- ScB in math and AB in philosophy, Brown University, 1993
- PhD in computer science and engineering, University of Michigan, 2004
- Postdoctoral research in psychology/neuroscience, Princeton University, 2004-2011
The primary focus of my research in cognitive neuroscience is on the role of reward and cost monitoring in human and animal decision-making and interval timing. I attempt to model basic decision-making and timing circuits in the brain, using mathematical models that are as simple as possible, but that achieve enough functionality to account for critical features of both behavioral and physiological data. These models typically incorporate a layer of neural control mechanisms for optimizing the performance of the underlying decision-making circuits: that is, they help these circuits maximize rewards during simulated task performance. The resulting models generate precise, quantitative hypotheses about choices, response times and brain activity that I test with experiments in human behavior, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI).
I also focus theoretically on the composition of these basic circuits into larger models capable of more complex behavior. Such complex behavior is typically modeled with rule-based systems in the artificial intelligence tradition of computer science. My mathematical and computational modeling work in this area is intended to provide a theoretical link between different levels of description in psychology and neuroscience. At the neural level of description, individual neurons and neural populations are the objects of study by physiological methods, and dynamical systems and stochastic processes are theoretical tools of choice. At the psychological level of description, entities such as percepts, goals and actions are the objects of behavioral investigation, and symbolic cognitive architectures known as "production systems" are leading theoretical constructs. In order to unify these different approaches, I seek to explain how the psychological description level emerges from the neural level by building neural networks that emulate production systems.
I live in Oberlin with my wife Maureen and my son Ben.
NSCI 201: The Brain: An Introduction to Neuroscience
NSCI 211: Neuroscience Laboratory
NSCI 360: Introduction to Cognitive Neuroscience
NSCI 361: Cognitive Neuroscience Research Methods
Krueger, P., van Vugt, M., Simen, P., Nystrom, L., Holmes, P. and Cohen, J. D. (2017). Evidence accumulation detected in BOLD signal using slow perceptual decision making. Journal of Neuroscience Methods, 281, 1-12.
Simen, P. and Matell, M. (2016). How does time fly when we're having fun? Science, 354, 1231-1232. Perspective article previewing Soares, S., Atallah, B. V. and Paton, J. J. (2016), Midbrain dopamine neurons control judgment of time (2016), Science, 354,1273-1277.
Srivastava, V., Holmes, P. and Simen, P. (2016). Explicit moments of decision times for single- and double-threshold drift-diffusion processes. Journal of Mathematical Psychology, 75, 96-109.
Balcı, F. and Simen, P. (2016). A decision model of timing. Current Opinion in Behavioral Sciences, 8, 94-101.
Simen, P., Vlasov, K.* and Papadakis, S.* (2016). Scale (in)variance in a unified diffusion model of decision making and timing. Psychological Review, 123:151-181.
Patrick Simen Gives Talks in AustraliaMay 28, 2018
Assistant Professor of Neuroscience Patrick Simen spent three weeks in Australia supported by a Powers Travel Grant. There, he visited labs and gave talks at University of Tasmania in Hobart, University of Melbourne, University of New South Wales in Sydney, and University of Newcastle. Simen’s talks focused on the mathematical modeling of perceptual decision making by humans and understanding how the brain incorporates reward information and timing information into simple perceptual decisions.
Patrick Simen PublishesNovember 17, 2015
Assistant Professor of Neuroscience Patrick Simen’s article “Scale (In)Variance in a Unified Diffusion Model of Decision Making and Timing” was published in Psychological Review. The article was written with student coauthors Ksenia Vlasov '13 and Samantha Papadakis '15.
The article derives behavioral predictions from a simplified mathematical model of neural activity, and it describes the results of human behavioral experiments carried out by students at Oberlin to test these predictions. Most of the predictions held up, suggesting that timing and perceptual decision making depend on a common process in which neural activity builds up over time at a constant rate.
Patrick Simen Gives Talks in U.K. and TurkeyFebruary 11, 2015
Patrick Simen, assistant professor of neuroscience, recently gave a series of talks in the U.K. and Turkey regarding a mathematical model of neural processing in perceptual decision making and interval timing. In the U.K., Simen spoke at the University of Warwick, the University of Oxford, and the Gatsby Computational Neuroscience Unit of University College London. In Turkey, Simen spoke at Koç University in Istanbul.
Simen's travel was supported by a Powers Travel Grant, the funding from which also gave him an opportunity to spend time with and see the research facilities of his collaborators at the aforementioned institutions.