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1. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author

Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L, Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, galassi, anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G, Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W, Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, and Gorgolewski, Krzysztof J.

Subjects
Quantitative Biology - Other Quantitative Biology
Abstract

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Published
2023
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4. Centering inclusivity in the design of online conferences—An OHBM–Open Science perspective

Author

Levitis, Elizabeth, van Praag, Cassandra D Gould, Gau, Rémi, Heunis, Stephan, DuPre, Elizabeth, Kiar, Gregory, Bottenhorn, Katherine L, Glatard, Tristan, Nikolaidis, Aki, Whitaker, Kirstie Jane, Mancini, Matteo, Niso, Guiomar, Afyouni, Soroosh, Alonso-Ortiz, Eva, Appelhoff, Stefan, Arnatkeviciute, Aurina, Atay, Selim Melvin, Auer, Tibor, Baracchini, Giulia, Bayer, Johanna MM, Beauvais, Michael JS, Bijsterbosch, Janine D, Bilgin, Isil P, Bollmann, Saskia, Bollmann, Steffen, Botvinik-Nezer, Rotem, Bright, Molly G, Calhoun, Vince D, Chen, Xiao, Chopra, Sidhant, Chuan-Peng, Hu, Close, Thomas G, Cookson, Savannah L, Craddock, R Cameron, De La Vega, Alejandro, De Leener, Benjamin, Demeter, Damion V, Di Maio, Paola, Dickie, Erin W, Eickhoff, Simon B, Esteban, Oscar, Finc, Karolina, Frigo, Matteo, Ganesan, Saampras, Ganz, Melanie, Garner, Kelly G, Garza-Villarreal, Eduardo A, Gonzalez-Escamilla, Gabriel, Goswami, Rohit, Griffiths, John D, Grootswagers, Tijl, Guay, Samuel, Guest, Olivia, Handwerker, Daniel A, Herholz, Peer, Heuer, Katja, Huijser, Dorien C, Iacovella, Vittorio, Joseph, Michael JE, Karakuzu, Agah, Keator, David B, Kobeleva, Xenia, Kumar, Manoj, Laird, Angela R, Larson-Prior, Linda J, Lautarescu, Alexandra, Lazari, Alberto, Legarreta, Jon Haitz, Li, Xue-Ying, Lv, Jinglei, L., Sina Mansour, Meunier, David, Moraczewski, Dustin, Nandi, Tulika, Nastase, Samuel A, Nau, Matthias, Noble, Stephanie, Norgaard, Martin, Obungoloch, Johnes, Oostenveld, Robert, Orchard, Edwina R, Pinho, Ana Luísa, Poldrack, Russell A, Qiu, Anqi, Raamana, Pradeep Reddy, Rokem, Ariel, Rutherford, Saige, Sharan, Malvika, Shaw, Thomas B, Syeda, Warda T, Testerman, Meghan M, Toro, Roberto, Valk, Sofie L, Van Den Bossche, Sofie, Varoquaux, Gaël, Váša, František, Veldsman, Michele, Vohryzek, Jakub, Wagner, Adina S, and Walsh, Reubs J

Subjects
online conferences, diversity, inclusivity, open science, collaborative events
Abstract

As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities. Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design. Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.

Published
2021

5. Brainhack: Developing a culture of open, inclusive, community-driven neuroscience

Author

Gau, Rémi, Noble, Stephanie, Heuer, Katja, Bottenhorn, Katherine L, Bilgin, Isil P, Yang, Yu-Fang, Huntenburg, Julia M, Bayer, Johanna MM, Bethlehem, Richard AI, Rhoads, Shawn A, Vogelbacher, Christoph, Borghesani, Valentina, Levitis, Elizabeth, Wang, Hao-Ting, Van Den Bossche, Sofie, Kobeleva, Xenia, Legarreta, Jon Haitz, Guay, Samuel, Atay, Selim Melvin, Varoquaux, Gael P, Huijser, Dorien C, Sandström, Malin S, Herholz, Peer, Nastase, Samuel A, Badhwar, AmanPreet, Dumas, Guillaume, Schwab, Simon, Moia, Stefano, Dayan, Michael, Bassil, Yasmine, Brooks, Paula P, Mancini, Matteo, Shine, James M, O’Connor, David, Xie, Xihe, Poggiali, Davide, Friedrich, Patrick, Heinsfeld, Anibal S, Riedl, Lydia, Toro, Roberto, Caballero-Gaudes, César, Eklund, Anders, Garner, Kelly G, Nolan, Christopher R, Demeter, Damion V, Barrios, Fernando A, Merchant, Junaid S, McDevitt, Elizabeth A, Oostenveld, Robert, Craddock, R Cameron, Rokem, Ariel, Doyle, Andrew, Ghosh, Satrajit S, Nikolaidis, Aki, Stanley, Olivia W, Uruñuela, Eneko, Community, The Brainhack, Anousheh, Nasim, Arnatkeviciute, Aurina, Auzias, Guillaume, Bachar, Dipankar, Bannier, Elise, Basanisi, Ruggero, Basavaraj, Arshitha, Bedini, Marco, Bellec, Pierre, Benn, R Austin, Berluti, Kathryn, Bollmann, Steffen, Bollmann, Saskia, Bradley, Claire, Brown, Jesse, Buchweitz, Augusto, Callahan, Patrick, Chan, Micaela Y, Chandio, Bramsh Q, Cheng, Theresa, Chopra, Sidhant, Chung, Ai Wern, Close, Thomas G, Combrisson, Etienne, Cona, Giorgia, Constable, R Todd, Cury, Claire, Dadi, Kamalaker, Damasceno, Pablo F, Das, Samir, De Vico Fallani, Fabrizio, DeStasio, Krista, Dickie, Erin W, Dorfschmidt, Lena, Duff, Eugene P, DuPre, Elizabeth, Dziura, Sarah, Esper, Nathalia B, Esteban, Oscar, Fadnavis, Shreyas, Flandin, Guillaume, Flannery, Jessica E, and Flournoy, John

