Brown, Frederick M.
Ph.D., 1971, University of Virginia
f3b@psu.edu
Frederick Brown investigates the neurobehavioral rhythms of life that underlie all human activity. They include daily (circadian, sleep/wake), monthly (lunar phase, reproductive), and seasonal ("wintertime blues") rhythms. His research involves measuring the daily rhythms of cognitive and performance variables, and determining any effects on them from fatigue and sleep deprivation. His collaborators include human factors and engineering colleagues at the Pennsylvania Transportation Institute, and scientists at the Walter Reed Army Institute for Research, Silver Spring, MD.
Carlson, Richard A.
Ph.D., 1984, University of Illinois at Urbana-Champaign
racarlson@psu.edu
Richard Carlson is studying how individuals control their mental activity in complex tasks such as symbolic and spatial problem solving and reasoning. His current research is concerned primarily with the roles of spatial and temporal frames of reference in the conscious control of skilled mental activity. His major conceptual focus is developing a theory of consciousness that relates conscious agency and information processing accounts of cognitive control. This theory emphasizes the parallel structures of perceptual, symbolic, and emotional awareness.
Dennis, Nancy A.
Ph.D., 2004, The Catholic University of America
nad12@psu.edu
My research focuses on elucidating the cognitive and neural mechanisms that support learning and memory in young and older adults. I employ both behavioral and neuroimaging methods, including diffusion tensor imaging (DTI) and functional MRI (fMRI) to explore the interaction of cognitive and neural processes involved in episodic memory. While my primary research investigates the neural correlates of item memory during both encoding and retrieval, my research also examines the neural processes associated with relational memory and false memory. With respect to cognitive aging, my research concentrates on the examination of age-related neural markers of cognitive decline, as well as mechanisms for neural compensation. Other lines of research include both implicit learning and genetic neuroimaging.
Gilmore, Rick O.
Ph.D., 1997, Carnegie Mellon University
rog1@psu.edu
Rick Gilmore's research asks three questions: What are the representations underlying spatial perception and action? How are these representations instantiated in the brain? How do they develop, and why? The developmental cognitive neuroscience approach he takes to these questions combines insights from behavioral studies, biological experiments, and computational models. The ultimate aim is a unified, biologically and computationally plausible, account of the development of spatial perception and action early in life.
Kroll, Judith F.
Ph.D., 1977, Brandeis University
jfk7@psu.edu
Judith Kroll is studying the cognitive processes that accompany the development of proficiency in a second language. Her work is focused on topics such as how adults learning a second language become able to think abstractly in their second language, how the representation of the two languages by fluent bilinguals is influenced by their acquisition history, and how individual differences in language processing in the first language predict second-language performance. Her research group has ongoing collaborations with colleagues in The Netherlands in Amsterdam and Nijmegen.
Li, Ping
Ph.D., 1990, Leiden University
pul8@psu.edu
Ping Li examines the computational and neural processes that underlie the acquisition and representation of monolingual (native) and bilingual (native and non-native) languages. It focuses on the dynamic changes that occur in the language learner and the dynamic interactions that occur in the competing language systems over the course of learning. In particular, his research attempts to identify the computational mechanisms and the neural structures that characterize the interactive dynamics underlying the learning of one or multiple lexical systems (e.g., words acquired early by children and by Chinese-English bilinguals). Researchers in his lab use self-organizing neural networks to simulate lexical development, and use ERP and fMRI methods to investigate the neural mechanisms that subserve lexical organization and competition in the monolingual and the bilingual brain.
Rosenbaum, David A.
Ph.D., 1977, Stanford University
dar12@psu.edu
David Rosenbaum is interested in the cognitive substrates of skilled performance, especially those underlying human motor control and perceptual-motor integration. He focuses on the planning and control of manual performance (mainly reaching and grasping objects), using computer modelling and recording of behavior. He also works on timing and rhythm, including issues related to rhythmic influences on basic cognitive processes.
Weiss, Daniel
Ph.D., 2000, Harvard University
djw21@psu.edu
Daniel Weiss is interested in the cognitive mechanisms underlying language acquisition. This work focuses on statistical learning mechanisms that have been implicated in the learning of phonetic categories, as well as word segmentation and rule-learning. He uses a comparative approach in order to determine whether these abilities are unique to humans. His research compares the abilities of infant and adult humans with the abilities of non-human primates. In addition, he is interested in animal communication, particularly vocal learning and recognition.
Wenger, Michael J.
Ph.D., 1994, Binghamton University, State University of New York
mjw19@psu.edu
Michael Wenger's research focuses on the dynamic interactions of perceptual and memory processes, facial perception and memory, perceptual and cognitive expertise, and latency-accuracy relations in perception and cognition. Central to each of these research endeavors is a commitment to developing and testing formal (mathematical and computational) models of the hypotheses and phenomena under consideration. Current work emphasizes the use of computational representations of circuits in the visual system hypothesized to be involved in the acquisition and expression of perceptual skill. These computational models are compared against human behavioral and electrophysiological (EEG) data.