This project aims to develop a novel visual training paradigm for use in visually-intact participants and those sufferings from stroke-induced visual impairments. Our task design is built upon theories of statistical learning to reduce the overall training burden while still producing profound improvements to visual abilities. Efficacy will be first established in visually-intact controls before testing in stroke survivors to assess the feasibility of this form of learning in the damaged visual system.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
BASIC_SCIENCE
Masking
NONE
Enrollment
30
Participants will be seated at a computer, and will be shown a random-noise visual stimulus drifting in one of eight directions. Participants will be instructed to indicate the direction of motion they perceive using a Sony Access Controller or a computer keyboard. Sound cues during stimulus presentation will also be used to ensure participants are aware of stimulus onset during the training task. After several repetitions of this visual training, a second set of visual cues will be presented to evaluate participant's learning of the program. Responses will be provided in the same manner by input from the controller or the keyboard.
University of Rochester Medical Center
Rochester, New York, United States
Explicit Learning - Response Time
Reaction time (ms) when performing motion discriminations for the final stimulus of a statistically-linked triplet will be compared against reaction times for stimuli with identical motion directions, presented with alternative placement within a triplet. Comparisons will be made only for correct responses in the final 20% of overall testing session trials.
Time frame: Baseline
Implicit Learning - Triplet Familiarity
Participant familiarity with statistically-linked triplets of motion will be assessed via a two-interval, forced-choice task. Familiarity will be measured as a percentage of comparisons in which the more prevalent triplet is selected as more familiar. Familiarity of high-probability, low-probability, and null-probability triplets will be compared following training.
Time frame: Baseline
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