Improved interpretability of brain-behavior CCA with Domain-driven Dimension Reduction

Canonical Correlation Analysis (CCA) has been widely applied to study correlations between neuroimaging data and behavioral data. Practical use of CCA typically requires dimensionality reduction with, for example, Principal Components Analysis (PCA), however, this can result in CCA components that are difficult to interpret. In this paper, we introduce a Domain-driven Dimension Reduction (DDR) method, reducing the dimensionality of the original datasets and combining human knowledge of the structure of the variables studied. We apply the method to the Human Connectome Project S1200 release and compare standard PCA across all variables with DDR applied to individual classes of variables, finding that DDR-CCA results are more stable and interpretable, allowing the contribution of each class of variable to be better understood. By carefully designing the analysis pipeline and cross-validating the results, we offer more insights into the interpretation of CCA applied to brain-behavior data

Executive control in older Welsh monolinguals and bilinguals

Evidence for a bilingual advantage in executive control has led to the suggestion that being bilingual might protect against late-life cognitive decline. We assessed the performance of socially homogeneous groups of older (≥ 60 years) bilingual Welsh/English (n = 50) and monolingual English (n = 49) speakers on a range of executive control tasks yielding 17 indices for comparison. Effect sizes (> .2) favoured monolinguals on 10 indices, with negligible differences observed on the remaining 7 indices. Univariate analyses indicated that monolinguals performed significantly better on two of 17 indices. Multivariate analysis indicated no significant overall differences between the two groups in performance on executive tasks. Older Welsh bilinguals do not show a bilingual advantage in executive control, and where differences are observed, these tend to favour monolinguals. A possible explanation may lie in the nature of the sociolinguistic context and its influence on cognitive processing in the bilingual group

Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex.

Complex network topology is characteristic of many biological systems, including anatomical and functional brain networks (connectomes). Here, we first constructed a structural covariance network from MRI measures of cortical thickness on 296 healthy volunteers, aged 14-24 years. Next, we designed a new algorithm for matching sample locations from the Allen Brain Atlas to the nodes of the SCN. Subsequently we used this to define, transcriptomic brain networks by estimating gene co-expression between pairs of cortical regions. Finally, we explored the hypothesis that transcriptional networks and structural MRI connectomes are coupled. A transcriptional brain network (TBN) and a structural covariance network (SCN) were correlated across connection weights and showed qualitatively similar complex topological properties: assortativity, small-worldness, modularity, and a rich-club. In both networks, the weight of an edge was inversely related to the anatomical (Euclidean) distance between regions. There were differences between networks in degree and distance distributions: the transcriptional network had a less fat-tailed degree distribution and a less positively skewed distance distribution than the SCN. However, cortical areas connected to each other within modules of the SCN had significantly higher levels of whole genome co-expression than expected by chance. Nodes connected in the SCN had especially high levels of expression and co-expression of a human supragranular enriched (HSE) gene set that has been specifically located to supragranular layers of human cerebral cortex and is known to be important for large-scale, long-distance cortico-cortical connectivity. This coupling of brain transcriptome and connectome topologies was largely but not entirely accounted for by the common constraint of physical distance on both networks

Schizotypy-Related Magnetization of Cortex in Healthy Adolescence Is Colocated With Expression of Schizophrenia-Related Genes.

BACKGROUND: Genetic risk is thought to drive clinical variation on a spectrum of schizophrenia-like traits, but the underlying changes in brain structure that mechanistically link genomic variation to schizotypal experience and behavior are unclear. METHODS: We assessed schizotypy using a self-reported questionnaire and measured magnetization transfer as a putative microstructural magnetic resonance imaging marker of intracortical myelination in 68 brain regions in 248 healthy young people (14-25 years of age). We used normative adult brain gene expression data and partial least squares analysis to find the weighted gene expression pattern that was most colocated with the cortical map of schizotypy-related magnetization. RESULTS: Magnetization was significantly correlated with schizotypy in the bilateral posterior cingulate cortex and precuneus (and for disorganized schizotypy, also in medial prefrontal cortex; all false discovery rate-corrected ps < .05), which are regions of the default mode network specialized for social and memory functions. The genes most positively weighted on the whole-genome expression map colocated with schizotypy-related magnetization were enriched for genes that were significantly downregulated in two prior case-control histological studies of brain gene expression in schizophrenia. Conversely, the most negatively weighted genes were enriched for genes that were transcriptionally upregulated in schizophrenia. Positively weighted (downregulated) genes were enriched for neuronal, specifically interneuronal, affiliations and coded a network of proteins comprising a few highly interactive "hubs" such as parvalbumin and calmodulin. CONCLUSIONS: Microstructural magnetic resonance imaging maps of intracortical magnetization can be linked to both the behavioral traits of schizotypy and prior histological data on dysregulated gene expression in schizophrenia

