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Framework for performing multi-subject analysis in electrophysiology within the BIDS format

Presented During:

Software Demonstrations  

Poster No:

1918 

Submission Type:

Abstract Submission 

Authors:

Aude Jegou1, Samuel Medina Villalon1,2, Bruno Colombet1, Aurélie Ponz1, Anthony Boyer3, Fabrice Bartolomei2,1, Olivier David3,1, Nicolas Roehri1, Christian Bénar1

Institutions:

1Aix Marseille University, Inserm, Institut de Neurosciences des Systèmes, Marseille, France, 2APHM, Timone Hospital, Clinical Neurophysiology, Marseille, France, 3Grenoble Alpes University, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences, Grenoble, France

First Author:

Aude Jegou  
Aix Marseille University, Inserm, Institut de Neurosciences des Systèmes
Marseille, France

Co-Author(s):

Samuel Medina Villalon  
Aix Marseille University, Inserm, Institut de Neurosciences des Systèmes|APHM, Timone Hospital, Clinical Neurophysiology
Marseille, France|Marseille, France
Bruno Colombet  
Aix Marseille University, Inserm, Institut de Neurosciences des Systèmes
Marseille, France
Aurélie Ponz  
Aix Marseille University, Inserm, Institut de Neurosciences des Systèmes
Marseille, France
Anthony Boyer  
Grenoble Alpes University, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences
Grenoble, France
Fabrice Bartolomei  
APHM, Timone Hospital, Clinical Neurophysiology|Aix Marseille University, Inserm, Institut de Neurosciences des Systèmes
Marseille, France|Marseille, France
Olivier David  
Grenoble Alpes University, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences|Aix Marseille University, Inserm, Institut de Neurosciences des Systèmes
Grenoble, France|Marseille, France
Nicolas Roehri  
Aix Marseille University, Inserm, Institut de Neurosciences des Systèmes
Marseille, France
Christian Bénar  
Aix Marseille University, Inserm, Institut de Neurosciences des Systèmes
Marseille, France

Introduction:

Neuroscience community has faced the challenge of reusing scripts to analyse data coming from different projects or different centers, however analysing large cohorts of data is very important to increase statistical power. Brain Imaging Data Structure (BIDS) has been developed, in part, to overcome this problem. BIDS allows to organize and share data easily [1]. Originally developed for neuroimaging, it has been extended to different modalities including intracranial-electroencephalography (iEEG) [2]. Structuring data in BIDS thus allows combining many subjects in a same analysis, in either single-center or multicenter studies. However, converting existing databases in this structure can be time consuming and transferring data from different centers can be prone to errors. Moreover, even if many software are now adapted to BIDS (e.g. Brainstorm) and BIDS App has been developed to standardize data analysis [3], these software solutions focused on anatomical data. Our goal was thus to develop tools for transferring and organising data (both electrophysiological and anatomical) from different centers in the BIDS format, and to launch automated analyses on several subjects with common criteria.

Methods:

In order to work on multicenter projects, we developed a framework to collect, organise, manage and automatically analyse multimodal datasets. To collect data, we designed an uploader programme to transfer the files (either locally or remotely) and prepare them for import into BIDS. Then, the data are automatically converted with our in-house AnyWave software [4] and organised in BIDS structure through a software suite called BIDS Manager [5]. Tests are performed to verify data readiness and integrity. For the analysis, Matlab script, Python script, AnyWave plugin, BIDS App and executable software (windows OS) can be launched on subjects through BIDS Pipeline, a BIDS Manager extension. BIDS Pipeline can be considered as a bridge between BIDS dataset and software. Thanks to the interface, users can filter the subject in the dataset by ID or by criteria, and input common analysis parameters. BIDS Pipeline controls whether the selected values can be applied to the selected subset, provided the inputs and the outputs, and run the process on all selected subjects. The way to store the results is based on BIDS derivatives specifications. Once the process is over, the output results are verified, and a log/error is given to the user. BIDS Pipeline also provides a batch system to launch several processes one after the other. BIDS Pipeline's user can create a software list with given parameter specification, then BIDS Pipeline will launch the selected software one after the other. The last BIDS Pipeline's function is to create a table gathering the different metrics resulting from the analysis across subjects, for later statistical analysis. The table compiles the subjects, their channels, and the different results by channel.

Results:

As a use case of the Medical Informatics Platform of the Human Brain Project, we converted iEEG and MRI data of the F-Tract project (f-tract.eu) in BIDS. Then, we performed automatic detection of epileptic spikes and oscillations on 40s-baseline sections in 50 subjects, using the Delphos software [6] implemented in BIDS Pipeline. The results stored in the derivatives section will be easily compared to the results originating from other analysis tools once similarly implemented in the same software environment. This will significantly improve interoperability of iEEG research software that are BIDS-compatible.

Conclusions:

Bids Manager/Pipeline allows organizing and analysing data from large cohorts, either in basic neuroscience or in clinical research. This framework can take advantage of tools developed by the neuroscience community, centralizing and facilitating their use.

Neuroinformatics and Data Sharing:

Databasing and Data Sharing 2
Workflows 1

Keywords:

Data analysis
Data Organization
ELECTROPHYSIOLOGY
Workflows
Other - BIDS, pipeline, software

1|2Indicates the priority used for review

My abstract is being submitted as a Software Demonstration.

Yes

Please indicate below if your study was a "resting state" or "task-activation” study.

Other

Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Patients

Was any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.

Yes

Was any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

Not applicable

Please indicate which methods were used in your research:

Neurophysiology
Structural MRI

Provide references using author date format

[1] K. J. Gorgolewski et al., “The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments,” Sci. Data, vol. 3, p. 160044, 2016.
[2] C. Holdgraf et al., “BIDS-iEEG : an extension to the brain imaging data structure ( BIDS ) specification for human intracranial electrophysiology,” PsyArXiv, pp. 1–26, 2018.
[3] K. J. Gorgolewski et al., “BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods,” PLoS Comput. Biol., vol. 13, no. 3, pp. 1–16, 2017.
[4] B. Colombet, M. Woodman, J. M. Badier, and C. G. Bénar, “AnyWave: A cross-platform and modular software for visualizing and processing electrophysiological signals,” J. Neurosci. Methods, vol. 242, pp. 118–126, 2015.
[5] N. Roehri, S. M. Villalon, A. Jegou, B. Colombet, B. Giusiano, and A. Ponz, “Transfer , collection and organisation of electrophysiological and imaging data for multicenter studies,” 2019.
[6] N. Roehri, J. M. Lina, J. C. Mosher, F. Bartolomei, and C. G. Benar, “Time-Frequency Strategies for Increasing High-Frequency Oscillation Detectability in Intracerebral EEG,” IEEE Trans. Biomed. Eng., vol. 63, no. 12, pp. 2595–2606, 2016.