Back to first pageBack to first page Centre for Artificial Intelligence of UNL
Browse our site
You are here:

CENTRIA seminar: Searching for the Mechanisms of Cognition

Main informationBy: Clark Glymour (Carnegie Mellon University & Florida Institute for Human and Machine Cognition)

Date: Wednesday, 25th of November 2009, 14h00

Location: FCT/UNL, Seminar Room (Ed. II)
AbstractNeuroimaging (e.g. fMRI) data are increasingly used to attempt to
identify not only brain regions of interest (ROIs) that are especially
active during perception, cognition, and action, but also the
qualitative causal relations among activity in these regions (known as
effective connectivity; Friston, 1994). Previous investigations and
anatomical and physiological knowledge may somewhat constrain the
possible hypotheses, but there often remains a vast space of possible
causal structures. To find actual effective connectivity relations,
search methods must accommodate indirect measurements of nonlinear time
series dependencies, feedback, multiple subjects possibly varying in
identified regions of interest, and unknown possible location-dependent
variations in BOLD response delays. We describe combinations of
procedures that under these conditions find feed-forward sub-structure
characteristic of a group of subjects. The method is illustrated with an
empirical data set and confirmed with simulations of time series of
non-linear, randomly generated, effective connectivities, with feedback,
subject to random differences of BOLD delays, with regions of interest
missing at random for some subjects, measured with noise approximating
the signal to noise ratio of the empirical data. This talk is based on
work (forthcoming in NeuroImage) with Ramsey, Hanson, Hanson, Halchenko
and Poldrack.
Short-bioClark Glymour is Alumni University Professor at Carnegie Mellon
University and Senior Research Scientist at the Florida Institute for
Human and Machine Cognition. He has been a Guggenheim Fellow, a Fellow
of the Center for Advanced Study in the Behavioral Sciences, a Phi Beta
Kappa Lecturer, and is a Fellow of the Statistics Section of the
American Association for the Advancement of Science. In the past he has
worked on confirmation theories (Theory and Evidence, Princeton, 1980),
the history of psychiatry, quantum logic, cosmological lensing in
general relativity, the early history of the theory of relativity, and
on topics in formal learning theory. With colleagues at Carnegie Mellon
he developed the causal interpretation of Bayes net models and the first
feasible, correct search algorithms and methods of prediction for such
structures (Causation, Prediction and Search, Springer, 1993). More
recently he and collaborators developed Bayes net models of children’s
causal judgement (The Mind’s Arrows, MIT, 2003). His current work
concerns extracting neural processing mechanisms from functional
magnetic resonance imaging data. A volume of personal essays, Galileo in
Pittsburgh (not eponymous for the author) will be published by Harvard
University Press in 2010.
Centre for Artificial Intelligence of UNL
Departamento de Informática, FCT/UNL
Quinta da Torre 2829-516 CAPARICA - Portugal
Tel. (+351) 21 294 8536 FAX (+351) 21 294 8541

Fundacao_FCT