Pediatric epilepsy surgery from 2000 to 2018: Changes in referral and surgical volumes, patient characteristics, genetic testing, and postsurgical outcomes

OBJECTIVE: Neurosurgery is a safe and effective form of treatment for select children with drug-resistant epilepsy. Still, there is concern that it remains underutilized, and that seizure freedom rates have not improved over time. We investigated referral and surgical practices, patient characteristics, and postoperative outcomes over the past two decades. METHODS: We performed a retrospective cohort study of children referred for epilepsy surgery at a tertiary center between 2000 and 2018. We extracted information from medical records and analyzed temporal trends using regression analyses. RESULTS: A total of 1443 children were evaluated for surgery. Of these, 859 (402 females) underwent surgical resection or disconnection at a median age of 8.5 years (interquartile range [IQR] = 4.6-13.4). Excluding palliative procedures, 67% of patients were seizure-free and 15% were on no antiseizure medication (ASM) at 1-year follow-up. There was an annual increase in the number of referrals (7%, 95% confidence interval [CI] = 5.3-8.6; p < .001) and surgeries (4% [95% CI = 2.9-5.6], p < .001) over time. Duration of epilepsy and total number of different ASMs trialed from epilepsy onset to surgery were, however, unchanged, and continued to exceed guidelines. Seizure freedom rates were also unchanged overall but showed improvement (odds ratio [OR] 1.09, 95% CI = 1.01-1.18; p = .027) after adjustment for an observed increase in complex cases. Children who underwent surgery more recently were more likely to be off ASMs postoperatively (OR 1.04, 95% CI = 1.01-1.08; p = .013). There was a 17% annual increase (95% CI = 8.4-28.4, p < .001) in children identified to have a genetic cause of epilepsy, which was associated with poor outcome. SIGNIFICANCE: Children with drug-resistant epilepsy continue to be put forward for surgery late, despite national and international guidelines urging prompt referral. Seizure freedom rates have improved over the past decades, but only after adjustment for a concurrent increase in complex cases. Finally, genetic testing in epilepsy surgery patients has expanded considerably over time and shows promise in identifying patients in whom surgery is less likely to be successful

Gene transcription profiles associated with inter-modular hubs and connection distance in human functional magnetic resonance imaging networks.

Human functional magnetic resonance imaging (fMRI) brain networks have a complex topology comprising integrative components, e.g. long-distance inter-modular edges, that are theoretically associated with higher biological cost. Here, we estimated intra-modular degree, inter-modular degree and connection distance for each of 285 cortical nodes in multi-echo fMRI data from 38 healthy adults. We used the multivariate technique of partial least squares (PLS) to reduce the dimensionality of the relationships between these three nodal network parameters and prior microarray data on regional expression of 20 737 genes. The first PLS component defined a transcriptional profile associated with high intra-modular degree and short connection distance, whereas the second PLS component was associated with high inter-modular degree and long connection distance. Nodes in superior and lateral cortex with high inter-modular degree and long connection distance had local transcriptional profiles enriched for oxidative metabolism and mitochondria, and for genes specific to supragranular layers of human cortex. In contrast, primary and secondary sensory cortical nodes in posterior cortex with high intra-modular degree and short connection distance had transcriptional profiles enriched for RNA translation and nuclear components. We conclude that, as predicted, topologically integrative hubs, mediating long-distance connections between modules, are more costly in terms of mitochondrial glucose metabolism.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'.PEV is supported by an MRC Bioinformatics Research Fellowship (MR/K020706/1). Functional MRI data acquisition was supported by a strategic award from the Wellcome Trust to the University of Cambridge (IMG, PBJ, ETB) and University College London (RJD, PF): the Neuroscience in Psychiatry Network (NSPN). Additional support was provided by the NIHR Cambridge Biomedical Research Centre. Access to gene expression data was provided by the Allen Institute for Brain Sciences Website: © 2015 Allen Institute for Brain Science. Allen Human Brain Atlas [Internet]. Available from: http://human.brain-map.org. FV is supported by a Gates Cambridge PhD studentship. KW is supported by the University of Cambridge MB/PhD Programme and the Wellcome Trust. We thank Gita Prabu, Roger Tait, Cinly Ooi, John Suckling and Becky Inkster for fMRI data collection and storage. ETB is employed half-time by the University of Cambridge and half-time by GlaxoSmithKline(GSK).This is the final version of the article. It first appeared from Royal Society Publishing via http://dx.doi.org/10.1098/rstb.2015.036

Adolescents with current major depressive disorder show dissimilar patterns of age-related differences in ACC and thalamus.

