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An assessment of functional-anatomical variability in neuroimaging studies
D L Hunton1, F M Miezin, R L Buckner
1Department of Neurology and Neurological Surgery, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
Human Brain Mapping
|April 22, 2010
Summary
Individual differences in brain activation cause variability in functional neuroimaging. This study quantizes this variability, finding it predictable and consistent across brain regions, supporting averaging techniques.
Area of Science:
- Neuroimaging
- Cognitive Neuroscience
- Brain Imaging Analysis
Background:
- Individual differences in brain anatomy and function introduce variability in neuroimaging studies.
- This variability impacts averaged images and group comparisons, posing a challenge for data interpretation.
Purpose of the Study:
- To explore functional-anatomical variability in brain activation at two distinct levels.
- To assess the replicability of activation patterns across different subject groups.
- To quantify the spatial clustering of peak activation locations within subjects.
Main Methods:
- Analysis of functional magnetic resonance imaging (fMRI) or positron emission tomography (PET) data from two subject groups.
- Statistical comparison of activation magnitudes and t-values between groups.
- Calculation of mean vector distance to measure peak location variability across subjects.
Main Results:
- Replicability of significant changes in a second group was predictable from the first group's response magnitudes and t-values.
- The mean vector distance of peak activation locations was approximately 11.5 mm, representing an upper bound for current PET analysis.
- Variability was consistent across cortical areas and the cerebellum.
Conclusions:
- Functional-anatomical variability in brain activation is quantifiable and predictable.
- Current PET data analysis techniques have an estimated upper bound of ~11.5 mm for functional-anatomical variability.
- The observed consistency in variability across brain regions challenges hypotheses of region-specific high anatomical variability, supporting the use of averaging techniques.
