Lightweight XML-based query, integration and visualization of distributed, multimodality brain imaging data

A need of many neuroimaging researchers is to integrate multimodality brain data that may be stored in separate databases. To address this need we have developed a framework that provides a uniform XML-based query interface across multiple online data sources. The development of this framework is driven by the need to integrate neurosurgical and neuroimaging data related to language. The data sources for the language studies are 1) a web-accessible relational database of neurosurgical cortical stimulation mapping data (CSM) that includes patient-specific 3-D coordinates of each stimulation site mapped to an MRI reconstruction of the patient brain surface; and 2) an XML database of fMRI and structural MRI data and analysis results, created automatically by a batch program we have embedded in SPM. To make these sources available for querying each is wrapped as an XML view embedded in a web service. A top level web application accepts distributed XQueries over the sources, which are dispatched to the underlying web services. Returned results can be displayed as XML, HTML, CSV (Excel format), a 2-D schematic of a parcellated brain, or a 3-D brain visualization. In the latter case the CSM patient-specific coordinates returned by the query are sent to a transformation web-service for conversion to normalized space, after which they are sent to our 3-D visualization program MindSeer, which is accessed via Java WebStart through a generated link. The anatomical distribution of pooled CSM sites can then be visualized using various surfaces derived from brain atlases. As this framework is further developed and generalized we believe it will have appeal for researchers who wish to query, integrate and visualize results across their own databases as well as those of collaborators

Overview of NASA Behavioral Health and Performance Standard Measures

NASAs Human Research Program (HRP) is developing a set of Standard Measures for use in spaceflight and spaceflight analog environments to monitor the risks of long-duration missions on human health and performance, including behavioral health, individual and team performance, and social processes. Based on measures selected, developed, and tested under the NASA-funded Behavioral Core Measures project (PI: D.F. Dinges) as well as other projects from NASAs Human Factors & Behavioral Performance research portfolio, NASAs Behavioral Health & Performance (BHP) Laboratory is further evaluating the operational feasibility, acceptability, and validity of a multidisciplinary suite of objective, subjective, behavioral, and biological measures for monitoring monitor behavioral health, individual and team performance, and social processes over time. The inaugural generation of the NASA Behavioral Health & Performance (BHP) Standard Measures includes a neurocognitive test battery, actigraphy, physical proximity sensors, cardiovascular monitors, and subjective self-reports of mood, depression, and various team and social processes and performance outcomes

Distributed XQuery-based integration and visualization of multimodality data: Application to brain mapping.

This paper addresses the need for relatively small groups of collaborating investigators to integrate distributed and heterogeneous data about the brain. Although various national efforts facilitate large-scale data sharing, these approaches are generally too “heavyweight” for individual or small groups of investigators, with the result that most data sharing among collaborators continues to be ad hoc. Our approach to this problem is to create a “lightweight” distributed query architecture, in which data sources are accessible via web services that accept arbitrary query languages but return XML results. A Distributed XQuery Processor (DXQP) accepts distributed XQueries in which subqueries are shipped to the remote data sources to be executed, with the resulting XML integrated by DXQP. A web-based application called DXBrain accesses DXQP, allowing a user to create, save and execute distributed XQueries, and to view the results in various formats including a 3-D brain visualization. Example results are presented using distributed brain mapping data sources obtained in studies of language organization in the brain, but any other XML source could be included. The advantage of this approach is that it is very easy to add and query a new source, the tradeoff being that the user needs to understand XQuery and the schemata of the underlying sources. For small numbers of known sources this burden is not onerous for a knowledgeable user, leading to the conclusion that the system helps to fill the gap between ad hoc local methods and large scale but complex national data sharing efforts

Kitaev's quantum double model from a local quantum physics point of view

A prominent example of a topologically ordered system is Kitaev's quantum double model $\mathcal{D}(G)$ for finite groups $G$ (which in particular includes $G = \mathbb{Z}_2$, the toric code). We will look at these models from the point of view of local quantum physics. In particular, we will review how in the abelian case, one can do a Doplicher-Haag-Roberts analysis to study the different superselection sectors of the model. In this way one finds that the charges are in one-to-one correspondence with the representations of $\mathcal{D}(G)$, and that they are in fact anyons. Interchanging two of such anyons gives a non-trivial phase, not just a possible sign change. The case of non-abelian groups $G$ is more complicated. We outline how one could use amplimorphisms, that is, morphisms $A \to M_n(A)$ to study the superselection structure in that case. Finally, we give a brief overview of applications of topologically ordered systems to the field of quantum computation.Comment: Chapter contributed to R. Brunetti, C. Dappiaggi, K. Fredenhagen, J. Yngvason (eds), Advances in Algebraic Quantum Field Theory (Springer 2015). Mainly revie

Rank-based model selection for multiple ions quantum tomography

The statistical analysis of measurement data has become a key component of many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional quantum systems, one needs to exploit prior information and the "sparsity" properties of the experimental state in order to reduce the dimensionality of the estimation problem. In this paper we propose model selection as a general principle for finding the simplest, or most parsimonious explanation of the data, by fitting different models and choosing the estimator with the best trade-off between likelihood fit and model complexity. We apply two well established model selection methods -- the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) -- to models consising of states of fixed rank and datasets such as are currently produced in multiple ions experiments. We test the performance of AIC and BIC on randomly chosen low rank states of 4 ions, and study the dependence of the selected rank with the number of measurement repetitions for one ion states. We then apply the methods to real data from a 4 ions experiment aimed at creating a Smolin state of rank 4. The two methods indicate that the optimal model for describing the data lies between ranks 6 and 9, and the Pearson $\chi^{2}$ test is applied to validate this conclusion. Additionally we find that the mean square error of the maximum likelihood estimator for pure states is close to that of the optimal over all possible measurements.Comment: 24 pages, 6 figures, 3 table

Padded Helmet Shell Covers in American Football: A Comprehensive Laboratory Evaluation with Preliminary On-Field Findings

Protective headgear effects measured in the laboratory may not always translate to the field. In this study, we evaluated the impact attenuation capabilities of a commercially available padded helmet shell cover in the laboratory and field. In the laboratory, we evaluated the efficacy of the padded helmet shell cover in attenuating impact magnitude across six impact locations and three impact velocities when equipped to three different helmet models. In a preliminary on-field investigation, we used instrumented mouthguards to monitor head impact magnitude in collegiate linebackers during practice sessions while not wearing the padded helmet shell covers (i.e., bare helmets) for one season and whilst wearing the padded helmet shell covers for another season. The addition of the padded helmet shell cover was effective in attenuating the magnitude of angular head accelerations and two brain injury risk metrics (DAMAGE, HARM) across most laboratory impact conditions, but did not significantly attenuate linear head accelerations for all helmets. Overall, HARM values were reduced in laboratory impact tests by an average of 25% at 3.5 m/s (range: 9.7 - 39.6%), 18% at 5.5 m/s (range: -5.5 - 40.5%), and 10% at 7.4 m/s (range: -6.0 - 31.0%). However, on the field, no significant differences in any measure of head impact magnitude were observed between the bare helmet impacts and padded helmet impacts. Further laboratory tests were conducted to evaluate the ability of the padded helmet shell cover to maintain its performance after exposure to repeated, successive impacts and across a range of temperatures. This research provides a detailed assessment of padded helmet shell covers and supports the continuation of in vivo helmet research to validate laboratory testing results.Comment: 49 references, 8 figure

Bostonia: The Boston University Alumni Magazine. Volume 12

Founded in 1900, Bostonia magazine is Boston University’s main alumni publication