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Studying Conscious and Unconscious Vision with Functional Magnetic Resonance Imaging : the BOLD Promise


Dubois, Julien Christian Roger (2013) Studying Conscious and Unconscious Vision with Functional Magnetic Resonance Imaging : the BOLD Promise. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/7EGE-FG03.


Waking up from a dreamless sleep, I open my eyes, recognize my wife’s face and am filled with joy. In this thesis, I used functional Magnetic Resonance Imaging (fMRI) to gain insights into the mechanisms involved in this seemingly simple daily occurrence, which poses at least three great challenges to neuroscience: how does conscious experience arise from the activity of the brain? How does the brain process visual input to the point of recognizing individual faces? How does the brain store semantic knowledge about people that we know? To start tackling the first question, I studied the neural correlates of unconscious processing of invisible faces. I was unable to image significant activations related to the processing of completely invisible faces, despite existing reports in the literature. I thus moved on to the next question and studied how recognition of a familiar person was achieved in the brain; I focused on finding invariant representations of person identity – representations that would be activated any time we think of a familiar person, read their name, see their picture, hear them talk, etc. There again, I could not find significant evidence for such representations with fMRI, even in regions where they had previously been found with single unit recordings in human patients (the Jennifer Aniston neurons). Faced with these null outcomes, the scope of my investigations eventually turned back towards the technique that I had been using, fMRI, and the recently praised analytical tools that I had been trusting, Multivariate Pattern Analysis. After a mostly disappointing attempt at replicating a strong single unit finding of a categorical response to animals in the right human amygdala with fMRI, I put fMRI decoding to an ultimate test with a unique dataset acquired in the macaque monkey. There I showed a dissociation between the ability of fMRI to pick up face viewpoint information and its inability to pick up face identity information, which I mostly traced back to the poor clustering of identity selective units. Though fMRI decoding is a powerful new analytical tool, it does not rid fMRI of its inherent limitations as a hemodynamics-based measure.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:face identity; person recognition; unconscious processing; functional Magnetic Resonance Imaging; multivariate pattern analysis
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Computation and Neural Systems
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Koch, Christof (advisor)
  • Adolphs, Ralph (co-advisor)
Thesis Committee:
  • O'Doherty, John P. (chair)
  • Tsao, Doris Y.
  • Tyszka, Julian Michael
  • Koch, Christof
  • Adolphs, Ralph
Defense Date:29 May 2013
Record Number:CaltechTHESIS:05312013-191910347
Persistent URL:
Related URLs:
URLURL TypeDescription adapted for ch. IV.A
Dubois, Julien Christian Roger0000-0002-3029-173X
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:7811
Deposited By: Julien Dubois
Deposited On:04 Sep 2014 18:13
Last Modified:30 Aug 2022 22:47

Thesis Files

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