Online games: a novel approach to explore how partial information influences human random searches

Many natural processes rely on optimizing the success ratio of a search process. We use an experimental setup consisting of a simple online game in which players have to find a target hidden on a board, to investigate the how the rounds are influenced by the detection of cues. We focus on the search duration and the statistics of the trajectories traced on the board. The experimental data are explained by a family of random-walk-based models and probabilistic analytical approximations. If no initial information is given to the players, the search is optimized for cues that cover an intermediate spatial scale. In addition, initial information about the extension of the cues results, in general, in faster searches. Finally, strategies used by informed players turn into non-stationary processes in which the length of each displacement evolves to show a well-defined characteristic scale that is not found in non-informed searches.Comment: 17 pages, 10 figure

The time course of attentional and oculomotor capture reveals a common cause

Eye movements are often misdirected toward a distractor when it appears abruptly, an effect known as oculomotor capture. Fundamental differences between eye movements and attention have led to questions about the relationship of oculomotor capture to the more general effect of sudden onsets on performance, known as attentional capture. This study explores that issue by examining the time course of eye movements and manual localization responses to targets in the presence of sudden-onset distractors. The results demonstrate that for both response types, the proportion of trials on which responses are erroneously directed to sudden onsets reflects the quality of information about the visual display at a given point in time. Oculomotor capture appears to be a specific instance of a more general attentional capture effect. Differences and similarities between the two types of capture can be explained by the critical idea that the quality of information about a visual display changes over time and that different response systems tend to access this information at different moments in time

Brand search

Consumers frequently buy the products they find most easily. This has forced manufacturers and retailers to invest in package design, shelf layouts, and expensive advertising campaigns to facilitate findability of their products. Surprisingly, there is no research in marketing that investigates how consumers localize products, which we call brand search. This dissertation investigates the brand search process and develops a statistical model that describes the eye movements of consumers while they are searching for a specific product. The proposed model uncovers the search strategies of consumers and suggests which marketing tools manufacturers and retailers may use to influence this process.

Brand Search.

Consumers frequently buy the products they find most easily. This has forced manufacturers and retailers to invest in package design, shelf layouts, and expensive advertising campaigns to facilitate findability of their products. Surprisingly, there is no research in marketing that investigates how consumers localize products, which we call brand search. This dissertation investigates the brand search process and develops a statistical model that describes the eye movements of consumers while they are searching for a specific product. The proposed model uncovers the search strategies of consumers and suggests which marketing tools manufacturers and retailers may use to influence this process.

Backwards is the way forward: feedback in the cortical hierarchy predicts the expected future

Clark offers a powerful description of the brain as a prediction machine, which offers progress on two distinct levels. First, on an abstract conceptual level, it provides a unifying framework for perception, action, and cognition (including subdivisions such as attention, expectation, and imagination). Second, hierarchical prediction offers progress on a concrete descriptive level for testing and constraining conceptual elements and mechanisms of predictive coding models (estimation of predictions, prediction errors, and internal models)