Biomedical subjects

C Bowd

Publications and source records attributed to C Bowd.

21 records · Page 2Linked to original sources

PubMed1994

Properties of the stereoscopic (cyclopean) motion aftereffect.

Across four experiments, this study investigated properties of the stereoscopic motion aftereffect (adaptation from moving retinal disparity information). The results showed that stereoscopic motion can induce an adaptation aftereffect across a wide range of conditions and observers, provided that the duration of adaptation is sufficiently long and a perceptually salient test pattern is viewed. Motion adaptation was found to transfer between the stereoscopic and luminance domains [replicating a previous report by Fox, Patterson and Lehmkuhle (1982) Investigative Ophthalmology and Visual Science (Suppl.), 22, 144], suggesting that motion perception from stereoscopic (second-order) and luminance (first-order) attributes is mediated by a common neural substrate.

Adaptation, Ocular↗

PubMed1990

Music during learning of a tactual-spatial task affects later response generalization.

Equal numbers of men and women learned a finger maze, with half of the subjects initially using their right hands and the other half using their left hands. To reach criterion, subjects receiving music in the ear ipsilateral to the hand used required more trials than did those receiving no music. Furthermore, when the right hand ran the maze, music played to the ipsilateral ear also delayed learning, compared with music played contralaterally. Binaural music delayed learning when the left hand was used but not when the right hand was used. Possible causes of these effects are suggested. When subjects switched hands and relearned the maze, the number of trials to criterion depended on the group subjects were in during initial learning and not on the group they were in during the hand reversal (response generalization) trials. Although the music condition used determined the effect of music on initial learning and on response generalization, some evidence is presented that indicates that the two effects are not entirely interdependent and that they may even involve different mechanisms.

Adult↗

PubMedDate not supplied

Glaucoma detection using the GDx nerve fiber analyzer and the retinal thickness analyzer (RTA).

PURPOSE: To compare the ability of the nerve fiber analyzer (GDx) and the retinal thickness analyzer (RTA) to discriminate between glaucomatous and healthy eyes. METHODS: Thirty-seven glaucoma patients (early to moderate severity) and 34 healthy controls were included. Glaucoma patients were defined as those with two repeatable abnormal visual fields by automated perimetry within 1 year. All subjects were examined with a GDx scanning laser polarimeter and RTA. Twelve GDx retinal nerve fiber layer parameters and 12 RTA optic disk topography parameters were obtained. GDx and RTA measurements were compared between both experimental groups using t-tests. Areas under the receiver operating characteristic curves (AUROC) for discriminating between healthy and glaucomatous eyes using GDx and RTA parameters were calculated and compared, and sensitivities at >or=80% and >or=95% specificity were reported. RESULTS: Statistically significant differences between glaucomatous and healthy eyes were found for most GDx and RTA parameters. For GDx, the parameter with the largest AUROC for discriminating between healthy and glaucomatous eyes was the number (AUROC = 0.91, sensitivity = 85% at specificity = 84%, sensitivity = 73% at specificity = 95%). For RTA, the parameter with the largest AUROC was mean cup depth (AUROC = 0.79, sensitivity = 61% at specificity = 82%, sensitivity = 33% at specificity = 95%). The AUROC for the GDx number was significantly larger than the AUROC for RTA mean cup depth (p<0.05). CONCLUSIONS: GDx showed better discrimination and better sensitivities at fixed specificities than RTA. The currently available RTA optic disk analysis software likely cannot replace GDx RNFL analysis software for successful glaucoma diagnosis.

Area Under Curve↗