Functional disconnectivity of the medial temporal lobe in Asperger's syndrome.

BACKGROUND: Autistic spectrum disorders (ASD) are neurodevelopmental conditions that may be caused by abnormal connectivity between brain regions constituting neurocognitive networks for specific aspects of social cognition. METHODS: We used three-way multidimensional scaling of regionally parcellated functional magnetic resonance imaging (fMRI) data to explore the hypothesis of abnormal functional connectivity in people with ASD. Thirteen high-functioning individuals with Asperger's syndrome and 13 healthy volunteers were scanned during incidental processing of fearful facial expressions. RESULTS: Using permutation tests for inference, we found evidence for significant abnormality of functional integration of amygdala and parahippocampal gyrus (p < .05, false discovery rate [FDR] corrected) in people with Asperger's syndrome. There were less salient abnormalities in functional connectivity of anterior cingulate, inferior occipital, and inferior frontal cortex, but there was no significant difference between groups in whole brain functional connectivity. CONCLUSIONS: We conclude there is evidence that functional connectivity of medial temporal lobe structures specifically is abnormal in people with Asperger's syndrome during fearful face processing.

Integrated software for the analysis of brain PET/SPECT studies with partial-volume-effect correction.

UNLABELLED: We present software for integrated analysis of brain PET studies and coregistered segmented MRI that couples a module for automated placement of regions of interest (ROI) with 4 alternative methods for partial-volume-effect correction (PVEc). The accuracy and precision of these methods have been measured using 4 simulated (18)F-FDG PET studies with increasing degrees of atrophy. METHODS: The software allows the application of a set of labels, defined a priori in the Talairach space, to segmented and coregistered MRI. Resulting ROIs are then transferred onto the PET study, and corresponding values are corrected according to the 4 PVEc techniques under investigation, providing corresponding corrected values. To evaluate the PVEc techniques, the software was applied to 4 simulated (18)F-FDG PET studies, introducing increasingly larger experimental errors, including errors in coregistration (0- to 6-pixel misregistration), segmentation (-13.7% to 14.1% gray matter [GM] volume change) and resolution estimate errors (-16.9% to 26.8% full-width-at-half-maximum mismatch). RESULTS: Even in the absence of segmentation and coregistration errors, uncorrected PET values showed -37.6% GM underestimation and 91.7% WM overestimation. Voxel-based correction only for the loss of GM activity as a result of spill-out onto extraparenchymal tissues left a residual underestimation of GM values (-21.2%). Application of the method that took into account both spill-in and spill-out effects between any possible pair of ROIs (R-PVEc) and of the voxel-based method that corrects also for the WM activity derived from R-PVEC (mMG-PVEc) provided an accuracy above 96%. The coefficient of variation of the GM ROIs, a measure of the imprecision of the GM concentration estimates, was 8.5% for uncorrected PET data and decreased with PVEc, reaching 6.0% for mMG-PVEc. Coregistration errors appeared to be the major determinant of the imprecision. CONCLUSION: Coupling of automated ROI placement and PVEc provides a tool for integrated analysis of brain PET/MRI data, which allows a recovery of true GM ROI values, with a high degree of accuracy when R-PVEc or mMG-PVEc is used. Among the 4 tested PVEc methods, R-PVEc showed the greatest accuracy and is suitable when corrected images are not specifically needed. Otherwise, if corrected images are desired, the mMG-PVEc method appears the most adequate, showing a similar accuracy.

Dissociating atrophy and hypometabolism impact on episodic memory in mild cognitive impairment.

The present study aims to unravel, in the same study, both morphological and functional specific substrates of encoding versus retrieval deficits in patients with amnestic mild cognitive impairment (MCI). For this purpose, 21 highly screened MCI patients with isolated memory impairment, who attended a memory clinic and fulfilled operational criteria for MCI, underwent (i) two episodic memory subtests designed to assess preferentially either incidental encoding or retrieval capacity; (ii) a high-resolution T1-weighted volume MRI scan; and (iii) a resting state [18F]fluoro-2-deoxy-D-glucose PET study. Using statistical parametric mapping, positive correlations between memory scores on one hand, and grey matter density and normalized partial volume effect-corrected brain glucose utilization (ncCMRglc) on the other hand, were computed. Deficits in both encoding and retrieval were correlated with declines in hippocampal region grey matter density. The encoding subtest also correlated with hippocampal ncCMRglc, whereas the retrieval subtest correlated with the posterior cingulate area ncCMRglc only. The present findings highlight a distinction in the neural substrates of encoding and retrieval deficits in MCI. Furthermore, they unravel a partial dissociation between metabolic and structural correlates, suggesting distinct interpretations. Hippocampal atrophy was related to both encoding and retrieval deficits, possibly reflecting a direct effect on hippocampal functioning, as well as an indirect effect, through remote functional disruption, on posterior cingulate region synaptic function, respectively.