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All eutherian mammals show chromosomal sex determination with contrasting sex chromosome dosages (SCDs) between males (XY) and females (XX). Studies in transgenic mice and humans with sex chromosome trisomy (SCT) have revealed direct SCD effects on regional mammalian brain anatomy, but we lack a formal test for cross-species conservation of these effects. Here, we develop a harmonized framework for comparative structural neuroimaging and apply this to systematically profile SCD effects on regional brain anatomy in both humans and mice by contrasting groups with SCT (XXY and XYY) versus XY controls. Total brain size was substantially altered by SCT in humans (significantly decreased by XXY and increased by XYY), but not in mice. Robust and spatially convergent effects of XXY and XYY on regional brain volume were observed in humans, but not mice, when controlling for global volume differences. However, mice do show subtle effects of XXY and XYY on regional volume, although there is not a general spatial convergence in these effects within mice or between species. Notwithstanding this general lack of conservation in SCT effects, we detect several brain regions that show overlapping effects of XXY and XYY both within and between species (cerebellar, parietal, and orbitofrontal cortex), thereby nominating high priority targets for future translational dissection of SCD effects on the mammalian brain. Our study introduces a generalizable framework for comparative neuroimaging in humans and mice and applies this to achieve a cross-species comparison of SCD effects on the mammalian brain through the lens of SCT.SIGNIFICANCE STATEMENTSex chromosome dosage (SCD) affects neuroanatomy and risk for psychopathology in humans. Performing mechanistic studies in the human brain is challenging but possible in mouse models. Here, we develop a framework for cross-species neuroimaging analysis and use this to show that an added X- or Y-chromosome significantly alters human brain anatomy but has muted effects in the mouse brain. However, we do find evidence for conserved cross-species impact of an added chromosome in the fronto-parietal cortices and cerebellum, which point to regions for future mechanistic dissection of sex chromosome dosage effects on brain development.

Aneuploidy syndromes impact multiple organ systems but understanding of tissue-specific aneuploidy effects remains limited—especially for the comparison between peripheral tissues and relatively inaccessible tissues like brain. Here, we address this gap in knowledge by studying the transcriptomic effects of chromosome X, Y, and 21 aneuploidies in lymphoblastoid cell lines, fibroblasts and iPSC-derived neuronal cells (LCLs, FCL, and iNs, respectively). We root our analyses in sex chromosome aneuploidies, which offer a uniquely wide karyotype range for dosage effect analysis. We first harness a large LCL RNA-seq dataset from 197 individuals with one of 6 sex chromosome dosages (SCDs: XX, XXX, XY, XXY, XYY, and XXYY) to i) validate theoretical models of SCD sensitivity and ii) define an expanded set of 41 genes that show obligate dosage sensitivity to SCD and are all in cis (i.e., reside on the X or Y chromosome). We then use multiple complementary analyses to show that cis effects of SCD in LCLs are preserved in both FCLs (n = 32) and iNs (n = 24), whereas trans effects (i.e., those on autosomal gene expression) are mostly not preserved. Analysis of additional datasets confirms that the greater cross-cell type reproducibility of cis vs. trans effects is also seen in trisomy 21 cell lines. These findings i) expand our understanding of X, Y, and 21 chromosome dosage effects on human gene expression and ii) suggest that LCLs may provide a good model system for understanding cis effects of aneuploidy in harder-to-access cell types.

Diverse gene dosage disorders (GDDs) increase risk for psychiatric impairment, but characterization of GDD effects on the human brain has so far been piecemeal and lacked simultaneous analysis of multiple brain features across different GDDs. Here, through multimodal neuroimaging of 3 aneuploidy syndromes (XXY, XYY, trisomy 21), we reveal considerable diversity in cortical changes across GDDs and imaging-derived phenotypes (IDPs). This variegation of IDP change underlines the limitations of studying GDD effects unimodally. Integration across all IDP maps reveals highly distinct architectures of cortical change in each GDD, along with partial coalescence onto a common spatial axis of cortical vulnerability. This common axis shows strong alignment with shared cortical changes in behaviorally defined psychiatric disorders, and is enriched for specific molecular and cellular signatures - offering a high-priority target for future translational research.

SummaryAll eutherian mammals show chromosomal sex determination with contrasting sex chromosome dosages (SCDs) between males (XY) and females (XX). Studies in transgenic mice and humans with sex chromosome trisomy (SCT) have revealed direct SCD effects on regional mammalian brain anatomy, but we lack a formal test for cross-species conservation of these effects. Here, we develop a harmonized framework for comparative structural neuroimaging and apply this to systematically profile SCD effects on regional brain anatomy in both humans and mice by contrasting groups with SCT (XXY and XYY) vs. XY controls. We show that total brain size is substantially altered by SCT in humans (significantly decreased by XXY and increased by XYY), but not in mice. Controlling for global effects reveals robust and spatially convergent effects of XXY and XYY on regional brain volume in humans, but not mice. However, mice do show subtle effects of XXY and XYY on regional volume, although there is not a general spatial convergence in these effects within mice or between species. Notwithstanding this general lack of conservation in SCT effects, we detect several brain regions that show overlapping effects of XXY and XYY both within and between species (cerebellum, parietal, and orbitofrontal cortex) - thereby nominating high priority targets for future translational dissection of SCD effects on the mammalian brain. Our study introduces a generalizable framework for comparative neuroimaging in humans and mice and applies this to achieve a cross-species comparison of SCD effects on the mammalian brain through the lens of SCT.HighlightsParallel structural neuroimaging in humans and mice with sex chromosome trisomiesDivergent X- and Y-chromosome effects on human brain size, but convergent effects on regional anatomyMuted impact of additional X or Y on mouse brain, but subtle regional effects evidentEvidence for conserved cross-species impact of X and Y on fronto-parietal cortices and cerebellum

Sex chromosome aneuploidies, a group of neurogenetic conditions characterized by aberrant sex chromosome dosage (SCD), are associated with increased risks for psychopathology as well as alterations in gray matter structure. However, we still lack a comprehensive understanding of potential SCD-associated changes in white matter structure, or knowledge of how these changes might relate to known alterations in gray matter anatomy. Thus, here, we use voxel-based morphometry on structural neuroimaging data to provide the first comprehensive maps of regional white matter volume (WMV) changes across individuals with varying SCD (n = 306). We show that mounting X- and Y-chromosome dosage are both associated with widespread WMV decreases, including in cortical, subcortical, and cerebellar tracts, as well as WMV increases in the genu of the corpus callosum and posterior thalamic radiation. We also correlate X- and Y-chromosome-linked WMV changes in certain regions to measures of internalizing and externalizing psychopathology. Finally, we demonstrate that SCD-driven WMV changes show a coordinated coupling with SCD-driven gray matter volume changes. These findings represent the most complete maps of X- and Y-chromosome effects on human white matter to date, and show how such changes connect to psychopathological symptoms and gray matter anatomy.

