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International audience; Component-based multitable methods, such as multiple factor analysis (MFA), STATIS, and DiSTATIS, are routinely used to analyze multiblock data, which are now common in chemometrics and sensory evaluation studies. These blocks of data form data tables that—for example, in sensory evaluation—describe how different assessors evaluate a set of products either on a set of descriptors or on the similarity between products. To analyze these data, component-based multitable methods extract orthogonal components explaining most of the variance of the data. However, when the data tables are heterogeneous or have complex structures, a single component space does not represent the data well and can give components that are difficult to interpret. Previous literature solved this interpretation problem by eliminating irrelevant variables—a process called sparsification—while keeping the components orthogonal. Here, we extended such methods to develop sparsification algorithms for three multitable methods, namely, “sparse MFA” (sMFA), “sparse STATIS” (sSTATIS), and “sparse DiSTATIS” (sDiSTATIS). In these sparse methods, we sparsified the data tables to identify the most informative assessors or products. In sMFA, we show how group sparsity can be used to sparsify whole tables (i.e., assessors or products), hereby greatly increasing the interpretability of sMFA's outcome. In sSTATIS and sDiSTATIS, we developed two different sparsification approaches: One approach creates subgroups of products and simplifies the components to facilitate interpretation; whereas the other approach creates subgroups of assessors and alleviates the problem of heterogeneity. We showed with three examples how these sparse methods increase interpretability of the results in sensory evaluation.

Teachers of the d/Deaf (TODs) struggle to select appropriate storybooks for elementary-aged Deaf pre-readers who use American Sign Language (Hayesamp; Shaw, 1994). Hayes and Shaw (1994) created a book selection system for TODs, but their methodology was difficult to evaluate. The purpose of the present research was to create an empirically derived book selection system using a sorting task methodology that has been successfully adapted for creating book selection systems (Schwarz et al., 2015, 2019). In a pilot study, 16 experienced TODs sorted 14 storybooks from published preschool curricula and explained the thinking behind their selections. Using content analysis and a multivariate technique, the authors created a book selection system with a two-tiered glossary and 4-point difficulty scale. They discuss how this system can be used with evidence-based read-aloud interventions compatible with the Framework of Early Literacy (Kuntzeamp; Golos, 2021).

Background: Prior work has shown that certain modifiable health, Alzheimer’s disease (AD) biomarker, and demographic variables are associated with cognitive performance. However, less is known about the relative importance of these different domains of variables in predicting longitudinal change in cognition.Objective: Identify novel relationships between modifiable physical and health variables, AD biomarkers, and slope of cognitive change over two years in a cohort of older adults with mild cognitive impairment (MCI).Methods: Metrics of cardiometabolic risk, stress, inflammation, neurotrophic/growth factors, and AD pathology were assessed in 123 older adults with MCI at baseline from the Alzheimer’s Disease Neuroimaging Initiative (mean age = 73.9; sd =7.6; mean education = 16.0; sd = 3.0). Partial least squares regression (PLSR)—a multivariate technique which creates components that best predict an outcome—was used to identify whether these physiological variables were important in predicting slope of change in episodic memory or executive function over two years.Results: At two-year follow-up, the two PLSR models predicted, respectively, 20.0% and 19.6% of the variance in change in episodic memory and executive function. Baseline levels of AD biomarkers were important in predicting change in both episodic memory and executive function. Baseline education and neurotrophic/growth factors were important in predicting change in episodic memory, whereas cardiometabolic variables such as blood pressure and cholesterol were important in predicting change in executive function. Conclusion: These data-driven analyses highlight the impact of AD biomarkers on cognitive change and further clarify potential domain specific relationships with predictors of cognitive change.

Influential research has focused on identifying the common neural and behavioural substrates underlying episodic memory (the re-experiencing of specific details from past experiences) and spatial cognition, with some theories proposing that these are supported by the same mechanisms. However, the similarities and differences between these two forms of memory in humans require further specification. We used an individual-differences approach based on self-reported survey data collected in a large online study (n = 7,487), focusing on autobiographical episodic memory and spatial navigation and their relationship to object and spatial imagery abilities. Multivariate analyses replicated prior findings that autobiographical episodic memory abilities dissociated from spatial navigational abilities. Considering imagery, episodic autobiographical memory overlapped with imagery of objects, whereas spatial navigation overlapped with a tendency to focus on spatial schematics and manipulation. These results suggest that trait episodic autobiographical memory and spatial navigation correspond to distinct mental processes.

Occupations are typically characterized in nominal form, a format that limits options for hypothesis testing and data analysis. We drew upon ratings of knowledge, skills, and abilities for 966 occupations listed in the US Department of Labor’s Occupational Classification Network (O*NET) database to create an accessible, standardized multidimensional space in which occupations can be quantitatively localized and compared. Principal components analysis revealed that the occupation space comprises three main dimensions that correspond to 1) the required amount of education and training, 2) the degree to which an occupation falls within a science, technology, engineering, and mathematics (STEM) discipline versus social sciences and humanities, and 3) whether occupations are more mathematically or health-related. Additional occupational spaces reflecting cognitive versus labour-oriented categories were created for finer grained characterization of dimensions within occupational sets defined by higher or lower required educational preparation. Data-driven groupings of related occupations were obtained with hierarchical cluster analysis (HCA). Proof-of-principle was demonstrated with a real-world dataset (470 participants from the Nathan Kline Institute – Rockland Sample; NKI-RS), whereby verbal and non-verbal abilities—as assessed by standardized testing—were related to the STEM versus social sciences and humanities dimension. Visualization of Latent Components Assessed in O*Net Occupations (VOLCANO) is provided to the research community as a freely accessible tool, along with a shiny app for users to extract quantitative scores along the relevant dimensions. VOLCANO brings much-needed standardization to unwieldy occupational data. Moreover, it can be used to create new occupational spaces customized to specific research domains.

Objectives. Efficient multisensory speech detection is critical for children who must quickly detect/encode a rapid stream of speech to participate in conversations and to have access to the audiovisual cues that underpin speech and language development, yet multisensory speech detection remains understudied in children with hearing loss (CHL). This research assessed detection, along with vigilant/goal-directed attention, for multisensory vs. uni-sensory speech in CHL vs. children with normal hearing (CNH). Design. Participants were 60 CHL who used hearing aids and communicated successfully aurally/orally and 60 age-matched CNH. Simple response times determined how quickly children could detect a pre-identified easy-to-hear stimulus (70 dB SPL, utterance “buh” presented in Auditory only (A), Visual only (V), or Audiovisual (AV) modes). The V mode formed two facial conditions: static vs. dynamic face. Faster detection for multisensory (AV) than uni-sensory (A or V) input indicates multisensory facilitation. We assessed mean responses and faster vs. slower responses (defined by 1st vs. 3rd quartiles of response-time distributions), which were respectively conceptualized as: faster responses (1st quartile) reflect efficient detection with efficient vigilant/goal-directed attention and slower responses (3rd quartile) reflect less efficient detection associated with attentional lapses. Lastly, we studied associations between these results and personal characteristics of CHL.Results. Uni-sensory A vs. V Modes: Both Groups showed better detection and attention for A than V input. The A input more readily captured children's attention and minimized attentional lapses, which supports A-bound processing even by CHL who were processing low fidelity A input. CNH and CHL did not differ in ability to detect A input at conversational speech level. Multisensory AV vs. A Modes. Both Groups showed better detection and attention for AV than A input. The advantage for AV input was facial effect (both static and dynamic faces), a pattern suggesting that communication is a social interaction that is more than just words. Attention did not differ between Groups; detection was faster in CHL than CNH for AV input, but not for A input. Associations Between Personal Characteristics/Degree of Hearing Loss of CHL and Results. CHL with greatest deficits in detection of V input had poorest word recognition skills and CHL with greatest reduction of attentional lapses from AV input had poorest vocabulary skills. Both outcomes are consistent with the idea that CHL who are processing low fidelity A input depend disproportionately on V and AV input to learn to identify words and associated them with concepts. As CHL aged, attention to V input improved. Degree of HL did not influence results.Conclusions. Understanding speech—a daily challenge for CHL—is a complex task that demands efficient detection of and attention to AV speech cues. Our results support the clinical importance of multisensory assessments in order to understand and advance spoken communication by CHL.

Background Prenatal maternal depression (PMD) and selective serotonin reuptake inhibitor (SSRI) antidepressants are associated with increased developmental risk in infants. Reports suggest that PMD is associated with hyperconnectivity of the insula and the amygdala, while SSRI exposure is associated with hyperconnectivity of the auditory network in the infant brain. However, associations between functional brain organization and PMD and/or SSRI exposure are not well understood. Methods We examined the relation between PMD or SSRI exposure and neonatal brain functional organization. Infants of control (n = 17), depressed SSRI-treated (n = 20) and depressed-only (HAM-D ≥ 8) (n = 16) women, underwent resting-state functional magnetic resonance imaging at postnatal Day 6. At 6 months, temperament was assessed using Infant Behavioral Questionnaire (IBQ). We applied GTA and partial least square regression (PLSR) to the resting-state time series to assess group differences in modularity, and connector and provincial hubs. Results Modularity was similar across all groups. The depressed-only group showed higher connector hub values in the left anterior cingulate, insula, and caudate as well as higher provincial hub values in the amygdala compared to the control group. The SSRI group showed higher provincial hub values in Heschl's gyrus relative to the depressed-only group. PLSR showed that newborns' hub values predicted 10% of the variability in infant temperament at 6 months, suggesting different developmental patterns between groups. Conclusions Prenatal exposures to maternal depression and SSRIs have differential impacts on neonatal functional brain organization. Hub values at 6 days predict variance in temperament between infant groups at 6 months of age.

