Visual LearningVisuallearningNCT07015840
Generalization and Specificity of Visual Learning During Sleep
A study testing Visual perceptual learning in people with Visual Learning and Healthy Volunteers, run by Brown University at 1 site in United States.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 to 30 years
- Conditions the study is for
- Visual Learning, Healthy Volunteers
- What is being tested?
- Visual perceptual learning
- Type of treatment
- Lifestyle or therapy programme
- How many people
- 12 participants
- Where
- 1 siteUnited States
- Study dates
- 1 Feb 2025to 30 Jun 2026
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 30 years
- All sexes
- No healthy volunteers
- Adult
Who may be able to join
- 18 - 30 years old
- Normal or corrected to normal visual acuity
Who cannot join
- 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
Show all 9Show fewer
- Use of any type of intrauterine devices
- Use of dentures
- Pregnancy
Trial locations and contacts
1 site in 1 country.
About this study
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.
Read the detailed 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.
- Conditions
- Visual Learning, Healthy Volunteers
- Being tested
- Visual perceptual learning
- Keywords
- Sleep, Behavioral
- Medical subject headings
- Spatial Learning, Behavior
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Visual perceptual learningBehavioural
Evaluation of the effect of visual training on cortical activity during sleep
What is being measured
The primary outcome is the main question the study is designed to answer.
Performance change
Visual sensitivity changes will be assessed behaviorally using a psychophysical orientation detection task. Participants will be asked to detect the orientation of a Gabor patch embedded in visual noise. The outcome measure will be the signal-to-noise ratio (SNR) threshold at which participants can reliably detect the target orientation (typically defined as 75% correct performance). Lower SNR thresholds indicate greater visual sensitivity.
Measured: 5 weeks
Secondary outcomes (1)
Decoding accuracy
Decoding accuracy will be assessed using multivoxel pattern analysis (MVPA) applied to fMRI data. Pattern classifiers (e.g., support vector machine) will be trained to distinguish neural activity patterns corresponding to different stimulus orientations. Classification accuracy (percentage correct) will be used as the primary metric of decoding performance. Analyses will focus on predefined regions of interest including early visual areas.
Measured: 5 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Jun 2025
- Study start1 Feb 2025
- Primary completion30 Apr 2026
- Study completion30 Jun 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Visual LearningStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Basic science
- Allocation
- Randomised
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 12 participants (actual)
Sponsor and investigators
- Lead sponsor
- Brown University
- Sponsor type
- University, hospital or other
- Collaborators
- National Institute of General Medical Sciences (NIGMS)
- Responsible party
- Principal investigator, Yuka Sasaki, Brown University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07015840
- Sponsor's protocol ID
- 1203000577
- Other IDs
- 5P30GM149405-02
- Acronym
- Visuallearning
- Status last verified
- Jul 2026
- First submitted
- 29 May 2025
- Last updated
- 27 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: De-identified behavioral data, fMRI data, and participants' demography information will be shared.
Study at a glance
From the registry record, last updated by the sponsor on 27 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Generalization and Specificity of Visual Learning During Sleep
- ClinicalTrials.gov ID
- NCT07015840
- Acronym / sponsor ID
- Visuallearning / 1203000577
- Conditions
- Visual Learning, Healthy Volunteers
- Keywords
- Sleep, Behavioral
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 12 participants (actual)
- Lead sponsor
- Brown UniversityUniversity, hospital or other
- Collaborators
- National Institute of General Medical Sciences (NIGMS)
- Study start
- 1 Feb 2025 (actual)
- Primary completion
- 30 Apr 2026 (actual)
- Study completion
- 30 Jun 2026 (actual)
- First posted
- 11 Jun 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed 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.
Study design
- Primary purpose
- Basic science
- Allocation
- Randomised
- Intervention model
- Single group
- Masking
- None (open label)
Who may qualify
- Ages
- 18 to 30 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult
Key inclusion criteria (2 listed)
- 18 - 30 years old
- Normal or corrected to normal visual acuity
Key exclusion criteria (9 listed)
- 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)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Visual perceptual learningEvaluation of the effect of visual training on cortical activity during sleep | Behavioural | – |
Primary outcome
Performance change
Time frame: 5 weeks
Visual sensitivity changes will be assessed behaviorally using a psychophysical orientation detection task. Participants will be asked to detect the orientation of a Gabor patch embedded in visual noise. The outcome measure will be the signal-to-noise ratio (SNR) threshold at which participants can reliably detect the target orientation (typically defined as 75% correct performance). Lower SNR thresholds indicate greater visual sensitivity.
1 secondary outcome
Decoding accuracy
Time frame: 5 weeks
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 27 Jul 2026.
- Individual participant dataSharing planned: Yes. De-identified behavioral data, fMRI data, and participants' demography information will be shared.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Visual perceptual learning in people with Visual Learning and Healthy Volunteers, run by Brown University at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 9 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 27 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Performance change (time frame: 5 weeks). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 27 Jul 2026.