Klinefelter syndrome (47, XXY; Henceforth: XXY syndrome) is a high impact but poorly understood genetic risk factor for neuropsychiatric impairment. Here, we provide the first neuroimaging study to map resting-state functional connectivity (rsFC) changes in XXY syndrome and ask how these might relate to brain anatomy and psychopathology. We collected resting state functional magnetic resonance imaging data from 75 individuals with XXY and 84 healthy XY males. We implemented a brain-wide screen to identify regions with altered global rsFC in XXY vs. XY males, and then used seed-based analysis to decompose these alterations. We further compared rsFC changes with regional changes in brain volume from voxel-based morphometry and tested for correlations between rsFC and symptom variation within XXY syndrome. We found that XXY syndrome was characterized by increased global rsFC in the left dorsolateral prefrontal cortex (DLPFC), associated with overconnectivity with diverse rsFC networks. Regional rsFC changes were partly coupled to regional volumetric changes in XXY syndrome. Within the precuneus, variation in DLPFC rsFC within XXY syndrome was correlated with the severity of psychopathology in XXY individuals. Our findings provide the first view of altered functional brain connectivity in XXY syndrome and delineate links between these alterations and those relating to both brain anatomy and psychopathology. Taken together, these insights advance biological understanding of XXY syndrome as a disorder in its own right, and as a model of genetic risk for psychopathology more broadly.

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes., R.A.I.B. was supported by a British Academy Postdoctoral fellowship and by the Autism Research Trust. J. Seidlitz was supported by NIMH T32MH019112-29 and K08MH120564. S.R.W. was funded by UKRI Medical Research Council MC_UU_00002/2 and was supported by the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). E.T.B. was supported by an NIHR Senior Investigator award and the Wellcome Trust collaborative award for the Neuroscience in Psychiatry Network. A.F.A.-B. was supported by NIMH K08MH120564. Data were curated and analysed using a computational facility funded by an MRC research infrastructure award (MR/M009041/1) to the School of Clinical Medicine, University of Cambridge and supported by the mental health theme of the NIHR Cambridge Biomedical Research Centre.

Sex chromosome aneuploidy (SCA) increases the risk for cognitive deficits, and confers changes in regional cortical thickness (CT) and surface area (SA). Neuroanatomical correlates of inter-individual variation in cognitive ability have been described in health, but are not well-characterized in SCA. Here, we modeled relationships between general cognitive ability (estimated using full-scale IQ [FSIQ] from Wechsler scales) and regional estimates of SA and CT (from structural MRI scans) in both aneuploid (28 XXX, 55 XXY, 22 XYY, 19 XXYY) and typically-developing euploid (79 XX, 85 XY) individuals. Results indicated widespread decoupling of normative anatomical–cognitive relationships in SCA: we found five regions where SCA significantly altered SA–FSIQ relationships, and five regions where SCA significantly altered CT–FSIQ relationships. The majority of areas were characterized by the presence of positive anatomy-IQ relationships in health, but no or slightly negative anatomy-IQ relationships in SCA. Disrupted anatomical–cognitive relationships generalized from the full cohort to karyotypically defined subcohorts (i.e., XX-XXX; XY-XYY; XY-XXY), demonstrating continuity across multiple supernumerary SCA conditions. As the first direct evidence of altered regional neuroanatomical–cognitive relationships in supernumerary SCA, our findings shed light on potential genetic and structural correlates of the cognitive phenotype in SCA, and may have implications for other neurogenetic disorders.

Scene inference under low-light is a challenging problem due to severe noise in the captured images. One way to reduce noise is to use longer exposure during the capture. However, in the presence of motion (scene or camera motion), longer exposures lead to motion blur, resulting in loss of image information. This creates a trade-off between these two kinds of image degradations: motion blur (due to long exposure) vs. noise (due to short exposure), also referred as a dual image corruption pair in this paper. With the rise of cameras capable of capturing multiple exposures of the same scene simultaneously, it is possible to overcome this trade-off. Our key observation is that although the amount and nature of degradation varies for these different image captures, the semantic content remains the same across all images. To this end, we propose a method to leverage these multi exposure captures for robust inference under low-light and motion. Our method builds on a feature consistency loss to encourage similar results from these individual captures, and uses the ensemble of their final predictions for robust visual recognition. We demonstrate the effectiveness of our approach on simulated images as well as real captures with multiple exposures, and across the tasks of object detection and image classification., Comment: ICCP 2022 Camera Ready

Highlights • 17-Year follow up linking pediatric brain anatomy with adult drinking. • Female-specific relationships between subcortical anatomy and adult drinking. • Effects localize to subregions of the amygdala and hippocampus., Men and women tend to differ in the age of first alcohol consumption, transition into disordered drinking, and the prevalence of alcohol use disorder. Here, we use a unique longitudinal dataset to test for potentially predispositonal sex-biases in brain organization prior to initial alcohol exposure. Our study combines measures of subcortical morphometry gathered in alcohol naive individuals during childhood (mean age: 9.43 years, SD = 2.06) with self-report measures of alcohol use in the same individuals an average of 17 years later (N = 81, 46 males, 35 females). We observe that pediatric amygdala and hippocampus volume both show sex-biased relationships with adult drinking. Specifically, females show a stronger association between subcortical volumetric reductions in childhood and peak drinking in adulthood as compared to males. Detailed analysis of subcortical shape localizes these effects to the rostro-medial hippocampus and basolateral amygdala subnuclei. In contrast, we did not observe sex-specific associations between striatal anatomy and peak alcohol consumption. These results are consistent with a model in which organization of the amygdala and hippocampus in childhood is more relevant for subsequent patterns of peak alcohol use in females as compared to males. Differential neuroanatomical precursors of alcohol use in males and females could provide a potential developmental basis for well recognized sex-differences in alcohol use behaviors.. Thus, our findings not only indicate that brain correlates of human alcohol consumption are manifest long before alcohol initiation, but that some of these correlates are not equivalent between males and females.

