The human cerebellum plays an essential role in motor control, is involved in cognitive function (i.e., attention, working memory, and language), and helps to regulate emotional responses. Quantitative in-vivo assessment of the cerebellum is important in the study of several neurological diseases including cerebellar ataxia, autism, and schizophrenia. Different structural subdivisions of the cerebellum have been shown to correlate with differing pathologies. To further understand these pathologies, it is helpful to automatically parcellate the cerebellum at the highest fidelity possible. In this paper, we coordinated with colleagues around the world to evaluate automated cerebellum parcellation algorithms on two clinical cohorts showing that the cerebellum can be parcellated to a high accuracy by newer methods. We characterize these various methods at four hierarchical levels: coarse (i.e., whole cerebellum and gross structures), lobe, subdivisions of the vermis, and the lobules. Due to the number of labels, the hierarchy of labels, the number of algorithms, and the two cohorts, we have restricted our analyses to the Dice measure of overlap. Under these conditions, machine learning based methods provide a collection of strategies that are efficient and deliver parcellations of a high standard across both cohorts, surpassing previous work in the area. In conjunction with the rank-sum computation, we identified an overall winning method.

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are the main syndromes of the chromosome 9 ORF72 (C9ORF72) hexanucleotide repeat expansion, but studies have shown a substantial phenotypic diversity that includes psychiatric presentations. This study describes hippocampal sclerosis dementia (HSD) in carriers of the C9ORF72 mutation. We compared clinical and neuropathological features of HSD in carriers and noncarriers autopsied at Johns Hopkins. Carriers presented with amnesia, agitation, dissocial behavior, and impaired self-care, whereas noncarriers showed little agitation. The groups were not dissimilar in cognitive or motor dysfunction. Neuropathological examination of carriers showed cerebellar neuronal inclusions positive for ubiquitin, p62, and ubiquilin-2, and negative for TAR DNA-binding protein 43. Noncarriers did not have cerebellar inclusions. C9ORF72 repeat-associated non-ATG translation was confirmed by immunohistochemistry. These observations broaden the C9ORF72 phenotype and place HSD in the FTD spectrum. The amnesic phenotype of HSD, which is consistent with the focal hippocampal atrophy, should be included in clinical categorizations of FTD.

Patients with early-onset Alzheimer's disease (EOAD) are commonly excluded from large-scale observational and therapeutic studies due to their young age, atypical presentation, or absence of pathogenic mutations. The goals of the Longitudinal EOAD Study (LEADS) are to (1) define the clinical, imaging, and fluid biomarker characteristics of EOAD; (2) develop sensitive cognitive and biomarker measures for future clinical and research use; and (3) establish a trial-ready network. LEADS will follow 400 amyloid beta (Aβ)-positive EOAD, 200 Aβ-negative EOnonAD that meet National Institute on Aging-Alzheimer's Association (NIA-AA) criteria for mild cognitive impairment (MCI) or AD dementia, and 100 age-matched controls. Participants will undergo clinical and cognitive assessments, magnetic resonance imaging (MRI), [18 F]Florbetaben and [18 F]Flortaucipir positron emission tomography (PET), lumbar puncture, and blood draw for DNA, RNA, plasma, serum and peripheral blood mononuclear cells, and post-mortem assessment. To develop more effective AD treatments, scientists need to understand the genetic, biological, and clinical processes involved in EOAD. LEADS will develop a public resource that will enable future planning and implementation of EOAD clinical trials.