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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-effects test within the variance component framework was performed on neurocognitive and cortical surface area traits in 1606 Mexican-American individuals from large, randomly ascertained extended pedigrees who participated in the Genetics of Brain Structure and Function study. As affecteds were excluded from analyses, results were 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.

BACKGROUND: We measured and compared heritability estimates for measures of functional brain connectivity extracted using the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) rsfMRI analysis pipeline in two cohorts: the GOBS (Genetics of Brain Structure) cohort and the HCP (the Human Connectome Project) cohort. These two cohorts were assessed using conventional (GOBS) and advanced (HCP) rsfMRI protocols, offering a test case for harmonization of rsfMRI phenotypes, and to determine measures that show consistent heritability for in-depth genome-wide analysis. METHODS: The GOBS cohort consisted of 334 Mexican-American individuals (124M/210F, average age=47.9±13.2 years) from 29 extended pedigrees (average family size=9 people; range 5–32). The GOBS rsfMRI data was collected using a 7.5-minute acquisition sequence (spatial resolution=1.72×1.72×3 mm(3)). The HCP cohort consisted of 518 twins and family members (240M/278F; average age=28.7± 3.7 years). rsfMRI data was collected using 28.8-minute sequence (spatial resolution=2×2×2 mm(3)). We used the single-modality ENIGMA rsfMRI preprocessing pipeline to estimate heritability values for measures from eight major functional networks, using (1) seed-based connectivity and (2) dual regression approaches. RESULTS: We observed significant heritability (h(2)=0.2–0.4, p

The cerebral cortex may be organized into anatomical genetic modules, communities of brain regions with shared genetic influences via pleiotropy. Such modules could represent novel phenotypes amenable to large-scale gene discovery. This modular structure was investigated with network analysis of in vivo MRI of extended pedigrees, revealing a “multiscale” structure where smaller and larger modules exist simultaneously and in partially overlapping fashion across spatial scales, in contrast to prior work suggesting a specific number of cortical thickness modules. Inter-regional genetic correlations, gene co-expression patterns and computational models indicate that two simple organizational principles account for a large proportion of the apparent complexity in the network of genetic correlations. First, regions are strongly genetically correlated with their homologs in the opposite cerebral hemisphere. Second, regions are strongly genetically correlated with nearby regions in the same hemisphere, with an initial steep decrease in genetic correlation with anatomical distance, followed by a more gradual decline. Understanding underlying organizational principles of genetic influence is a critical step towards a mechanistic model of how specific genes influence brain anatomy and mediate neuropsychiatric risk.

Coordinate-based meta-analyses (CBMA) allow researchers to combine the results from multiple fMRI experiments with the goal of obtaining results that are more likely to generalise. However, the interpretation of CBMA findings can be impaired by the file drawer problem, a type of publications bias that refers to experiments that are carried out but are not published. Using foci per contrast count data from the BrainMap database, we propose a zero-truncated modelling approach that allows us to estimate the prevalence of non-significant experiments. We validate our method with simulations and real coordinate data generated from the Human Connectome Project. Application of our method to the data from BrainMap provides evidence for the existence of a file drawer effect, with the rate of missing experiments estimated as at least 6 per 100 reported. The R code that we used is available at https://osf.io/ayhfv/. This article is protected by copyright. All rights reserved.

Neuropsychiatric disorders are increasingly conceptualized as disconnection syndromes that are associated with abnormal network integrity in the brain. However, whether different neuropsychiatric disorders show commonly dysfunctional connectivity architectures in large-scale brain networks remains largely unknown. Here, we performed a meta-connectomic study to identify disorder-related functional modules and brain regions by combining meta-analyses of 182 published resting-state functional MRI studies in 11 neuropsychiatric disorders and graph-theoretical analyses of 3 independent resting-state functional MRI datasets with healthy and diseased populations (Alzheimer's disease and major depressive disorder [MDD]). Three major functional modules, the default mode, frontoparietal, and sensorimotor networks were commonly abnormal across disorders. Moreover, most of the disorders preferred to target the network connector nodes that were primarily involved in intermodule communications and multiple cognitive components. Apart from these common dysfunctions, different brain disorders were associated with specific alterations in network modules and connector regions. Finally, these meta-connectomic findings were confirmed by two empirical example cases of Alzheimer's disease and MDD. Collectively, our findings shed light on the shared biological mechanisms of network dysfunctions of diverse disorders and have implications for clinical diagnosis and treatment from a network perspective.

Neuroimaging evidence suggests that executive functions (EF) depend on brain regions that are not closely tied to specific cognitive demands but rather to a wide range of behaviors. A multiple-demand (MD) system has been proposed, consisting of regions showing conjoint activation across multiple demands. Additionally, a number of studies defining networks specific to certain cognitive tasks suggest that the MD system may be composed of a number of sub-networks each subserving specific roles within the system. We here provide a robust definition of an extended MDN (eMDN) based on task-dependent and task-independent functional connectivity analyses seeded from regions previously shown to be convergently recruited across neuroimaging studies probing working memory, attention and inhibition, i.e., the proposed key components of EF. Additionally, we investigated potential sub-networks within the eMDN based on their connectional and functional similarities. We propose an eMDN network consisting of a core whose integrity should be crucial to performance of most operations that are considered higher cognitive or EF. This then recruits additional areas depending on specific demands.

[Image: see text] COVER ILLUSTRATION: Locked‐in Children. Children resuscitated after near‐fatal drowning often incur anoxic brain injury (ABI). Locked‐in syndrome — a condition defined by the co‐occurrence of quadriplegia and aphonia — is a previously unreported consequence of pediatric ABI. In this issue, Ishaque and colleagues report ICA analysis of resting‐state fMRI (rs‐fMRI) and network‐based quantitative behavioral assessments in 10 children with drowning‐induced ABI, each of whom exhibit some form of lockedin syndrome. On a per‐subject basis, rs‐fMRI network preservation closely paralleled behavioral results (r = 0.74), suggesting that rs‐fMRI has the potential to assess cognitive status when communication is compromised.

