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Felix A. Wichmann

Publications and source records attributed to Felix A. Wichmann.

20 records · Page 2Linked to original sources

Influence of initial fixation position in scene viewing

During scene perception our eyes generate complex sequences of fixations. Predictors of fixation locations are bottom-up factors like luminance contrast, top-down factors like viewing instruction, and systematic biases like the tendency to place fixations near the center of an image. However, comparatively little is known about the dynamics of scanpaths after experimental manipulation of specific fixation locations. Here we investigate the influence of initial fixation position on subsequent eye-movement behavior on an image. We presented 64 colored photographs to participants who started their scanpaths from one of two experimentally controlled positions in the right or left part of an image. Additionally, we computed the images' saliency maps and classified them as balanced images or images with high saliency values on either the left or right side of a picture. As a result of the starting point manipulation, we found long transients of mean fixation position and a tendency to overshoot to the image side opposite to the starting position. Possible mechanisms for the generation of this overshoot were investigated using numerical simulations of statistical and dynamical models. We conclude that inhibitory tagging is a viable mechanism for dynamical planning of scanpaths.

q-bio.NC↗

Spatial statistics and attentional dynamics in scene viewing

In humans and in foveated animals visual acuity is highly concentrated at the center of gaze, so that choosing where to look next is an important example of online, rapid decision making. Computational neuroscientists have developed biologically-inspired models of visual attention, termed saliency maps, which successfully predict where people fixate on average. Using point process theory for spatial statistics, we show that scanpaths contain, however, important statistical structure, such as spatial clustering on top of distributions of gaze positions. Here we develop a dynamical model of saccadic selection that accurately predicts the distribution of gaze positions as well as spatial clustering along individual scanpaths. Our model relies on, first, activation dynamics via spatially- limited (foveated) access to saliency information, and, second, a leaky memory process controlling the re-inspection of target regions. This theoretical framework models a form of context-dependent decision-making, linking neural dynamics of attention to behavioral gaze data.

q-bio.NC↗