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In any case, each jurisdiction treats insanity claims in its own way, so they may well disagree over whether brain-image data are exculpatory.

Imaging data Inferential statistics on brain imaging data were conducted using SPM2 (Department of Cognitive Neurology, Institute of Neurology, London, UK).

Whole-brain high angular resolution diffusion image data were acquired using a diffusion weighted single-shot spin-echo echo-planar imaging (EPI) pulse sequence with the following parameters: TE = 87 ms; voxel dimensions = 2.4 × 2.4 × 2.4 mm; field of view = 23 × 23 cm; 96 × 96 acquisition matrix; 60 contiguous slices acquired along an oblique axial plane with 2.4-mm thickness (no gap).

Image data were acquired with the brain inside the skull to preserve native spatial relationships.

The image data were segmented into three main brain regions: cerebrum, hippocampus, and cerebellum.

After this activity normalization, PET image data were non-linearly spatially normalized into Montreal Neurological Institute (MNI) space using the SPM5 standard PET brain template.

Image data were analyzed with BeadStudio V2.0.

Imaging data were preprocessed and analyzed using BrainVoyager 4.9 and QX (Brain Innovation, Maastricht, Holland).

The whole-body PET and CT images were cropped to isolate the brain image data sets.

SVM [Vapnik, 1995] was implemented using PROBID (Pattern Recognition of Brain Image Data) software (http://www.brainmap.co.uk/probid.htm) version 1.04.

The results of filtering SENSE images reconstructed from patient brain data were shown in Figure 10.