10 Participants Needed

Visual Features for Visual Attention

TS
EM
Overseen ByEmily Machniak
Age: 18 - 65
Sex: Any
Trial Phase: Academic
Sponsor: University of California, Santa Barbara
No Placebo GroupAll trial participants will receive the active study treatment (no placebo)
Approved in 2 JurisdictionsThis treatment is already approved in other countries

Trial Summary

What is the purpose of this trial?

How does one know what to look at in a scene? Imagine a "Where's Waldo" game - it's challenging to find Waldo because there are many 'salient' locations in the picture, each vying for one's attention. One can only attend to a small location on the picture at a given moment, so to find Waldo, one needs to direct their attention to different locations. One prominent theory about how one accomplishes this claims that important locations are identified based on distinct feature types (for example, motion or color), with locations most unique compared to the background most likely to be attended. An important component of this theory is that individual feature dimensions (again, color or motion) are computed within their own 'feature maps', which are thought to be implemented in specific brain regions. However, whether and how specific brain regions contribute to these feature maps remains unknown. The goal of this study is to determine how brain regions that respond strongly to different feature types (color and motion) and which encode spatial locations of visual stimuli extract 'feature dimension maps' based on stimulus properties, including feature contrast. The investigators hypothesize that feature-selective brain regions act as neural feature dimension maps, and thus encode representations of salient location(s) based on their preferred feature dimension. The investigators will scan healthy human participants using functional MRI (fMRI) in a repeated-measures design while they view visual stimuli made salient based on different combinations of feature dimensions. The investigators will employ state-of-the-art multivariate analysis techniques that allow them to reconstruct an 'image' of the stimulus representation encoded by each brain region to dissect how neural tissue identifies salient locations. Each participant will perform a challenging task at the center of the screen to ensure they keep their eyes still and ignore the stimuli presented in the periphery, which are used to gauge how the visual system automatically extracts important locations without confounding factors like eye movements. Across trials and experiments the investigators will manipulate 1) the 'strength' of the salient locations based on how different the salient stimulus is compared to the background, 2) the number of salient locations, and 3) the feature value(s) used to make each location salient. Altogether, these manipulations will help the investigators fully understand these critical salience computations in the healthy human visual system.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your doctor.

How does this treatment for visual attention differ from other treatments?

This treatment is unique because it focuses on using visual features to guide attention by integrating different feature dimensions like color and motion into a priority map, which helps in identifying and focusing on important visual information. Unlike other treatments, it leverages the brain's natural ability to prioritize visual stimuli based on salience and relevance, potentially offering a more targeted approach to improving visual attention.12345

Research Team

TC

Tommy C Sprague

Principal Investigator

University of California, Santa Barbara

Eligibility Criteria

This trial is for healthy individuals interested in how the brain processes visual information. Participants should be able to focus on a task without moving their eyes, as they will view stimuli with varying levels of 'salience' or importance, like color and motion differences.

Inclusion Criteria

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

Exclusion Criteria

I have reported having a neurological condition.
Implanted medical devices (e.g., cardiac pacemaker; metallic aneurism clip)
Non-removable metallic piercings
See 4 more

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Anatomical & Retinotopic Mapping

Participants undergo an anatomical and retinotopic mapping session to identify brain regions for further analysis

2 hours
1 visit (in-person)

Experimental fMRI Sessions

Participants engage in visual attention tasks during fMRI scanning to study the role of feature-selective brain regions

3-4 hours
2 visits (in-person)

Follow-up

Participants are monitored for safety and effectiveness after the experimental sessions

2 weeks

Treatment Details

Interventions

  • Probing the Role of Feature Dimension Maps in Visual Cognition: Impact of Salience Level (Expt 1.1)
Trial Overview The study tests how certain brain regions create 'feature dimension maps' from visual stimuli properties using fMRI scans. It examines if these areas encode salient locations by feature contrast while participants perform a central screen task.
Participant Groups
1Treatment groups
Experimental Treatment
Group I: Manipulations of graded feature salience (Expt 1.1)Experimental Treatment2 Interventions
Participants will view stimuli made salient based on feature contrast in one feature dimensions (color or motion direction; or checkerboard luminance contrast). The degree to which a location is salient will be manipulated based on the feature contrast across multiple values

Find a Clinic Near You

Who Is Running the Clinical Trial?

University of California, Santa Barbara

Lead Sponsor

Trials
33
Recruited
3,100+

National Eye Institute (NEI)

Collaborator

Trials
572
Recruited
1,320,000+

Findings from Research

The study supports the feature integration theory (FIT) by demonstrating that detection tasks rely on dimension-specific mechanisms, while localization tasks utilize a more general approach across dimensions.
Results showed that switching between dimensions in detection tasks incurs costs, indicating that different cognitive processes are at play, which reinforces the idea that distinct mechanisms govern parallel and focal attention searches.
Feature integration theory revisited: dissociating feature detection and attentional guidance in visual search.Chan, LK., Hayward, WG.[2009]
This study provides evidence that specific regions in the human visual cortex act as 'feature dimension maps' that prioritize locations based on distinct visual features, such as color or motion, using fMRI to analyze brain activation patterns.
The results show a double dissociation where color-selective regions highlight color-defined salient locations while motion-selective regions do the same for motion-defined salience, supporting the idea that the brain processes different visual features independently to guide attention.
Feature-Specific Salience Maps in Human Cortex.Thayer, DD., Sprague, TC.[2023]
Bundesen's Theory of Visual Attention (TVA) can be effectively used to quantitatively measure the salience of visual features, which helps in understanding how differences between objects and their surroundings capture attention.
Through four experiments, including orientation pop-out displays and luminance assessments, the study demonstrates that TVA can be applied to various types of stimuli, enhancing our ability to analyze salience effects in visual attention research.
Fast and Conspicuous? Quantifying Salience With the Theory of Visual Attention.Krüger, A., Tünnermann, J., Scharlau, I.[2020]

References

Feature integration theory revisited: dissociating feature detection and attentional guidance in visual search. [2009]
Feature-Specific Salience Maps in Human Cortex. [2023]
Fast and Conspicuous? Quantifying Salience With the Theory of Visual Attention. [2020]
Dynamic weighting of feature dimensions in visual search: behavioral and psychophysiological evidence. [2021]
Visual search for singleton feature targets across dimensions: Stimulus- and expectancy-driven effects in dimensional weighting. [2019]
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