Many neuropsychiatric risk genes contribute to epigenetic regulation but little is known about specific chromatin-associated mechanisms governing the formation of neuronal connectivity. Here we show that transcallosal connectivity is critically dependent on C11orf46, a nuclear protein encoded in the chromosome 11p13 WAGR risk locus. C11orf46 haploinsufficiency was associated with hypoplasia of the corpus callosum. C11orf46 knockdown disrupted transcallosal projections and was rescued by wild type C11orf46 but not the C11orf46R236H mutant associated with intellectual disability. Multiple genes encoding key regulators of axonal development, including Sema6a, were hyperexpressed in C11orf46-knockdown neurons. RNA-guided epigenetic editing of Sema6a gene promoters via a dCas9-SunTag system with C11orf46 binding normalized SEMA6A expression and rescued transcallosal dysconnectivity via repressive chromatin remodeling by the SETDB1 repressor complex. Our study demonstrates that interhemispheric communication is sensitive to locus-specific remodeling of neuronal chromatin, revealing the therapeutic potential for shaping the brain’s connectome via gene-targeted designer activators and repressor proteins., Although many neuropsychiatric risk genes are known to contribute to epigenetic regulation of gene expression, very little is known about specific chromatin-associated mechanisms that govern the formation and maintenance of neuronal connectivity. Here, the authors report that transcallosal connectivity is critically dependent on C11orf46/ARL14EP, a nuclear protein encoded in the chromosome 11p13 WAGR risk locus, and that RNA-guided epigenetic editing of hyperexpressed Sema6a gene promoters in C11orf46-knockdown neurons resulted in normalization of expression and rescue of transcallosal dysconnectivity via repressive chromatin remodeling.

Brain structural covariance norms capture the coordination of neurodevelopmental programs between different brain regions. We develop and apply anatomical imbalance mapping (AIM), a method to measure and model individual deviations from these norms, to provide a lifespan map of morphological integration in the human cortex. In cross-sectional and longitudinal data, analysis of whole-brain average anatomical imbalance reveals a reproducible tightening of structural covariance by age 25 y, which loosens after the seventh decade of life. Anatomical imbalance change in development and in aging is greatest in the association cortex and least in the sensorimotor cortex. Finally, we show that interindividual variation in whole-brain average anatomical imbalance is positively correlated with a marker of human prenatal stress (birthweight disparity between monozygotic twins) and negatively correlated with general cognitive ability. This work provides methods and empirical insights to advance our understanding of coordinated anatomical organization of the human brain and its interindividual variation.

We introduce Mixture-based Feature Space Learning (MixtFSL) for obtaining a rich and robust feature representation in the context of few-shot image classification. Previous works have proposed to model each base class either with a single point or with a mixture model by relying on offline clustering algorithms. In contrast, we propose to model base classes with mixture models by simultaneously training the feature extractor and learning the mixture model parameters in an online manner. This results in a richer and more discriminative feature space which can be employed to classify novel examples from very few samples. Two main stages are proposed to train the MixtFSL model. First, the multimodal mixtures for each base class and the feature extractor parameters are learned using a combination of two loss functions. Second, the resulting network and mixture models are progressively refined through a leader-follower learning procedure, which uses the current estimate as a "target" network. This target network is used to make a consistent assignment of instances to mixture components, which increases performance and stabilizes training. The effectiveness of our end-to-end feature space learning approach is demonstrated with extensive experiments on four standard datasets and four backbones. Notably, we demonstrate that when we combine our robust representation with recent alignment-based approaches, we achieve new state-of-the-art results in the inductive setting, with an absolute accuracy for 5-shot classification of 82.45 on miniImageNet, 88.20 with tieredImageNet, and 60.70 in FC100 using the ResNet-12 backbone.

Neurodevelopmental disorders have a heritable component and are associated with region specific alterations in brain anatomy. However, it is unclear how genetic risks for neurodevelopmental disorders are translated into spatially patterned brain vulnerabilities. Here, we integrated cortical neuroimaging data from patients with neurodevelopmental disorders caused by genomic copy number variations (CNVs) and gene expression data from healthy subjects. For each of the six investigated disorders, we show that spatial patterns of cortical anatomy changes in youth are correlated with cortical spatial expression of CNV genes in neurotypical adults. By transforming normative bulk-tissue cortical expression data into cell-type expression maps, we link anatomical change maps in each analysed disorder to specific cell classes as well as the CNV-region genes they express. Our findings reveal organizing principles that regulate the mapping of genetic risks onto regional brain changes in neurogenetic disorders. Our findings will enable screening for candidate molecular mechanisms from readily available neuroimaging data.

Neurodevelopmental disorders have a heritable component and are associated with region specific alterations in brain anatomy. However, it is unclear how genetic risks for neurodevelopmental disorders are translated into spatially patterned brain vulnerabilities. Here, we integrated cortical neuroimaging data from patients with neurodevelopmental disorders caused by genomic copy number variations (CNVs) and gene expression data from healthy subjects. For each of the six investigated disorders, we show that spatial patterns of cortical anatomy changes in youth are correlated with cortical spatial expression of CNV genes in neurotypical adults. By transforming normative bulk-tissue cortical expression data into cell-type expression maps, we link anatomical change maps in each analysed disorder to specific cell classes as well as the CNV-region genes they express. Our findings reveal organizing principles that regulate the mapping of genetic risks onto regional brain changes in neurogenetic disorders. Our findings will enable screening for candidate molecular mechanisms from readily available neuroimaging data., How neurodevelopmental disorder-associated risk genes are translated into spatially patterned brain vulnerabilities is unclear. Here, the authors show that disorder-specific patterns of neuroanatomical changes are aligned to brain expression maps of disease risk genes in healthy subjects.

Data-driven methods to assist lens design have recently begun to emerge; in particular, under the form of lens design extrapolation to find starting points (lenses and freeform reflective system). I proposed a trip over the years to better understand why the AI have been applied first to the starting point problems and where we are going in the future.

Childhood-onset schizophrenia (COS) is a rare, severe form of the adult-onset disorder (AOS). Our previous resting-state fMRI study identified attenuated functional connectivity in COS compared with controls. Here, we ask whether COS and AOS patients and their siblings exhibit similar abnormalities of functional connectivity.A whole-brain, data-driven approach was used to assess resting-state functional connectivity differences in COS (patients/siblings/controls, n: 26/28/33) and AOS (n: 19/28/30). There were no significant differences in age, sex, or head motion across groups in each dataset and as designed, the COS dataset has a significantly lower age than the AOS.Both COS and AOS patients showed decreased functional connectivity relative to controls among a wide set of brain regions (P0.05, corrected), but their siblings did not. Decreased connectivity in COS and AOS patients showed no amplitude differences and was not modulated by age-at-onset or medication doses. Cluster analysis revealed that these regions fell into two large-scale networks: one sensorimotor network and one centered on default-mode network regions, but including higher-order cognitive areas only in COS. Decreased connectivity between these two networks was notable (P0.05, corrected) for both patient groups.A shared pattern of attenuated functional connectivity was found in COS and AOS, supporting the continuity of childhood-onset and adult-onset schizophrenia. Connections were altered between sensorimotor areas and default-mode areas in both COS and AOS, suggesting potential abnormalities in processes of self-monitoring and sensory prediction. The absence of substantial dysconnectivity in siblings indicates that attenuation is state-related.