The neural systems of lexical tone processing have been studied for many years. However, previous findings have been mixed with regard to the hemispheric specialization for the perception of linguistic pitch patterns in native speakers of tonal language. In this study, we performed two activation likelihood estimation (ALE) meta-analyses, one on neuroimaging studies of auditory processing of lexical tones in tonal languages (17 studies), and the other on auditory processing of lexical information in non-tonal languages as a control analysis for comparison (15 studies). The lexical tone ALE analysis showed significant brain activations in bilateral inferior prefrontal regions, bilateral superior temporal regions and the right caudate. While the control ALE analysis showed significant cortical activity in the left inferior frontal gyrus and left temporo-parietal regions. However, we failed to obtain significant differences from the contrast analysis between two auditory conditions, which might be caused by the limited number of studies available for comparison. Although the current study lack evidence to argue for a lexical tone specific activation pattern, our results provide clues and directions for future investigations on this topic, more and more sophisticated methods are needed to explore this question in more depth as well.

By means of a novel methodology that can statistically derive patterns of co-alterations distribution from voxel-based morphological data, this study analyzes the patterns of brain alterations of three important psychiatric spectra-that is, schizophrenia spectrum disorder (SCZD), autistic spectrum disorder (ASD), and obsessive-compulsive spectrum disorder (OCSD). Our analysis provides five important results. First, in SCZD, ASD, and OCSD brain alterations do not distribute randomly but, rather, follow network-like patterns of co-alteration. Second, the clusters of co-altered areas form a net of alterations that can be defined as morphometric co-alteration network or co-atrophy network (in the case of gray matter decreases). Third, within this network certain cerebral areas can be identified as pathoconnectivity hubs, the alteration of which is supposed to enhance the development of neuronal abnormalities. Fourth, within the morphometric co-atrophy network of SCZD, ASD, and OCSD, a subnetwork composed of eleven highly connected nodes can be distinguished. This subnetwork encompasses the anterior insulae, inferior frontal areas, left superior temporal areas, left parahippocampal regions, left thalamus and right precentral gyri. Fifth, the co-altered areas also exhibit a normal structural covariance pattern which overlaps, for some of these areas (like the insulae), the co-alteration pattern. These findings reveal that, similarly to neurodegenerative diseases, psychiatric disorders are characterized by anatomical alterations that distribute according to connectivity constraints so as to form identifiable morphometric co-atrophy patterns.

Background Given the inaccessibility of brain tissue for large cohort-based and longitudinal studies, analysis of peripheral blood as a surrogate tissue has become a mainstay within the neuropsychiatric field for analysis of gene and miRNA expression and DNA methylation. Although the importance of peripheral biomarkers as diagnostic and prognostic indicators is well recognized, translation of findings into meaningful pathology is more difficult to achieve. Lack of validation of peripheral biomarkers in brain tissue may be confounded by smaller sample sizes, investigation of inappropriate brain regions, or post-mortem complications. Methods To shed some light on the utility of blood-based biomarkers to inform upon pathology of disease, we investigated correlations between miRNA expression levels in blood and brain tissue from 14 cortical and subcortical regions within two groups of baboons (n=4, n=6; 7 brain regions each). To better understand how blood-brain correlations might relate to human biology and disease, we investigated a subset of 212 miRNAs whose peripheral blood expression was at least moderately correlated (r≥0.5) with 50% or more of the brain regions examined in a family-based cohort of Mexican Americans (n=896) for whom we have extensive neurocognitive and neuroanatomical phenotypes as well as peripheral blood miRNA profiles. We tested 145 human peripheral blood-expressed miRNAs for association against 34 cortical and 10 subcortical structures (using magnetic resonance imaging data), and 24 neurocognitive phenotypes. Due to high inter-relatedness and potentially unknown correlations across many of the phenotypes assessed, we corrected only for the number of miRNAs tested, setting the significance threshold at p Results The overall correlation (r) of miRNA expression profiles between blood and 14 different brain regions in baboons ranged from 0.62–0.66. We identified 444 miRNAs that were expressed in 90% of all samples analyzed and of these, 212 showed at least moderate correlation (r≥0.5) between blood and 50% or more of the brain regions examined. Within this subset of baboon-defined correlated miRNAs, we identified 145 that were also expressed in at least 90% of our human cohort and tested these for association with neurological traits. We identified 34 significant associations between miRNAs and neurological traits. Of these, one of the most interesting findings was association of peripheral miR-144-3p expression with amygdala (p=8.50×10-5) and hippocampus (p=5.86×10-5) volumes, as well as thickness of the fusiform gyrus (p=1.98×10-5). In our baboon study, peripheral expression of this miRNA was highly correlated with expression in the amygdala (r=1.00) and hippocampus (r=0.66), expression was not measured in the fusiform gyrus. Discussion Prior studies have shown that overexpression of miR-144-3p in the basolateral amygdala of mice rescued impaired fear extinction, and also that expression of miR-144-3p is increased in the hippocampus of rats following chronic treatment of both lithium and valproate mood stabilizers. Our studies highlight the utility of using peripheral blood as a surrogate tissue for miRNA profiling and indicate that disease associations identified using peripheral blood may point toward pathological processes within the brain, particularly for miRNAs whose expression is correlated between blood and brain.

