Melting and freezing beneath Larsen C Ice Shelf, Antarctica.

Observations of recent surface lowering of Larsen C Ice Shelf (LCIS), Antarctica, and the calving of a large iceberg in 2017, have prompted concern about the stability of this ice shelf. The influence on grounded ice upstream that would result from ice shelf thinning or collapse could affect global sea level rise on decadal time scales. In this thesis, the extent to which oceanic basal melting has driven ice loss beneath LCIS, resulting in the observed lowering, was investigated by simulating ocean conditions in this region using a high resolution ocean model. The model included a new bathymetry containing a southern seabed trough discovered by seismic observations. Ocean circulation within the cavity was found to be separated into two distinct components, connected by an eastward, cross-cavity flow initially steered by the trough. In a simulation using an older seabed without the trough, this circulation was not seen. The greatest melting in the cavity corresponded to the location of rapid, inflowing water from the continental shelf which followed the trough. Using a different, older bathymetry which shallowed significantly in the northern half of the cavity, intense melting shifted from the south to the northeast. In experiments subjected to a uniform ocean warming, an increase in local melting occurred, concentrated in the trough. This does not correspond to the observed northward-intensified lowering of LCIS, suggesting oceanic forcing is not responsible for these changes. The extent of marine ice, deposited when ocean water freezes to the base of the ice shelf and advects downstream, is significantly reduced in critical regions of the ice shelf base when ocean temperatures are raised. As marine ice is thought to stabilise LCIS, potential future ocean warming may therefore lead to collapse. This demonstrates a high sensitivity of LCIS stability to even small changes in ocean forcing

Sensitivity of melting, freezing and marine ice beneath Larsen C Ice Shelf to changes in ocean forcing

Observations of surface lowering on Larsen C Ice Shelf (LCIS), Antarctica, have prompted concern about its stability. In this study, an ocean model is used to investigate the extent to which changes in ocean forcing may have influenced ice loss and the distribution of stabilising marine ice beneath LCIS. The model uses a new bathymetry, containing a southern seabed trough discovered using seismic observations. The modelled extent of marine ice, thought to stabilise LCIS, is in good agreement with observations. Experiments applying idealised ocean warming yield an increase in melting over the southern trough. This is inconsistent with lowering observed in northern LCIS, suggesting oceanic forcing is not responsible for that signal. The marine ice extent and thickness reduces significantly under ocean warming, implying a high sensitivity of LCIS stability to changes in ocean forcing. This result could have wide implications for other cold-water ice shelves around Antarctica

An updated seabed bathymetry beneath Larsen C Ice Shelf, west Antarctic

Abstract. In recent decades, rapid ice-shelf disintegration along the Antarctic Peninsula has had a global impact through enhancing outlet glacier flow, and hence sea level rise, and the freshening of Antarctic Bottom Water. Ice shelf thinning due to basal melting results from the circulation of relatively warm water in the underlying ocean cavity. However, the effect of sub-shelf circulation on future ice-shelf stability cannot be predicted accurately with computer simulations if the geometry of the ice-shelf cavity is unknown. To address this deficit for Larsen C Ice Shelf, west Antarctica, we integrate new water-column thickness measurements with existing observations. We present these new data here along with an updated bathymetry grid of the ocean cavity. Key findings include relatively deep seabed to the south-east of the Kenyon Peninsula, along the grounding line and around the key ice shelf pinning point of Bawden Ice Rise. In addition, we can confirm that the cavity’s southern trough stretches from Mobiloil Inlet to the open ocean. These areas of deep seabed will influence ocean circulation and tidal mixing, and will therefore affect the basal-melt distribution. These results will help constrain models of ice-shelf cavity circulation with the aim of improving our understanding of sub-shelf processes and their potential influence on ice shelf stability. The data set comprises all point measurements of seabed depth and a gridded data product, derived using additional measurements of both offshore seabed depth and the thickness of grounded ice. We present all new depth measurements here as well as a compilation of previously published measurements used in the gridding process. The gridded data product is included in the supplementary material. The underlying seismic data sets which were used to determine bed depth and ice thickness are available at https://doi.org/10.5285/315740B1-A7B9-4CF0-9521-86F046E33E9A (Brisbourne et al., 2019), https://doi.org/10.5285/5D63777D-B375-4791-918F-9A5527093298 (Booth, 2019), https://doi.org/10.5285/FFF8AFEE-4978-495E-9210-120872983A8D (Kulessa and Bevan, 2019) and https://doi.org/10.5285/147BAF64-B9AF-4A97-8091-26AEC0D3C0BB (Booth et al., 2019). </jats:p

