Functional MRI Speaker Series
Each year our laboratory provides opportunities for our users and researchers to learn about advances in fields related to Functional MRI.
Please see below the confirmed list of the speakers for this academic year. Additional detail about each talk and speaker will be provided as the date approaches.
Date, Time, and Location
All Speaker Series are held during the academic year on the second or third Tuesday of each month, from 3:30 - 5:00, at the Colloquium Room, located at East Hall, 4th floor, ***room 4464** note the slight change in location.
No RSVP is required. To be added to the Speaker Series email group and receive notifications about the speaker series talks, please contact the Administrator.
Academic Year 2013-2014 Speaker Series
Click here to see the abstract for Dr. Daphna Shohamy's talk.
Tuesday, March 25, 2014; 3:30 - 5:00
Daphna Shohamy, Ph.D., Assistant Professor, Department of Psychology, Columbia University
Specialization:approach that draws broadly on neuroscience to make predictions about cognition. These predictions are tested by combining fMRI with behavioral, pharmacological and patients studies in humans. Her work has focused on understanding how multiple brain systems for learning interact to support adaptive behavior, challenging traditional conceptions of learning and memory as depending on distinct and independent brain systems, and demonstrating the important link between how we learn, and how we use what we learn to guide decisions and actions.
Completed Talks - Academic Year 2013-2014 Speaker Series
Tuesday, October 8, 2013; 3:30 - 5:00
Jody Culham, Ph.D., Associate Professor, Brain and Mind Institute and Department of Psychology,
University of Western Ontario
Specialization: Dr. Culham's research uses functional magnetic resonance imaging (fMRI) to study human brain mechanisms subserving perception and action. Her lab aims to "bring the real world into the brain scanner" by using real objects (rather than images) and having participants perform real actions (such as reaching, grasping, or tool use rather than pantomimed actions) and finds that this yields qualitatively and quantitatively brain activation than less realistic situations.
Tuesday, November 5, 2013; 3:30 - 5:00
Bharat Biswal, Ph.D., Professor and Chair, Department of Biomedical Engineering, New Jersey Institute of Technology
Specialization: Dr. Biswal's research focuses on statistical and procedural methods of fMRI measurement to assess functional organization of the brain. His laboratory investigates resting state functional connectivity (RSFC) using fMRI methods in normal and diseased states. The RSFC imaging community has rapidly turned to clinical populations, noting the potential for developing MRI-based RSFC approaches as clinically valuable tools, capable of detecting pathological processes and monitoring both disease progression and treatment response. Having provided an initial assessment of test-retest reliability of RSFC measures, his lab continues to further its examination of "real world" factors likely to impact RSFC measures and examine these issues in healthy and patient populations.
Tuesday, January 14, 2014; 3:30 - 5:00
John Foxe, Ph.D., Professor, Department of Pediatrics and Department of Neuroscience, Director of Research of the Children's Evaluation and Rehabilitation Center, Albert Einstein College of Medicine, Yeshiva University
Specialization: Dr. Foxe is a translational researcher with a history of research studies on the basic neurophysiology of schizophrenia and autism. His work places special emphasis on the identification of endophenotypic markers in childhood neuropsychiatric diseases and in the linking of these biomarkers to the underlying genotype.
Tuesday, February 11, 2014; 3:30 - 5:00
Nathaniel Daw, Ph.D., Associate Professor, Center for Neural Science and Department of Psychology,
New York University
Specialization:Dr. Daw studies how people and animals learn from trial and error (and from rewards and punishments) to make decisions, combining computational, neural, and behavioral perspectives. Having trained partly in computer science, he is particularly interested in machine learning, reinforcement learning, and Bayesian techniques as frameworks for understanding and analyzing biological decision making. He therefore focuses on how the brain copes with the sorts of computationally demanding decision situations that his methods address, such as choice under uncertainty and in tasks (such as mazes or chess) requiring many decisions to be made in sequence.