We present a Descriptive Analysis (DA) of a large representative sample (24 whiskeys) of two legally distinct types of American whiskeys: bourbon and rye whiskey (respectively distilled from a fermented ?mashbill? of at least 51% corn or rye). We wanted to determine whether a trained panel could find sensory differences between these two products. We used standard DA: 11 judges were trained for 10 hours to develop a lexicon of 24 flavor, taste, and mouthfeel descriptors for the 24 whiskey samples (15 bourbons and 9 ryes). Then, subjects rated each whiskey sample on each attribute, using unstructured line scales, in standard good sensory-evaluation conditions, and in triplicate. Results were analyzed using MANOVA, Barycentric Discriminant Analysis, and Hierarchical Cluster Analysis. Overall, while 10 descriptors significantly differentiated the whiskeys, no attribute or combination of attributes was predicted by mashbill: The judges did not find differences in sensory character between bourbon and rye whiskeys as categories. However, significant differences could be attributed to the producer of the whiskey and to age at bottling. These results are important because American whiskey has recently become staggeringly popular, and because there is a consistent belief that bourbon and rye whiskeys?as categories?have distinct sensory characteristics. Practical Application This research contradicts popular and expert beliefs about the distinction between the popular and important American rye and bourbon whiskeys. A comprehensive sensory DA study of 24 American whiskeys with different mashbills (9 ryes and 15 bourbons) shows that?while each whiskey is individually distinct on a number of sensory dimensions?sensory differences between rye and bourbon whiskeys as product categories cannot be predicted by mashbill. For producers, consumers, and researchers, this research points to the need for new theories on the origins of flavors in whiskey, as it is now clear that the grain content alone cannot predict sensory qualities.

For d/Deaf and hard-of-hearing prereaders who communicate predominately in spoken and/or signed English (DHH-English), Teachers of the d/Deaf (TODs) read books aloud to increase English skills, aud...

The dynamic structure of proteins is essential for their functions and may include large conformational transitions which can be studied by molecular dynamics (MD) simulations. However, details of these transitions are difficult to automatically track. To facilitate their analysis, we developed two scores of correlation between sidechain dihedral angles. The CIRCULAR and OMES scores are computed from, respectively, dihedral angle values and rotamer distributions. As a case study, we applied our methods to an activation-like transition of the chemokine receptor CXCR4, observed during accelerated MD simulations. The principal component analysis of the correlation matrices was consistent with the networking structure of the top ranking pairs. Both scores identify a set of residues whose “collaborative” sidechain rotamerization immediately preceded or accompanied the conformational transition of CXCR4. Detailed analysis of the sequential order of these rotamerizations suggests that an allosteric mechanism, involving the outward motion of an asparagine residue in transmembrane helix 3, might be a prerequisite to the large scale conformational transition of CXCR4. This case study provides the proof-of-concept that the correlation methods developed here are valuable exploratory techniques to help decipher complex reactional pathways.

Healthy aging is accompanied by reduced cognitive control and widespread alterations in the underlying brain networks; but the extent to which large-scale functional networks in older age show reduced specificity across different domains of cognitive control is unclear. Here we use cov-STATIS (a multi-table multivariate technique) to examine similarity of functional connectivity during different domains of cognitive control-inhibition, initiation, shifting, and working memory-across the adult lifespan. We report two major findings: (1) Functional connectivity patterns during initiation, inhibition, and shifting were more similar in older ages, particularly for control and default networks, a pattern consistent with dedifferentiation of the neural correlates associated with cognitive control; and (2) Networks exhibited age-related reconfiguration such that frontal, default, and dorsal attention networks were more integrated whereas sub-networks of somato-motor system were more segregated in older age. Together these findings offer new evidence for dedifferentiation and reconfiguration of functional connectivity underlying different aspects of cognitive control in normal aging.

International audience; Multiple Correspondence Analysis (MCA) is the method of choicefor themultivariate analysis of categorical data. In MCA each qualitative variable is representedby a group of binary variables (with a coding scheme called “complete disjunctive coding”)and each binary variable has a weight inversely proportional to its frequency. The datamatrix concatenates all these binary variables, and once normalized and centered thisdata matrix is analyzed with a generalized singular value decomposition (GSVD) thatincorporates the variable weights as constraints (or “metric”). The GSVD is, of course,based on the plain SVD and so MCA can be sparsified by extending algorithms designedto sparsify the SVD. To do so requires two additional features: to include weights andto be able to sparsify entire groups of variables at once. Another important feature ofsuch a sparsification should be to preserve the orthogonality of the components, Here, weintegrate all these constraints by using an exact projection scheme onto the intersectionof subspaces (i.e., balls) where each ball represents a specific type of constraints. Weillustrate our procedure with the data from a questionnaire survey on the perception ofcheese in two French cities.