OBJECTIVE: There is little understanding of the neural system abnormalities subserving adolescent major depressive disorder (MDD). In a cross-sectional study we compare currently unipolar depressed with healthy adolescents to determine if group differences in grey matter volume (GMV) were influenced by age and illness severity. METHOD: Structural neuroimaging was performed on 109 adolescents with current MDD and 36 healthy controls, matched for age, gender, and handedness. GMV differences were examined within the anterior cingulate cortex (ACC) and across the whole-brain. The effects of age and self-reported depressive symptoms were also examined in regions showing significant main or interaction effects. RESULTS: Whole-brain voxel based morphometry revealed no significant group differences. At the whole-brain level, both groups showed a main effect of age on GMV, although this effect was more pronounced in controls. Significant group-by-age interactions were noted: A significant regional group-by-age interaction was observed in the ACC. GMV in the ACC showed patterns of age-related differences that were dissimilar between adolescents with MDD and healthy controls. GMV in the thalamus showed an opposite pattern of age-related differences in adolescent patients compared to healthy controls. In patients, GMV in the thalamus, but not the ACC, was inversely related with self-reported depressive symptoms. CONCLUSIONS: The depressed adolescent brain shows dissimilar age-related and symptom-sensitive patterns of GMV differences compared with controls. The thalamus and ACC may comprise neural markers for detecting these effects in youth. Further investigations therefore need to take both age and level of current symptoms into account when disaggregating antecedent neural vulnerabilities for MDD from the effects of MDD on the developing brain.This study was funded by the UK Medial Research Council (grant: G0802226), theNational Institute for Health Research (NIHR) (grant: 06/05/01) and the Behavioural and Clinical Neuroscience Institute (BCNI), University of Cambridge. The BCNI is jointly funded by the Medical Research Council and the Wellcome Trust. Additional support was received from the Cambridge Biomedical Research Centre. CCH is supported by a Parke Davis Fellowship from the University of Cambridge and resides at Columbia University.This is the final published version. It first appeared at: http://www.sciencedirect.com/science/article/pii/S2213158214002046#

Resilient functioning is associated with altered structural brain network topology in adolescents exposed to childhood adversity

Childhood adversity is one of the strongest predictors of adolescent mental illness. Therefore, it is critical that the mechanisms that aid resilient functioning in individuals exposed to childhood adversity are better understood. Here, we examined whether resilient functioning was related to structural brain network topology. We quantified resilient functioning at the individual level as psychosocial functioning adjusted for the severity of childhood adversity in a large sample of adolescents (N = 2406, aged 14–24). Next, we examined nodal degree (the number of connections that brain regions have in a network) using brain-wide cortical thickness measures in a representative subset (N = 275) using a sliding window approach. We found that higher resilient functioning was associated with lower nodal degree of multiple regions including the dorsolateral prefrontal cortex, the medial prefrontal cortex, and the posterior superior temporal sulcus (z > 1.645). During adolescence, decreases in nodal degree are thought to reflect a normative developmental process that is part of the extensive remodeling of structural brain network topology. Prior findings in this sample showed that decreased nodal degree was associated with age, as such our findings of negative associations between nodal degree and resilient functioning may therefore potentially resemble a more mature structural network configuration in individuals with higher resilient functioning

Conservative and disruptive modes of adolescent change in human brain functional connectivity.

Adolescent changes in human brain function are not entirely understood. Here, we used multiecho functional MRI (fMRI) to measure developmental change in functional connectivity (FC) of resting-state oscillations between pairs of 330 cortical regions and 16 subcortical regions in 298 healthy adolescents scanned 520 times. Participants were aged 14 to 26 y and were scanned on 1 to 3 occasions at least 6 mo apart. We found 2 distinct modes of age-related change in FC: "conservative" and "disruptive." Conservative development was characteristic of primary cortex, which was strongly connected at 14 y and became even more connected in the period from 14 to 26 y. Disruptive development was characteristic of association cortex and subcortical regions, where connectivity was remodeled: connections that were weak at 14 y became stronger during adolescence, and connections that were strong at 14 y became weaker. These modes of development were quantified using the maturational index (MI), estimated as Spearman's correlation between edgewise baseline FC (at 14 y, [Formula: see text]) and adolescent change in FC ([Formula: see text]), at each region. Disruptive systems (with negative MI) were activated by social cognition and autobiographical memory tasks in prior fMRI data and significantly colocated with prior maps of aerobic glycolysis (AG), AG-related gene expression, postnatal cortical surface expansion, and adolescent shrinkage of cortical thickness. The presence of these 2 modes of development was robust to numerous sensitivity analyses. We conclude that human brain organization is disrupted during adolescence by remodeling of FC between association cortical and subcortical areas