untrained locations are inhibited during late processing, leading to the location specificity. In SA2, investigators will examine the specificity and generalizability of VPL for NS. Our first step is to test H3: VPL for the dominant orientation in NS is specific (H3-a) or generalized (H3-b) to other orientations. Preliminary results support H3-b. If true, investigators will further investigate the aspects in NS that induce the generalization of VPL. Preliminary result suggests that higher-order statistics, involving correlations between different orientation and spatial frequency channels derived from NS, play a role in the generalization of VPL for NS. Investigators further aim to test H1 and H2 for NS images, using both the BM and RSDC methods.

Enrollment

400 estimated patients

Sex

All

Ages

18 to 60 years old

Volunteers

No Healthy Volunteers

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