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Marcel Just Ph.D. D.O. Hebb Professor of Psychology and the Center's Director. He received his Ph.D. from Stanford in 1972. His current research uses fMRI studies to provide key information about the cortical organization underlying various high-level cognitive processes. This information is used for developing a comprehensive theory of cognition, expressed as the 4CAPS computational theory that links cognition to brain activation. The content areas of the studies include language, visual thinking, automaticity in complex tasks, and autism. He is also co-Director of the Brain Imaging Research Center (BIRC).
Just, M. A., Cherkassky, V. L., Keller, T. A., Kana, R. K., & Minshew,
N. J. (in press). Functional and anatomical cortical underconnectivity in
autism: Evidence from an fMRI study of an executive function task and corpus
callosum morphometry. Cerebral Cortex. |
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William F. Eddy, Ph.D. Professor of Statistics at Carnegie Mellon, is an internationally recognized expert on statistical methodology, particularly for the analysis of functional neuroimaging data. He has published widely on the topics of statistical computation and statistical graphics, especially dynamic graphics. He was a founding editor of CHANCE magazine and of the Journal of Computational and Graphical Statistics. He has served as Chairman of the Committee on Applied and Theoretical Statistics of the National Academy of Sciences.
Eddy, W. F., Fitzgerald, M., Genovese, C. R., Mockus, A., &
Noll, D. C. (1996). Functional Imaging Analysis Software - Computational
Olio. in Proceedings in Computational Statistics, A. Prat (Ed.), Physica-Verlag,
Heidelberg. |
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Inmaculada Escudero, Ph.D. is a Visiting Scholar from Spain. She is Assistant Professor in the Department of General Psychology at Autónoma University of Madrid. Her current interests are in text comprehension, causal cognition, and neural correlates of inferencing. She is currently using fMRI with the aim of combining behavioral and neuroimaging techniques to further investigate the cognitive and neural bases of inference processes.
Escudero, I. & León, J.A. (in press). Discourse comprehension processes
between types of texts: A cross-language study based on elaborative inferences
generation. Journal of Cross-Cultural Psychology. |
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Zohar Eviatar, Ph.D. Dr. Eviatar is a member of the Institute for Information Processing and Decision Making, and of the Psychology Department at the University of Haifa. Her work revolves around brain mechanisms for language, with special emphasis on hemispheric functions in different languages and in special populations.
Sapir, S., Maimon, T., & Eviatar, Z. (2002)Linguistic
and Nonlinguistic Auditory Processing of Rapid Vowel Formant (F2)Modulations
in University Students with and without Developmental Dyslexia. Brain and
Cognition, 48(2/3), 520-526. |
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Chris Genovese, Ph.D. Associate Professor of Statistics at Carnegie Mellon, develops statistical models to account for fMRI phenomena. His approach uses both Bayesian and non-Bayesian techniques to apply content area knowledge and advanced mathematical techniques to enhance the value of statistical analyses.
Genovese, C. R., Noll, D. C., and Eddy, W. F. (1997). Estimating
Test-Retest Reliability in fMRI I: Statistical Methodology, Magnetic Resonance
in Medicine, 38, 497-507. |
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Cleotilde (Coty) Gonzalez, Ph.D. Associate Research Professor in the Department of Social and Decision Sciences. Director of the Dynamic Decision Making Laboratory. She earned her Ph. D. from Texas Tech University. Her research goals are: to understand decision-making cognitive processes in complex, real-time, dynamic environments and to help people make better decisions in these situations. Her research is mainly behavioral, using realistic computer simulations. Other methods include computational cognitive modeling, eye tracking, and fMRI.
Gonzalez C., & Wimisberg, J. (2007). Situation awareness in dynamic decision-making:
Effects of practice and working memory. Journal of Cognitive Engineering and Decision Making, 1(1), 56-74.
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Rajesh Kumar Kana, Ph.D., Assistant Professor at the University of Alabama at Birmingham. He is a former CCBI Post-Doctoral Fellow working on fMRI studies of autism. His primary research interest is to explore the neural substrates of social cognition and the impact of social cognition on language, communication and other cognitive functions in autism. He uses functional and structural MRI to study the neural architecture of autism.
