George A. Alvarez - US grants

[unreadable] DESCRIPTION (provided by applicant): The proposed studies are intended to contribute to our understanding of the processes of encoding and storing information in visual short-term memory and is concerned with four specific aims. The first aim is to investigate the nature of the information limit on visual short-term memory. Multiple methods will be employed to measure the amount of information stored per object and the maximum number of objects that can be stored in memory for several different classes of objects. If there is a limit to the total amount of information that can be stored in memory, then as the amount of information stored per object increases, the total number of objects that can be stored in memory should decrease. The second specific aim is to determine whether basic features of an object can be selectively encoded into memory. While performing a memory task for a particular target feature (e.g., color) subjects will be tested unexpectedly on an irrelevant feature (e.g., orientation). If only task-relevant features are stored, then memory performance for task-irrelevant features should be at chance. The third specific aim is to determine whether visual memory stores boundary features more efficiently than surface features. Finally, the fourth specific aim is to investigate the relationship between limits on attentional selection and memory capacity. [unreadable] [unreadable]

How does learning mathematics in a spatial format affect children's understanding of number, and the basic cognitive processes that support it? The proposed project will explore this question by investigating users of 'mental abacus' a system of mental arithmetic practiced by children throughout the world. Children who use mental abacus first learn to do arithmetic on a physical device, and then internalize these computations by creating a mental image of an abacus. By moving beads in their mental representation, children perform computations like addition, subtraction, multiplication, and division, all with astonishing speed and accuracy. In three sets of experiments, we will explore how visualizing beads on an abacus to do arithmetic affects abilities such as estimation and comparison of amount, visual attention and working memory, and children's understanding of early numerical concepts, such as addition, place value, and commutativity. Participants will include children in Gujarat Province, India, who are highly trained in abacus, as well as children and adults in the US. Our hypothesis is that learning to do math in a spatial format facilitates not only early understanding of number, but also lays the groundwork for learning advanced mathematics, by training the underlying cognitive processes that support numerical reasoning.

Imagine you are driving in the middle lane of a busy three-lane highway, approaching your exit, with the radio on so you can hear the weather report, and with your children in the backseat calling for you. How are you going to manage this situation? Will you ignore all but one thing, and pay full attention to the road signs to determine when to switch lanes, or to cars in the rearview mirror as you change lanes, or to the radio, or to your children? Or will you somehow divide your attention between all of these incoming streams of information? What is the optimal thing to do under these circumstances, and can you do it? With the support of an NSF CAREER award, Dr. George Alvarez at Harvard University will examine whether people can optimize the way they divide their attention, and how this affects their ability to see and accurately report information in their field of view. We are limited in our ability to attend to multiple things at once, and given the limits on our attention, there is an optimal strategy for how to pay attention in any given situation. This optimal strategy could involve flexibly distributing attention (e.g., paying 40% to the road signs, 40% to cars in other lanes, and 20% to the children in the backseat), or using clever strategies for combing information (e.g., you can get the gist of whether the chatter in the backseat requires your immediate attention without paying attention to each individual voice). The proposed research will examine whether, and how, these different strategies are employed to optimize the use of our limited attentional resources.

A basic level understanding of how people optimize the use of their limited attentional resources opens the door to studying the extent to which attention deficits in humans are due to sub-optimal use of available resources. Thus, the results of the research will have implications for disorders such as Attention Deficit Disorder, Obsessive Compulsive Disorder, Autism, Schizophrenia, Dementia, or disorders due to stroke or brain damage, such as Visual Neglect or Executive Dysfunction. In addition, Dr. Alvarez will use the research project as an opportunity to mentor a cadre of undergraduate students from underrepresented groups. Dr. Alvarez helps coordinate a summer research program that places students in labs, providing them with hands on training in conducting behavioral research. As a professor of Hispanic background, Dr. Alvarez is in a unique position to increase minority representation and visibility in the brain and cognitive sciences.

DESCRIPTION (provided by applicant): An important, yet relatively unexplored aspect of learning and working memory is how, and under what conditions, a perceiver can capitalize on regularities in the environment to remember more information. How can our prior experiences influence how we remember our current experiences? How can such influences be exploited as tools to enhance cognitive processes in those with learning disabilities (e.g., in Autism), or to assist those with memory deficits? To address these issues, this proposal makes use of a powerful form of implicit learning known as visual statistical learning. Previous research has shown that observers are extremely sensitive to regularities in the visual environment (e.g., quickly learning that 'A'is usually followed by 'B'). Surprisingly, this learning is often completely implicit: when asked to explicitly report these regularities observers perform at chance. This implies that visual statistical learning is a powerful process that operates automatically without our intent or conscious control. However, it remains unclear what the benefits of visual statistical learning are for memory processes. In particular, statistical regularities are a form of redundancy, and to the extent that human memory compresses redundant information, learning regularities between objects should enable observers to remember information about more objects. The proposed experiments have three aims: (1) to determine whether visual statistical learning enables observers to compress information and remember more, (2) to determine the "units" of compression, and (3) to determine the "level" at which compression occurs. To investigate these issues, observers will be required to remember simple objects. Over time, some observers will see patterns in the input (e.g., 'A'often occurs with 'B'), while other observers will see random input. To the extent that observers can learn regularities, and compress them to form more efficient memory representations, observers in the patterned group should remember details about more objects. Previous research has not directly explored how visual statistical learning impacts the capacity of working memory, and the proposed studies will provide important insight into the interactions between learning and memory. PUBLIC HEALTH RELEVANCE: An exciting aspect of this proposal is that it promises to inform basic science by studying how statistical learning impacts working memory and cognition, and therefore has potential to increase understanding of mental illnesses with learning or memory related symptoms. For instance, individuals with Autism have certain learning deficits, but it is unknown whether statistical learning, and its interaction with working memory, is impaired in Autism as well. The proposed studies lay the groundwork for future clinical translational research addressing such questions.