Influence of Processing Pipeline on Cortical Thickness Measurement

In recent years, replicability of neuroscientific findings, specifically those concerning correlates of morphological properties of gray matter (GM), have been subject of major scrutiny. Use of different processing pipelines and differences in their estimates of the macroscale GM may play an important role in this context. To address this issue, here, we investigated the cortical thickness estimates of three widely used pipelines. Based on analyses in two independent large-scale cohorts, we report high levels of within-pipeline reliability of the absolute cortical thickness-estimates and comparable spatial patterns of cortical thickness-estimates across all pipelines. Within each individual, absolute regional thickness differed between pipelines, indicating that in-vivo thickness measurements are only a proxy of actual thickness of the cortex, which shall only be compared within the same software package and thickness estimation technique. However, at group level, cortical thickness-estimates correlated strongly between pipelines, in most brain regions. The smallest between-pipeline correlations were observed in para-limbic areas and insula. These regions also demonstrated the highest interindividual variability and the lowest reliability of cortical thickness-estimates within each pipeline, suggesting that structural variations within these regions should be interpreted with caution

Quantitative genetics of human brain structure and function

The human brain is an incredibly complex organ that can be described and measured in many different ways. Whichever way we choose, no two brains are exactly the same. The general focus of this thesis will be to understand the causes of this inter-individual variability, how different aspects of the brain are affected, how these effects vary over time and space, and how this can ultimately further our understanding of cognition, behavior and neurological disorders.In Chapter 1, a more detailed introduction to these concepts and to the structure of the thesis is provided. Chapter 2 first provides an overview of the anatomy of the brain from the perspective of structure and function, which introduces the measures that will be used to describe the brain in the following chapters. This is followed by a short account of the inter-species differences found, at the macroscopic level, between human and primate brains. This emphasizes that inter-individual variation in quantitative traits is most relevant and that genetic variation is necessarily an important cause of this inter-individual variability. The second section of Chapter 2 then provides an overview of the structure and function of the human genome along with the types of genetic variation that can be found within. Given the importance of quantitative variation, a complete account of how discrete genetic factors can account for the inheritance of quantitative traits is then provided, followed by a description of the methods used to estimate this effect and the definition of the specific parameters of interest for this thesis.Chapter 3 then takes a first look at the quantitative genetics of brain structure, specifically from the perspective of age-related changes in the genetic influences over cortical thickness. Chapter 4 then looks at the quantitative genetics of brain function from the perspective of resting-state functional connectivity. This includes the complete mapping of heritability, age-related interactions and genetic correlations across the entire functional connectome. The results are then further analyzed and interpreted in view of the evolutionary history of the brain's functional systems. Finally, Chapter 5 moves beyond the analysis of structure and function to show how the results from the previous two chapters could be used to inform other traits related to cognition, behavior and disease. The focus is placed on the genetics of intelligence and the identification specific brain areas where measures of cortical structure are influenced by these same genetic factors.Taken together, these results demonstrate that genetic variation is an important cause of inter-individual variation in measures of brain structure and function in the population. They also show that the detailed investigation and proper interpretation of these influences could offer valuable insight into the genetics of cognition, behavior, and neurological disorders, and perhaps even into the evolution of the human brain.Le cerveau humain est un organe incroyablement complexe qui peut être décrit et mesuré de nombreuses façons. Peu importe le moyen choisi, aucun cerveau n’est identique. L’objectif général de cette thèse sera de comprendre les causes de cette variabilité interindividuelle, comment différents aspects du cerveau en sont affectés, comment ces effets peuvent varier spatialement et à travers le temps, et comment ceci pourra ultimement améliorer notre compréhension des processus cognitifs, comportementaux et des maladies neurologiques.Le premier chapitre fournit une introduction plus détaillée de ces concepts et de la structure de cette thèse. Le second chapitre offre d’abord un survol de la neuroanatomie structurelle et fonctionnelle du cerveau, ce qui introduit les traits qui seront utilisées pour mesurer le cerveau dans les chapitres suivants. Ces sections sont suivies d’un court résumé des différences inter-espèces qui sont observées, au niveau macroscopique, entre le cerveau humain et celui des primates. Ceci met l’emphase sur l’importance de l’étude des traits quantitatifs au niveau interindividuel et sur le fait que des variations génétiques sont nécessairement une cause importante de cette variation interindividuelle. La seconde section de ce chapitre offre donc un survol de l’organisation structurelle et fonctionnelle du génome, ainsi que des types de variations génétiques qui peuvent y être trouvées. Vu l’importance des traits quantitatifs, une description détaillées des mécanismes par lesquels la variance des traits quantitatifs peut être héritée est fournie, suivie d’une description des méthodes statistiques qui permettent d’estimer cet effet et des paramètres d’intérêt qui en découlent.Ensuite, the troisième chapitre jette un premier regard sur la génétique quantitative de la structure du cortex cérébral, spécifiquement du point de vue des interactions entre l’âge et les influences génétiques sur l’épaisseur corticale. Le quatrième chapitre s’attarde aux influences génétiques au niveau fonctionnel, spécifiquement du point de vue de la connectivité fonctionnelle au repos. Ceci inclut la cartographie complète de l’héritabilité, de ses interactions avec l’âge et des corrélations génétiques à travers le connectome fonctionnel en entier. Les résultats sont ensuite analysés et interprétés en rapport à l’histoire évolutive des systèmes fonctionnels du cerveau. Finalement, le cinquième chapitre dépasse l’analyse seule des aspects structurels et fonctionnels pour démontrer comment les résultats des chapitres précédents peuvent être utilisés dans l’étude d’autres traits liés aux aptitudes cognitives, au comportement et aux maladies. Le focus est placé sur la génétique de l’intelligence et sur l’identification de régions du cerveau où les mesures corticales sont sous l’influences des mêmes facteurs génétiques.Dans l’ensemble, ces résultats démontrent que la variation génétique est une cause importante de variation interindividuelle dans les mesures structurelles et fonctionnelles du cerveau. Ils démontrent aussi que l’étude détaillée et la juste interprétation de ces influences pourrait nous fournir d’importantes informations sur la génétique des traits cognitifs, comportementaux, des maladies neurodégénératives et peut-être même sur l’évolution du cerveau humain

