The left visual field attentional advantage: No evidence of different speeds of processing across visual hemifields.

Temporal-order judgment (TOJ) and simultaneity judgment (SJ) tasks are used to study differences in speed of processing across sensory modalities, stimulus types, or experimental conditions. Matthews and Welch (2015) reported that observed performance in SJ and TOJ tasks is superior when visual stimuli are presented in the left visual field (LVF) compared to the right visual field (RVF), revealing an LVF advantage presumably reflecting attentional influences. Because observed performance reflects the interplay of perceptual and decisional processes involved in carrying out the tasks, analyses that separate out these influences are needed to determine the origin of the LVF advantage. We re-analyzed the data of Matthews and Welch (2015) using a model of performance in SJ and TOJ tasks that separates out these influences. Parameter estimates capturing the operation of perceptual processes did not differ between hemifields by these analyses, whereas parameter estimates capturing the operation of decisional processes differed. In line with other evidence, perceptual processing also did not differ between SJ and TOJ tasks. Thus, the LVF advantage occurs with identical speeds of processing in both visual hemifields. If attention is responsible for the LVF advantage, it does not exert its influence via prior entry.

A Diagnostic Calculator for Detecting Glaucoma on the Basis of Retinal Nerve Fiber Layer, Optic Disc, and Retinal Ganglion Cell Analysis by Optical Coherence Tomography

Purpose: The purpose of this study was to develop and validate a multivariate predictive model to detect glaucoma by using a combination of retinal nerve fiber layer (RNFL), retinal ganglion cell-inner plexiform (GCIPL), and optic disc parameters measured using spectral-domain optical coherence tomography (OCT). Methods: Five hundred eyes from 500 participants and 187 eyes of another 187 participants were included in the study and validation groups, respectively. Patients with glaucoma were classified in five groups based on visual field damage. Sensitivity and specificity of all glaucoma OCT parameters were analyzed. Receiver operating characteristic curves (ROC) and areas under the ROC (AUC) were compared. Three predictive multivariate models (quantitative, qualitative, and combined) that used a combination of the best OCT parameters were constructed. A diagnostic calculator was created using the combined multivariate model. Results: The best AUC parameters were: inferior RNFL, average RNFL, vertical cup/disc ratio, minimal GCIPL, and inferior-temporal GCIPL. Comparisons among the parameters did not show that the GCIPL parameters were better than those of the RNFL in early and advanced glaucoma. The highest AUC was in the combined predictive model (0.937; 95% confidence interval, 0.911–0.957) and was significantly (P = 0.0001) higher than the other isolated parameters considered in early and advanced glaucoma. The validation group displayed similar results to those of the study group. Conclusions: Best GCIPL, RNFL, and optic disc parameters showed a similar ability to detect glaucoma. The combined predictive formula improved the glaucoma detection compared to the best isolated parameters evaluated. The diagnostic calculator obtained good classification from participants in both the study and validation groups.