Adaptation to multiple radial optic flows.

There is long-standing evidence suggesting that our visual system can adapt to new visual environments, like a single radial optic flow generated when driving (Brown, 1931; Denton, 1966). In fact, as we move through the environment multiple optic flows can be generated. For example, when driving, we are often exposed to more than one radial optic flow at the same time. In this thesis I investigate whether the visual system can simultaneously adapt to two radial motion optic flows. More specifically, I explored this issue in three ways. First, I investigated whether the visual system could – through a fast low-level process – adapt to two optic flows present at two specific locations in space. Second, I probed whether the visual system could – through a perceptual learning process – learn to associate two radial optic flows with their locations in space. Third, I examined whether the visual system could – through a perceptual learning process – learn to associate each of two radial optic flows with preceding eye-movements. With regard to the first issue, the results from Experiments 1 – 6 suggested following exposure to two radial motion stimuli, a fast low-level process in the visual system could adapt to a radial flow pattern at one location in space: the radial flow pattern generated by the most recently presented radial motion stimulus. With respect to the second issue, the results from Experiments 7 – 10 indicated that the visual system could not learn to associate specific locations with two different radial motion stimuli. Finally, regarding the third issue, the results from Experiment 11 suggest that the visual system can associate specific eye-movements with two different radial motion stimuli. Taken together, these results suggest constraints on the way in which the visual system can adapt to radial motion, and emphasize the importance of self-movement in generating adaption to new visual environments

Principles of Multisensory Behavior

The combined use of multisensory signals is often beneficial. Based on neuronal recordings in the superior colliculus of cats, three basic rules were formulated to describe the effectiveness of multisensory signals: the enhancement of neuronal responses to multisensory compared with unisensory signals is largest when signals occur at the same location ("spatial rule"), when signals are presented at the same time ("temporal rule"), and when signals are rather weak ("principle of inverse effectiveness"). These rules are also considered with respect to multisensory benefits as observed with behavioral measures, but do they capture these benefits best? To uncover the principles that rule benefits in multisensory behavior, we here investigated the classical redundant signal effect (RSE; i.e., the speedup of response times in multisensory compared with unisensory conditions) in humans. Based on theoretical considerations using probability summation, we derived two alternative principles to explain the effect. First, the "principle of congruent effectiveness" states that the benefit in multisensory behavior (here the speedup of response times) is largest when behavioral performance in corresponding unisensory conditions is similar. Second, the "variability rule" states that the benefit is largest when performance in corresponding unisensory conditions is unreliable. We then tested these predictions in two experiments, in which we manipulated the relative onset and the physical strength of distinct audiovisual signals. Our results, which are based on a systematic analysis of response time distributions, show that the RSE follows these principles very well, thereby providing compelling evidence in favor of probability summation as the underlying combination rule.</p