Key words that describe work we have done or are currently conducting in the lab: Reinforcement learning, Decision-making, Categorization, Associative learning, Aging and cognition, Mathematical modeling, fMRI, Substance abuse, disinhibition, depression, Choking under pressure, Personality, Dopamine, Spontaneuous eye-blink rate, Gambling tasks, Bayesian statistics.
Dr. Worthy’s research uses behavioral methods, computational modeling, and neuroscience methods to examine the topics listed above. One broad focus of our research is to develop formal mathematical models of cognitive processes such as learning or decision-making that lead to testable predictions using behavioral or fMRI experiments. This line of work examines issues relevant to the fields of Cognition and Cognitive Neuroscience with the goal of fully understanding how and why people think and behave the way they do in different situations.
A second line of research utilizes cognition and cognitive neuroscience methods to examine individual differences in cognitive processes such as learning and decision-making. For example, how do clinical issues like depression or substance abuse affect the way people respond to rewards or punishments? Or, how does gender or aging affect decision-making? This line of work seeks to bridge gaps across sub-disciplines in psychology by applying cognitive neuroscience methods to questions traditionally examined by researchers in other fields.
Smayda, K.E., Worthy, D.A., & Chandrasekaran, B. (in press). Better late than never (or early): Late music training enhances decision-making. Psychology of Music. (5- Year Impact Factor: 2.357.
Pang, B., Blanco, N.J., Maddox, W.T., & Worthy, D.A. (2017). To Not Settle for Small Losses: Evidence for an Ecological Aspiration Level of Zero in Dynamic Decision-Making. Psychonomic Bulletin and Review, 24(2), 536-546. (5-Year Impact Factor: 3.650).
Byrne, K.A., & Worthy, D.A. (2016). Toward a Mechanistic Account of Gender Differences in Reward-Based Decision-Making. Journal of Neuroscience, Psychology, and Economics, 9, 157-168. (5-Year Impact Factor: 1.21).
Byrne, K.A.*, Davis, T., & Worthy, D.A. (2016). Dopaminergic genetic polymorphisms predict rule-based category-learning. Journal of Cognitive Neuroscience, 28, 959-970. (5-Year Impact Factor: 5.705).
Worthy, D.A., Davis, T., Gorlick, M.A., Cooper, J.A., Bakkour, A., Mumford, J., Poldrack, R.A., & Maddox, W.T. (2016). Neural correlates of state-based decision-making in younger and older adults. Neuroimage, 130, 13-23. (5-Year Impact Factor 7.289).
Byrne, K.A.*, Patrick, C.J., & Worthy, D.A. (2016). Striatal dopamine, externalizing proneness, and substance abuse. Effects of wanting and learning during reward- based decision-making. Clinical Psychological Science, 4, 760-774. (5-Year Impact Factor Not Yet Available).
Byrne, K.A.*, Norris, D.D.**, & Worthy, D.A. (2016). Dopamine, depressive symptoms, and decision-making: The relationship between spontaneous eyeblink rate, and depressive symptoms predicts Iowa Gambling Task performance. Cognitive, Affective, and Behavioral Neuroscience, 16,23-36. (5-Year Impact Factor: 4.319). *Awarded Best Article in Cognitive, Affective, and Behavioral Neuroscience for 2016.
Byrne, K.A.*, Tibbett, T.P., Carter-Sowell, A.R., Laserna, L.N.**, & Worthy, D.A. (2016). Ostracism reduces reliance on poor advice from others during decision- making. Journal of Behavioral Decision Making, 29, 409-418. (5-Year Impact Factor: 2.552).
Cooper, J.A.*, Worthy, D.A., & Maddox, W.T. (2016). Information about foregone rewards impedes dynamic decision-making in older adults. Aging, Neuropsychology, & Cognition, 23, 103-116. (5-Year Impact Factor: 1.711).