An updated seabed bathymetry beneath Larsen C Ice Shelf, Antarctic Peninsula

Abstract. In recent decades, rapid ice shelf disintegration along the Antarctic Peninsula has had a global impact through enhancing outlet glacier flow and hence sea level rise and the freshening of Antarctic Bottom Water. Ice shelf thinning due to basal melting results from the circulation of relatively warm water in the underlying ocean cavity. However, the effect of sub-shelf circulation on future ice shelf stability cannot be predicted accurately with computer simulations if the geometry of the ice shelf cavity is unknown. To address this deficit for Larsen C Ice Shelf, West Antarctica, we integrate new water column thickness measurements from recent seismic campaigns with existing observations. We present these new data here along with an updated bathymetry grid of the ocean cavity. Key findings include a relatively deep seabed to the southeast of the Kenyon Peninsula, along the grounding line and around the key ice shelf pinning-point of Bawden Ice Rise. In addition, we can confirm that the cavity's southern trough stretches from Mobiloil Inlet to the open ocean. These areas of deep seabed will influence ocean circulation and tidal mixing and will therefore affect the basal-melt distribution. These results will help constrain models of ice shelf cavity circulation with the aim of improving our understanding of sub-shelf processes and their potential influence on ice shelf stability. The datasets are comprised of all the new point measurements of seabed depth. We present the new depth measurements here, as well as a compilation of previously published measurements. To demonstrate the improvements to the sub-shelf bathymetry map that these new data provide we include a gridded data product in the Supplement of this paper, derived using the additional measurements of both offshore seabed depth and the thickness of grounded ice. The underlying seismic datasets that were used to determine bed depth and ice thickness are available at https://doi.org/10.5285/315740B1-A7B9-4CF0-9521-86F046E33E9A (Brisbourne et al., 2019), https://doi.org/10.5285/5D63777D-B375-4791-918F-9A5527093298 (Booth, 2019), https://doi.org/10.5285/FFF8AFEE-4978-495E-9210-120872983A8D (Kulessa and Bevan, 2019) and https://doi.org/10.5285/147BAF64-B9AF-4A97-8091-26AEC0D3C0BB (Booth et al., 2019). </jats:p

DenseNet and Support Vector Machine classifications of major depressive disorder using vertex-wise cortical features

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing an extensive sample of people with MDD (N=2,772) and HC (N=4,240), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3–90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Consortium to examine age‐related trajectories inferred from cross‐sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3–90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter‐individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age‐related morphometric patterns

Subcortical brain volume, regional cortical thickness, and cortical surface area across disorders: findings from the ENIGMA ADHD, ASD, and OCD Working Groups

Objective Attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. We aimed to directly compare all three disorders. The ENIGMA consortium is ideally positioned to investigate structural brain alterations across these disorders. Methods Structural T1-weighted whole-brain MRI of controls (n=5,827) and patients with ADHD (n=2,271), ASD (n=1,777), and OCD (n=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. We examined subcortical volume, cortical thickness and surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults using linear mixed-effects models adjusting for age, sex and site (and ICV for subcortical and surface area measures). Results We found no shared alterations among all three disorders, while shared alterations between any two disorders did not survive multiple comparisons correction. Children with ADHD compared to those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller ICV than controls and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared to adult controls and other clinical groups. No OCD-specific alterations across different age-groups and surface area alterations among all disorders in childhood and adulthood were observed. Conclusion Our findings suggest robust but subtle alterations across different age-groups among ADHD, ASD, and OCD. ADHD-specific ICV and hippocampal alterations in children and adolescents, and ASD-specific cortical thickness alterations in the frontal cortex in adults support previous work emphasizing neurodevelopmental alterations in these disorders