Brain Wave Analysis for Attention in Visual Search Tasks

Age: 18 - 65

Sex: Any

Trial Phase: Academic

Sponsor: Lehigh University

Disqualifiers: Neurological disorders

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 1

50 Participants Needed

Trial Summary

Do I need to stop taking my current medications for this trial?

The trial information does not specify whether you need to stop taking your current medications.

What data supports the effectiveness of the treatment SSVEP for attention in visual search tasks?

Research shows that SSVEPs (steady-state visual evoked potentials) can effectively track and enhance attention by measuring brain responses to visual stimuli. Studies have demonstrated that SSVEPs can be used to improve attention accuracy and control in brain-computer interfaces, suggesting potential benefits for visual search tasks. ^{1 2 3 4 5}

Is the use of SSVEPs in brain wave analysis for attention tasks safe for humans?

The research articles do not provide specific safety data for SSVEPs, but they have been used in studies with human participants without reported safety concerns. ^{1 3 4 6 7}

How does the treatment in the Brain Wave Analysis for Attention in Visual Search Tasks trial differ from other treatments for attention in visual tasks?

This treatment is unique because it uses brain-computer interfaces (BCIs) to analyze brain waves, specifically steady-state visual evoked potentials (SSVEPs), to enhance attention in visual tasks. Unlike traditional methods, it focuses on decoding neural activity patterns in real-time to improve selective attention without relying on eye movements. ^{1 3 8 9 10}

What is the purpose of this trial?

In this line of research, the researchers are utilizing an EEG measure of repeated visual stimulation, the Steady-State Visually Evoked Potential (SSVEP) to examine processing of target and distractor information during visual search. This is a basic science study.

Research Team

Nancy Carlisle, PhD

Principal Investigator

Lehigh University

Eligibility Criteria

This trial is for healthy individuals with normal or corrected-to-normal vision and color perception. It's not suitable for those with a history of neurological disorders.

Inclusion Criteria

My vision is normal or corrected to normal with glasses or contacts.

Normal color vision

Exclusion Criteria

I have a history of neurological disorders.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

1-2 weeks

Testing

Participants undergo EEG testing to measure brain responses to visual stimuli

1 day

1 visit (in-person)

Follow-up

Participants are monitored for any immediate post-testing effects

1 week

Treatment Details

Interventions

• SSVEP

Trial Overview The study is examining how people process visual information when searching for targets or ignoring distractions, using an EEG technique called SSVEP to measure brain activity during the task.

Participant Groups

Group I: Within-Subjects Attentional Information Experimental Treatment 1 Intervention

Within-Subjects, all participants receive all interventions

Who Is Running the Clinical Trial?

Lehigh University

Lead Sponsor

Trials

24

Recruited

6,800+

References

1. United States pubmed.ncbi.nlm.nih.gov

Visual spatial attention tracking using high-density SSVEP data for independent brain-computer communication. [2007]

2. United States pubmed.ncbi.nlm.nih.gov

Steady-State Visually Evoked Potentials and Feature-based Attention: Preregistered Null Results and a Focused Review of Methodological Considerations. [2023]

3. England pubmed.ncbi.nlm.nih.gov

Optimising the classification of feature-based attention in frequency-tagged electroencephalography data. [2022]

4. United States pubmed.ncbi.nlm.nih.gov

Selective attention to stimulus location modulates the steady-state visual evoked potential. [2022]

5. England pubmed.ncbi.nlm.nih.gov

Tracking momentary fluctuations in human attention with a cognitive brain-machine interface. [2023]

6. Netherlands pubmed.ncbi.nlm.nih.gov

Using frequency tagging to quantify attentional deployment in a visual divided attention task. [2019]

7. England pubmed.ncbi.nlm.nih.gov

Tracking feature-based attention. [2020]

8. England pubmed.ncbi.nlm.nih.gov

Enhancing performances of SSVEP-based brain-computer interfaces via exploiting inter-subject information. [2015]

9. England pubmed.ncbi.nlm.nih.gov

Discriminative codewaves: a symbolic dynamics approach to SSVEP recognition for asynchronous BCI. [2019]

10. Netherlands pubmed.ncbi.nlm.nih.gov

Sequence detection analysis based on canonical correlation for steady-state visual evoked potential brain computer interfaces. [2019]