Highlights • Developed and validated an overt continuous speech paradigm for use in fMRI. • The speech paradigm successfully identified the neural circuit of speech production. • The speech paradigm is effective in mapping disordered motor speech. • The fMRI paradigm will be useful for studying normal and disordered speech., We developed a task paradigm whereby subjects spoke aloud while minimizing head motion during functional MRI (fMRI) in order to better understand the neural circuitry involved in motor speech disorders due to dysfunction of the central nervous system. To validate our overt continuous speech paradigm, we mapped the speech production network (SPN) in typical speakers (n = 19, 10 females) and speakers with hypokinetic dysarthria as a manifestation of Parkinson disease (HKD; n = 21, 8 females) in fMRI. We then compared it with the SPN derived during overt speech production by 15O-water PET in the same group of typical speakers and another HKD cohort (n = 10, 2 females). The fMRI overt connected speech paradigm did not result in excessive motion artifacts and successfully identified the same brain areas demonstrated in the PET studies in the two cohorts. The SPN derived in fMRI demonstrated significant spatial overlap with the corresponding PET derived maps (typical speakers: r = 0.52; speakers with HKD: r = 0.43) and identified the components of the neural circuit of speech production belonging to the feedforward and feedback subsystems. The fMRI study in speakers with HKD identified significantly decreased activity in critical feedforward (bilateral dorsal premotor and motor cortices) and feedback (auditory and somatosensory areas) subsystems replicating previous PET study findings in this cohort. These results demonstrate that the overt connected speech paradigm is feasible during fMRI and can accurately localize the neural substrates of typical and disordered speech production. Our fMRI paradigm should prove useful for study of motor speech and voice disorders, including stuttering, apraxia of speech, dysarthria, and spasmodic dysphonia.

Neuroscience literature increasingly suggests a conceptual self composed of interacting neu- ral regions, rather than independent local activations, yet such claims have yet to be investigated. We, thus, combined task-dependent meta-analytic connectivity modeling (MACM) with task-independent resting-state (RS) connectivity analysis to delineate the neural network of the self, across both states. Given psychological evidence implicating the self's interdependence on social information, we also delineated the neural network underlying conceptual other-processing. To elucidate the relation between the self-/other-networks and their function, we mined the MACM metadata to generate a cognitive-behavioral profile for an empirically identified region specific to conceptual self, the prege- nual anterior cingulate (pACC), and conceptual other, posterior cingulate/precuneus (PCC/PC). Min- ing of 7,200 published, task-dependent, neuroimaging studies, using healthy human subjects, yielded 193 studies activating the self-related seed and were conjoined with RS connectivity analysis to delin- eate a differentiated self-network composed of the pACC (seed) and anterior insula, relative to other functional connectivity. Additionally, 106 studies activating the other-related seed were conjoined with RS connectivity analysis to delineate a differentiated other-network of PCC/PC (seed) and angular gyrus/temporoparietal junction, relative to self-functional connectivity. The self-network seed related to emotional conflict resolution and motivational processing, whereas the other-network seed related

The human dorsomedial prefrontal cortex (dmPFC) has been implicated in various complex cognitive processes, including social cognition. To unravel its functional organization, we assessed the dmPFC's regional heterogeneity, connectivity patterns, and functional profiles. First, the heterogeneity of a dmPFC seed, engaged during social processing, was investigated by assessing local differences in whole-brain coactivation profiles. Second, functional connectivity of the ensuing dmPFC clusters was compared by task-constrained meta-analytic coactivation mapping and task-unconstrained resting-state correlations. Third, dmPFC clusters were functionally profiled by forward/reverse inference. The dmPFC seed was thus segregated into 4 clusters (rostroventral, rostrodorsal, caudal-right, and caudal-left). Both rostral clusters were connected to the amygdala and hippocampus and associated with memory and social cognitive tasks in functional decoding. The rostroventral cluster exhibited strongest connectivity to the default mode network. Unlike the rostral segregation, the caudal dmPFC was divided by hemispheres. The caudal-right cluster was strongly connected to a frontoparietal network (dorsal attention network), whereas the caudal-left cluster was strongly connected to the anterior midcingulate cortex and bilateral anterior insula (salience network). In conclusion, we demonstrate that a dmPFC seed reflecting social processing can be divided into 4 separate functional modules that contribute to distinct facets of advanced human cognition.

Research on how lexical tone is neuroanatomically represented in the human brain is central to our understanding of cortical regions subserving language. Past studies have exclusively focused on tone perception of the spoken language, and little is known as to the lexical tone processing in reading visual words and its associated brain mechanisms. In this study, we performed two experiments to identify neural substrates in Chinese tone reading. First, we used a tone judgment paradigm to investigate tone processing of visually presented Chinese characters. We found that, relative to baseline, tone perception of printed Chinese characters were mediated by strong brain activation in bilateral frontal regions, left inferior parietal lobule, left posterior middle/medial temporal gyrus, left inferior temporal region, bilateral visual systems, and cerebellum. Surprisingly, no activation was found in superior temporal regions, brain sites well known for speech tone processing. In activation likelihood estimation (ALE) meta-analysis to combine results of relevant published studies, we attempted to elucidate whether the left temporal cortex activities identified in Experiment one is consistent with those found in previous studies of auditory lexical tone perception. ALE results showed that only the left superior temporal gyrus and putamen were critical in auditory lexical tone processing. These findings suggest that activation in the superior temporal cortex associated with lexical tone perception is modality-dependent.

The superior parietal lobule (SPL) plays a pivotal role in many cognitive, perceptive, and motor-related processes. This implies that a mosaic of distinct functional and structural subregions may exist in this area. Recent studies have demonstrated that the ongoing spontaneous fluctuations in the brain at rest are highly structured and, like coactivation patterns, reflect the integration of cortical locations into long-distance networks. This suggests that the internal differentiation of a complex brain region may be revealed by interaction patterns that are reflected in different neuroimaging modalities. On the basis of this perspective, we aimed to identify a convergent functional organization of the SPL using multimodal neuroimaging approaches. The SPL was first parcellated based on its structural connections as well as on its resting-state connectivity and coactivation patterns. Then, post hoc functional characterizations and connectivity analyses were performed for each subregion. The three types of connectivity-based parcellations consistently identified five subregions in the SPL of each hemisphere. The two anterior subregions were found to be primarily involved in action processes and in visually guided visuomotor functions, whereas the three posterior subregions were primarily associated with visual perception, spatial cognition, reasoning, working memory, and attention. This parcellation scheme for the SPL was further supported by revealing distinct connectivity patterns for each subregion in all the used modalities. These results thus indicate a convergent functional architecture of the SPL that can be revealed based on different types of connectivity and is reflected by different functions and interactions.

Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses., Highlights • A thalamic disease model informed connectivity analyses in temporal lobe epilepsy. • No patient vs. control group differences in thalamic connection strength were observed. • Yet thalamic functional connection strength predicted seizure onset laterality. • Lack of group difference should not deter constrained assessment in individuals. • Meta-analytic disease models successfully guide individual patient biomarker development.

Individuals with a family history of substance use disorder (FH+) show impaired frontal white matter as indicated by diffusion tensor imaging (DTI). This impairment may be due to impaired or delayed development of myelin in frontal regions, potentially contributing to this population's increased risk for developing substance use disorders. In this study, we examined high angular resolution DTI and proton magnetic resonance spectroscopy data from the anterior corona radiata were collected in 80 FH+ and 34 FH- youths (12.9 ± 1.0 years old). White matter integrity indices included fractional anisotropy (FA), N-acetylaspartate (NAA), and total choline (tCho). Lower FA suggests decreased myelination. Decreased NAA coupled with higher tCho suggests impaired build-up and maintenance of cerebral myelin and consequently greater breakdown of cellular membranes. We found FH+ youths had lower FA (P < 0.0001) and NAA (P = 0.017) and higher tCho (P = 0.04). FH density (number of parents and grandparents with substance use disorders) was negatively correlated with FA (P < 0.0001) and NAA (P = 0.011) and positively correlated with tCho (P = 0.001). FA was independently predicted by both FH density (P = 0.006) and NAA (P = 0.002), and NAA and tCho were both independent predictors of FH density (P < 0.001). Our finding of lower frontal FA in FH+ youths corresponding to lower NAA and increased tCho is consistent with delayed or impaired development of frontal white matter in FH+ youths. Longitudinal studies are needed to determine how these differences relate to substance use outcomes.

Spatial normalization—applying standardized coordinates as anatomical addresses within a reference space—was introduced to human neuroimaging research nearly 30 years ago. Over these three decades, an impressive series of methodological advances have adopted, extended, and popularized this standard. Collectively, this work has generated a methodologically coherent literature of unprecedented rigor, size, and scope. Large-scale online databases have compiled these observations and their associated meta-data, stimulating the development of meta-analytic methods to exploit this expanding corpus. Coordinate-based meta-analytic methods have emerged and evolved in rigor and utility. Early methods computed cross-study consensus, in a manner roughly comparable to traditional (nonimaging) meta-analysis. Recent advances now compute coactivation-based connectivity, connectivity-based functional parcellation, and complex network models powered from data sets representing tens of thousands of subjects. Meta-analyses of human neuroimaging data in large-scale databases now stand at the forefront of computational neurobiology.

The right temporoparietal junction (rTPJ) is frequently associated with different capacities that to shift attention to unexpected stimuli (reorienting of attention) and to understand others' (false) mental state [theory of mind (ToM), typically represented by false belief tasks]. Competing hypotheses either suggest the rTPJ representing a unitary region involved in separate cognitive functions or consisting of subregions subserving distinct processes. We conducted activation likelihood estimation (ALE) meta-analyses to test these hypotheses. A conjunction analysis across ALE meta-analyses delineating regions consistently recruited by reorienting of attention and false belief studies revealed the anterior rTPJ, suggesting an overarching role of this specific region. Moreover, the anatomical difference analysis unravelled the posterior rTPJ as higher converging in false belief compared with reorienting of attention tasks. This supports the concept of an exclusive role of the posterior rTPJ in the social domain. These results were complemented by meta-analytic connectivity mapping (MACM) and resting-state functional connectivity (RSFC) analysis to investigate whole-brain connectivity patterns in task-constrained and task-free brain states. This allowed for detailing the functional separation of the anterior and posterior rTPJ. The combination of MACM and RSFC mapping showed that the posterior rTPJ has connectivity patterns with typical ToM regions, whereas the anterior part of rTPJ co-activates with the attentional network. Taken together, our data suggest that rTPJ contains two functionally fractionated subregions: while posterior rTPJ seems exclusively involved in the social domain, anterior rTPJ is involved in both, attention and ToM, conceivably indicating an attentional shifting role of this region.

Individuals with a family history of substance use disorders (FH+) are at a greater risk of developing substance use disorders than their peers with no such family histories (FH−) and this vulnerability is proportional to the number of affected relatives (FH density). The risk for developing substance use disorders peaks during adolescence to early adulthood in the general population, and that is thought to be related to delayed maturation of frontocortical and frontostriatal functional circuits. We hypothesized that FH+ youth and young adults have impaired myelination of frontocortical and frontostriatal white matter tracts. We examined fractional anisotropy (FA) data in 80 FH+ and 34 FH− youths (12.9±1.0 years) and in 25 FH+ and 30 FH− young adults (24.3±3.4 years). FH+ youths had lower FA values in both frontocortical and frontostriatal tracts as well as parietocortical tracts including the anterior, superior and posterior corona radiata and the superior frontal-occipital fasciculus. Moreover, FA values in these tracts were negatively correlated with FH density. FH+ adults had lower FA values in two frontocortical tracts: the genu of the corpus callosum and anterior corona radiata and also significant negative correlations between FA and FH density in these same tracts. In both groups, lower FA values corresponded to higher radial diffusivity suggesting reduced axonal myelination. We interpreted our findings as evidence for impaired myelination of frontal white matter that was proportional to FH density. Our data suggest that deficits may partially resolve with age, paralleling an age-related decline in risk for developing substance use disorders.

