Derek Beaton

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We explore the relationships between the cortex functional organization and genetic expression (as provided by the Allen Human Brain Atlas). Previous work suggests that functional cortical networks (resting state and task based) are organized as two large networks (differentiated by their preferred information processing mode) shaped like two rings. The(More)
We present an extension of PLS—called partial least squares correspondence analysis (PLSCA)—tailored for the analysis of nominal data. As the name indicates, PLSCA combines features of PLS (analyzing the information common to two tables) and correspondence analysis (CA, analyzing nominal data). We also present inferential techniques for PLSCA such as(More)
PLS as a general multivariate method has been applied to many types of data with various covariance structures, signal strengths, numbers of observations and numbers of variables. We present a simulation framework that can cover a wide spectrum of applications by generating realistic data sets with predetermined effect sizes and distributions. In standard(More)
A converging body of clinical and empirical reports indicates that autism features elevated rates of paranoia comparable to those of individuals with paranoid schizophrenia. However, the distinct developmental courses and symptom manifestations of these two disorders suggest that the nature of paranoid ideation may differ between them in important and(More)
Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high(More)
ExPosition is a new comprehensive R package providing crisp graphics and implementing multivariate analysis methods based on the singular value decomposition (svd). The core techniques implemented in ExPosition are: principal components analysis, (metric) multidimensional scaling, correspondence analysis, and several of their recent extensions such as(More)
In the realm of unsupervised classification, clustering algorithms have presented themselves as being inefficient in the detection of non-linearly separable or non-spherically shaped based clusters, without utilizing complex implementations or computational expense. In clustering algorithm advancements, excellent results are produced with complex concepts(More)
For nearly a century, detecting the genetic contributions to cognitive and behavioral phenomena has been a core interest for psychological research. Recently, this interest has been reinvigorated by the availability of genotyping technologies (e.g., microarrays) that provide new genetic data, such as single nucleotide polymorphisms (SNPs). These SNPs-which(More)
UNLABELLED Abstract Background: Impulsivity is a complex trait often studied in substance abuse and overeating disorders, but the exact nature of impulsivity traits and their contribution to these disorders are still debated. Thus, understanding how to measure impulsivity is essential for comprehending addictive behaviors. OBJECTIVES Identify unique(More)