Grant: Discovery Grants Program - Individual

Our visual environment contains a great deal of redundancy, especially where sets of similar items are concerned. For example, when searching for a parking spot in a crowded lot, we likely do not attend to and remember every car in the lot because this is not necessary for the task at hand. Instead, researchers now believe that at any one time, the brain rapidly calculates certain properties of the set that are important for understanding the meaning of the scene, and for accomplishing goals. In this example, as we are driving through the crowded parking lot watching carefully for pedestrians and other cars, it would be helpful to be able to rapidly estimate the average size of the vehicles in a portion of the lot in order to decide whether there is likely to be a space that is appropriate for our vehicle. In the proposed work, I will examine whether this rapid averaging process can be carried out when attention is unavailable, and how it might contribute to performance of everyday tasks like the one described above. In the short-term, my goal is to establish the utility of several promising indirect measures of size averaging that are less susceptible to contamination from response biases and sophisticated guessing strategies than currently-used methods. This will be accomplished by testing perception and memory for the average size of displays indirectly using reaction time measures in tasks that do not explicitly require people to estimate average size. Because size averaging is not part of the task instructions, it is unlikely that performance will reflect the use of size averaging strategies. Ultimately, I hope to integrate my work in size averaging with findings from well-established paradigms to yield a better understanding of how we use attention and perception in ordinary tasks we encounter in the real world.