Objective The purpose of this study was to compare the results of the three food-cue paradigms most commonly used for functional neuroimaging studies to determine: i) commonalities and differences in the neural response patterns by paradigm and ii) the relative robustness and reliability of responses to each paradigm. Methods Functional magnetic resonance imaging studies using standardized stereotactic coordinates to report brain responses to food cues were identified using online databases. Studies were grouped by food-cue modality as: i) tastes (8 studies); ii) odors (8 studies); and, iii) images (11 studies). Activation likelihood estimation was used to identify statistically reliable regional responses within each stimulation paradigm. Results Brain response distributions were distinctly different for the three stimulation modalities, corresponding to known differences in location of the respective primary and associative cortices. Visual stimulation induced the most robust and extensive responses. The left anterior insula was the only brain region reliably responding to all three stimulus categories. Conclusions These findings suggest visual food-cue paradigm as promising candidate for imaging studies addressing the neural substrate of therapeutic interventions.

19 F and 1 H NMR experiments have been used to assign the resonances of end groups and branching structures in poly(VDF- co -HFP) copolymer. Multidimensional NMR experiments, spin–lattice relaxation ( T 1 ) analysis, and diffusion ordered spectroscopy (DOSY) NMR were used as complementary NMR methods to identify and also to obtain the structures of the end groups in these copolymers. Resonances of chain branching structures (long chain branch (LCB) and short chain branch (SCB)) were also identified with T 1 and 2D DOSY NMR experiments; other 2D NMR experiments, such as selective COSY (correlation spectroscopy) and gradient heteronuclear single quantum coherence (gHSQC) were used to provide atomic connectivity information to determine resonance assignments. The amount of each end group in the poly(VDF- co -HFP) copolymers was quantified with the aid of an internal reference, 1,4-dichloro-2-(trifluoromethyl)benzene. The –CH 2 CF 2 H end group was found to be the most prevalent in the copolymers studied.

Recent evidence suggests considerable overlap between the default mode network (DMN) and regions involved in social, affective and introspective processes. We considered these overlapping regions as the social-affective part of the default mode network. In this study we established a robust mapping of the underlying brain network formed by these regions and those strongly connected to them (the extended social-affective default network: eSAD). We first seeded meta-analytic connectivity modeling and resting state analyses in the meta-analytically defined DMN regions that showed statistical overlap with regions associated with social and affective processing. Consensus connectivity of each seed was subsequently delineated by a conjunction across both connectivity analyses. We then functionally characterized the ensuing regions and performed several cluster analyses. Among the identified regions the amygdala/hippocampus formed a cluster associated with emotional processes and memory functions. The ventral striatum, anterior cingulum, subgenual cingulum and ventromedial prefrontal cortex formed a heterogeneous subgroup associated with motivation, reward and cognitive modulation of affect. Posterior cingulum/precuneus and dorsomedial prefrontal cortex were associated with mentalizing, self-reference and autobiographic information. The cluster formed by the temporo-parietal junction and anterior middle temporal sulcus/gyrus was associated with language and social cognition. Taken together, the current work highlights a robustly interconnected network that may be central to interospective, socio-affective, that is, self- and other-related mental processes.

It is well established that risk for developing psychosis is largely mediated by the influence of genes, but identifying precisely which genes underlie that risk has been problematic. Focusing on endophenotypes, rather than illness risk, is one solution to this problem. Impaired cognition is a well-established endophenotype of psychosis. Here we aimed to characterize the genetic architecture of cognition using phenotypically detailed models as opposed to relying on general IQ or individual neuropsychological measures. In so doing we hoped to identify genes that mediate cognitive ability, which might also contribute to psychosis risk. Hierarchical factor models of genetically clustered cognitive traits were subjected to linkage analysis followed by QTL region-specific association analyses in a sample of 1,269 Mexican American individuals from extended pedigrees. We identified four genome wide significant QTLs, two for working and two for spatial memory, and a number of plausible and interesting candidate genes. The creation of detailed models of cognition seemingly enhanced the power to detect genetic effects on cognition and provided a number of possible candidate genes for psychosis.

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.

Background: Currently, it is difficult to predict precise regions of cortical activation in response to transcranial magnetic stimulation (TMS). Most analytical approaches focus on applied magnetic field strength in the target region as the primary factor, placing activation on the gyral crowns. However, imaging studies support M1 targets being typically located in the sulcal banks. Objective/hypothesis: To more thoroughly investigate this inconsistency, we sought to determine whether neocortical surface orientation was a critical determinant of regional activation. Methods: MR images were used to construct cortical and scalp surfaces for 18 subjects. The angle (θ) between the cortical surface normal and its nearest scalp normal for ∼50,000 cortical points per subject was used to quantify cortical location (i.e., gyral vs. sulcal). TMS-induced activations of primary motor cortex (M1) were compared to brain activations recorded during a finger-tapping task using concurrent positron emission tomographic (PET) imaging. Results: Brain activations were primarily sulcal for both the TMS and task activations (P

r r Abstract: Theories positing that the cerebellum contributes to cognitive as well as motor control are driven by two sources of information: (1) studies highlighting connections between the cerebellum and both prefrontal and motor territories, (2) functional neuroimaging studies demonstrating cerebellar activa- tions evoked during the performance of both cognitive and motor tasks. However, almost no studies to date have combined these two sources of information and investigated cortico-cerebellar connectivity during task performance. Through the use of a novel neuroimaging tool (Meta-Analytic Connectivity Modelling) we demonstrate for the first time that cortico-cerebellar connectivity patterns seen in anatomi- cal studies and resting fMRI are also present during task performance. Consistent with human and non- human primate anatomical studies cerebellar lobules Crus I and II were significantly coactivated with prefrontal and parietal cortices during task performance, whilst lobules HV, HVI, HVIIb, and HVIII were significantly coactivated with the pre- and postcentral gyrus. An analysis of the behavioral domains showed that these circuits were driven by distinct tasks. Prefrontal-parietal-cerebellar circuits were more active during cognitive and emotion tasks whilst motor-cerebellar circuits were more active during action execution tasks. These results highlight the separation of prefrontal and motor cortico-cerebellar loops during task performance, and further demonstrate that activity within these circuits relates to dis- tinct functions. Hum Brain Mapp 00:000-000, 2013. V C 2013 Wiley Periodicals, Inc.