Subtypes of brain activation are heritable and genetically linked with behavior in the Human Connectome Project sample

Many imaging and genetics studies have aimed to clarify whether the brain acts as an intermediate phenotype mediating the influence of genes in human behaviour. Brain activations in response to task demands are heterogeneous at the individual level, but also follow common patterns at the group level. Some studies have addressed this tension between heterogeneity and homogeneity by identifying groups of individuals that share the same brain activations patterns, called brain activation subtypes. In this work, we aimed to assess the viability of brain subtypes as endophenotypes intermediate between genes and behavior. We extracted brain activation subtypes separately for seven fMRI tasks, in 842 participants from the Human Connectome Project (HCP). We estimated the heritability of these subtypes and their genetic correlation with behavioral measures obtained inside and outside the scanner. Across all tasks, subtypes ranged from a predominantly ‘deactivating’ pattern towards a more ‘activating’ pattern of brain activity, with a heritability estimate ranging from 0 to 0.62. We observed high genetic and phenotypic correlation between behavioral measures and brain activation subtypes only for language and working memory tasks. Our results showed a significant genetic grounding of brain activation subtypes and they appear as a simple yet effective technique to tackle heterogeneity into imaging genetics studies

Influence of processing pipeline on cortical thickness measurement and its heritability estimates