Shifts in brain regions with brain size Brain size among normal humans varies as much as twofold. Reardon et al. surveyed the cortical and subcortical structure of more than 3000 human brains by noninvasive imaging (see the Perspective by Van Essen). They found that the scaling of different regions across the range of brain sizes is not consistent: Some brain regions are metabolically costly and are favored in larger brains. This shifts the balance between associative and sensorimotor brain systems in a brain size–dependent way. Science , this issue p. 1222 ; see also p. 1184

Neurodevelopmental disorders are highly heritable and associated with spatially-selective disruptions of brain anatomy. The logic that translates genetic risks into spatially patterned brain vulnerabilities remains unclear but is a fundamental question in disease pathogenesis. Here, we approach this question by integrating (i)in vivoneuroimaging data from patient subgroups with known causal genomic copy number variations (CNVs), and (ii) bulk and single-cell gene expression data from healthy cortex. First, for each of six different CNV disorders, we show that spatial patterns of cortical anatomy change in youth are correlated with spatial patterns of expression for CNV region genes in bulk cortical tissue from typically-developing adults. Next, by transforming normative bulk-tissue cortical expression data into cell-type expression maps, we further link each disorder’s anatomical change map to specific cell classes and specific CNV-region genes that these cells express. Finally, we establish convergent validity of this “transcriptional vulnerability model” by inter-relating patient neuroimaging data with measures of altered gene expression in both brain and blood-derived patient tissue. Our work clarifies general biological principles that govern the mapping of genetic risks onto regional brain disruption in neurodevelopmental disorders. We present new methods that can harness these principles to screen for potential cellular and molecular determinants of disease from readily available patient neuroimaging data.

Childhood socioeconomic status (SES) impacts cognitive development and mental health, but its association with human structural brain development is not yet well characterized. Here, we analyzed 1243 longitudinally acquired structural MRI scans from 623 youth (299 female/324 male) to investigate the relation between SES and cortical and subcortical morphology between ages 5 and 25 years. We found positive associations between SES and total volumes of the brain, cortical sheet, and four separate subcortical structures. These associations were stable between ages 5 and 25. Surface-based shape analysis revealed that higher SES is associated with areal expansion of lateral prefrontal, anterior cingulate, lateral temporal, and superior parietal cortices and ventrolateral thalamic, and medial amygdalo-hippocampal subregions. Meta-analyses of functional imaging data indicate that cortical correlates of SES are centered on brain systems subserving sensorimotor functions, language, memory, and emotional processing. We further show that anatomical variation within a subset of these cortical regions partially mediates the positive association between SES and IQ. Finally, we identify neuroanatomical correlates of SES that exist above and beyond accompanying variation in IQ. Although SES is clearly a complex construct that likely relates to development through diverse, nondeterministic processes, our findings elucidate potential neuroanatomical mediators of the association between SES and cognitive outcomes.SIGNIFICANCE STATEMENTChildhood socioeconomic status (SES) has been associated with developmental disparities in mental health, cognitive ability, and academic achievement, but efforts to understand underlying SES–brain relationships are ongoing. Here, we leverage a unique developmental neuroimaging dataset to longitudinally map the associations between SES and regional brain anatomy at high spatiotemporal resolution. We find widespread associations between SES and global cortical and subcortical volumes and surface area and localize these correlations to a distributed set of cortical, thalamic, and amygdalo-hippocampal subregions. Anatomical variation within a subset of these regions partially mediates the positive relationship between SES and IQ. Our findings help to localize cortical and subcortical systems that represent candidate biological substrates for the known relationships between SES and cognition.

While the potential for small amounts of motion in functional magnetic resonance imaging (fMRI) scans to bias the results of functional neuroimaging studies is well appreciated, the impact of in-scanner motion on morphological analysis of structural MRI is relatively under-studied. Even among "good quality" structural scans, there may be systematic effects of motion on measures of brain morphometry. In the present study, the subjects' tendency to move during fMRI scans, acquired in the same scanning sessions as their structural scans, yielded a reliable, continuous estimate of in-scanner motion. Using this approach within a sample of 127 children, adolescents, and young adults, significant relationships were found between this measure and estimates of cortical gray matter volume and mean curvature, as well as trend-level relationships with cortical thickness. Specifically, cortical volume and thickness decreased with greater motion, and mean curvature increased. These effects of subtle motion were anatomically heterogeneous, were present across different automated imaging pipelines, showed convergent validity with effects of frank motion assessed in a separate sample of 274 scans, and could be demonstrated in both pediatric and adult populations. Thus, using different motion assays in two large non-overlapping sets of structural MRI scans, convergent evidence showed that in-scanner motion-even at levels which do not manifest in visible motion artifact-can lead to systematic and regionally specific biases in anatomical estimation. These findings have special relevance to structural neuroimaging in developmental and clinical datasets, and inform ongoing efforts to optimize neuroanatomical analysis of existing and future structural MRI datasets in non-sedated humans. Hum Brain Mapp 37:2385-2397, 2016. © 2016 Wiley Periodicals, Inc.

Many neuropsychiatric risk genes contribute to epigenetic regulation of gene expression but very little is known about specific chromatin-associated mechanisms governing the formation and maintenance of neuronal connectivity. Here we show that transcallosal connectivity is critically dependent on C11orf46 (also known as ARL14EP), a small nuclear protein encoded in the chromosome 11p13 Wilms Tumor, Aniridia, Genitourinary Abnormalities, intellectual disability (formerly referred to as Mental Retardation) (WAGR) risk locus. C11orf46 haploinsufficiency in WAGR microdeletion cases was associated with severe hypoplasia of the corpus callosum. In utero short hairpin RNA-mediated C11orf46 knockdown disrupted transcallosal projections of cortical pyramidal neurons, a phenotype that was rescued by wild type C11orf46 but not the C11orf46R236H mutant associated with autosomal recessive intellectual disability. Multiple genes encoding key regulators of axonal growth and differentiation, including Sema6A, were hyperexpressed in C11orf46-knockdown neurons. Importantly, RNA-guided epigenetic editing of neuronal Sema6a gene promoters via a dCas9 protein-conjugated SunTag scaffold with multimeric (10x) C11orf46 binding during early developmental periods, resulted in normalization of expression and rescue of transcallosal dysconnectivity via repressive chromatin remodeling, including up-regulated histone H3K9 methylation by the KAP1-SETDB1 repressor complex. Our study demonstrates that interhemispheric communication is highly sensitive to locus-specific remodeling of neuronal chromatin, revealing the therapeutic potential for shaping the brain’s connectome via gene-targeted designer activators and repressor proteins.

