Diffusion Model

See here for more about the diffusion model, here for information for non-specialists, and here for demonstrations.

Aging and Development

We currently have two grants from the National Institute on Aging funding research with older adults. Our R01 focuses on two-choice decision making involving numeracy, speed of processing, and perception. Our R56 grant explores modeling perceptual and numeracy decisions on a continuous scale. We also study these areas in older adults with Alzheimer’s disease and Mild Cognitive Impairment.

Clinical and Neuropsychology

Our NIA grants also focus on methodological research on modeling techniques aimed toward developing comprehensive decision making models for neuropsychological testing.

Human Neuroscience

Through collaborations with researchers at the University of Amsterdam, Columbia University, Brown University, and other institutions, we apply the diffusion model to accuracy data and reaction time distributions in the neuroscience domain, to relate theoretical processes to issues such as brain area activation.

Language Processing

We recently completed work on a grant funded by the Department of Education’s Institute for Educational Studies to examine the component processes of reading comprehension in struggling adult readers. Our research participants for these studies were adults of varying ages who have dropped out of high school and who read on a 4th to 9th grade level.

Applications

The diffusion model has been used to fit data from research in many applied domains, including:
aging
memory disorders
sleep deprivation
aphasia
hypoglycemia
anxiety and depression
children
neurophysiology
EEG
fMRI
language processing

Theory

Comparisons between individuals or groups of individuals usually focus on three main components of processing, identified by the diffusion model as drift rates, boundary settings, and nondecision times. Separating these three components means that within a task, it is possible that drift rates, boundary separation, and nondecision time do not correlate with each other. In other words, the values of none of the three components can be predicted from the values of either of the other two. The model allows determination of these components at the level of individuals and so can provide a picture of how the three components vary within and between age groups.