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Linking brain imaging signals to visual perception

Published online by Cambridge University Press:  29 October 2013

ANDREW E. WELCHMAN  and
ZOE KOURTZI
ANDREW E. WELCHMAN*
Affiliation:
School of Psychology, University of Birmingham, Birmingham, UK Laboratory for Neuro- and Psychophysiology, K.U. Leuven, Leuven, Belgium
ZOE KOURTZI*
Affiliation:
School of Psychology, University of Birmingham, Birmingham, UK Laboratory for Neuro- and Psychophysiology, K.U. Leuven, Leuven, Belgium
*
*Address correspondence to: Andrew E. Welchman, University of Birmingham, School of Psychology, Edgbaston, Birmingham B15 2TT, UK. E-mail: [email protected] and Zoe Kourtzi. E-mail: [email protected]
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Abstract

The rapid advances in brain imaging technology over the past 20 years are affording new insights into cortical processing hierarchies in the human brain. These new data provide a complementary front in seeking to understand the links between perceptual and physiological states. Here we review some of the challenges associated with incorporating brain imaging data into such “linking hypotheses,” highlighting some of the considerations needed in brain imaging data acquisition and analysis. We discuss work that has sought to link human brain imaging signals to existing electrophysiological data and opened up new opportunities in studying the neural basis of complex perceptual judgments. We consider a range of approaches when using human functional magnetic resonance imaging to identify brain circuits whose activity changes in a similar manner to perceptual judgments and illustrate these approaches by discussing work that has studied the neural basis of 3D perception and perceptual learning. Finally, we describe approaches that have sought to understand the information content of brain imaging data using machine learning and work that has integrated multimodal data to overcome the limitations associated with individual brain imaging approaches. Together these approaches provide an important route in seeking to understand the links between physiological and psychological states.

Keywords

fMRIAdaptation, pattern classification3D shape perceptionPerceptual learning
Type
Retrospective and prospective analyses of linking propositions
Information
Visual Neuroscience , Volume 30 , Special Issue 5-6: Linking Hypotheses in Visual Neuroscience: A Tribute to Davida Teller , November 2013 , pp. 229 - 241
Copyright
Copyright © Cambridge University Press 2013 

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