The rostral cingulate cortex has been associated with a multitude of cognitive control functions. Recent neuroimaging data suggest that the anterior midcingulate cortex (aMCC) has a key role for cognitive aspects of movement generation, i.e., intentional motor control. We here tested the functional connectivity of this area using two complementary approaches: (1) resting-state connectivity of the aMCC based on fMRI scans obtained in 100 subjects, and (2) functional connectivity in the context of explicit task conditions using meta-analytic connectivity modeling (MACM) over 656 imaging experiment. Both approaches revealed a convergent functional network architecture of the aMCC with prefrontal, premotor and parietal cortices as well as anterior insula, area 44/45, cerebellum and dorsal striatum. To specifically test the role of the aMCC’s task-based functional connectivity in cognitive motor control, separate MACM analyses were conducted over “cognitive” and “action” related experimental paradigms. Both analyses confirmed the same task-based connectivity pattern of the aMCC. While the “cognition” domain showed higher convergence of activity in supramodal association areas in prefrontal cortex and anterior insula, “action” related experiments yielded higher convergence in somatosensory and premotor areas. Secondly, to probe the functional specificity of the aMCC’s convergent functional connectivity, it was compared with a neural network of intentional movement initiation. This exemplary comparison confirmed the involvement of the state independent FC network of the aMCC in the intentional generation of movements. In summary, the different experiments of the present study suggest that the aMCC constitute a key region in the network realizing intentional motor control.

The ventral stream of the human extrastriate visual cortex shows a considerable functional heterogeneity from early visual processing (posterior) to higher, domain-specific processing (anterior). The fusiform gyrus hosts several of those "high-level" functional areas. We recently found a subdivision of the posterior fusiform gyrus on the microstructural level, that is, two distinct cytoarchitectonic areas, FG1 and FG2 (Caspers et al., Brain Structure & Function, 2013). To gain a first insight in the function of these two areas, here we studied their behavioral involvement and coactivation patterns by means of meta-analytic connectivity modeling based on the BrainMap database (www.brainmap.org), using probabilistic maps of these areas as seed regions. The coactivation patterns of the areas support the concept of a common involvement in a core network subserving different cognitive tasks, that is, object recognition, visual language perception, or visual attention. In addition, the analysis supports the previous cytoarchitectonic parcellation, indicating that FG1 appears as a transitional area between early and higher visual cortex and FG2 as a higher-order one. The latter area is furthermore lateralized, as it shows strong relations to the visual language processing system in the left hemisphere, while its right side is stronger associated with face selective regions. These findings indicate that functional lateralization of area FG2 relies on a different pattern of connectivity rather than side-specific cytoarchitectonic features.

2D-NMR techniques were used to identify the detailed structures of chain end and branching units in poly(vinylidene fluoride-co-tetrafluoroethylene), poly(VDF-co-TFE). Atomic connectivity information was provided by selective 19F–19F COSY (correlation spectroscopy), 19F{1H} gHETCOR (gradient heteronuclear correlated), and 1H{13C} HSQC (heteronuclear single quantum correlation) experiments. Diffusion ordered spectroscopy (DOSY) and spin–lattice relaxation (T1) data permitted distinction of backbone, short chain branch, and chain end resonances from one another. Quantitative data on these structures are reported; quantitation also supported assignments through the consistent relative intensities of resonances from the same structures. Possible reactions during the polymerization which could lead to these structures are discussed.

Background: Transcranial magnetic stimulation (TMS) has the potential to treat brain disorders by tonically modulating firing patterns in disease-specific neural circuits. The selection of treatment parameters for clinical repetitive transcranial magnetic stimulation (rTMS) trials has not been rule based, likely contributing to the variability of observed outcomes. Objective: To utilize our newly developed baboon (Papio hamadryas anubis) model of rTMS during position-emission tomography (PET) to quantify the brain's rate–response functions in the motor system during rTMS. Methods: We delivered image-guided, suprathreshold rTMS at 3 Hz, 5 Hz, 10 Hz, 15 Hz and rest (in separate randomized sessions) to the primary motor cortex (M1) of the lightly anesthetized baboon during PET imaging; we also administered a (reversible) paralytic to eliminate any somatosensory feedback due to rTMS-induced muscle contractions. Each rTMS/PET session was analyzed using normalized cerebral blood flow (CBF) measurements; statistical parametric images and the resulting areas of significance underwent post-hoc analysis to determine any rate-specific rTMS effects throughout the motor network. Results: The motor system's rate–response curves were unimodal and system wide—with all nodes in the network showing highly similar rate response functions—and an optimal network stimulation frequency of 5 Hz. Conclusion(s): These findings suggest that non-invasive brain stimulation may be more efficiently delivered at (system-specific) optimal frequencies throughout the targeted network and that functional imaging in non-human primates is a promising strategy for identifying the optimal treatment parameters for TMS clinical trials in specific brain regions and/or networks.

To demonstrate that U-2 pilot occupational exposure to hypobaria leads to increased incidence of white matter hyperintensities (WMH) with a more uniform distribution throughout the brain irrespective of clinical neurologic decompression sickness history.We evaluated imaging findings in 102 U-2 pilots and 91 controls matched for age, health, and education levels. Three-dimensional, T2-weighted, high-resolution (1-mm isotropic) imaging data were collected using fluid-attenuated inversion recovery sequence on a 3-tesla MRI scanner. Whole-brain and regional WMH volume and number were compared between groups using a 2-tailed Wilcoxon rank sum test.U-2 pilots demonstrated an increase in volume (394%; p = 0.004) and number (295%; p0.001) of WMH. Analysis of regional distribution demonstrated WMH more uniformly distributed throughout the brain in U-2 pilots compared with mainly frontal distribution in controls.Pilots with occupational exposure to hypobaria showed a significant increase in WMH lesion volume and number. Unlike the healthy controls with predominantly WMH in the frontal white matter, WMH in pilots were more uniformly distributed throughout the brain. This is consistent with our hypothesized pattern of damage produced by interaction between microemboli and cerebral tissue, leading to thrombosis, coagulation, inflammation, and/or activation of innate immune response, although further studies will be necessary to clarify the pathologic mechanisms responsible.

