Reminder and 2AFC tasks provide similar estimates of the difference limen: a reanalysis of data from Lapid, Ulrich, and Rammsayer (2008) and a discussion of Ulrich and Vorberg (2009)

Lapid, Ulrich, and Rammsayer (2008) reported that estimates of the difference limen (DL) from a two-alternative forced choice (2AFC) task are higher than those obtained from a reminder task. This article reanalyzes their data in order to correct an error in their estimates of the DL from 2AFC data. We also extend the psychometric functions fitted to data from both tasks to incorporate an extra parameter that has been shown to allow obtaining accurate estimates of the DL that are unaffected by lapses. Contrary to Lapid et al.'s conclusion, our reanalysis shows that DLs estimated with the 2AFC task are only minimally (and not always significantly) larger than those estimated with the reminder task. We also show that their data are contaminated by response bias, and that the small remaining difference between DLs estimated with 2AFC and reminder tasks can be reasonably attributed to the differential effects that response bias has in either task as they were defined in Lapid et al.'s experiments. Finally, we discuss a novel approach presented by Ulrich and Vorberg (2009) for fitting psychometric functions to 2AFC discrimination data.

Principal Component Analysis of Results Obtained from Finite-Difference Time-Domain Algorithms

Finite-Differences Time-Domain (FDTD) algorithms are well established tools of computational electromagnetism. Because of their practical implementation as computer codes, they are affected by many numerical artefact and noise. In order to obtain better results we propose using Principal Component Analysis (PCA) based on multivariate statistical techniques. The PCA has been successfully used for the analysis of noise and spatial temporal structure in a sequence of images. It allows a straightforward discrimination between the numerical noise and the actual electromagnetic variables, and the quantitative estimation of their respective contributions. Besides, The GDTD results can be filtered to clean the effect of the noise. In this contribution we will show how the method can be applied to several FDTD simulations: the propagation of a pulse in vacuum, the analysis of two-dimensional photonic crystals. In this last case, PCA has revealed hidden electromagnetic structures related to actual modes of the photonic crystal.

The difference model with guessing explains interval bias in two-alternative forced- chocice detection procedures

The standard difference model of two-alternative forced-choice (2AFC) tasks implies that performance should be the same when the target is presented in the first or the second interval. Empirical data often show “interval bias” in that percentage correct differs significantly when the signal is presented in the first or the second interval. We present an extension of the standard difference model that accounts for interval bias by incorporating an indifference zone around the null value of the decision variable. Analytical predictions are derived which reveal how interval bias may occur when data generated by the guessing model are analyzed as prescribed by the standard difference model. Parameter estimation methods and goodness-of-fit testing approaches for the guessing model are also developed and presented. A simulation study is included whose results show that the parameters of the guessing model can be estimated accurately. Finally, the guessing model is tested empirically in a 2AFC detection procedure in which guesses were explicitly recorded. The results support the guessing model and indicate that interval bias is not observed when guesses are separated out.

Correction to “Reminder and 2AFC tasks provide similar estimates of the difference limen: A reanalysis of data from Lapid, Ulrich, and Rammsayer (2008) and a discussion of Ulrich and Vorberg (2009)”

We recently published an article (García-Pérez & Alcalá- Quintana, 2010) reanalyzing data presented by Lapid, Ulrich, and Rammsayer (2008) and discussing a theoretical argument developed by Ulrich and Vorberg (2009). The purpose of this note is to correct an error in our study that has some theoretical importance, although it does not affect the conclusion that was raised. The error lies in that asymptote parameters reflecting lapses or finger errors should not enter the constraint relating the psychometric functions that describe performance when the comparison stimulus in a two-alternative forced choice (2AFC) discrimination task is presented in the first or second interval.