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Decoding and Predicting Attention

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A School of Psychology Colloquium by Marvin Chun, Yale University

Major advances in functional magnetic resonance imaging (fMRI) have given psychologists and neuroscientists unprecedented access to the workings of the human mind.  Incorporating tools from machine learning and computational vision, we are using fMRI to decode from natural scene viewing where people attend and look (O’Connell et al., in prep). In a separate project to quantify attention, functional network analyses of whole brain functional connectivity allow us to fingerprint individual differences in sustained attention tasks (Finn et al., 2015; Rosenberg et al., 2015). Our models also show potential as neuromarkers to predict ADHD symptoms and the effects of attention-enhancing drugs such as Ritalin.  fMRI can decode and predict behavior with increasing power and sophistication.

Reception follows in J.S. Coon second floor atrium.

 

 

 

 

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  • Workflow Status:Published
  • Created By:lwhite35
  • Created:02/27/2018
  • Modified By:lwhite35
  • Modified:02/28/2018