Recent studies have challenged the prevailing view that reduced mitochondrial function and increased oxidative stress are correlated with reduced longevity. Mice carrying a homozygous knockout (KO) of the Surf1 gene showed a significant decrease in mitochondrial electron transport chain Complex IV activity, yet displayed increased lifespan and reduced brain damage after excitotoxic insults. In the present study, we examined brain metabolism, brain hemodynamics, and memory of Surf1 KO mice using in vitro measures of mitochondrial function, in vivo neuroimaging, and behavioral testing. We show that decreased respiration and increased generation of hydrogen peroxide in isolated Surf1 KO brain mitochondria are associated with increased brain glucose metabolism, cerebral blood flow, and lactate levels, and with enhanced memory in Surf1 KO mice. These metabolic and functional changes in Surf1 KO brains were accompanied by higher levels of hypoxia-inducible factor 1 alpha, and by increases in the activated form of cyclic AMP response element-binding factor, which is integral to memory formation. These findings suggest that Surf1 deficiency-induced metabolic alterations may have positive effects on brain function. Exploring the relationship between mitochondrial activity, oxidative stress, and brain function will enhance our understanding of cognitive aging and of age-related neurologic disorders.

Advanced modern multidimensional solution NMR experiments have been used to deduce the sequence distribution in poly(VDF-co-HFP) copolymers. Assignment of 19F resonances from different monomer- and regio-sequences in poly(VDF-co-HFP) copolymer were identified. In addition to corroborating some assignments reported in earlier literature, this work provides assignments of some new resonances from the spectra of poly(VDF-co-HFP) copolymer, which resulted from better dispersion of the resonances. These assignments are used for the monomer sequence analyses of two polymers using first-order Markovian statistics, and the relative reactivities of the monomers during polymerization are discussed. The results from this study provide insight into the polymerization chemistry for this fluoropolymer.

Susceptibility genes for psychiatric and neurological disorders - including APOE, BDNF, CLU,CNTNAP2, COMT, DISC1, DTNBP1, ErbB4, HFE, NRG1, NTKR3, and ZNF804A - have been reported to affect white matter (WM) microstructure in the healthy human brain, as assessed through diffusion tensor imaging (DTI). However, effects of single nucleotide polymorphisms (SNPs) in these genes explain only a small fraction of the overall variance and are challenging to detect reliably in single cohort studies. To date, few studies have evaluated the reproducibility of these results. As part of the ENIGMA-DTI consortium, we pooled regional fractional anisotropy (FA) measures for 6,165 subjects (CEU ancestry N=4,458) from 11 cohorts worldwide to evaluate effects of 15 candidate SNPs by examining their associations with WM microstructure. Additive association tests were conducted for each SNP. We used several meta-analytic and mega-analytic designs, and we evaluated regions of interest at multiple granularity levels. The ENIGMA-DTI protocol was able to detect single-cohort findings as originally reported. Even so, in this very large sample, no significant associations remained after multiple-testing correction for the 15 SNPs investigated. Suggestive associations (1.3×10-4 < p < 0.05, uncorrected) were found for BDNF, COMT, and ZNF804A in specific tracts. Meta-and mega-analyses revealed similar findings. Regardless of the approach, the previously reported candidate SNPs did not show significant associations with WM microstructure in this largest genetic study of DTI to date; the negative findings are likely not due to insufficient power. Genome-wide studies, involving large-scale meta-analyses, may help to discover SNPs robustly influencing WM microstructure.

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness., published version, peerReviewed

Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d = 20 to 300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how “parent” functional brain systems decompose into constituent “child” sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication.

Parkinson’s disease (PD) is a common progressive neurodegenerative disorder. Studies using resting-state functional magnetic resonance imaging (fMRI) to investigate underlying pathophysiology of motor and non-motor symptoms in PD yielded largely inconsistent results. This quantitative neuroimaging meta-analysis aims to identify consistent abnormal intrinsic functional patterns in PD across studies. We used PubMed to retrieve suitable resting-state studies and stereotactic data were extracted from 28 individual between-group comparisons. Convergence across their findings was tested using the activation likelihood estimation (ALE) approach. We found convergent evidence for intrinsic functional disturbances in bilateral inferior parietal lobule (IPL) and the supramarginal gyrus in PD patients compared to healthy subjects. In follow-up task-based and task-independent functional connectivity (FC) analyses using two independent healthy subject data sets, we found that the regions showing convergent aberrations in PD formed an interconnected network mainly with the default mode network (DMN). Behavioral characterization of these regions using the BrainMap database suggested associated dysfunction of perception and executive processes. Taken together, our findings highlight the role of parietal cortex in the pathophysiology of PD.

Contains fulltext : 169032.pdf (Publisher’s version ) (Closed access) The right dorsal premotor cortex (PMd) of humans has been reported to be involved in a broad range of motor and cognitive functions. We explored the basis of this behavioral heterogeneity by performing a connectivity-based parcellation using meta-analytic approach applied to PMd coactivations. We compared our connectivity-based parcellation results with parcellations obtained through resting-state functional connectivity and probabilistic diffusion tractography. Functional connectivity profiles and behavioral decoding of the resulting PMd subregions allowed characterizing their respective behavior profile. These procedures divided the right PMd into 5 distinct subregions that formed a cognitive-motor gradient along a rostro-caudal axis. In particular, we found 1) a rostral subregion functionally connected with prefrontal cortex, which likely supports high-level cognitive processes, such as working memory, 2) a central subregion showing a mixed behavioral profile and functional connectivity to parietal regions of the dorsal attention network, and 3) a caudal subregion closely integrated with the motor system. Additionally, we found 4) a dorsal subregion, preferentially related to hand movements and connected to both cognitive and motor regions, and 5) a ventral subregion, whose functional profile fits the concept of an eye movement-related field. In conclusion, right PMd may be considered as a functional mosaic formed by 5 subregions. 16 p.