Kana, R.K., Keller, T.A., Minshew, N .J., & Just, M.A. (2007). Inhibitory Control in High
Functioning Autism: Decreased Activation and Underconnectivity in Inhibition
Networks. Biological Psychiatry, 62, 198-206.
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Hideya Koshino, Ph.D., Assistant Professor at California State University at San Bernadino. He is a former CCBI Post-Doctoral Fellow working in the area of attention, executive function, spatial information, and autism. He earned his Ph.D. from the University of Kansas. He is continuing his CCBI work using tele-collaboration and summer visits.
Koshino, H., Carpenter, P. A., Cherkassky, V. L., Keller, T. A., & Just, M. A.
(2005). Functional connectivity in an fMRI working memory task in high-functioning autism.
NeuroImage, 24, 810-821.
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Jose A. León, Ph.D. is a Visiting Scholar from Spain. He is a Professor in the Department of Psychology at the Autónoma University of Madrid. Dr. León teaches courses in cognitive mechanisms of Language and Discourse Comprehension, Knowledge Acquisition and Reading Processes in text comprehension. His primary interests are in the cognitive mechanisms underlying language comprehension and discourse, inferences, causality, mental representations and reading. His current research is focused on fMRI studies in processing of backward/forward inferences and causal cognition.
León, J.A., Olmos, R., Escudero, Cañas, J.J. & Salmerón, L. (in press).
Assessing Short Summaries With Human Judgments Procedure and Latent Semantic Analysis
in narrative and expository texts. Behavioral Research Methods, Instruments, & Computers
Journal. |
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Beatriz Luna, Ph.D. is a developmental psychologist who is an assistant professor in the Department of Psychiatry at the University of Pittsburgh. She is interested in characterizing changes in brain function (using fMRI) that subserve cognitive development and are related to maturational changes in the neurophysiology of neocortex in late childhood and early adolescence using oculomotor tasks.
Luna, B., Sweeney, J.A.. (1999). Cognitive functional magnetic
resonance imaging at very-high-field: Eye movement control. Topics in Magnetic
Imaging, 10(1). 3-15. |
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Malcolm R. "Mick" McNeil, Ph.D. Professor and Chair, Department of Communication Science Disorders and Professor, Department of Otolaryngology; and Research Scientist, Pittsburgh VA Healthcare Systems. Dr. McNeil teaches course in cognitive mechanisms of speech and language comprehension and production and in neurological speech and language pathologies. His primary interests are in the cognitive mechanisms underlying the language impairments in persons with aphasia and motor speech disorders (the dysarthrias and apraxia of speech), and in their efficacious treatment. His current research is focused on: a) attention and resource allocation mechanisms and deficits in persons with aphasia, b) the development of a quality of life measurement instrument for stroke survivors (the Burden of Stroke Scale), c) instrumental biofeedback mechanisms for the treatment of apraxia of speech, and d) the impact of peripheral neural hearing loss on central auditory language processing in non-brain-injured adults and persons with aphasia.
McNeil, M.R. & Pratt, S.R. A Standard Definition of
Aphasia: Toward a general theory of aphasia. Aphasiology, 15,
10/11, 901-911, 2001. |
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Nancy J. Minshew, Ph.D. Professor of Psychiatry and Neurology at the University of Pittsburgh School of Medicine, is a research neurologist who has developed a theory of cognitive and neural deficits in autism. Her research, conducted in collaboration with her extensive research team, has completed large-scale neuropsychologic studies, eye movement and posturography studies, structural MRI, and MRS (magnetic resonance spectroscopy) of high functioning autistic individuals. This research has resulted in the definition of deficits in complex cognitive abilities across domains with the exception of the visuospatial domain and evidence of neocortical systems as the primary site of CNS dysfunction in autism.
Minshew, N.J., Luna, B., & Sweeney, J.A. (1999). Oculomotor
evidence for neocortical systems but not cerebellar dysfunction in autism.
Neurology, 52, 917-922. |
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Tom Mitchell, Ph.D. Professor in the Department of Computer Science and Director of the Center for Automated Learning and Discovery (CALD). One of the leading figures in machine learning, his research employs various statistical and analytic methods in an effort to construct computer programs (algorithms) that learn from experience. His work with the CCBI conjoins machine learning with neuroimaging to help form theories of brain function, using classifiers to find stimulus unique patterns of brain activation. In essence, the machine learning algorithms are being trained to detect cognitive states. He also directs CALD, an interdisciplinary center whose mission is to invent new methods for using historical data to improve future decisions.