Childhood socioeconomic status (SES) impacts cognitive development and mental health, but its association with structural brain development is not yet well-characterized. Here, we analyzed 1243 longitudinally-acquired structural MRI scans from 623 youth to investigate the relation between SES and cortical and subcortical morphology between ages 5 and 25 years. We found positive associations between SES and total volumes of the brain, cortical sheet, and four separate subcortical structures. These associations were developmentally fixed rather than age-dependent. Surface-based shape analysis revealed that higher SES is associated with areal expansion of (i) lateral prefrontal, anterior cingulate, lateral temporal, and superior parietal cortices and (ii) ventrolateral thalamic, and medial amygdalo-hippocampal sub-regions. Meta-analyses of functional imaging data indicate that cortical correlates of SES are centered on brain systems subserving sensorimotor functions, language, memory, and emotional processing. We further show that anatomical variation within a subset of these cortical regions partially mediates the positive association between SES and IQ. Finally, we identify neuroanatomical correlates of SES that exist above and beyond accompanying variation in IQ. Our findings clarify the spatiotemporal patterning of SES-related neuroanatomical variation and inform ongoing efforts to dissect the causal pathways underpinning observed associations between childhood SES and regional brain anatomy.

Sex chromosome aneuploidy (SCA) enhances risk for several psychiatric disorders associated with the limbic system, including mood and autism spectrum disorders. These patients provide a powerful genetics-first model for understanding the biological basis of psychopathology. Additionally, these disorders are frequently sex-biased in prevalence, further suggesting an etiological role for sex chromosomes. To clarify how limbic anatomy varies across sex and sex chromosome complement, we characterized amygdala and hippocampus structure in a uniquely large sample of patients carrying supernumerary sex chromosomes (n = 132) and typically developing controls (n=166). After correction for sex-differences in brain size, karyotypically normal males (XY) and females (XX) did not differ in volume or shape of either structure. In contrast, all SCAs were associated with lowered amygdala volume relative to gonadally-matched controls. This effect was robust to three different methods for total brain volume correction, including an allometric analysis that derived normative scaling rules for these structures in a separate, typically developing population (n = 79). Hippocampal volume was insensitive to SCA after correction for total brain volume. However, surface-based analysis revealed that SCA, regardless of specific karyotype, was consistently associated with a spatially specific pattern of shape change in both amygdala and hippocampus. In particular, SCA was accompanied by contraction around the basomedial nucleus of the amygdala and an area within the hippocampal surface that cuts across hippocampal subfields. These results demonstrate the power of SCA as a model to understand how copy number variation can precipitate changes in brain systems relevant to psychiatric disease.

In MRI, subject motion results in image artifacts. High-resolution 3D scans, like MPRAGE, are particularly susceptible to motion because of long scan times and acquisition of data over multiple-shots. Such motion related artifacts have been shown to cause a bias in cortical measures extracted from segmentation of high-resolution MPRAGE images. Prospective motion correction (PMC) techniques have been developed to help mitigate artifacts due to subject motion. In this work, high-resolution MPRAGE images are acquired during intentional head motion to evaluate the effectiveness of navigator-based PMC techniques to improve both the accuracy and reproducibility of cortical morphometry measures obtained from image segmentation. The contribution of reacquiring segments of k-space affected by motion to the overall performance of PMC is assessed. Additionally, the effect of subject motion on subcortical structure volumes is investigated. In the presence of head motion, navigator-based PMC is shown to improve both the accuracy and reproducibility of cortical and subcortical measures. It is shown that reacquiring segments of k-space data that are corrupted by motion is an essential part of navigator-based PMC performance. Subcortical structure volumes are not affected by motion in the same way as cortical measures; there is not a consistent underestimation.

We present a novel technique to determine camera parameters when the sun is visible in an image sequence. The technique requires a user to label the position of the sun in a few images. We show that it can be used to successfully recover the camera focal length, as well as its azimuth and zenith angles. The method is thoroughly evaluated on synthetic data under a wide range of operating conditions, and representative examples are shown on real data. Ground truth parameters can be recovered with less than 3% error in challenging cases.

The appearance of an outdoor scene is determined to a great extent by the prevailing illumination conditions. However, most practical computer vision applications treat illumination more as a nuisance rather than a source of signal. In this dissertation, we suggest that we should instead embrace illumination, even in the challenging, uncontrolled world of consumer photographs. Our first main contribution is an understanding of natural illumination from images. This is, in general, a hard problem given the wide appearance variation in scenes. Fortunately, natural illumination, while complex, is far from being completely arbitrary. It has a structure that is well understood in atmospheric optics, but which has hardly been exploited in vision and graphics. We introduce methods for automatically estimating the illumination conditions from two types of uncontrolled outdoor image datasets: webcams and single images. The variation in sun position and sky appearance over time can be exploited to obtain viewing and illumination geometry in webcam sequences. For single images, the sky is combined in a probabilistic way with other scene features such as cast shadows and shading on vertical surfaces and convex objects, as well as with illumination priors from large image collections. Our second main contribution is to exploit the knowledge of illumination in order to synthesize novel, realistic visual content. Instead of creating appearance using the traditional computer graphics pipeline, we propose to borrow the appearance of the world that is contained in existing photo collections and webcam datasets. We also demonstrate realistic 3-D object insertion by creating plausible high-dynamic range environment maps. This can be done in image sequences, and even in single images, completely automatically. Addressing such questions has implications in a broad range of applications including intelligent transportation, surveillance, human-robot interaction, and digital entertainment.

Working memory (WM) deficits are consistently reported in schizophrenia and are related to poor functional outcomes. Functional magnetic resonance imaging studies of adult-onset schizophrenia have reported decreased functional activations and connectivity in the WM network, but no prior functional magnetic resonance imaging study has examined WM in childhood-onset schizophrenia (COS). The aim of this study was to examine the neural correlates of WM in COS.Adult patients with COS (n = 32, 21.3 ± 1.1 years), nonpsychotic siblings of patients with COS (n = 30, 19.4 ± 0.8 years), and healthy controls (n = 39, 20.0 ± 0.7 years) completed 1- and 2-back WM tasks during 3-T functional magnetic resonance imaging. Functional activation and connectivity analyses were conducted. A separate group of 23 younger patients with COS (17.9 ± 7.4 years) could not perform the tasks after twice completing a standard training and are not included in this report.Patients with COS who were included scored significantly lower than controls on all tasks (p .001). Patients with COS showed significantly lower activations in the dorsolateral prefrontal cortices, posterior parietal cortices, cerebellum, and caudate and decreased frontoparietal and corticostriatal functional connectivity compared with controls (p .05, corrected). Siblings had functional activations and connectivity intermediate between those of patients and controls in a similar set of regions (p .05, corrected). In patients, functional connectivity strength in the left frontoparietal network correlated positively with accuracy scores during the 1-back task (p = .0023, corrected).Decreased functional activation and connectivity in the WM network in COS supports pathophysiologic continuity with adult-onset schizophrenia. The low participation rate and accuracy of the patients highlights the disease severity of COS. Hypo-activations and hypo-connectivity were shared by siblings of patients with COS, suggesting COS as a potential endophenotype.Evaluating Genetic Risk Factors for Childhood-Onset Schizophrenia; http://ClinicalTrials.gov;NCT00001198.

