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Lauren E. Salminen

Researcher at University of Southern California

Publications -  59
Citations -  1741

Lauren E. Salminen is an academic researcher from University of Southern California. The author has contributed to research in topics: White matter & Medicine. The author has an hindex of 17, co-authored 50 publications receiving 1055 citations. Previous affiliations of Lauren E. Salminen include University of Missouri–St. Louis & Washington University in St. Louis.

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Regional age differences in gray matter diffusivity among healthy older adults

TL;DR: It is suggested that aging has a significant and differential impact on GM/WM diffusion in healthy older adults, which may explain a modest degree of cognitive variability at specific time points during older adulthood.
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Impact of body mass index on neuronal fiber bundle lengths among healthy older adults.

TL;DR: Investigation of the relationship between BMI and white matter fiber bundle length in 72 otherwise healthy older adults revealed that elevated BMI was associated with shorter FBL in the temporal lobe, independent of age, and offered evidence for additive adverse effects of high BMI on the brain.
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Impact of the HIV Tat C30C31S dicysteine substitution on neuropsychological function in patients with clade C disease.

TL;DR: It is confirmed that the C31S dicysteine motif substitution of the Tat protein does not appreciably moderate neuropsychological outcomes in clade C, and highlights the importance of clinical management of cognitive symptoms among individuals infected with this viral clade worldwide.
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Reducing csf partial volume effects to enhance diffusion tensor imaging metrics of brain microstructure.

TL;DR: A technique that has been recently shown to effectively suppress the CSF signal in DTI data, resulting in fewer errors and improved measurement of brain tissue is discussed, which has the potential to significantly improve the understanding of "normal" brain aging and neuropsychiatric and neurodegenerative diseases.
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Uncovering Biologically Coherent Peripheral Signatures of Health and Risk for Alzheimer's Disease in the Aging Brain.

TL;DR: The utility of a novel unsupervised machine learning technique – Correlation Explanation (CorEx) is shown to discover how individual measures from structural brain imaging, genetics, plasma, and CSF markers can jointly provide information on risk for Alzheimer’s disease.