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MetaNIRS: A Relational Database for the Categorization, Organization and Meta-Analysis of Optical Functional Neuroimaging Research

Jan L. Watson1, Adrian Curtin1 and Hasan Ayaz1, 2, 3*
  • 1 Drexel University, School of Biomedical Engineering, Science & Health Systems, United States
  • 2 University of Pennsylvania, Department of Family and Community Health, United States
  • 3 Children's Hospital of Philadelphia, Division of General Pediatrics, United States

Recent technological advances have created a surge of interest in the use and application of mobile neuroimaging tools. With an increasing number of publications accumulating every year, there’s a need for automated methods of tracking and relating the collective results of published functional neuroimaging studies. There are currently several projects across the neuroimaging research community that are committed to both the qualitative and quantitative organization of neuroinformatics data and its related research publications for numerous functional neuroimaging modalities and cognitive research domains (Jezek & Mou, 2009; Laird et al., 2011; Poldrack et al., 2013; Poldrack et al., 2011). However, no such project exists which provides such a comprehensive schema for the categorization, organization and meta-analyses of the vast body of functional near infrared spectroscopy (fNIRS) literature that has emerged in the past two decades. We are currently developing MetaNIRS (accessible online at http://www.metanirs.com), a collaborative project that aims to provide a comprehensive knowledge base for fNIRS research publication results with the potential to drive new and novel research surrounding fNIRS and brain function. The project aims to address the qualitative problems of ambiguous terminology and the confounding of both cognitive processes and the tasks used to measure them (Poldrack et al., 2011) by implementing a collaborative social knowledge framework with existing query and data management strategies. The relational model for database management (Codd, 1970) has proved optimal for the organization of text information and strategies have been developed for the graphical visualization of database search and search history (Hoppe, Rao, & Mackinlay, 1996). More recently, advances in keyword search algorithm development have optimized information retrieval (IR) for a rapidly increasing volume of text data in various areas of research and industry (Fritz, 2009; Liu, Yu, Meng, & Chowdhury, 2006). In addition, techniques and methodologies related to association mining facilitate the development of powerful research aids (Nielsen, Hansen, & Balslev, 2004), allowing for more efficient information management as well as large scale meta-analyses and the mapping and modeling of information (Lipsey & Wilson, 2001). Using a structured query language tool (MySQL) for the purposes of the open-source relational database management system (RDBMS) along with its affiliated Linux, Apache and PHP (LAMP) open-source application stack, MetaNIRS will provide researchers with both a search query tool and graphical user interface (GUI) to help visualize relevant regions of interest (ROI) in the human brain which have been identified experimentally in fNIRS neuroimaging literature. The MetaNIRS prototype described by the Entity Relationship Diagram in Figure 1 illustrates a summary overview of the organizational design which uses a publication’s Digital Object Identifier (DOI) as the principle key for identification of each contribution within the database. Using a human-based expert review protocol to sort publications over multiple fields, we have created a parallel data structure of values and a pointer to the publication(s) it relates to. This index structure can then be sorted allowing for binary searches to be performed. The described functionality is available to the user via a web-based interface that provides both direct access to the information being requested as well as a localized visual description of the ROI(s) to which each publication pertains. MetaNIRS is aimed to be a community driven effort poised to meet a practical need among the optical functional neuroimaging community and enable researchers to submit, review, query and identify previous research both individually and collectively in an open source, expert peer review fashion. Figure 1. Entity Relationship Diagram describing the logical structure of the MetaNIRS database for one journal publication.

Figure 1
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References

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Poldrack, R. A., Barch, D. M., Mitchell, J., Wager, T., Wagner, A. D., Devlin, J. T., . . . Milham, M. (2013). Toward open sharing of task-based fMRI data: the OpenfMRI project. Frontiers in neuroinformatics, 7, 12.

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Keywords: fNIRS, Meta-analysis, MySQL, Relational database, MetaNIRS

Conference: 2nd International Neuroergonomics Conference, Philadelphia, PA, United States, 27 Jun - 29 Jun, 2018.

Presentation Type: Poster Presentation

Topic: Neuroergonomics

Citation: Watson JL, Curtin A and Ayaz H (2019). MetaNIRS: A Relational Database for the Categorization, Organization and Meta-Analysis of Optical Functional Neuroimaging Research. Conference Abstract: 2nd International Neuroergonomics Conference. doi: 10.3389/conf.fnhum.2018.227.00053

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Received: 14 Apr 2018; Published Online: 27 Sep 2019.

* Correspondence: Dr. Hasan Ayaz, Drexel University, School of Biomedical Engineering, Science & Health Systems, Philadelphia, PA, 19104, United States, ha45@drexel.edu