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Pitfalls in comparing functional magnetic resonance imaging and invasive electrophysiology recordings

  • D. L. G. Hill
  • A. Simmons
  • A. D. Castellano Smith
  • C. R. MaurerJr.
  • T. C. S. Cox
  • R. Elwes
  • M. J. Brammer
  • D. J. Hawkes
  • C. E. Polkey
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1496)

Abstract

Several authors have recently compared the results of fMRI studies on neurosurgery patients with invasive electrophysiology. These studies aim to validate MRI against an accepted gold standard, and ascertain whether fMRI could replace invasive electrophysiology in neurosurgical patients. We have identified and quantified two characteristics of these data that make such comparisons problematic. Firstly, the epilepsy surgery patients (n=8) studied move significantly more during fMRI experiments than normal volunteers (n=6) performing the same task. This motion has a particularly large out-of-plane component, and is significantly more correlated with the stimulus than for the normal volunteers. This motion is especially large when performing a task on the side affected by the lesion. This additional motion is hard to correct and substantially degrades the quality of the resulting fMRI images, making it a much less reliable technique on these surgical patients than on other subjects. Secondly, we have found that, following electrode implantation, the brain surface can shift by more than 10 mm relative to the skull compared to its preoperative location, substantially degrading the accuracy of the comparison of electrophysiology measurements made on the deformed brain and fMRI studies carried out preoperatively. Taken together, these findings suggest that studies of this sort are currently of limited use for validating fMRI, and further image analysis research is necessary to solve the problems caused by subject motion and brain deformation.

Keywords

Normal Volunteer Functional Region Brain Surface Subject Motion Subdural Electrode 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • D. L. G. Hill
    • 1
  • A. Simmons
    • 2
    • 3
  • A. D. Castellano Smith
    • 1
  • C. R. MaurerJr.
    • 1
  • T. C. S. Cox
    • 1
    • 2
  • R. Elwes
    • 2
  • M. J. Brammer
    • 3
  • D. J. Hawkes
    • 1
  • C. E. Polkey
    • 2
  1. 1.Radiological Sciences & Medical EngineeringKing’s CollegeLondonUK
  2. 2.Clinical NeurosciencesKing’s CollegeLondonUK
  3. 3.Institute of PsychiatryKing’s CollegeLondonUK

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