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Sharlene Newman, Ph.D. Assistant Professor of Psychology at Indiana University. She earned her Ph.D. at the Biomedical Engineering Department of the University of Alabama at Birmingham and is a former CCBI Post-Doctoral Fellow. Her research interests are in the areas of fMRI of language processes, problem-solving, and planning.
Just, M. A., Newman, S. D., Keller, T. A., McElaney, A., & Carpenter,
P. A.. (2004) Imagery in sentence comprehension: An fMRI study. NeuroImage.
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Walter Schneider, Ph.D. Professor of Psychology at the University of Pittsburgh and Director of the Center for the Neural Basis of Cognition. Dr. Schneider investigates dynamic cortical processing through human behavioral and brain imaging studies, as well as computer simulation models. Behavioral and brain imaging studies focus on understanding the processes involved in human learning and attention allocation. His research examines cortical areas involved in both learning and sensory processing. The data from these studies is used to detail how rapidly and in what forms attention moves and what are the component structures of learning (goal popping, memory retrieval, feedback processing). His CCBI-related work is on fMRI studies of automaticity in high level cognition, bringing his pioneering expertise in automaticity to apply to cortical function in complex tasks.
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Christian Schunn, Ph.D. Assistant Professor of Psychology and of the Intelligent Systems Program at the University of Pittsburgh, as well as a Research Scientist in the Learning Research and Development Center. His research focuses on many aspects of scientific discovery, most commonly the cognitive processes involved in the design of experiments, the development and use of experimental paradigms, and the development and change of representations of data. He asks such questions as “Can domain-general reasoning skills be taught?”, and to answer this question, has focused specifically on research methods courses in psychology. This work has led to a number of innovations in course and lab structure. Other areas of his research include understanding how strategies are chosen, understanding causal reasoning and its relationship to concept structure, and how knowledge transfers across situations. His work with the CCBI explores the impact of learning and task demands on neural activation in a spatial reasoning (navigation) task in a Quake-implemented environment.
Schunn, C. D., Lovett, M., & Reder, L. M. (2001). Awareness
and working memory in strategy adaptivity. Memory & Cognition, 29(2),
256-266. |
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Svetlana Shinkareva, Ph.D. Assistant Professor at the University of South Carolina. She is a former CCBI Post-Doctoral Fellow. Dr. Shinkareva’s research focuses on the development and application of quantitative methods to neuroimaging data. Her current interests include applying machine learning methods to fMRI data to study the neural basis of semantic knowledge representation.
Shinkareva, S.V., Mason, R.A., Malave, V.L., Wang, W., Mitchell, T.M., et al (2008). Using fMRI brain activation to identify cognitive states associated with perception of tools and dwellings. PLoS ONE 3(1): e1394. |
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Bob Siegler, Ph.D. Professor of Psychology at Carnegie Mellon University. His research focuses on the growth of problem solving and reasoning skills throughout childhood. Three areas of particular interest are strategy choices, long-term learning, and educational applications of cognitive-developmental theory. Past work has led to the development of computational models of how children make intelligent strategic decisions, while current work focuses on developing tests that reveal indicators for later difficulty in mathematics learning. His CCBI-related work uses fMRI to examine the development of the concepts for space, distance, and time in autistic children and normal controls.
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John Sweeney, Ph.D. Professor of Psychiatry, Neurology and Psychology at the University of Illinois, works in the area of human neurophysiology, focusing on executive and attentional factors regulating the control of eye movements, as well as the basic cortical sensorimotor systems involved in eye movement control. He directs the Center for Cognitive Medicine, which conducts a program of research investigating the clinical application of fMRI with schizophrenia, autism, traumatic brain injury, mood disorders and the pharmacologic enhancement of cognitive abilities.
Sweeney JA, Luna B, Srinivasagam NM, Keshavan MS, Schooler NR,
Haas GL, Carl JR: Eye tracking abnormalities in schizophrenia: Evidence
for dysfunction in the frontal eye fields. Biological Psychiatry 1998 Jan;44(8):698-708
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