Item does not contain fulltext Drowning is a leading cause of accidental injury and death in young children. Anoxic brain injury (ABI) is a common consequence of drowning and can cause severe neurological morbidity in survivors. Assessment of functional status and prognostication in drowning victims can be extremely challenging, both acutely and chronically. Structural neuroimaging modalities (CT and MRI) have been of limited clinical value. Here, we tested the utility of resting-state functional MRI (rs-fMRI) for assessing brain functional integrity in this population. Eleven children with chronic, spastic quadriplegia due to drowning-induced ABI were investigated. All were comatose immediately after the injury and gradually regained consciousness, but with varying ability to communicate their cognitive state. Eleven neurotypical children matched for age and gender formed the control group. Resting-state fMRI and co-registered T1-weighted anatomical MRI were acquired at night during drug-aided sleep. Network integrity was quantified by independent components analysis (ICA), at both group- and per-subject levels. Functional-status assessments based on in-home observations were provided by families and caregivers. Motor ICNs were grossly compromised in ABI patients both group-wise and individually, concordant with their prominent motor deficits. Striking preservations of perceptual and cognitive ICNs were observed, and the degree of network preservation correlated (rho = 0.74) with the per-subject functional status assessments. Collectively, our findings indicate that rs-fMRI has promise for assessing brain functional integrity in ABI and, potentially, in other disorders. Furthermore, our observations suggest that the severe motor deficits observed in this population can mask relatively intact perceptual and cognitive capabilities. Hum Brain Mapp 38:4813-4831, 2017. (c) 2017 Wiley Periodicals, Inc.

Purpose Medial temporal lobe epilepsy (MTLE) is associated with MTLE network pathology within and beyond the hippocampus. The purpose of this meta-analysis was to identify consistent MTLE structural change to guide subsequent targeted analyses of these areas. Methods We performed an anatomic likelihood estimation (ALE) meta-analysis of 22 whole-brain voxel-based morphometry experiments from 11 published studies. We grouped these experiments in three ways. We then constructed a meta-analytic connectivity model (MACM) for regions of consistent MTLE structural change as reported by the ALE analysis. Key findings ALE reported spatially consistent structural change across VBM studies only in the epileptogenic hippocampus and the bilateral thalamus; within the thalamus, the medial dorsal nucleus of the thalamus (MDN thalamus) represented the greatest convergence (P, Highlights ► Meta-analyzed 11 studies of pathology in medial temporal lobe epilepsy (MTLE). ► The bilateral thalamus is the most consistent extra-hippocampal pathology. ► Within the thalamus, the medial dorsal nucleus (MDN) was the most significant. ► We suggest the MDN thalamus as a target for future studies in MTLE. ► We recommend these modified methods for future VBM meta-analyses.

This Article explores the use of the trade preference program to pressure a State to comply with its international law obligations. Examining recent international investment disputes involving Argentina, Ecuador, and the Russian Federation, this Article discusses the increasing role of U.S. and EU trade preference programs as retaliatory mechanisms for noncompliance. This Article concludes that the use of the trade preference program as a leveraging tool can meaningfully impact a host State involved in an international investment dispute, particularly where the host State either has not consented to arbitration or has allegedly failed to comply with an adverse award.

Contains fulltext : 165723pub.pdf (Publisher’s version ) (Closed access) Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (rhogenetic = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.

Head movements are typically viewed as a nuisance to functional magnetic resonance imaging (fMRI) analysis, and are particularly problematic for resting state fMRI. However, there is growing evidence that head motion is a behavioral trait with neural and genetic underpinnings. Using data from a large randomly ascertained extended pedigree sample of Mexican Americans (n = 689), we modeled the genetic structure of head motion during resting state fMRI and its relation to 48 other demographic and behavioral phenotypes. A replication analysis was performed using data from the Human Connectome Project, which uses an extended twin design (n = 864). In both samples, head motion was significantly heritable (h2 = 0.313 and 0.427, respectively), and phenotypically correlated with numerous traits. The most strongly replicated relationship was between head motion and body mass index, which showed evidence of shared genetic influences in both data sets. These results highlight the need to view head motion in fMRI as a complex neurobehavioral trait correlated with a number of other demographic and behavioral phenotypes. Given this, when examining individual differences in functional connectivity, the confounding of head motion with other traits of interest needs to be taken into consideration alongside the critical important of addressing head motion artifacts.

BACKGROUND AND PURPOSE: Although drowning is a leading cause of mortality and morbidity in young children, the neuropathologic consequences have not been fully determined. The purpose of this article was to quantitatively characterize white matter microstructural abnormalities in pediatric anoxic brain injury from nonfatal drowning and investigate the correlation with motor function. MATERIALS AND METHODS: Whole-brain T1-weighted and diffusion-weighted MR imaging datasets were acquired in 11 children with chronic anoxic brain injury and 11 age- and sex-matched neurotypical controls (4–12 years of age). A systematic evaluation form and scoring system were created to assess motor function. Tract-Based Spatial Statistics was used to quantify between-group alterations in the diffusion tensor imaging indices of fractional anisotropy and mean diffusivity and to correlate with per-subject functional motor scores. RESULTS: Group-wise Tract-Based Spatial Statistics analyses demonstrated reduced fractional anisotropy in the bilateral posterior limbs of the internal capsule and the splenium of the corpus callosum (P CONCLUSIONS: These data particularly implicate the deep white matter, predominantly the posterior limbs of the internal capsule, as targets of damage in pediatric anoxic brain injury with drowning. The substantial involvement of motor-system tracts with relative sparing elsewhere is notable. These results localize white matter pathology and inform future diagnostic and prognostic markers.