High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas.

The amygdala is composed of multiple nuclei with unique functions and connections in the limbic system and to the rest of the brain. However, standard in vivo neuroimaging tools to automatically delineate the amygdala into its multiple nuclei are still rare. By scanning postmortem specimens at high resolution (100-150µm) at 7T field strength (n = 10), we were able to visualize and label nine amygdala nuclei (anterior amygdaloid, cortico-amygdaloid transition area; basal, lateral, accessory basal, central, cortical medial, paralaminar nuclei). We created an atlas from these labels using a recently developed atlas building algorithm based on Bayesian inference. This atlas, which will be released as part of FreeSurfer, can be used to automatically segment nine amygdala nuclei from a standard resolution structural MR image. We applied this atlas to two publicly available datasets (ADNI and ABIDE) with standard resolution T1 data, used individual volumetric data of the amygdala nuclei as the measure and found that our atlas i) discriminates between Alzheimer's disease participants and age-matched control participants with 84% accuracy (AUC=0.915), and ii) discriminates between individuals with autism and age-, sex- and IQ-matched neurotypically developed control participants with 59.5% accuracy (AUC=0.59). For both datasets, the new ex vivo atlas significantly outperformed (all p < .05) estimations of the whole amygdala derived from the segmentation in FreeSurfer 5.1 (ADNI: 75%, ABIDE: 54% accuracy), as well as classification based on whole amygdala volume (using the sum of all amygdala nuclei volumes; ADNI: 81%, ABIDE: 55% accuracy). This new atlas and the segmentation tools that utilize it will provide neuroimaging researchers with the ability to explore the function and connectivity of the human amygdala nuclei with unprecedented detail in healthy adults as well as those with neurodevelopmental and neurodegenerative disorders.

A tensor-based morphometry analysis of regional differences in brain volume in relation to prenatal alcohol exposure.

Reductions in brain volumes represent a neurobiological signature of fetal alcohol spectrum disorders (FASD). Less clear is how regional brain tissue reductions differ after normalizing for brain size differences linked with FASD and whether these profiles can predict the degree of prenatal exposure to alcohol. To examine associations of regional brain tissue excesses/deficits with degree of prenatal alcohol exposure and diagnosis with and without correction for overall brain volume, tensor-based morphometry (TBM) methods were applied to structural imaging data from a well-characterized, demographically homogeneous sample of children diagnosed with FASD (n = 39, 9.6-11.0 years) and controls (n = 16, 9.5-11.0 years). Degree of prenatal alcohol exposure was significantly associated with regionally pervasive brain tissue reductions in: (1) the thalamus, midbrain, and ventromedial frontal lobe, (2) the superior cerebellum and inferior occipital lobe, (3) the dorsolateral frontal cortex, and (4) the precuneus and superior parietal lobule. When overall brain size was factored out of the analysis on a subject-by-subject basis, no regions showed significant associations with alcohol exposure. FASD diagnosis was associated with a similar deformation pattern, but few of the regions survived FDR correction. In data-driven independent component analyses (ICA) regional brain tissue deformations successfully distinguished individuals based on extent of prenatal alcohol exposure and to a lesser degree, diagnosis. The greater sensitivity of the continuous measure of alcohol exposure compared with the categorical diagnosis across diverse brain regions underscores the dose dependence of these effects. The ICA results illustrate that profiles of brain tissue alterations may be a useful indicator of prenatal alcohol exposure when reliable historical data are not available and facial features are not apparent.

White matter pathology isolates the hippocampal formation in Alzheimer's disease.

Prior work has demonstrated that the memory dysfunction of Alzheimer's disease (AD) is accompanied by marked cortical pathology in medial temporal lobe (MTL) gray matter. In contrast, changes in white matter (WM) of pathways associated with the MTL have rarely been studied. We used diffusion tensor imaging (DTI) to examine regional patterns of WM tissue changes in individuals with AD. Alterations of diffusion properties with AD were found in several regions including parahippocampal WM, and in regions with direct and secondary connections to the MTL. A portion of the changes measured, including effects in the parahippocampal WM, were independent of gray matter degeneration as measured by hippocampal volume. Examination of regional changes in unique diffusion parameters including anisotropy and axial and radial diffusivity demonstrated distinct zones of alterations, potentially stemming from differences in underlying pathology, with a potential myelin specific pathology in the parahippocampal WM. These results demonstrate that deterioration of neocortical connections to the hippocampal formation results in part from the degeneration of critical MTL and associated fiber pathways.

Neuroimaging H.M.: a 10-year follow-up examination.

In 1997, Corkin et al. described the anatomical boundaries of the amnesic patient H.M.'s surgical resection, based on a comprehensive analysis of magnetic resonance imaging (MRI) scans collected in 1992 and 1993 (Corkin et al. (1997) J Neurosci 17:3964-3979). We subsequently scanned H.M. on several occasions, employing more advanced data acquisition and analysis methods, and now describe additional details about his brain anatomy and pathology. This account combines results from high-resolution T1-weighted scans, which provide measures of cortical and subcortical morphometry, diffusion tensor images, which provide quantitative information about white matter microstructure and the anatomy of major fasciculi, and T2-weighted images, which highlight damage to deep white matter. We applied new MRI analysis techniques to these scans to assess the integrity of areas throughout H.M.'s brain. We documented a number of new changes, including cortical thinning, atrophy of deep gray matter structures, and a large volume of abnormal white matter and deep gray matter signal. Most of these alterations were not apparent in his prior scans, suggesting that they are of recent origin. Advanced age and hypertension likely contributed to these new findings.

Age-related alterations in white matter microstructure measured by diffusion tensor imaging.

Cerebral white matter (WM) undergoes various degenerative changes with normal aging, including decreases in myelin density and alterations in myelin structure. We acquired whole-head, high-resolution diffusion tensor images (DTI) in 38 participants across the adult age span. Maps of fractional anisotropy (FA), a measure of WM microstructure, were calculated for each participant to determine whether particular fiber systems of the brain are preferentially vulnerable to WM degeneration. Regional FA measures were estimated from nine regions of interest in each hemisphere and from the genu and splenium of the corpus callosum (CC). The results showed significant age-related decline in FA in frontal WM, the posterior limb of the internal capsule (PLIC), and the genu of the CC. In contrast, temporal and posterior WM was relatively preserved. These findings suggest that WM alterations are variable throughout the brain and that particular fiber populations within prefrontal region and PLIC are most vulnerable to age-related degeneration.