iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology

Holdgraf, Chris; Appelhoff, Stefan; Bickel, Stephan; Bouchard, Kristofer E.; D’Ambrosio, Sasha; David, Olivier; Devinsky, Orrin; Dichter, Benjamin; Flinker, Adeen; Foster, Brett L.; Gorgolewski, Krzysztof J.; Groen, Iris; Groppe, David M.; Gündüz, Ayşegül; Hamilton, Liberty S.; Honey, Christopher J.; Jas, Mainak; Knight, Robert T.; Lachaux, Jean Philippe; Lau, Jonathan C.; Lee‐Messer, Christopher; Lundstrom, Brian Nils; Miller, Kai J.; Ojemann, Jeffrey G.; Oostenveld, Robert; Petridou, Natalia; Piantoni, Gio; Pigorini, Andrea; Pouratian, Nader; Ramsey, Nick; Stolk, Arjen; Swann, Nicole C.; Tadel, François; Voytek, Bradley; Wandell, Brian A.; Winawer, Jonathan; Whitaker, Kirstie; Zehl, Lyuba; Hermes, Dora

doi:10.1038/s41597-019-0105-7

Cited by 140 publications

(105 citation statements)

References 17 publications

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“…Given that EGI's trigger channel is sampled at 1000 Hz, which introduced jitter between the onset of the trigger and the onset of the stimulation, epochs were fine-aligned by matching the peaks of the stimulation artifacts within sessions. All good epochs were saved in MNE's fif format in the interval between −250 and 10 ms and subsequently converted to BIDS format 26,27 .…”

Section: Methodsmentioning

confidence: 99%

Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods

et al. 2020

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Precisely localizing the sources of brain activity as recorded by EEG is a fundamental procedure and a major challenge for both research and clinical practice. Even though many methods and algorithms have been proposed, their relative advantages and limitations are still not well established. Moreover, these methods involve tuning multiple parameters, for which no principled way of selection exists yet. these uncertainties are emphasized due to the lack of ground-truth for their validation and testing. Here we present the Localize-MI dataset, which constitutes the first open dataset that comprises EEG recorded electrical activity originating from precisely known locations inside the brain of living humans. High-density EEG was recorded as single-pulse biphasic currents were delivered at intensities ranging from 0.1 to 5 mA through stereotactically implanted electrodes in diverse brain regions during presurgical evaluation of patients with drug-resistant epilepsy. the uses of this dataset range from the estimation of in vivo tissue conductivity to the development, validation and testing of forward and inverse solution methods.

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Section: Methodsmentioning

confidence: 99%

Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods

et al. 2020

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“…As noted earlier, the original standard has recently been extended to cover other imaging modalities, such as MEG, 20 EEG, 21 and intracranial EEG. 22 However, in its current form, the BIDS standard does not cover derivatives of the raw data such as preprocessed or otherwise modeled data. Extensions to the specification are being investigated for derived data as well as for additional modalities such as PET.…”

Section: Data Structure For Pet and Mrimentioning

confidence: 99%

Guidelines for the content and format of PET brain data in publications and archives: A consensus paper

Knudsen

Ganz

Appelhoff

et al. 2020

J Cereb Blood Flow Metab

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It is a growing concern that outcomes of neuroimaging studies often cannot be replicated. To counteract this, the magnetic resonance (MR) neuroimaging community has promoted acquisition standards and created data sharing platforms, based on a consensus on how to organize and share MR neuroimaging data. Here, we take a similar approach to positron emission tomography (PET) data. To facilitate comparison of findings across studies, we first recommend publication standards for tracer characteristics, image acquisition, image preprocessing, and outcome estimation for PET neuroimaging data. The co-authors of this paper, representing more than 25 PET centers worldwide, voted to classify information as mandatory, recommended, or optional. Second, we describe a framework to facilitate data archiving and data sharing within and across centers. Because of the high cost of PET neuroimaging studies, sample sizes tend to be small and relatively few sites worldwide have the required multidisciplinary expertise to properly conduct and analyze PET studies. Data sharing will make it easier to combine datasets from different centers to achieve larger sample sizes and stronger statistical power to test hypotheses. The combining of datasets from different centers may be enhanced by adoption of a common set of best practices in data acquisition and analysis.

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“…While BIDS was originally intended for magnetic resonance imaging (MRI) data, it has extensions for other data modalities including: magnetoencephalography (MEG; Niso et al, 2018), electroencephalography (EEG; Pernet et al, 2019), and intracranial encephalography (iEEG; Holdgraf et al, 2019). Software packages analyzing MEG, EEG, and iEEG are now starting to support data organized using the BIDS standard, thereby becoming "BIDS compatible".…”

Section: Discussionmentioning

confidence: 99%

MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis

Appelhoff¹,

Sanderson²,

Brooks³

et al. 2019

JOSS

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iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology

Cited by 140 publications

References 17 publications

Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods

Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods

Guidelines for the content and format of PET brain data in publications and archives: A consensus paper

MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis

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