The amygdala and hippocampus are two adjacent allocortical structures implicated in sex-biased and developmentally-emergent psychopathology. However, the spatiotemporal dynamics of amygdalo-hippocampal development remain poorly understood in healthy humans. The current study defined trajectories of volume and shape change for the amygdala and hippocampus by applying a multi-atlas segmentation pipeline (MAGeT-Brain) and semi-parametric mixed-effects spline modeling to 1,529 longitudinally-acquired structural MRI brain scans from a large, single-center cohort of 792 youth (403 males, 389 females) between the ages of 5 and 25 years old. We found that amygdala and hippocampus volumes both follow curvilinear and sexually dimorphic growth trajectories. These sex-biases were particularly striking in the amygdala: males showed a significantly later and slower adolescent deceleration in volume expansion (at age 20 years) than females (age 13 years). Shape analysis localized significant hot-spots of sex-biased anatomical development in sub-regional territories overlying rostral and caudal extremes of the CA1/2 in the hippocampus, and the centromedial nuclear group of the amygdala. In both sexes, principal components analysis revealed close integration of amygdala and hippocampus shape change along two main topographically-organized axes – low vs. high areal expansion, and early vs. late growth deceleration. These results bring greater resolution to our spatiotemporal understanding of amygdalo-hippocampal development in healthy males and females and discover focal sex-differences in the structural maturation of the brain components that may contribute to differences in behavior and psychopathology that emerge during adolescence.SIGNIFICANCE STATEMENTThe amygdala and hippocampus are implicated in several developmentally-dynamic and sex-biased psychiatric disorders, but the spatiotemporal organization and sex-biased patterning of amygdalo-hippocampal maturation remains unclear in humans. Here, by integrating new methods for analysis of longitudinal neuroimaging data, we resolve the developmental milestones and spatial gradients that organize human amygdalo-hippocampal maturation. Each structure’s volume follows a tri-phasic, curvilinear growth trajectory which - for the amygdala - shows rapid male-female size divergence in mid-adolescence through delayed growth deceleration in males. Spatially fine-grained shape analyses localize these sex differences, and further reveal highly orchestrated shape changes across the amygdala and hippocampus that are organized by two topographical gradients. These data provide a new framework for understanding amygdalo-hippocampal organization in human development.

Neuroimaging studies have implicated the corpus callosum (CC) in the pathophysiology of obsessive-compulsive disorder (OCD). Putative dysfunctions in prefrontal cortical regions suggest anomalies in anterior segments of the CC. However, recent studies have also implicated the middle and posterior CC. The present study soughts to examine the CC using parcellation scheme informed by diffusion tensor imaging. Anatomic brain magnetic resonance scans were obtained from 21 OCD subjects (mean age=26.9 ± 9.93) and 42 healthy age- and sex-matched controls (mean age=26.6 ± 9.46) between the ages of 14 and 49. Area and volume measures of five subregions of the CC were obtained via manual tracings. A multivariate analysis of variance (after correcting for multiple comparisons) identified smaller area and volume in the mid-anterior region of the CC in OCD patients relative to controls. These findings implicate medio-frontal regions of the cortex in the pathophysiology of OCD.

The corpus callosum (CC) has been implicated in the pathogenesis of schizophrenia, and CC deficits have been reported in adults with schizophrenia. We explored the developmental trajectory of the corpus callosum in childhood-onset schizophrenia (COS) patients, their healthy siblings (SIB) and healthy volunteers. We obtained 235 anatomic brain magnetic resonance imaging (MRI) scans from 98 COS patients, 153 scans from 71 of their healthy siblings, and 253 scans from 100 age- and gender-matched healthy volunteers, across ages 9–30 years. The volumes of five sub-regions of the CC were calculated using FreeSurfer, and summed to give the total volume. Longitudinal data were examined using mixed model regression analysis. There were no significant differences for the total or sub-regional CC volumes between the three groups. There were also no significant differences between the groups for developmental trajectory (slope) of the CC. This is the largest longitudinal study of CC development in schizophrenia and the first COS study of the CC to include healthy siblings. Overall, CC volume and growth trajectory did not differ between COS patients, healthy siblings, or healthy volunteers. These results suggest that CC development, at least at a macroscopic level, may not be a salient feature of schizophrenia.

LAY ABSTRACT—Autism is known to be highly heritable, and has been associated with abnormalities in the development of several brain structures, including the cerebellum. Previous research has hinted that a gene controlling the development of posterior brain regions such as the cerebellum, may influence risk for autism. This gene is called Homeobox Domain A1 (HOXA1), and the variant within HOXA1 that has been most studied in relation to autism (A218G) falls within a gene region that is important for HOXA1 protein functioning. Although we know that autism appear to influence the dynamics of brain development, and that cerebellar anatomy continues to change over the lifespan – we do not know if A218G genotype influences cerebellar development over time. We studied this issue in typically developing controls who had a total of 296 repeat structural brain scans taken between ages 5 and 23 years of age. The volume of multiple cerebellar components was measures by hand in each scan, and we related developmental changes in these volumes to A218G genotype. We found that, in a part of the cerebellum implicated in autism, A218G genotype modified the rate of cerebellar growth. This suggests for the first time that the putative ASD risk gene HOXA1 has the capacity to modify the longitudinal development of cerebellar systems implicated in ASD neurobiology. SCIENTIFIC ABSTRACT—Homeobox-A-1 (HOXA1) has been proposed as a candidate gene for autism spectrum disorder (ASD) as it regulates embryological patterning of hind-brain structures implicated in autism neurobiology. In line with this notion, a non-synonymous single nucleotide polymorphism within a highly conserved domain of HOXA1 - A218G (rs10951154) has been linked to both ASD risk, and cross-sectional differences in superior posterior lobar cerebellar anatomy in late adulthood. Despite evidence for early onset and developmentally dynamic cerebellar involvement in ASD, little is known of the relationship between A218G genotype and maturation of the cerebellum over early development. We addressed this issue using 296 longitudinally acquired structural magnetic resonance imaging brain scans from 116 healthy individuals between 5 and 23 years of age. Mixed models were used to compare the relationship between age and semi-automated measures of cerebellar volume in A-homozygotes (AA) and carriers of the G allele (Gcar). Total cerebellar volume increased between ages 5 and 23 years in both groups. However, this was accelerated in the Gcar relative to the AA group (Genotype-byage interaction term, p=0.03), and driven by genotype-dependent differences in the rate of bilateral

