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Identification and characterisation of midbrain nuclei using optimised functional magnetic resonance imaging.
- Source :
-
NeuroImage [Neuroimage] 2012 Jan 16; Vol. 59 (2), pp. 1230-8. Date of Electronic Publication: 2011 Aug 16. - Publication Year :
- 2012
-
Abstract
- Localising activity in the human midbrain with conventional functional MRI (fMRI) is challenging because the midbrain nuclei are small and located in an area that is prone to physiological artefacts. Here we present a replicable and automated method to improve the detection and localisation of midbrain fMRI signals. We designed a visual fMRI task that was predicted would activate the superior colliculi (SC) bilaterally. A limited number of coronal slices were scanned, orientated along the long axis of the brainstem, whilst simultaneously recording cardiac and respiratory traces. A novel anatomical registration pathway was used to optimise the localisation of the small midbrain nuclei in stereotactic space. Two additional structural scans were used to improve registration between functional and structural T1-weighted images: an echo-planar image (EPI) that matched the functional data but had whole-brain coverage, and a whole-brain T2-weighted image. This pathway was compared to conventional registration pathways, and was shown to significantly improve midbrain registration. To reduce the physiological artefacts in the functional data, we estimated and removed structured noise using a modified version of a previously described physiological noise model (PNM). Whereas a conventional analysis revealed only unilateral SC activity, the PNM analysis revealed the predicted bilateral activity. We demonstrate that these methods improve the measurement of a biologically plausible fMRI signal. Moreover they could be used to investigate the function of other midbrain nuclei.<br /> (Copyright © 2011 Elsevier Inc. All rights reserved.)
- Subjects :
- Adult
Algorithms
Evoked Potentials, Visual physiology
Female
Humans
Image Enhancement methods
Male
Middle Aged
Pattern Recognition, Automated methods
Reproducibility of Results
Sensitivity and Specificity
Image Interpretation, Computer-Assisted methods
Magnetic Resonance Imaging methods
Mesencephalon anatomy & histology
Mesencephalon physiology
Nerve Net anatomy & histology
Nerve Net physiology
Visual Perception physiology
Subjects
Details
- Language :
- English
- ISSN :
- 1095-9572
- Volume :
- 59
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- NeuroImage
- Publication Type :
- Academic Journal
- Accession number :
- 21867762
- Full Text :
- https://doi.org/10.1016/j.neuroimage.2011.08.016