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Author(s): Rubel, Oliver; Tritt, Andrew; Dichter, Benjamin; Braun, Thomas; Cain, Nicholas; Clack, Nathan; Davidson, Thomas; Dougherty, Max; Fillion-Robin, Jean-Christophe; Graddis, Nile; Grauer, Michael; Kiggins, Justin; Niu, Lawrence; Ozturk, Doruk; Schroeder, William; Soltesz, Ivan; Sommer, Friedrich; Svoboda, Karel; Lydia, Ng; Frank, Loren; Bouchard, Kristofer | Abstract: ABSTRACT Neurodata Without Borders: Neurophysiology (NWB:N) is a data standard for neurophysiology, providing neuroscientists with a common standard to share, archive, use, and build common analysis tools for neurophysiology data. With NWB:N version 2.0 (NWB:N 2.0) we made significant advances towards creating a usable standard, software ecosystem, and vibrant community for standardizing neurophysiology data. In this manuscript we focus in particular on the NWB:N data standard schema and present advances towards creating an accessible data standard for neurophysiology.

Neuroscience continues to experience a tremendous growth in data; in terms of the volume and variety of data, the velocity at which data is acquired, and in turn the veracity of data. These challenges are a serious impediment to sharing of data, analyses, and tools within and across labs. Here, we introduce BRAINformat, a novel data standardization framework for the design and management of scientific data formats. The BRAINformat library defines application-independent design concepts and modules that together create a general framework for standardization of scientific data. We describe the formal specification of scientific data standards, which facilitates sharing and verification of data and formats. We introduce the concept of Managed Objects, enabling semantic components of data formats to be specified as self-contained units, supporting modular and reusable design of data format components and file storage. We also introduce the novel concept of Relationship Attributes for modeling and use of semantic relationships between data objects. Based on these concepts we demonstrate the application of our framework to design and implement a standard format for electrophysiology data and show how data standardization and relationship-modeling facilitate data analysis and sharing. The format uses HDF5, enabling portable, scalable, and self-describing data storage and integration with modern high-performance computing for data-driven discovery. The BRAINformat library is open source, easy-to-use, and provides detailed user and developer documentation and is freely available at: https://bitbucket.org/oruebel/brainformat.

Copyright 2016 ACM. We present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) to compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. We present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.

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In the design of a thermal protection system (TPS) for a planetary entry vehicle, accurate modeling of the trajectory aero-heating poses a significant challenge owing to large uncertainties in chemical processes taking place at the surface. Even for surface-catalyzed reactions, which have been investigated extensively, there is no consensus on how they should be modeled; or, in some cases, on which reactions are likely to occur. Current TPS designs for Mars missions rely on a supercatalytic boundary condition, which assumes that all dissociated species recombine to the free stream composition. While this is recognized to be the the most conservative approach and leads to an increased TPS mass, discrepancies in aero-heating measurements in ground test facilities preclude less conservative design options. The present work is aimed at providing more information about surface catalyzed reactions for Mars exploration missions. Measurements of dissociated species above a catalytic surface are obtained using two-photon absorption laser-induced fluorescence (TALIF) implemented in a new 30 kW inductively coupled plasma torch facility.

Discrepancies exist as to whether appreciable amounts of CO2 recombine at the surface of Martian entry vehicles. This is a significant concern as overly conservative design measures need to be used to accommodate this uncertainty owing to the the variation in heat-fluxes that arise for different recombination models used. The University of Vermont (UVM) has recently developed an 30kW Inductively Coupled Plasma (ICP) Torch Facility. This facility is designed for investigation of material testing and gas-surface interaction chemistry. Two-photon absorption laser induced fluorescence (TALIF) and diode laser absorption spectroscopy (DLAS) strategies to characterize O, CO and CO2 concentrations near sample material surfaces are presented here.