Resting-state or intrinsic connectivity network functional magnetic resonance imaging provides a new tool for mapping large-scale neural network function and dysfunction. Recently, we showed that behavioural variant frontotemporal dementia and Alzheimer's disease cause atrophy within two major networks, an anterior 'Salience Network' (atrophied in behavioural variant frontotemporal dementia) and a posterior 'Default Mode Network' (atrophied in Alzheimer's disease). These networks exhibit an anti-correlated relationship with each other in the healthy brain. The two diseases also feature divergent symptom-deficit profiles, with behavioural variant frontotemporal dementia undermining social-emotional function and preserving or enhancing visuospatial skills, and Alzheimer's disease showing the inverse pattern. We hypothesized that these disorders would exert opposing connectivity effects within the Salience Network (disrupted in behavioural variant frontotemporal dementia but enhanced in Alzheimer's disease) and the Default Mode Network (disrupted in Alzheimer's disease but enhanced in behavioural variant frontotemporal dementia). With task-free functional magnetic resonance imaging, we tested these ideas in behavioural variant frontotemporal dementia, Alzheimer's disease and healthy age-matched controls (n = 12 per group), using independent component analyses to generate group-level network contrasts. As predicted, behavioural variant frontotemporal dementia attenuated Salience Network connectivity, most notably in frontoinsular, cingulate, striatal, thalamic and brainstem nodes, but enhanced connectivity within the Default Mode Network. Alzheimer's disease, in contrast, reduced Default Mode Network connectivity to posterior hippocampus, medial cingulo-parieto-occipital regions and the dorsal raphe nucleus, but intensified Salience Network connectivity. Specific regions of connectivity disruption within each targeted network predicted intrinsic connectivity enhancement within the reciprocal network. In behavioural variant frontotemporal dementia, clinical severity correlated with loss of right frontoinsular Salience Network connectivity and with biparietal Default Mode Network connectivity enhancement. Based on these results, we explored whether a combined index of Salience Network and Default Mode Network connectivity might discriminate between the three groups. Linear discriminant analysis achieved 92% clinical classification accuracy, including 100% separation of behavioural variant frontotemporal dementia and Alzheimer's disease. Patients whose clinical diagnoses were supported by molecular imaging, genetics, or pathology showed 100% separation using this method, including four diagnostically equivocal 'test' patients not used to train the algorithm. Overall, the findings suggest that behavioural variant frontotemporal dementia and Alzheimer's disease lead to divergent network connectivity patterns, consistent with known reciprocal network interactions and the strength and deficit profiles of the two disorders. ...

Objective To characterize cognitive and behavioral features, physical findings and brain atrophy patterns in pathology-proven corticobasal degeneration (CBD) and corticobasal syndrome (CBS) with known histopathology. Methods We reviewed clinical and MRI data in all patients evaluated at our center with either an autopsy diagnosis of CBD (n=18) or clinical CBS at first presentation with known histopathology (n=40). Atrophy patterns were compared using voxel-based morphometry. Results CBD was associated with four clinical syndromes: progressive nonfluent aphasia (5), behavioral variant frontotemporal dementia (5), executive-motor (7), and posterior cortical atrophy (1). Behavioral or cognitive problems were the initial symptoms in 15/18 patients; less than half exhibited early motor findings. Compared to controls, CBD patients showed atrophy in dorsal prefrontal and peri-rolandic cortex, striatum and brainstem (p<0.001 uncorrected). The most common pathologic substrates for clinical CBS were CBD (35%), Alzheimer’s disease (AD, 23%), progressive supranuclear palsy (13%), and frontotemporal lobar degeneration (FTLD) with TDP inclusions (13%). CBS was associated with perirolandic atrophy irrespective of underlying pathology. In CBS due to FTLD (tau or TDP), atrophy extended into prefrontal cortex, striatum and brainstem, while in CBS due to AD, atrophy extended into temporoparietal cortex and precuneus (p<0.001 uncorrected). Interpretation Frontal lobe involvement is characteristic of CBD, and in many patients frontal, not parietal or basal ganglia symptoms, dominate early-stage disease. CBS is driven by medial peri-rolandic dysfunction, but this anatomy is not specific to one single underlying histopathology. Antemortem prediction of CBD will remain challenging until clinical features of CBD are redefined, and sensitive, specific biomarkers are identified.

In the following brief report, we examined gender differences in incidence rates of any dementia, Alzheimer's disease (AD) alone, and non-Alzheimer's dementia alone in 16,926 women and men in the Swedish Twin Registry aged 65+. Dementia diagnoses were based on clinical workup and national health registry linkage. Incidence rates of any dementia and AD were greater in women than men, with any dementia rates diverging after age 85 and AD rates diverging around 80. This pattern is consistent with women's survival to older ages compared to men. These findings are similar to incidence rates reported in other Swedish samples.

Objective:To compare the diagnostic performance of PET with the amyloid ligand Pittsburgh compound B (PiB-PET) to fluorodeoxyglucose (FDG-PET) in discriminating between Alzheimer disease (AD) and frontotemporal lobar degeneration (FTLD). Methods:Patients meeting clinical criteria for AD (n ϭ 62) and FTLD (n ϭ 45) underwent PiB and FDG-PET. PiB scans were classified as positive or negative by 2 visual raters blinded to clinical diagnosis, and using a quantitative threshold derived from controls (n ϭ 25). FDG scans were visually rated as consistent with AD or FTLD, and quantitatively classified based on the region of lowest metabolism relative to controls.Results: PiB visual reads had a higher sensitivity for AD (89.5% average between raters) than FDG visual reads (77.5%) with similar specificity (PiB 83%, FDG 84%). When scans were classified quantitatively, PiB had higher sensitivity (89% vs 73%) while FDG had higher specificity (83% vs 98%). On receiver operating characteristic analysis, areas under the curve for PiB (0.888) and FDG (0.910) were similar. Interrater agreement was higher for PiB ( ϭ 0.96) than FDG ( ϭ 0.72), as was agreement between visual and quantitative classification (PiB ϭ 0.88-0.92; FDG ϭ 0.64-0.68). In patients with known histopathology, overall classification accuracy (2 visual and 1 quantitative classification per patient) was 97% for PiB (n ϭ 12 patients) and 87% for FDG (n ϭ 10). Conclusions:PiB and FDG showed similar accuracy in discriminating AD and FTLD. PiB was more sensitive when interpreted qualitatively or quantitatively. FDG was more specific, but only when scans were classified quantitatively. PiB slightly outperformed FDG in patients with known histopathology. Neurology Differentiating Alzheimer disease (AD) and frontotemporal lobar degeneration (FTLD) has implications for prognosis and symptomatic treatment, 1,2 and is critical for the efforts to develop disease-specific therapies. Making an accurate diagnosis during life can be challenging given overlapping clinical features.3,4 MRI or fluorodeoxyglucose PET (FDG-PET) can improve diagnostic accuracy by demonstrating distinct topographic patterns of atrophy or hypometabolism (temporoparietal predominant in AD; frontal and anterior temporal involvement in FTLD), 5,6 but anatomic overlap between the diseases is increasingly apparent. 5,7 Consequently, many patients with pathologically confirmed FTLD are diagnosed with AD during