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Andrew J. Aschenbrenner

Researcher at Washington University in St. Louis

Publications -  61
Citations -  1102

Andrew J. Aschenbrenner is an academic researcher from Washington University in St. Louis. The author has contributed to research in topics: Medicine & Cognition. The author has an hindex of 13, co-authored 44 publications receiving 658 citations. Previous affiliations of Andrew J. Aschenbrenner include University of Washington & University of Kansas.

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Influence of tau PET, amyloid PET, and hippocampal volume on cognition in Alzheimer disease.

TL;DR: The results suggest that increasing levels of tau most consistently relate to declines in cognition preceding biomarker collection, and support models of Alzheimer disease staging that suggest that elevated β-amyloid alone may be insufficient to produce cognitive change in individuals at risk for AD.
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A trial of gantenerumab or solanezumab in dominantly inherited Alzheimer's disease.

Stephen Salloway, +64 more
- 21 Jun 2021 - 
TL;DR: A randomized, placebo-controlled, multi-arm trial of gantenerumab or solanezumab in participants with DIAD across asymptomatic and symptomatic disease stages was conducted in this paper.
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Clinical and psychological characteristics of the initial cohort of the Dominantly Inherited Alzheimer Network (DIAN).

TL;DR: Overall cognitive and personality deficits in very mild ADAD are similar to those seen in sporadic AD and differences in the relation between 3 measures indicate that cognitive deficits on some measures can be detected in mutation carriers prior to symptomatic AD, and hence should be useful markers in subsequent longitudinal follow-up.
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Additive effects of word frequency and stimulus quality: the influence of trial history and data transformations.

TL;DR: This work reanalyzed data from 3 published studies to determine if previous trial history moderated the additive pattern when semantic priming was not also manipulated, and showed how a common transformation used in linear mixed effects analyses to normalize the residuals can systematically alter the way in which two variables combine to influence performance.