Multivariate genotypic analyses that identify specific genotypes to characterize disease and control groups in ADNI

Beaton, Derek; Rieck,; Alhazmi, Fahd H.; Abdi, Hervé

doi:10.1101/235945

Cited by 3 publications

(2 citation statements)

References 101 publications

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“…The need to understand not only the expected course of senescence, but the interaction of brain structure and behavior will become increasingly important to understand the myriad of conditions that can impede independence later in life. Early open projects of this nature, such as the Alzheimer’s Disease Neuroimaging Initiative (ADNI), have required large publicly available tools to facilitate the larger number of researchers who have analyzed factors related to ones in this dataset [15,16,106–109]. More recent, large-scale population projects such as the Human Connectome Project, the ENIGMA Consortium, and the UK Biobank [60,110,111] have collected, organized, and openly distributed data to allow the implementation of data-driven neuroscience methods, mine novel findings, and build normative models of brain structure and function [94].…”

Section: Discussionmentioning

confidence: 99%

A single-mode associates global patterns of brain network structure and behavior across the human lifespan

McPherson

Pestilli

2020

Preprint

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Multiple human behaviors improve early in life, peaking in young adulthood, and declining thereafter. Several properties of brain structure and function progress similarly across the lifespan. Cognitive and neuroscience research has approached aging primarily using associations between a few behaviors, brain functions, and structures. Because of this, the multivariate, global factors relating brain and behavior across the lifespan are not understood. We investigated the global patterns of associations between 334 behavioral and clinical measures and 376 brain structural connections in 594 individuals across the lifespan. A single-axis associated changes in multiple behavioral domains and brain structural connections (r=0.5808). Individual variability within the single association-axis well predicted the subjects age (r=0.6275). Representational similarity analysis evidenced global patterns of interactions across multiple brain networks systems and behavioral domains. Results show that a global process of human aging is well captured by multivariate data fusion approach. [147]

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Section: Discussionmentioning

confidence: 99%

A single-mode associates global patterns of brain network structure and behavior across the human lifespan

McPherson

Pestilli

2020

Preprint

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“…For the present analysis we conducted Barycentric Discriminant Analysis (BADA) and inference tests with the TInPosition [Beaton et al, ; see also Beaton et al, ] package in R (R Core Team, Vienna, Austria). BADA was particularly suited to identify subtle differences between groups of participants through the use of a between‐class (i.e., group‐level) PCA [also equivalent to mean‐centered partial least squares; Krishnan et al, ; McIntosh et al, ].…”

Section: Methodsmentioning

confidence: 99%

The effect of beta‐amyloid on face processing in young and old adults: A multivariate analysis of the BOLD signal

Rieck

Rodrigue

Kennedy

et al. 2015

Human Brain Mapping

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The recent ability to measure in vivo beta-amyloid (Aβ), a marker of Alzheimer's disease (AD), has led to an increased focus on the significance of Aβ deposition in clinically normal adults. Evidence suggests that healthy adults with elevated cortical Aβ show differences in neural activity associated with memory encoding—specifically encoding of face stimuli. Here, we examined if Aβ deposition in clinically normal adults was related to differences in neural activity in ventral visual cortex during face viewing. Our sample included 23 high-Aβ older adults, 23 demographically matched low-Aβ older adults, and 16 young adults. Participants underwent cognitive testing, Aβ positron emission tomography imaging with 18F-Florbetapir, and functional magnetic resonance imaging to measure neural activity while participants passively viewed photographs of faces. Using barycentric discriminant analysis—a between-groups classification technique—we found that patterns of neural activity in the left fusiform gyrus, a region highly responsive to faces, distinguished Aβ status of participants. Older adults with elevated Aβ were characterized by decreased activity in left fusiform compared to Aβ-negative older adults. Further, we found that the degree to which older adults expressed decreased fusiform activity was related to worse performance on tasks of processing speed. Our results provide unique evidence that, in addition to previously studied memory and default regions, decreased neural activity in a region important for face perception was associated with elevated Aβ and may be an early manifestation of AD.

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A single mode of population covariation associates brain networks structure and behavior and predicts individual subjects’ age

McPherson

Pestilli

2021

Commun Biol

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Multiple human behaviors improve early in life, peaking in young adulthood, and declining thereafter. Several properties of brain structure and function progress similarly across the lifespan. Cognitive and neuroscience research has approached aging primarily using associations between a few behaviors, brain functions, and structures. Because of this, the multivariate, global factors relating brain and behavior across the lifespan are not well understood. We investigated the global patterns of associations between 334 behavioral and clinical measures and 376 brain structural connections in 594 individuals across the lifespan. A single-axis associated changes in multiple behavioral domains and brain structural connections (r = 0.5808). Individual variability within the single association axis well predicted the age of the subject (r = 0.6275). Representational similarity analysis evidenced global patterns of interactions across multiple brain network systems and behavioral domains. Results show that global processes of human aging can be well captured by a multivariate data fusion approach.

show abstract

Multivariate genotypic analyses that identify specific genotypes to characterize disease and control groups in ADNI

Cited by 3 publications

References 101 publications

A single-mode associates global patterns of brain network structure and behavior across the human lifespan

A single-mode associates global patterns of brain network structure and behavior across the human lifespan

The effect of beta‐amyloid on face processing in young and old adults: A multivariate analysis of the BOLD signal

A single mode of population covariation associates brain networks structure and behavior and predicts individual subjects’ age

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