Background It was recently found that the development of typical patterns of prefrontal, but not posterior, cortical asymmetry is disrupted in right-handed youth with attention-deficit/hyperactivity disorder (ADHD). Using longitudinal data, we tested the hypothesis that there would be a congruent disruption in the growth of the anterior corpus callosum, which contains white matter tracts connecting prefrontal cortical regions. Methods Areas of five subregions of the corpus callosum were quantified using a semiautomated method from 828 neuroanatomic magnetic resonance scans acquired from 236 children and adolescents with ADHD (429 scans) and 230 typically developing youth (399 scans), most of whom had repeated neuroimaging. Growth rates of each diagnostic group were defined using mixed-model linear regression. Results Right-handed participants with ADHD showed a significantly higher rate of growth in the anterior-most region of the corpus callosum (estimated annual increase in area of .97%, SEM .12%) than their typically developing peers (annual increase in area of .32% SEM .13%; t = 3.64, p = .0003). No significant diagnostic differences in growth rates were found in any other regions in right-handed participants, and no significant diagnostic differences were found in non-right-handed participants. Conclusions As hypothesized, we found anomalous growth trajectories in the anterior corpus callosum in ADHD. This disrupted anterior callosal growth may reflect, or even drive, the previously reported disruption in the development of prefrontal cortex asymmetry. The finding documents the dynamic, age-dependent nature of callosal and congruent prefrontal cortical abnormalities characterizing ADHD.

Detailed descriptions of cortical anatomy in youth with Down syndrome (DS), the most common genetic cause of intellectual disability (ID), are scant. Thus, the current study examined deviations in cortical thickness (CT) and surface area (SA), at high spatial resolution, in youth with DS, to identify focal differences relative to typically developing (TD) youth. Participants included 31 youth with DS and 45 age- and sex-matched TD controls (mean age ∼16 years; range = 5-24 years). All participants completed T1-weighted ASSET-calibrated magnetization prepared rapid gradient echo scans on a 3-T magnetic resonance imaging scanner. Replicating prior investigations, cortical volume was reduced in DS compared with controls. However, a novel dissociation for SA and CT was found-namely, SA was reduced (predominantly in frontal and temporal regions) while CT was increased (notably in several regions thought to belong to the default mode network; DMN). These findings suggest that reductions in SA rather than CT are driving the cortical volume reductions reported in prior investigations of DS. Moreover, given the link between DMN functionality and Alzheimer's symptomatology in chromosomally typical populations, future DS studies may benefit from focusing on the cortex in DMN regions, as such investigations may provide clues to the precocious onset of Alzheimer's disease in this at-risk group.

While the potential for small amounts of motion in functional magnetic resonance imaging (fMRI) scans to bias the results of functional neuroimaging studies is well appreciated, the impact of in-scanner motion on morphological analysis of structural MRI is relatively under-studied. Even among "good quality" structural scans, there may be systematic effects of motion on measures of brain morphometry. In the present study, the subjects' tendency to move during fMRI scans, acquired in the same scanning sessions as their structural scans, yielded a reliable, continuous estimate of in-scanner motion. Using this approach within a sample of 127 children, adolescents, and young adults, significant relationships were found between this measure and estimates of cortical gray matter volume and mean curvature, as well as trend-level relationships with cortical thickness. Specifically, cortical volume and thickness decreased with greater motion, and mean curvature increased. These effects of subtle motion were anatomically heterogeneous, were present across different automated imaging pipelines, showed convergent validity with effects of frank motion assessed in a separate sample of 274 scans, and could be demonstrated in both pediatric and adult populations. Thus, using different motion assays in two large non-overlapping sets of structural MRI scans, convergent evidence showed that in-scanner motion-even at levels which do not manifest in visible motion artifact-can lead to systematic and regionally specific biases in anatomical estimation. These findings have special relevance to structural neuroimaging in developmental and clinical datasets, and inform ongoing efforts to optimize neuroanatomical analysis of existing and future structural MRI datasets in non-sedated humans. Hum Brain Mapp 37:2385-2397, 2016. © 2016 Wiley Periodicals, Inc.

The human brain displays stereotyped and early emerging patterns of cortical asymmetry in health. It is unclear if these asymmetries are highly sensitive to genetic and environmental variation or fundamental features of the brain that can survive severe developmental perturbations. To address this question, we mapped cortical thickness (CT) asymmetry in a group of genetically defined disorders known to impact CT development. Participants included 137 youth with one of five sex-chromosome aneuploidies [SCAs; XXX (n= 28), XXY (n= 58), XYY (n= 26), XXYY (n= 20), and XXXXY (n= 5)], and 169 age-matched typically developing controls (80 female). In controls, we replicated previously reported rightward inferior frontal and leftward lateral parietal CT asymmetry. These opposing frontoparietal CT asymmetries were broadly preserved in all five SCA groups. However, we also detected foci of shifting CT asymmetry with aneuploidy, which fell almost exclusively within regions of significant CT asymmetry in controls. Specifically, X-chromosome aneuploidy accentuated normative rightward inferior frontal asymmetries, while Y-chromosome aneuploidy reversed normative rightward medial prefrontal and lateral temporal asymmetries. These findings indicate that (1) the stereotyped normative pattern of opposing frontoparietal CT asymmetry arises from developmental mechanisms that can withstand gross chromosomal aneuploidy and (2) X and Y chromosomes can exert focal, nonoverlapping and directionally opposed influences on CT asymmetry within cortical regions of significant asymmetry in health. Our study attests to the resilience of developmental mechanisms that support the global patterning of CT asymmetry in humans, and motivates future research into the molecular bases and functional consequences of sex chromosome dosage effects on CT asymmetry.

Studies in experimental animals and humans have stressed the role of the cerebellum in motor skill learning. Yet, the relative importance of the cerebellar cortex and deep nuclei, as well as the nature of the dynamic functional changes occurring between these and other motor-related structures during learning, remains in dispute. Using functional magnetic resonance imaging and a motor sequence learning paradigm in humans, we found evidence of an experience-dependent shift of activation from the cerebellar cortex to the dentate nucleus during early learning, and from a cerebellar–cortical to a striatal–cortical network with extended practice. The results indicate that intrinsic modulation within the cerebellum, in concert with activation of motor-related cortical regions, serves to set up a procedurally acquired sequence of movements that is then maintained elsewhere in the brain.

