Robin D. Thomas - US grants

DESCRIPTION (Applicant's Abstract): Cognitive functioning that can correctly process the structure in the environment is one of the hallmarks of mental health. Failing to mentally represent properties in the world accurately often indicates the presence of mental illness. Consequently, before psychologists can recognize when such failures occur they need to understand how normal cognitive processes operate. One important, perhaps fundamental, cognitive process is that of categorizing objects that are alike in some way into a common group, such as classifying an animate, winged object as a 'bird'. One reason to categorize an object as a kind of something is to distinguish the object from other objects that are not of the same kind (e.g., the object is a 'bird' and not a bat'), A different motivation would be to use information derived from knowledge of category membership to make predictions about the features of the object immediately at hand (e.g., if this is a bird then it is likely to sing and lay eggs). Underlying all of this is the need for perception of the attributes of an individual object so that this categorization, whatever the motivation, can take place. Researchers have assumed that this perception occurs prior to the categorization of the object and is mediated by a largely fixed set of features comprising the object. Recently, some researchers have questioned the independence of the perceptual process from the categorization process and the fixed-feature set hypothesis. That is, how we process attributes of an object, such as its size, color, shape, etc., may be influenced by the category into which we place it and what we know about that category. This proposal describes several experiments in which the structure of categories of simple visual objects is manipulated so that the effects on the low-level perception of the properties of those objects can be assessed. This proposal also contains experiments which assess how perceptual phenomena, akin to visual illusions, may alter or distort the memories of category properties. The goal is to establish the existence of these phenomena, and to accurately measure, in quantitative detail, their type and degree so that future models of this interactive process is possible.

Models are tools that scientists use to make sense of data, explore new ideas, and generate new avenues of research. Some models are physical or biological, like the solar system model of the atom or the biologist's trusty fruit fly. But many scientific models take the form of a set of equations or algorithms that can be implemented as computer programs. Such computational models can be extremely useful in deciding between competing theories and ideas, because their corresponding computer programs can be pitted against each other to see which one provides a better account of the data. The problem is that often it is not so easy to determine what a "better" account is. A model might capture one data set very well, but provide little insight beyond that particular data set. Since scientific theories are usually concerned with general principles rather particular sets of data, it is useful to have methods that are sensitive to more than just the fit of a model to a given data set.

With support of the National Science Foundation, Dr. Thomas will develop methods that can be used broadly to test models against one another on the basis of model form and function, rather than just fit to data. These methods will be developed in the context of theories of human pattern recognition, a topic that is general enough to be relevant to range of areas in the behavioral and social sciences. From hearing a word to driving a car to making an investment, the ability to detect and recognize patterns in the world is central to human activity. The importance of this topic has led many researchers to formulate many computational models that capture theories about how patterns are recognized in the brain and mind. Therefore this topic domain provides an apt testing ground for the development of methods that will help to identify theories that are and are not worth pursuing as evidence comes to light.

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5

How neural activity in the brain translates into the "mind" is a critical question facing psychology and cognitive science. With support from the National Science Foundation, the Center for Psychophysiology at Miami University will acquire two high density electroencephalography (EEG) systems to help answer this question.

Housed in the recently constructed Psychology Building on the Oxford campus, the Center for Psychophysiology will serve to further Miami University's dedication to high-quality teaching and research. The Center will enable access to modern cognitive and behavioral neuroscience technologies and will build expertise in their use. The acquisition of these systems will allow researchers from a broad range of disciplines to augment their current behavioral methodologies with a variety of noninvasive means of measuring and modeling human brain function.

The continuous, scalp-recorded EEG and its derivative, event-related potentials (ERP), provide windows into the brain activities that underlie psychological processing. This technology measures brain activity by recording rapid changes in the electromagnetic fields generated by neurons as they engage in processing. The acquisition of high-density (64 channel and 256 channel) EEG systems will enable researchers at the Center to identify the sources of this electrophysiological activity. By taking advantage of recent advances in mathematical modeling techniques, this spatial information can be used to localize activity observed in the EEG signal to specific parts of the brain, and thus clarify the relationship between neural activity and psychological function.

Planned projects span multiple disciplines, some of which will involve cross-disciplinary collaborations. These include relating neural activation to working memory and category learning, identifying the neural correlates of value in decision-making, measuring brain activities during play in young children, and contrasting the neural components of same-race and other-race face recognition. Researchers planning to use the new equipment come from eight departments spanning all five divisions of the Miami University campuses including a regional campus in Hamilton.

In addition to supporting faculty and student research efforts, this acquisition will also enable the Center to offer a unique undergraduate curriculum in psychophysiology and cognitive neuroscience that embodies the "Student as Scholar" learning model. Students will obtain hands-on experiences in the collection and analysis of EEG data, broaden that knowledge to include applications outside of their own specific disciplines, and design and conduct independent research projects in their final year of study. This tiered curriculum initiative is one-of-a kind in its focus on undergraduate training as it relates to science, technology, engineering and mathematics (STEM) disciplines, and is exemplary of Miami's goal of creating the engaged learner.

Recent advances in decision research seek to identify the cognitive and brain processes that cause people to choose one option over another. This is notable because it allows us to understand and predict not just what decisions people make, but why they make them. One significant limitation of this more meaningful work is the lack of empirical methods that are capable of revealing the inner workings of an individual's thinking while they choose among options. The current work remedies this shortcoming by examining a new measure of choice behavior -- the movement of a person's hand, arm, or other effector, while they are trying to pick one option over others in tasks requiring them to make choices. Human movement, often referred to as response dynamics in this context, has become an exciting new metric for a number of cognitive processes thought to be hidden from view inside the "black box" of the mind. The innovation of the current research program is to validate and extend this methodology using computational modeling, neuro-electric brain imagery, and additional physiological measures (e.g., eye-tracking) to further reveal how response dynamics can inform scientists about how people make choices.

There are many opportunities for broader impact of this research beyond the immediate scope and research questions. First, the systematic and comprehensive investigation of the limitations, qualifications, and generalizability of the response dynamics paradigm can influence other domains where it has been employed, including: categorization, speech perception, stereotyping, deceptive intentions, learning and memory, and perception of culture, race and gender. Second, the theoretical questions addressed can make significant contributions to specific content areas and real-world issues. Any situation where society might benefit from better understanding of how individual decision-making actually occurs -- such as public policy making, educational reform, medical care choices, etc. -- stands to gain from our theoretical advances. For example, we would have new potential to target interventions to improve suboptimal or deviant decision making, and/or to structure decision situations to account for people's natural tendencies.