A gauge-compatible Hamiltonian splitting algorithm for particle-in-cell simulations using finite element exterior calculus

A particle-in-cell algorithm is derived with a canonical Poisson structure in the formalism of finite element exterior calculus. The resulting method belongs to the class of gauge-compatible splitting algorithms, which exactly preserve gauge symmetries and their associated conservation laws via the momentum map. We numerically demonstrate this time invariance of the momentum map and its usefulness in establishing precise initial conditions with a desired initial electric field and fixed background charge. The restriction of this canonical, finite element Poisson structure to the 1X2P phase space is also considered and simulated numerically

Using high angular resolution diffusion imaging data to discriminate cortical regions

Brodmann's 100-year-old summary map has been widely used for cortical localization in neuroscience. There is a pressing need to update this map using non-invasive, high-resolution and reproducible data, in a way that captures individual variability. We demonstrate here that standard HARDI data has sufficiently diverse directional variation among grey matter regions to inform parcellation into distinct functional regions, and that this variation is reproducible across scans. This characterization of the signal variation as non-random and reproducible is the critical condition for successful cortical parcellation using HARDI data. This paper is a first step towards an individual cortex-wide map of grey matter microstructure, The gray/white matter and pial boundaries were identified on the high-resolution structural MRI images. Two HARDI data sets were collected from each individual and aligned with the corresponding structural image. At each vertex point on the surface tessellation, the diffusion-weighted signal was extracted from each image in the HARDI data set at a point, half way between gray/white matter and pial boundaries. We then derived several features of the HARDI profile with respect to the local cortical normal direction, as well as several fully orientationally invariant features. These features were taken as a fingerprint of the underlying grey matter tissue, and used to distinguish separate cortical areas. A support-vector machine classifier, trained on three distinct areas in repeat 1 achieved 80-82% correct classification of the same three areas in the unseen data from repeat 2 in three volunteers. Though gray matter anisotropy has been mostly overlooked hitherto, this approach may eventually form the foundation of a new cortical parcellation method in living humans. Our approach allows for further studies on the consistency of HARDI based parcellation across subjects and comparison with independent microstructural measures such as ex-vivo histology

Reconstruction of ice-sheet changes in the Antarctic Peninsula since the Last Glacial Maximum

This paper compiles and reviews marine and terrestrial data constraining the dimensions and configuration of the Antarctic Peninsula Ice Sheet (APIS) from the Last Glacial Maximum (LGM) through deglaciation to the present day. These data are used to reconstruct grounding-line retreat in 5ka time-steps from 25kaBP to present. Glacial landforms and subglacial tills on the eastern and western Antarctic Peninsula (AP) shelf indicate that the APIS was grounded to the outer shelf/shelf edge at the LGM and contained a series of fast-flowing ice streams that drained along cross-shelf bathymetric troughs. The ice sheet was grounded at the shelf edge until ~20calkaBP. Chronological control on retreat is provided by radiocarbon dates on glacimarine sediments from the shelf troughs and on lacustrine and terrestrial organic remains, as well as cosmogenic nuclide dates on erratics and ice moulded bedrock. Retreat in the east was underway by about 18calkaBP. The earliest dates on recession in the west are from Bransfield Basin where recession was underway by 17.5calkaBP. Ice streams were active during deglaciation at least until the ice sheet had pulled back to the mid-shelf. The timing of initial retreat decreased progressively southwards along the western AP shelf; the large ice stream in Marguerite Trough may have remained grounded at the shelf edge until about 14calkaBP, although terrestrial cosmogenic nuclide ages indicate that thinning had commenced by 18kaBP. Between 15 and 10calkaBP the APIS underwent significant recession along the western AP margin, although retreat between individual troughs was asynchronous. Ice in Marguerite Trough may have still been grounded on the mid-shelf at 10calkaBP. In the Larsen-A region the transition from grounded to floating ice was established by 10.7-10.6calkaBP. The APIS had retreated towards its present configuration in the western AP by the mid-Holocene but on the eastern peninsula may have approached its present configuration several thousand years earlier, by the start of the Holocene. Mid to late-Holocene retreat was diachronous with stillstands, re-advances and changes in ice-shelf configuration being recorded in most places. Subglacial topography exerted a major control on grounding-line retreat with grounding-zone wedges, and thus by inference slow-downs or stillstands in the retreat of the grounding line, occurring in some cases on reverse bed slopes

Studying neuroanatomy using MRI

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging, and disease. Developments in MRI acquisition, image processing, and data modelling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and inferring microstructural properties; we also describe key artefacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, though methods need to improve and caution is required in its interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works

Building connectomes using diffusion MRI: why, how and but

Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI-based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically-relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments