Design of interactive visualization of models and students data

This document reports the design of the interactive visualizations of open student models that will be performed in GRAPPLE. The visualizations will be based on data stored in the domain model and student model, and aim at supporting learners to be more engaged in the learning process, and instructors in assisting the learners

Genetic Contributions to the Midsagittal Area of the Corpus Callosum

The degree to which genes and environment determine variations in brain structure and function is fundamentally important to understanding normal and disease-related patterns of neural organization and activity. We studied genetic contributions to the midsagittal area of the corpus callosum (CC) in pedigreed baboons (68 males, 112 females) to replicate findings of high genetic contribution to that area of the CC reported in humans, and to determine if the heritability of the CC midsagittal area in adults was modulated by fetal development rate. Measurements of callosal area were obtained from high-resolution MRI scans. Heritability was estimated from pedigree-based maximum likelihood estimation of genetic and non-genetic variance components as implemented in Sequential Oligogenic Linkage Analysis Routines (SOLAR). Our analyses revealed significant heritability for the total area of the CC and all of its subdivisions, with h2 = .46 for the total CC, and h 2 = .54, .37, .62, .56, and .29 for genu, anterior midbody, medial midbody, posterior midbody and splenium, respectively. Genetic correlation analysis demonstrated that the individual subdivisions shared between 41% and 98% of genetic variability. Combined with previous research reporting high heritability of other brain structures in baboons, these results reveal a consistent pattern of high heritability for brain morphometric measures in baboons

Progressive Bidirectional Age-Related Changes in Default Mode Network Effective Connectivity across Six Decades

The default mode network (DMN) is a set of regions that is tonically engaged during the resting state and exhibits task-related deactivation that is readily reproducible across a wide range of paradigms and modalities. The DMN has been implicated in numerous disorders of cognition and, in particular, in disorders exhibiting age-related cognitive decline. Despite these observations, investigations of the DMN in normal aging are scant. Here, we used blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) acquired during rest to investigate age-related changes in functional connectivity of the DMN in 120 healthy normal volunteers comprising six, 20-subject, decade cohorts (from 20–29 to 70–79). Structural equation modeling (SEM) was used to assess age-related changes in inter-regional connectivity within the DMN. SEM was applied both using a previously published, meta-analytically derived, node-and-edge model, and using exploratory modeling searching for connections that optimized model fit improvement. Although the two models were highly similar (only 3 of 13 paths differed), the sample demonstrated significantly better fit with the exploratory model. For this reason, the exploratory model was used to assess age-related changes across the decade cohorts. Progressive, highly significant changes in path weights were found in 8 (of 13) paths: four rising, and four falling (most changes were significant by the third or fourth decade). In all cases, rising paths and falling paths projected in pairs onto the same nodes, suggesting compensatory increases associated with age-related decreases. This study demonstrates that age-related changes in DMN physiology (inter-regional connectivity) are bidirectional, progressive, of early onset and part of normal aging

Progressive Bidirectional Age-Related Changes in Default Mode Network Effective Connectivity across Six Decades

The default mode network (DMN) is a set of regions that is tonically engaged during the resting state and exhibits task-related deactivation that is readily reproducible across a wide range of paradigms and modalities. The DMN has been implicated in numerous disorders of cognition and, in particular, in disorders exhibiting age-related cognitive decline. Despite these observations, investigations of the DMN in normal aging are scant. Here, we used blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) acquired during rest to investigate age-related changes in functional connectivity of the DMN in 120 healthy normal volunteers comprising six, 20-subject, decade cohorts (from 20–29 to 70–79). Structural equation modeling (SEM) was used to assess age-related changes in inter-regional connectivity within the DMN. SEM was applied both using a previously published, meta-analytically derived, node-and-edge model, and using exploratory modeling searching for connections that optimized model fit improvement. Although the two models were highly similar (only 3 of 13 paths differed), the sample demonstrated significantly better fit with the exploratory model. For this reason, the exploratory model was used to assess age-related changes across the decade cohorts. Progressive, highly significant changes in path weights were found in 8 (of 13) paths: four rising, and four falling (most changes were significant by the third or fourth decade). In all cases, rising paths and falling paths projected in pairs onto the same nodes, suggesting compensatory increases associated with age-related decreases. This study demonstrates that age-related changes in DMN physiology (inter-regional connectivity) are bidirectional, progressive, of early onset and part of normal aging

Multi-Region Hemispheric Specialization Differentiates Human from Nonhuman Primate Brain Function

The human behavioral repertoire greatly exceeds that of nonhuman primates. Anatomical specializations of the human brain include an enlarged neocortex and prefrontal cortex (Semendeferi et al. in Am J Phys Anthropol 114:224–241, 2001), but regional enlargements alone cannot account for these vast functional differences. Hemispheric specialization has long believed to be a major contributing factor to such distinctive human characteristics as motor dominance, attentional control and language. Yet structural cerebral asymmetries, documented in both humans and some nonhuman primate species, are relatively minor compared to behavioral lateralization. Identifying the mechanisms that underlie these functional differences remains a goal of considerable interest. Here, we investigate the intrinsic connectivity networks in four primate species (humans, chimpanzees, baboons, and capuchin monkeys) using resting-state fMRI to evaluate the intra- and inter- hemispheric coherences of spontaneous BOLD fluctuation. All three nonhuman primate species displayed lateralized functional networks that were strikingly similar to those observed in humans. However, only humans had multi-region lateralized networks, which provide fronto-parietal connectivity. Our results indicate that this pattern of within-hemisphere connectivity distinguishes humans from nonhuman primates

Influence of age, sex and genetic factors on the human brain

We report effects of age, age(2), sex and additive genetic factors on variability in gray matter thickness, surface area and white matter integrity in 1,010 subjects from the Genetics of Brain Structure and Function Study. Age was more strongly associated with gray matter thickness and fractional anisotropy of water diffusion in white matter tracts, while sex was more strongly associated with gray matter surface area. Widespread heritability of neuroanatomic traits was observed, suggesting that brain structure is under strong genetic control. Furthermore, our findings indicate that neuroimaging-based measurements of cerebral variability are sensitive to genetic mediation. Fundamental studies of genetic influence on the brain will help inform gene discovery initiatives in both clinical and normative samples

Multi-region hemispheric specialization differentiates human from nonhuman primate brain function

The human behavioral repertoire greatly exceeds that of nonhuman primates. Anatomical specializations of the human brain include an enlarged neocortex and prefrontal cortex (Semendeferi et al. in Am J Phys Anthropol 114:224?241, 2001), but regional enlargements alone cannot account for these vast functional differences. Hemispheric specialization has long believed to be a major contributing factor to such distinctive human characteristics as motor dominance, attentional control and language. Yet structural cerebral asymmetries, documented in both humans and some nonhuman primate species, are relatively minor compared to behavioral lateralization. Identifying the mechanisms that underlie these functional differences remains a goal of considerable interest. Here, we investigate the intrinsic connectivity networks in four primate species (humans, chimpanzees, baboons, and capuchin monkeys) using resting-state fMRI to evaluate the intra- and inter- hemispheric coherences of spontaneous BOLD fluctuation. All three nonhuman primate species displayed lateralized functional networks that were strikingly similar to those observed in humans. However, only humans had multi-region lateralized networks, which provide fronto-parietal connectivity. Our results indicate that this pattern of within-hemisphere connectivity distinguishes humans from nonhuman primates

Genetic basis of neurocognitive decline and reduced white-matter integrity in normal human brain aging

Identification of genes associated with brain aging should markedly improve our understanding of the biological processes that govern normal age-related decline. However, challenges to identifying genes that facilitate successful brain aging are considerable, including a lack of established phenotypes and difficulties in modeling the effects of aging per se, rather than genes that influence the underlying trait. In a large cohort of randomly selected pedigrees (n = 1,129 subjects), we documented profound aging effects from young adulthood to old age (18-83 y) on neurocognitive ability and diffusion-based white-matter measures. Despite significant phenotypic correlation between white-matter integrity and tests of processing speed, working memory, declarative memory, and intelligence, no evidence for pleiotropy between these classes of phenotypes was observed. Applying an advanced quantitative gene-by-environment interaction analysis where age is treated as an environmental factor, we demonstrate a heritable basis for neurocognitive deterioration as a function of age. Furthermore, by decomposing gene-by-aging (G × A) interactions, we infer that different genes influence some neurocognitive traits as a function of age, whereas other neurocognitive traits are influenced by the same genes, but to differential levels, from young adulthood to old age. In contrast, increasing white-matter incoherence with age appears to be nongenetic. These results clearly demonstrate that traits sensitive to the genetic influences on brain aging can be identified, a critical first step in delineating the biological mechanisms of successful aging

Discovering schizophrenia endophenotypes in randomly ascertained pedigrees

Background Although case-control approaches are beginning to disentangle schizophrenia’s complex polygenic burden, other methods will likely be necessary to fully identify and characterize risk genes. Endophenotypes, traits genetically correlated with an illness, can help characterize the impact of risk genes by providing genetically relevant traits that are more tractable than the behavioral symptoms that classify mental illness. Here we present an analytic approach for discovering and empirically validating endophenotypes in extended pedigrees with very few affected individuals. Our approach indexes each family member’s risk as a function of shared genetic kinship with an affected individual, often referred to as the coefficient of relatedness. To demonstrate the utility of this approach, we search for neurocognitive and neuroanatomic endophenotypes for schizophrenia in large unselected multigenerational pedigrees. Methods A fixed effect test within the variance component framework was performed on neurocognitive and cortical surface area traits in 1,606 Mexican-American individuals from large, randomly ascertained extended pedigrees who participate in the “Genetics of Brain Structure and Function” study. As affecteds are excluded from analyses, results are not influenced by disease state or medication usage. Results Despite having sampled just 6 individuals with schizophrenia, our sample provided 233 individuals at various levels of genetic risk for the disorder. We identified three neurocognitive measures (digit-symbol substitution, facial memory, and emotion recognition) and six medial temporal and prefrontal cortical surfaces associated with liability for schizophrenia. Conclusions With our novel analytic approach one can discover and rank endophenotypes for schizophrenia, or any heritable disease, in randomly ascertained pedigrees