SAD: semi-supervised automatic detection of BOLD activations in high temporal resolution fMRI data.

Journal: Magma (New York, N.Y.)
PMID:

Abstract

OBJECTIVE: Despite the prevalent use of the general linear model (GLM) in fMRI data analysis, assuming a pre-defined hemodynamic response function (HRF) for all voxels can lead to reduced reliability and may distort the inferences derived from it. To overcome the necessity of presuming a specific model for the hemodynamic response, we introduce a semi-supervised automatic detection (SAD) method.

Authors

  • Tim Schmidt
    Laboratory for Social and Neural Systems Research, SNS-Lab, University of Zurich, Rämistrasse 100, CH-8091, Zurich, Switzerland. tim.schmidt@econ.uzh.ch.
  • Zoltan Nagy
    Laboratory for Social and Neural Systems Research, University of Zurich, Zurich, Switzerland; Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, United Kingdom.