Systematic Artifact Reduction in Auditory fMRI

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DESCRIPTION (provided by applicant): Functional magnetic resonance imaging (fMRI) using echo-planar imaging (EPI) results in generation of a systematic confound-acoustic noise ("acoustic imaging noise")-that can interfere with the fMRI measurement of cortical activity related to a desired (acoustic) stimulus. Acoustic imaging noise is unavoidably perceived by a hearing subject, leading to neuronal activity throughout the auditory pathway, including cortex. Perception of acoustic imaging noise can alter sensory perception of the desired stimulus-an alteration that will affect physiologic activity and distort measurement of the hemodynamic response (HDR) to the desired stimulus. Methods, initially directed at auditory fMRI, are proposed to develop correction algorithms that may be used to correct distortions of the "ideal" HDR (that measured in the absence of confound) associated with systematic confounds. Significant benefit to the fMRI community arises from the process by which the correction algorithm is developed, as the process may be applied to other systematic confounds known to be associated with acquisition of fMRI data. The specific aims of this research are summarized as follows: Aim 1: Obtain "ideal" measurements of the HDR to the systematic confound of acoustic imaging noise for blipped-EPI at 1.5T. Aim 2: Obtain non-ideal measurements of HDRs to a desired (acoustic) stimulus, parameterized by variations in the systematic confound (acoustic imaging noise), allowing quantification of interactions between the HDRs. Aim 3: Develop correction algorithms to compensate for distortions present in non-ideal HDR measurements to a desired (acoustic) stimulus, such that resulting HDR estimates resemble those which would be obtained in absence of the systematic confound (acoustic imaging noise). Relevance: Improvements in localization accuracy and detection sensitivity for fMRI experiments conducted in the presence of repeated confounds (e.g., acoustic noise associated with imaging) will allow more precise discrimination of cortical responses to stimuli that may differ only in a subtle fashion. These benefits will provide greater confidence in location and extent of detected activity, significantly impacting human brain mapping, but also directly benefiting efforts at pre-surgical mapping.