• Thursday, January 26th 2017 at 16:00 - 17:00 UTC (Other timezones)
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The use of brain imaging data to provide individualized information about a given individual has great potential, and is gaining traction as the field is becoming more comfortable with machine learning approaches. In this talk I will present some of the work we have been doing in this regard in the context of trying to both evaluate the utility of fMRI (e.g. static and dynamic whole brain connectivity) and multimodal imaging markers for identifying existing categories of mental illness and for predicting future outcomes, as well as work in trying to utilize brain imaging data to potentially help refine clinical categories.  I will also touch on some of the many challenges we still face and present some possible ways forward.

Vince Calhoun

Executive Science Officer and Director,
Image Analysis MR Research Professor of Translational Neuroscience
The Mind Research Network

Distinguished Professor
Departments of Electrical and Computer Engineering (primary)
Neurosciences, Computer Science, and Psychiatry
The University of New Mexico

Vince Calhoun – Individual subject classification/prediction from brain imaging data

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