The NEMAR gateway to neuroelectromagnetic (NEM) brain imaging data

2239 

Abstract Submission 

Arnaud Delorme¹, Dung Truong², Choonhan Youn³, annalisa salazar⁴, Subhashini Sivagnanam³, Claire Stirm³, Kenneth Yoshimoto³, Russell Poldrack⁵, Amitrava Majumdar⁴, Scott Makeig⁶

¹SCCN, INC, University of California San Diego, La Jolla, CA, ²UCSD, La Jola, CA, ³UCSD, La jolla, CA, ⁴UCSD, La Jolla, CA, ⁵Stanford University, Palo Alto, CA, ⁶University of California - San Diego, Asheville, NC

Arnaud Delorme  
SCCN, INC, University of California San Diego
La Jolla, CA

Dung Truong  
UCSD
La Jola, CA

Choonhan Youn  
UCSD
La jolla, CA

annalisa salazar  
UCSD
La Jolla, CA

Subhashini Sivagnanam  
UCSD
La jolla, CA

Claire Stirm  
UCSD
La jolla, CA

Kenneth Yoshimoto  
UCSD
La jolla, CA

Russell Poldrack  
Stanford University
Palo Alto, CA

Amitrava Majumdar  
UCSD
La Jolla, CA

Scott Makeig, PhD  
University of California - San Diego
Asheville, NC

Although electroencephalography (EEG) was the first functional human brain monitoring modality (1926-), EEG data analysis long lagged in adapting new data analysis approaches – both in neurology, where visual pattern recognition applied to the raw scalp signal data is still the dominant approach, and in cognitive neuroscience where event-related potential (ERP) averages of individual scalp channel signals, collected from relatively small numbers of participants, long remained the predominant research measure. These methods, however, leave unrevealed much information about brain function contained in the data, and also cannot exploit consistencies in complex data that can only be identified in and extracted from large to very large data collections using new statistical and machine learning methods. Sharing neuroelectromagnetic (NEM) data is critical to leveraging public research investment and to supporting rigor and reproducibility in funded research. Several funding bodies require data sharing. Data sharing also allows researchers to use modern research tools to evaluate new data in a new way, by directly comparing it directly to ever accumulating stores of shared data collected in related or compatible paradigms.
Here we report initial results of building NEMAR (nemar.org), a large, publicly available human neuroelectromagnetic (NEM) data, tools, and compute resource tightly linked to a freely available high-performance computing resource, the Neuroscience Gateway (NSG). Our goal is to build a widely used and scientifically productive open resource for archiving, sharing, and further analysis and meta-analysis of NEM data.

The OpenNeuro archive [1] currently offers more than 933 open neuroimaging datasets from more than 37,000 participants. The NEMAR project [4] (Figure 1) is capitalizing on the ongoing achievements of the OpenNeuro, Neuroscience Gateway (NSG) [2], Open EEGLAB Portal [3], and BIDS standards development projects by creating a community portal to a large and ever-growing archive of human neuroelectromagnetic (NEM: EEG, MEG, iEEG) brain imaging data, data analysis tools, and advanced computational resources. Our overall goal is to support the creation, maintenance, analysis, and cross-study mining of human neuroelectromagnetic (NEM) data by seeding and growing a 'minable' archive of NEM data deposited in the OpenNeuro resource. After users upload NEM data to OpenNeuro, those data are automatically copied to the San Diego Supercomputer Center (SDSC) storage using the DataLad cloning mechanism. New DataLad snapshots from OpenNeuro are synched daily. NEM relevant data measures are then automatically computed on the Neuroscience Gateway and made available for display to users through the NEMAR web interface.

Since 2013, the Neuroscience Gateway (NSG) [3] has been serving the neuroscience community by providing easy access to many software and pipelines running primarily on high-performance computing (HPC) resources provided by the Extreme Science and Engineering Discovery Environment (XSEDE) network that coordinates resources across the NSF-funded supercomputer centers. The NEMAR gateway project shares the same infrastructure as NSG, and NSG capabilities have been expanded to allow users to run data processing tools and pipelines on NEM data of their own or from the OpenNeuro archive. NEMAR already uses NSG for computing NEM data quality metrics and also allows users to run custom MATLAB and Python scripts on NSG (nsgportal.org) using NEMAR data.

The NEMAR (nemar.org) front-end portal to neuroelectromagnetic neuroimaging data allows users to search for and optionally explore data submitted to OpenNeuro (openneuro.org) by viewing precomputed data quality metrics and visualized dataset information, and then process selected data using the XSEDE high-performance resources in conjunction with The Neuroscience Gateway (nsgportal.org) without requiring a data download and subsequent re-upload.

Non-invasive Electrical/tDCS/tACS/tRNS

EEG/MEG Modeling and Analysis ²

Databasing and Data Sharing ¹

EEG

MEG

Data analysis

ELECTROPHYSIOLOGY

MEG

Open-Source Software