Projects

Visual Psychophysics of Size Perception

Visual size illusions, in which the size of an object is perceived to be larger or smaller than it really is, have been utilized for over a century to study the process of size perception. We recently described a novel illusory effect that is well-illustrated by our Dynamic Ebbinghaus illusion (Mruczek et al., 2015; see video to left). In this illusion, the combination of expanding inducers and target motion yields a stronger illusory effect than the classic, static illusion; in contrast, the expanding inducers in the absence of additional target motion yields a weaker effect than the static illusion. Thus, the effect depends critically on the interaction between size-contrast and motion leading to changes in the contributions of different cues (e.g., angular size and relative size) to perceived size.

We are currently exploring the effects of motion dynamics on other classic size illusions, such as the Corridor and Ponzo illusions.

Tripolar EEG for Studies of Visual Perception

Electroencephalography (EEG) is a non-invasive methods suitable for studying human visual perception. However, EEG is limited in spatial resolution and is subject to artifacts from eye and muscle movements. Tripolar concentric ring electrodes offer a potential solution to both of these issues (Koka & Besio, 2007).

In collaboration with colleagues at the University of Nevada, Reno, we are currently testing the suitability of tripolar EEG for the study of visual-evoked potentials (VEPs). In particular, we are applying multivariate statistical analyses to quantify how the information content of the tripolar EEG signal compared to that collected from conventional disc electrodes.

Human Electrophysiology of Predictive Coding

Visual perception is thought to arise from the coordinated activity of neurons across multiple brain regions. Predictive coding models (Friston, 2005) posit a hierarchy of feedback (signaling predictions, or the expected sensory input) and feedfoward (signaling error, or the difference between the prediction and the sensory input) connections within the visual system carrying distinct types of information related to perception. The predictions are updated so as to minimize the error signals that propagate through the visual system.

We are currently testing aspects of this model as it applies to human object recognition using high-density electroencephalography (EEG) in humans.