Generalization and Specificity of Visual Learning During Sleep (Visuallearning)

Brown University

Status

Enrolling

Conditions

Healthy Volunteers

Visual Learning

Treatments

Behavioral: Visual perceptual learning

Study type

Interventional

Funder types

Other

NIH

Identifiers

NCT07015840

5P30GM149405-02 (U.S. NIH Grant/Contract)

1203000577

Details and patient eligibility

About

A growing body of evidence suggests that sleep facilitates and is beneficial to perceptual learning. However, the underlying mechanism of this facilitatory action is largely unknown. One must know what type of processing occurs during sleep to clarify the mechanism of sleep facilitating perceptual learning. For this purpose, investigators will obtain highly localized spatio-temporal information about brain activation during sleep using magnetic resonance imaging (MRI) and polysomnography (PSG) measurement.

Full description

The proposed study plans to collect pilot data for a study that investigates the role of sleep in the formation of feature and location specificity of VPL. Ten participants will be asked to do a visual task and nap inside the magnetic resonance imaging scanner with polysomnography.

Investigators will collect data from 10 participants, which was determined by the power analysis based on the previously published data.

Investigators will require each subject to attend six visits for six sessions. Session 1 includes the pretest of orientation detection, Session 2 orientation decoder construction, Session 3 adaptation nap, Session 4 baseline nap, Session 5 orientation detection training stage + posttraining nap, and Session 6 posttest of orientation detection. To assess the extent of performance improvement resulting from visual training, investigators will conduct behavioral sessions using an orientation detection task before and after a training session (Sessions 1, 5, and 6). For decoding orientations in each region of interest (ROI), investigators will construct an orientation decoder (Session 2) to utilize in later stages (Sessions 4 and 5) to estimate how much each orientation is represented in each ROI during sleep. Since it is well documented that young and healthy human subjects with no chronic sleep problems do not sleep well in the very first session of a sleep experiment, known as the first night effect (FNE), the adaptation nap session (Session 3) will be conducted so that participants will familiarize themselves with the experimental setting, to minimize the FNE and facilitate normal sleep from the next sleep session on. Each session will be done on separate days. In Session 5, the posttraining nap will follow the detection training on the same day.

As a behavioral measure, investigators will use an orientation detection task in the left or right visual field. Investigators will randomly determine the trained stimulus location for each participant. The stimulus will be masked with noise. Investigators will estimate the threshold signal-to-noise ratio (SNR) for an orientation detection task. Participants will engage in a two-interval forced choice task for orientation detection: they will be asked to indicate which interval (the first or the second) contained stripes by pressing either the '1' or '2' button on a keyboard while maintaining their gaze on a fixation point at the center of the display throughout trials. Investigators will present several orientations, and one of them will be specifically trained for the training session. Training usually decreases the threshold SNR, meaning that a participant could detect the trained orientation with more noise, while the threshold SNR would remain the same for untrained orientations.

An orientation decoder is a statistical algorithm that allow us to estimate how much feature information is there in a local brain region. Investigators will apply the decoder to each ROI, including early visual areas and the frontal regions, while participants are asleep to estimate whether the trained orientation is intensively processed.

The orientation decoder construction stage will be conducted inside the MRI scanner. First, a stimulus localizer scan will be run to identify the cortical regions that respond to the stimulus presentation in each ROI using BOLD signals. Second, BOLD signals will be recorded, while each orientation with a 50% SNR will be randomly selected and presented in both the trained and untrained visual fields. Throughout the fMRI run, the subjects will be instructed to maintain their gaze at the small fixation point at the center of the display. To keep participants' vigilance levels, they will be asked to detect a color change in the fixation point. A standard echo-planner imaging sequence will be utilized for BOLD signal collection to cover the whole brain.

All adaptation, baseline, and posttraining nap sessions will be conducted for 90 min in the early afternoon in the same manner. Investigators will measure BOLD signals and polysomnography to determine sleep stages objectively.

Investigators will do the analysis in the following way. First, investigators will co-register BOLD signals and sleep stages. Next, investigators will decode the likelihood for each of the orientations for sleep stages for each ROI in the baseline and posttraining nap sessions. The critical question is whether the likelihoods of trained and untrained orientations change during sleep periods in the posttraining nap sessions. If sleep plays a role in the specificity of VPL, then invesigators would see differences in the likelihood of trained and untrained orientations at the trained location during the sleep period in the posttraining nap session in ROIs, which are involved in visual training.

Enrollment

10 estimated patients

Sex

All

Ages

18 to 30 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

18 - 30 years old
Normal or corrected to normal visual acuity

Exclusion criteria

Self-report of visual and 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)
History of sleep disorders (sleep apnea, insomnia)
Failure to meet the criteria on the visual acuity test
Magnetically or mechanically activated implants (such as cardiac pacemakers)
Clips on blood vessels in the brain
Use of any type of intrauterine devices
Use of dentures
Pregnancy