Electroencephalogram Analysis Regarding Visual Information Processing in a Grapheme-color Synesthete

In order to explore characteristics of visual information processing in grapheme-color synesthesia, we examined behavior (response correctness and reaction time) and temporal activities of EEG during the performance of two kinds of "embedded shape tasks" in one synesthete and 16 nonsynesthetic subjects. We used three black capital letters, including one letter which a synesthetic subject perceived in color. The target grapheme was made of a letter which a synesthetic subject perceived in color (TASK1), and one that was not perceived in color (TASK2). There was a significant difference in reaction time between the two tasks. Measuring the difference in amplitude of EEG activity at P4 between the two tasks, biphasic activity change was observed. At 232.5 ms in the late phase, the bilateral occipital and parietal lobes, and the left frontal lobe were activated. These results suggest that biphasic activity change is related to different visual information processing in synesthesia; the early phase is related to directing attention to a shape with color, while the late phase to the recognition of a shape with color. It is also suggested that activated areas of the brain in the late phase function separately in causing grapheme-color synesthesia

The Parametric and Non-parametric Bootstrap Resamplings for the Visual Acuity Measurement

We propose a useful tool for the visual acuity measurement from the results of parametric and non-parametric bootstrap algorithms in the logistic regression model. We present the kurtosis and the variance of deviance residuals to estimate the efficiency of bootstrap resampling. We applied our parametric and non-parametric algorithms to the problem of the visual acuity measurement and obtained the efficiency measures for the comparison of the parametric and non-parametric bootstrap resamplings

Psychophysical Threshold Estimates in Logistic Regression Using the Bootstrap Resampling

We propose the non-parametric bootstrap resampling algorithm for the problem of psychophysical threshold estimates. We use the logistic regression with guessing rate and the log-likelihood ratio test statistics of two samples for testing the hypothesis by using the bootstrap resampling. We apply our algorithm to the visual acuity test, and show that the bootstrap resampling is useful for the problem of the two-sample test when the numbers of observations are not identical between the two samples. We also propose the bootstrap algorithm for one-sample testing to certify the values of parameters and threshold obtained by logistic regression

A statistical modelling of the visual acuity measurement and its multiple test procedure

To establish the computer assisted system of the visual acuity test, we propose a statistical modelling of the visual acuity measurement and its multiple test procedure. The psychometric functions for individual patients are produced by the logistic regression combined with the guessing rate. We adopt test statistics based on (i) psychometric functions (the Cochran-Mantel-Haenszel method) and (ii) psychophysical thresholds (the delta method). The multiple comparisons are performed by the step-down procedure with Ryan-Einot-Gabriel-Welsch (REGW) significance levels. To show the practical effectiveness of our system, we present a numerical example of four patient groups