We have developed a simple system for tagging and purifying proteins. Recent experiments have demonstrated that RTX (Repeat in Toxin) motifs from the adenylate cyclase toxin gene (CyaA) of B. pertussis undergo a conformational change upon binding calcium, resulting in precipitation of fused proteins and making this method a viable alternative for bioseparation. We have designed an iGEM Biobrick comprised of an RTX tag that can be easily fused to any protein of interest. In this paper, we detail the process of creating an RTX tagged version of the restriction enzyme EcoRI and describe a method for expression and purification of the functional enzyme.

Since the Brain Order Disorder (BOD) group reported on a high density Electroencephalogram (EEG) to capture the neuronal information using EEG to wirelessly interface with a Smartphone [1,2], a larger BOD group has been assembled, including the Obama BRAIN program, CUA Brain Computer Interface Lab and the UCSD Swartz Computational Neuroscience Center. We can implement the pair-electrodes correlation functions in order to operate in a real time daily environment, which is of the computation complexity of O(N3) for N=102~3 known as functional f-EEG. The daily monitoring requires two areas of focus. Area #(1) to quantify the neuronal information flow under arbitrary daily stimuli-response sources. Approach to #1: (i) We have asserted that the sources contained in the EEG signals may be discovered by an unsupervised learning neural network called blind sources separation (BSS) of independent entropy components, based on the irreversible Boltzmann cellular thermodynamics(ΔS < 0), where the entropy is a degree of uniformity. What is the entropy? Loosely speaking, sand on the beach is more uniform at a higher entropy value than the rocks composing a mountain – the internal binding energy tells the paleontologists the existence of information. To a politician, landside voting results has only the winning information but more entropy, while a non-uniform voting distribution record has more information. For the human’s effortless brain at constant temperature, we can solve the minimum of Helmholtz free energy (H = E − TS) by computing BSS, and then their pairwise-entropy source correlation function. (i) Although the entropy itself is not the information per se, but the concurrence of the entropy sources is the information flow as a functional-EEG, sketched in this 2nd BOD report. Area #(2) applying EEG bio-feedback will improve collective decision making (TBD). Approach to #2: We introduce a novel performance quality metrics, in terms of the throughput rate of faster (Δt) & more accurate (ΔA) decision making, which applies to individual, as well as team brain dynamics. Following Nobel Laureate Daniel Kahnmen’s novel “Thinking fast and slow”, through the brainwave biofeedback we can first identify an individual’s “anchored cognitive bias sources”. This is done in order to remove the biases by means of individually tailored pre-processing. Then the training effectiveness can be maximized by the collective product Δt * ΔA. For Area #1, we compute a spatiotemporally windowed EEG in vitro average using adaptive time-window sampling. The sampling rate depends on the type of neuronal responses, which is what we seek. The averaged traditional EEG measurements and are further improved by BSS decomposition into finer stimulus-response source mixing matrix [A] having finer & faster spatial grids with rapid temporal updates. Then, the functional EEG is the second order co-variance matrix defined as the electrode-pair fluctuation correlation function C(s~, s~’) of independent thermodynamic source components. (1) We define a 1-D Space filling curve as a spiral curve without origin. This pattern is historically known as the Peano-Hilbert arc length a. By taking the most significant bits of the Cartesian product a≡ O(x * y * z), it represents the arc length in the numerical size with values that map the 3-D neighborhood proximity into a 1-D neighborhood arc length representation. (2) 1-D Fourier coefficients spectrum have no spurious high frequency contents, which typically arise in lexicographical (zig-zag scanning) discontinuity [Hsu & Szu, “Peano-Hilbert curve,” SPIE 2014]. A simple Fourier spectrum histogram fits nicely with the Compressive Sensing CRDT Mathematics. (3) Stationary power spectral density is a reasonable approximation of EEG responses in striate layers in resonance feedback loops capable of producing a 100, 000 neuronal collective Impulse Response Function (IRF). The striate brain layer architecture represents an ensemble

Systems capable of real-time monitoring have several potential health-related applications, particularly for individuals who desire to age in place as well as those living with acute health conditions. An electrical response exists near the scalp from ionic transmission within neurons (brain cells) and may be measured noninvasively by electroencephalography (EEG). Use of EEG for detecting convulsive1, 2 and nonconvulsive3 epilepsy is well developed and documented in the literature with sensitivities between 80 and 90%. Real-time EEG monitoring during sleep may provide valuable information on alterations in sleep patterns, which has been shown to be effective in detecting and predicting anxiety, depression, and early dementia in the elderly.4, 5 Anxiety and depression in turn have been directly correlated to numerous deleterious chronic health conditions such as cardiovascular disease, stroke, sleep disorders, and diabetes. Having a mechanism to detect and predict onset of anxiety and depression would be a powerful out-of-clinic tool. A potential application for at-home EEGmonitoring is assessment of head injuries and post-concussion syndrome. As these conditions affect the alertness of individuals, there is evidence that head injuries affect the alpha wave patterns of the EEG in the range of 8–12Hz.6 While many previous studies have shown the potential for EEG to detect and assess cognitive impairments, most have been conducted under controlled research conditions in the clinic. Extension of these findings to the home requires further investigation as environmental conditions are likely to affect the EEG data collected. Wang and colleagues7 showed the efficacy of an untethered, wireless brain-machine interface system using 20 dry electrodes embedded into a head cap. This wireless ‘functional’ EEG Figure 1. (a) User-friendly smartphone interface to the functional electroencephalography (f-EEG) head mount. (b) 1D Peano-Hilberttype space-filling curve replaces the 3D layout of the electrodes. (c) High-density wired conventional EEG is replaced by a wireless hat. (d) Right-hemisphere brain f-EEG response stimulated by the visual input for a left eye dominator: before (left) and after compressive sensing (middle), as well as the difference errors (right). (e) Singlet electrode-averaged EEG (left) vs. pair-electrode fluctuation f-EEG (right) reflecting the subject’s intention to point a computer screen cursor to the left as opposed to the right: 121 electrodes (1 node to 82 points), 250Hz (averaged over 1/16 second).

Using the National Center of Health Statistics' mortality statistics databases for 1991 through 1996 (12,430,473 deaths), we isolated 144,364 individuals 40 years of age or older with a primary diagnosis of Parkinson's disease (PD). Of these, 122 died by suicide. The rate of suicide in the general population was about 10 times higher than in patients with PD (0.8% compared with only 0.08%, respectively). These different rates of suicide cannot be attrib uted to differences in age, gender, race, education, or marital status. Compared with patients with suicidal PD, patients with PD who died from other causes manifested significantly lower rates of affective disorders. The refer ent population exhibited a higher rate of malignancy and a lower rate of depression. The findings suggest that marital status, mood disorder, and somatic comorbidity provide only a limited understanding of completed suicide. ( J Geriatr Psychiatry Neurol 2001; 14:120-124).