Graduate Student Seminar

Seminar | March 4 | 11:10 a.m.-12:30 p.m. | 489 Minor Hall

 Katharina Foote, Roorda Lab; Liz Lawler, Silver Lab

 Neuroscience Institute, Helen Wills

Katharina Foote's Abstract
Structure and function in retinitis pigmentosa patients with mutations in RHO vs. RPGR

Retinitis pigmentosa (RP) causes slow, progressive, relentless death of photoreceptors. In order to gain insight on how cone survival differs between different mutations affecting rods vs. affecting rods and cones, we measured cone structure and function in patients with mutations in rhodopsin (RHO), expressed only in rods, and patients with mutations in RPGR, expressed in both rods and cones. Cone structure was studied with adaptive optics scanning laser ophthalmoscopy (AOSLO) and function was measured with microperimetry using Macular Integrity Assessment and AOSLO microperimetry. Cone density was measured as close as possible to each test location and the ratio of cone sensitivity to density was computed. Normal subjects showed significantly greater sensitivity per cone compared with RP patients with RHO mutations, while sensitivity was even lower in patients with RPGR mutations. Using high-resolution microperimetry, we hope to provide insight into mechanisms of cone degeneration in patients with different forms of RP.

Liz Lawler's Abstract
Unconscious learning of simple stimulus sequences leads to perceptual suppression of the unexpected

Perception relies on making predictions about the environment, and these predictions are informed by prior experiences. I will discuss how various methods of creating a prediction affects subjects’ perceptual selection of information from the visual environment. Next, I will present a study that examines the effects of stimulus complexity and the method of inducing predictive context on perceptual selection. Specifically, I used statistical learning to teach observers arbitrary sequences of Gabor gratings of various orientations and then used binocular rivalry to measure the effects of this statistical learning on perceptual selection. Finally, I will show that statistical learning of recently acquired, arbitrary sequential structures impacts subsequent visual perception and awareness, causing the visual system to prioritize the expected stimuli while suppressing unexpected stimuli.

 nrterranova@berkeley.edu