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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. Further developed, intrinsic connectivity network signatures may provide simple, inexpensive, and non-invasive biomarkers for dementia differential diagnosis and disease monitoring. [ABSTRACT FROM AUTHOR]

We performed a pilot randomized, controlled trial of intensive, computer-based cognitive training in 47 subjects with mild cognitive impairment. The intervention group performed exercises specifically designed to improve auditory processing speed and accuracy for 100 min/d, 5 d/wk for 6 weeks; the control group performed more passive computer activities (reading, listening, visuospatial game) for similar amounts of time. Subjects had a mean age of 74 years and 60% were men; 77% successfully completed training. On our primary outcome, Repeatable Battery for Assessment of Neuropsychological Status total scores improved 0.36 standard deviations (SD) in the intervention group (P=0.097) compared with 0.03 SD in the control group (P=0.88) for a nonsignificant difference between the groups of 0.33 SD (P=0.26). On 12 secondary outcome measures, most differences between the groups were not statistically significant. However, we observed a pattern in which effect sizes for verbal learning and memory measures tended to favor the intervention group whereas effect sizes for language and visuospatial function measures tended to favor the control group, which raises the possibility that these training programs may have domain-specific effects. We conclude that intensive, computer-based mental activity is feasible in subjects with mild cognitive impairment and that larger trials are warranted. [ABSTRACT FROM AUTHOR]

To better define the anatomic distinctions between Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD), we retrospectively applied voxel-based morphometry to the earliest magnetic resonance imaging scans of autopsy-proven AD (N = 11), FTLD (N = 18), and controls (N = 40). Compared with controls, AD patients showed gray matter reductions in posterior temporoparietal and occipital cortex; FTLD patients showed atrophy in medial prefrontal and medial temporal cortex, insula, hippocampus, and amygdala; and patients with both disorders showed atrophy in dorsolateral and orbital prefrontal cortex and lateral temporal cortex (P(FWE-corr) < .05). Compared with FTLD, AD patients had decreased gray matter in posterior parietal and occipital cortex, whereas FTLD patients had selective atrophy in anterior cingulate, frontal insula, subcallosal gyrus, and striatum (P < .001, uncorrected). These findings suggest that AD and FTLD are anatomically distinct, with degeneration of a posterior parietal network in AD and degeneration of a paralimbic fronto-insular-striatal network in FTLD. [ABSTRACT FROM AUTHOR]

Alzheimer's disease and frontotemporal dementia (FTD) can be difficult to differentiate clinically because of overlapping symptoms. Distinguishing the two dementias based on volumetric measurements of brain atrophy with MRI has been only partially successful. Whether MRI measurements of cortical thinning improve the differentiation between Alzheimer's disease and FTD is unclear. In this study, we measured cortical thickness using a set of automated tools (Freesurfer) to reconstruct the brain's cortical surface from T1-weighted structural MRI data in 22 patients with Alzheimer's disease, 19 patients with FTD and 23 cognitively normal subjects. The goals were to detect the characteristic patterns of cortical thinning in these two types of dementia, to test the relationship between cortical thickness and cognitive impairment, to determine if measurement of cortical thickness is better than that of cortical volume for differentiating between these dementias and normal ageing and improving the classification of Alzheimer's disease and FTD based on neuropsychological scores alone. Compared to cognitively normal subjects, Alzheimer's disease patients had a thinner cortex primarily in bilateral, frontal, parietal, temporal and occipital lobes (P < 0.001), while FTD patients had a thinner cortex in bilateral, frontal and temporal regions and some thinning in inferior parietal regions and the posterior cingulate (P < 0.001). Compared to FTD patients, Alzheimer's disease patients had a thinner cortex (P < 0.001) in parts of bilateral parietal and precuneus regions. Cognitive impairment was negatively correlated with cortical thickness of frontal, parietal and temporal lobes in Alzheimer's disease, while similar correlations were not significant in FTD. Measurement of cortical thickness was similar to that of cortical volume in differentiating between normal ageing, Alzheimer's disease and FTD. Furthermore, cortical thickness measurements significantly improved the classification between Alzheimer's disease and FTD based on neuropsychological scores alone, including the Mini-Mental State Examination and a modified version of the Trail-Making Test. In conclusion, the characteristic patterns of cortical thinning in Alzheimer's disease and FTD suggest that cortical thickness may be a useful surrogate marker for these types of dementia. [ABSTRACT FROM AUTHOR]

Apolipoprotein B has been shown to be a better predictor of coronary heart disease than low-density lipoprotein (LDL) cholesterol, and non-high-density lipoprotein (non-HDL) cholesterol may also be a better parameter for coronary heart disease risk assessment and as a target for therapy. Data from the Atorvastatin Comparative Cholesterol Efficacy and Safety Study (ACCESS) were used to assess the correlation between lipid and apolipoprotein B levels before and after lipid-lowering therapy and to examine the effects of 5 hydroxymethylglutaryl coenzyme A reductase inhibitors on lipids and apolipoprotein B. The 54-week study randomized 3,916 hypercholesterolemic patients to atorvastatin, fluvastatin, lovastatin, pravastatin, or simvastatin, initiated at recommended starting doses with titrations as needed at weeks 6, 12, and 18 to achieve National Cholesterol Education Program LDL targets. Compared with LDL cholesterol, non-HDL cholesterol correlated better with apolipoprotein B levels at baseline (r = 0.914, p <0.0001) and at week 54 (r = 0.938, p <0.0001), and the correlation was strong across all baseline triglyceride strata. At starting doses, atorvastatin (10 mg) lowered non-HDL cholesterol by 33.3% compared with 26.6% with simvastatin (10 mg), 24.1% with lovastatin (20 mg), 17.2% with fluvastatin (20 mg), and 17.0% with pravastatin (10 mg). Atorvastatin also provided greater reductions in non-HDL cholesterol after dose titration, and a greater percentage of patients taking atorvastatin achieved non-HDL cholesterol targets. Baseline triglyceride did not affect non-HDL cholesterol reductions with any of the 5 hydroxymethylglutaryl coenzyme A reductase inhibitors. Fewer patients achieved non-HDL cholesterol targets than LDL cholesterol targets, particularly among high-risk patients, implying that if non-HDL cholesterol was used as a target for treatment, more patients would need to be treated more aggressively than National Cholesterol Education Program guidelines require. [ABSTRACT FROM AUTHOR]