Multistable Rivalry Visual Assessment Using Continuous Perceptual Tracking
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Solution Overview
Problem
Current methods for assessing visual function through binocular rivalry are limited by lack of validated individual introspection, inability to capture dynamic perceptual transitions, and sparse data collection, leading to inaccurate or incomplete diagnoses in clinical and neurological assessments.
Innovation Solution
A 4-phase method involving training, practice, and actual rivalry phases using a stereoscopic viewing device and input device to collect high-resolution data on conscious visual perception, employing machine learning for analysis and validation of perceptual states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional binocular rivalry methods are used with forced-choice procedures, then the testing process is simple, but the dynamic and gradual nature of perceptual transitions cannot be captured
Solution Approach 1:
The patent implements continuous tracking of perceptual states during binocular rivalry, transitioning from static forced-choice measurements to dynamic continuous monitoring. The system records perceptual state changes over time, capturing the gradual transitions and temporal dynamics of perception that were lost in the original forced-choice paradigm.
Solution Approach 2:
The patent employs continuous data collection throughout the binocular rivalry task, maintaining continuous monitoring of perceptual states rather than relying on discrete forced-choice responses. This continuous action allows the system to capture the entire trajectory of perceptual transitions, including intermediate states and transition probabilities.
2Duration of action of moving object
If standard binocular rivalry testing is used with limited data collection, then the test duration is short, but the data is too sparse to capture dynamic perceptual speed and velocity
Solution Approach 1:
The patent implements continuous data collection at high frequency throughout the test duration, transforming sparse discrete measurements into dense continuous data streams. This allows capture of perceptual speed and velocity metrics that require fine-grained temporal resolution, while the test itself remains relatively brief.
Solution Approach 2:
The system automatically extracts meaningful metrics including transition probabilities, perceptual velocity, and state duration from the continuous data without requiring additional manual analysis or extended testing. The computational analysis is performed on the rich data already collected during the standard test duration.
3Device complexity
If conventional binocular rivalry methods are used, then the testing approach is straightforward, but validated individual introspection of perception is lacking
Solution Approach 1:
The patent incorporates feedback mechanisms where participants continuously indicate their perceived state during binocular rivalry, and this feedback is immediately processed to validate and adjust the measurement. The system compares reported perceptual states with objective measures to ensure accurate capture of individual experience, thereby validating introspection.
Solution Approach 2:
The patent replaces traditional mechanical forced-choice response systems with a computational system that processes continuous perceptual state reports. This substitution enables more sophisticated analysis of individual introspection through machine learning algorithms that can validate and interpret subjective perceptual experiences.
4Device complexity
If standard forced-choice procedures are used, then the measurement process is simple, but the interaction between states and transition probabilities are not measured
Solution Approach 1:
The patent implements continuous monitoring of perceptual state transitions, capturing the temporal sequence and probability of transitions between different perceptual states. This continuous action enables measurement of transition probabilities and state interactions that are completely lost in discrete forced-choice procedures.
Solution Approach 2:
The patent introduces computational analysis as an intermediary layer that processes continuous perceptual state data to extract transition probabilities and state interaction metrics. This intermediary computational layer transforms raw perceptual data into meaningful measures of state dynamics without adding complexity to the basic measurement process.
Data Source
AI summary
Testing methods for evaluating visual and neurological functions of a human or animal subject that involve conscious perception. The tests include a training phase, a practice phase, and a visual rivalry phase for detecting binocular rivalry or multistate competition. The design of the testing methods offers simple, rapidly administered, nonverbal visual testing with high time resolution and access to changing conscious perceptual states of the test subject. The methods also make possible the collection of a large amount of data in a short time for analysis of the subjects visual function and brain function, and can be used in the diagnosis of many medical conditions.