Introduction Cortical thickness (CT) is one aspect of the brain structure that is studied in the context of development, aging and inter-individual variability of behaviour. Also, local variations of CT has frequently been used as an intermediate phenotype in imaging genetics studies. While no gold standard assessment of CT exists, a wealth of analysis tools has been created to estimate CT from the in-vivo T1w MRIs with three of these (FreeSurfer (FS), CAT and CIVET) enjoying high popularity. The current study compares global (gb-) and regional CT estimation from three different pipelines and assesses whether variation of tools also affect estimation of CT heritability. Methods A sample composed of 977 related-adults (age: 28.8 3.7) was provided through the Human Connectome Project (HCP; http://www.hcp.org), WU-Minn Consortium [Van Essen, 2012]. CT-estimation were performed using two surface-based pipelines (FS v5.3 and CIVET v2.1.0) and a volume-based one (CAT v12.5). FS-preprocessed surfaces (modified FS-pipeline for high resolution data and using T2w-images to improve surface estimations) were downloaded from the HCP website, while we assessed CT in CIVET and CAT using standard pipelines (on distortion and bias-field corrected T1w-images, identical to T1w-input of the FS-routine but without T2w-images) and resampled the CT-estimations to faverage (Lewis, 2019; Yotter, 2011). Comparisons are performed on mean gb- as well as regional mean CT-estimations on 400 functionally defined parcels [Schaefer, 2017]. Univariate analysis of heritability (h2) was performed using Solar Eclipse 8.4.0 (http://solar-eclipse-genetics.org). Results While CT-estimations from FS-pipeline were generally lower than the other pipelines (FS: 2.6 .08 mm, CIVET 2.7 .07 mm, CAT 2.8 .09 mm), the global and regional CT correlated highly between three routines (Fig1). Gb-CT from all three pipelines showed high h2 (FS: .86, CIVET: .78 and CAT: .88), when controlling for linear and quadratic effect of age, sex and their interaction. Nevertheless, examination of parcel-wise CT estimates revealed that, despite comparably higher h2 of CT within the sensorimotor, superior temporal, entorhinal cortex and dorsal medial frontal cortex in all three methods, differences as large as 20% between estimated regional h2 were evidenced in the precentral gyrus, subgenual-cingulate cortex, medial and lateral frontal and parietal lobes (see Fig2 A-C). Conclusion Examining the replicability of gb- and regional CT across three CT-estimation pipelines confirmed thinner FS-CT-estimates and thicker CAT’s CT-estimates, as previously reported [Seiger et al., 2018; Walhovd et al., 2017]. In interpreting our results three issues should be taken into account: 1) Our FS-based CT-estimations are assessed using modified FS-pipeline that uses the high resolution T1w-MRI and additionally use T2w-MRI to refine surface estimation. For the other two routines we used standard pipelines without T2w. Yet, it is possible to improve surface estimations by incorporating T2w-MRI as well as automatic blood-vessels masking in CIVET to improve gray and white surface estimations. 2) While FS and CAT CTs are resampled only once from subject-space to fsaverage space, CT-estimations in CIVET are resampled twice, namely from subject space to ICBM surface and then resampled to fsaverage space to extract the mean regional CT. 3) FS-surfaces are extensively visually quality controlled, yet CAT and CIVET QC consisted of only excluding subjects with gross failed surface estimations. Despite these differences, our results suggest acceptable similarity of CT estimation using these three pipelines [Dickie, 2017], with few regions showing poor correspondence between pipelines. Also, we show that while all the three pipelines depicted qualitatively comparable spatial distribution of h2, one could not directly compare h2 values of CT-estimations from different softwares

Influence of Processing Pipeline on Cortical Thickness Measurement

In recent years, replicability of neuroscientific findings, specifically those concerning correlates of morphological properties of gray matter (GM), have been subject of major scrutiny. Use of different processing pipelines and differences in their estimates of the macroscale GM may play an important role in this context. To address this issue, here, we investigated the cortical thickness estimates of three widely used pipelines. Based on analyses in two independent large-scale cohorts, we report high levels of within-pipeline reliability of the absolute cortical thickness-estimates and comparable spatial patterns of cortical thickness-estimates across all pipelines. Within each individual, absolute regional thickness differed between pipelines, indicating that in-vivo thickness measurements are only a proxy of actual thickness of the cortex, which shall only be compared within the same software package and thickness estimation technique. However, at group level, cortical thickness-estimates correlated strongly between pipelines, in most brain regions. The smallest between-pipeline correlations were observed in para-limbic areas and insula. These regions also demonstrated the highest interindividual variability and the lowest reliability of cortical thickness-estimates within each pipeline, suggesting that structural variations within these regions should be interpreted with caution

Toward next-generation primate neuroscience: A collaboration-based strategic plan for integrative neuroimaging

Open science initiatives are creating opportunities to increase research coordination and impact in nonhuman primate (NHP) imaging. The PRIMatE Data and Resource Exchange community recently developed a collaboration-based strategic plan to advance NHP imaging as an integrative approach for multiscale neuroscience