Abstract: 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.

Abstract: Methods and systems providing adaptive assessment of a physical subject to efficiently collect assessment data and modify an assessment schedule based on the analyses. The methods and systems can control the timing of each assessment in order to collect data at times and under conditions that are most informative about the physical subject. Such adaptive methods and systems significantly minimize the frequency of data collection without loss in accuracy or precision and can increase test reliability through reduction in redundancy. The ability to estimate an unknown, underlying function using a small number of free parameters that remain constant regardless of the number of data points being estimated substantially reduces the error of the function estimate. Because estimates of the measurement error are achieved with a minimum of sampled assessments, and with great accuracy, the statistical power of clinical trials, for example, can be greatly increased.

Abstract: Methods and systems providing adaptive assessment of a physical subject to efficiently collect assessment data and modify an assessment schedule based on the analyses. The methods and systems can control the timing of each assessment in order to collect data at times and under conditions that are most informative about the physical subject. Such adaptive methods and systems significantly minimize the frequency of data collection without loss in accuracy or precision and can increase test reliability through reduction in redundancy. The ability to estimate an unknown, underlying function using a small number of free parameters that remain constant regardless of the number of data points being estimated substantially reduces the error of the function estimate. Because estimates of the measurement error are achieved with a minimum of sampled assessments, and with great accuracy, the statistical power of clinical trials, for example, can be greatly increased.