Alejandro Lleras - US grants

These NSF Starter Grant Funds will support one year of research infrastructure for a PI who has just completed an NSF Minority Post-Doc Fellowship and is now in a tenure-track position in Cognitive Neuroscience at the University of Illinois/Urbana-Champaign. Funds will provide research support for a proposed project examining the phenomenon of Rapid Resumption, which the PI discovered during his NSF Postdoctoral Fellowship at the University of British Columbia (NSF award #0309998). The initial experiments conducted are described in a paper accepted for publication in the journal Psychological Science, a leading peer reviewed journal in the field. The project focuses on Rapid Resumption, which refers to the phenomenon that humans are much better at resuming a search after an interruption, than they are at initially starting the search. The phenomenon is studied using a paradigm that the researchers call interrupted search. In this paradigm, participants are shown a visual search display for a brief period of time ("look" time = 100 ms) in alternation with a blank display ("wait" time = 900 ms). Because of the task difficulty, participants cannot finish the search with just one look at the display and therefore, are forced to interrupt their search behavior until the search display re-appears. Under such interruption conditions, the researchers showed that participants are very good at resuming their search (as measured by very fast reaction times following each display reappearance), thus the name of Rapid Resumption (RR). The results showed that when participants "rapidly resume" the search task, they do so with no previous conscious knowledge nor any intuition about the target identity. Thus, the researchers interpreted RR as a case of "rapid perception" that comes about because of interactions between visual processes (at play during search) and memory processes (at play during the interruptions). The goal of this project is to continue the study of this phenomenon so that a better understanding can be achieved on how vision and memory interact during search, and more generally, how these systems interact to provide a stable perceptual representation of the world around us. In this project, nine specific experiments are proposed to study RR (not including pilot and/or follow-up studies that may be necessary). The proposed work will advance our knowledge of an important everyday human behavior: how is it that humans search their environment, particularly under conditions where they have to repeatedly interrupt their search behavior (as we often must do). Second, it will provide us with new insights regarding the interactions between two important cognitive systems: memory and vision. Studying the nature of these interactions will also enhance our understanding of various other cognitive phenomena where these two systems are involved (e.g., Change Blindness, Inattentional Blindness, and Contextual Cueing among others). Third, this line of research is the first to investigate the act of "resumption", i.e., of reengaging on a previously interrupted task. While most research on the task-switching literature has found cognitive costs to switching from one task to another, this is the first research to show a natural ability for humans to go back to a previously started task. The principal investigator is committed to using research as an educational experience, both at the undergraduate and graduate levels and to disseminate research findings via presentations at professional conferences and publications in peer-reviewed journals. Also, by supporting this project, the NSF will be supporting the participation of Hispanics in the field of psychology. Last, the broader significance of this work extends to applied fields studying how human operators interact with complex systems, in which they often have to perform multiple tasks in tandem. The work has the potential to be extended in such a way that guidelines may be able to be developed that would alleviate some of the cognitive costs usually present in multi-task environments (for example, by allowing operators to quickly return to a previously unfinished task, so that they may rapidly resume it).

Imagine looking for a female friend of yours in a crowd filled with your male friends. How successful you are at finding your female friend this time around will partly determine how successful you will be in the future at the same task. The proposed research will examine the question of how perceiver's prior visual experience affects subsequent processes in which the perceiver attends to and ultimately sees the world. The research builds on the finding that by looking for a female (target) within a group of males (distractors), the visual attention system creates a bias against attending to male faces. Such an inhibitory bias against distractors persists over time and will consequently affect how the perceiver attends to any future scene that contains male faces or any stimuli within the same category of the distractor. The proposed research will use a variety of tasks to examine such biases and their consequences in visual processing, for example, whether the bias exists in the context of both spatial search (looking for an object) and temporal search (looking for the appearance of an object, within a stream of briefly presented objects).

The research project begins to address a fundamental question that has not received much research attention, that is, how our prior visual experience affects where, what and how we will look at a scene in subsequent visual information processing. The investigator is committed to integrating research and training activities in this CAREER project by using the project as a training opportunity in functional neuroimaging to study the brain mechanisms involved in creating these experience-based biases of attention. Further, the investigator will integrate research and education activities at the undergraduate and graduate levels, by actively involving students in the projects and by developing courses that will provide students with the tools and the theoretical knowledge for independent research. Finally, the project will also open the door to study attention-based deficits in humans and deficits in inhibitory control, such as Attention Deficit Disorders, Obsessive Compulsive Disorders, Depression, Executive Control Function Impairments, Schizophrenia and Dementia. As a researcher of Hispanic background, the investigator is in a unique position to improve minority representation and visibility in science in general and cognitive psychology in particular.

One of the most common visual tasks humans do is use their eyes to find objects in the world around them. This task involves analyzing all the visual objects and backgrounds in the scene. This is a complicated task because the brain has to separate objects from the background. The brain also has to process the color, shape, and size of all objects. The aim of the research is to build a mathematical model that can find objects in scenes, despite the difficulty of the problem. The model is inspired by the visual system. It uses two ways to process information. First, it uses central vision to get a fine-grained analysis of the object it is looking at. Second, it also uses peripheral vision, which is the area around and away from central vision. Peripheral vision can analyze several objects at the same time but is less precise than central vision. The ultimate goal of the project is to develop a free, open-source software toolbox that anyone can use. The toolbox will visualize how the visual system processes complex scenes. It will determine which regions in a scene should be ignored and which regions the eyes should focus on. One strength of the proposal is that it makes specific predictions that can be tested in various fields of neuroscience. It might also lead to improvements in visual aids for visually impaired individuals because it can guide users toward areas in a scene that are likely to contain the target object.

The starting point for the proposed work is a mathematically explicit model of goal-directed visual processing. The model incorporates two components of visual complexity: a parameter that measures the visual difference between objects in the scene and the object the observer is looking for (the target) and a parameter that measures how similar objects in the scene are to one another. The preliminary work indicated that the model is very capable of predicting how long it will take observers to find targets in visually complex scenes. The first two goals of the present research aim at evaluating other components of visual complexity to improve the model and its ability to predict visual processing in more complex visual scenes. The experiments in Goals 1 and 2 will help determine how to combine the visual qualities of objects (such as color, shape and texture) as well as how to account for the contrast between objects and their background. Results from Goals 1 and 2 will directly guide the development of a computational toolbox. The toolbox will allow users to visualize visual processing of simple and complex scenes and make predictions about where observers are likely to move their eyes as a function of their current goals (freely inspect the scene or find a specific object within it). The proposed work combines behavioral psychophysics and computational simulations (Goals 1 and 2), toolbox implementation and eye-tracking validation (Goal 3). The merits of the toolbox include the fact that: 1) it combines different types of visual processing (visual conspicuity contrast and target template contrast), 2) it can predict eye movements over different time scales, and 3) it can evaluate the contribution of these two types of processing to performance. This implementation is important because the contribution of these two processes is known to vary as a function of search goals (free-view vs. goal-directed) and search strategy adopted by observers (active search vs. passive search). Finally, another innovation of the toolbox is that it will be able to make predictions when targets are only defined in abstract terms, that is, when observers only have vague descriptions about the item they are supposed to find in the scene, which is particularly challenging for current computer vision systems to achieve.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.