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Neurosciences, Psychology, Communication, Congresses as Topic, Internet, Practice Guidelines as Topic, Brainhack Community, Brainhack, best practices, collaboration, community building, hackathon, inclusivity, neuroscience, open science, reproducibility, training, Cognitive Sciences, Neurology & Neurosurgery, Biological psychology
Abstract

Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress.

Published
2021

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

Author

Holdgraf, Christopher, Appelhoff, Stefan, Bickel, Stephan, Bouchard, Kristofer, D’Ambrosio, Sasha, David, Olivier, Devinsky, Orrin, Dichter, Benjamin, Flinker, Adeen, Foster, Brett L, Gorgolewski, Krzysztof J, Groen, Iris, Groppe, David, Gunduz, Aysegul, Hamilton, Liberty, Honey, Christopher J, Jas, Mainak, Knight, Robert, Lachaux, Jean-Philippe, Lau, Jonathan C, Lee-Messer, Christopher, Lundstrom, Brian N, Miller, Kai J, Ojemann, Jeffrey G, Oostenveld, Robert, Petridou, Natalia, Piantoni, Gio, Pigorini, Andrea, Pouratian, Nader, Ramsey, Nick F, Stolk, Arjen, Swann, Nicole C, Tadel, François, Voytek, Bradley, Wandell, Brian A, Winawer, Jonathan, Whitaker, Kirstie, Zehl, Lyuba, and Hermes, Dora

Subjects
Biological Psychology, Physical Sciences, Psychology, Brain Disorders, Neurosciences, 1.1 Normal biological development and functioning, Underpinning research, Neurological, Brain, Datasets as Topic, Electroencephalography, Humans, Information Storage and Retrieval, Neuroimaging
Abstract

The Brain Imaging Data Structure (BIDS) is a community-driven specification for organizing neuroscience data and metadata with the aim to make datasets more transparent, reusable, and reproducible. Intracranial electroencephalography (iEEG) data offer a unique combination of high spatial and temporal resolution measurements of the living human brain. To improve internal (re)use and external sharing of these unique data, we present a specification for storing and sharing iEEG data: iEEG-BIDS.

Published
2019

8. Advances in human intracranial electroencephalography research, guidelines and good practices

Author

Mercier, Manuel R., Dubarry, Anne-Sophie, Tadel, François, Avanzini, Pietro, Axmacher, Nikolai, Cellier, Dillan, Vecchio, Maria Del, Hamilton, Liberty S., Hermes, Dora, Kahana, Michael J., Knight, Robert T., Llorens, Anais, Megevand, Pierre, Melloni, Lucia, Miller, Kai J., Piai, Vitória, Puce, Aina, Ramsey, Nick F, Schwiedrzik, Caspar M., Smith, Sydney E., Stolk, Arjen, Swann, Nicole C., Vansteensel, Mariska J, Voytek, Bradley, Wang, Liang, Lachaux, Jean-Philippe, and Oostenveld, Robert

Published
2022
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11. PET-BIDS, an extension to the brain imaging data structure for positron emission tomography

Author

Norgaard, Martin, Matheson, Granville J., Hansen, Hanne D., Thomas, Adam, Searle, Graham, Rizzo, Gaia, Veronese, Mattia, Giacomel, Alessio, Yaqub, Maqsood, Tonietto, Matteo, Funck, Thomas, Gillman, Ashley, Boniface, Hugo, Routier, Alexandre, Dalenberg, Jelle R., Betthauser, Tobey, Feingold, Franklin, Markiewicz, Christopher J., Gorgolewski, Krzysztof J., Blair, Ross W., Appelhoff, Stefan, Gau, Remi, Salo, Taylor, Niso, Guiomar, Pernet, Cyril, Phillips, Christophe, Oostenveld, Robert, Gallezot, Jean-Dominique, Carson, Richard E., Knudsen, Gitte M., Innis, Robert B., and Ganz, Melanie

Published
2022
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15. Integrated analysis of anatomical and electrophysiological human intracranial data

Author

Stolk, Arjen, Griffin, Sandon, van der Meij, Roemer, Dewar, Callum, Saez, Ignacio, Lin, Jack J, Piantoni, Giovanni, Schoffelen, Jan-Mathijs, Knight, Robert T, and Oostenveld, Robert

Subjects
Biomedical Imaging, Brain, Electrocorticography, Electronic Data Processing, Humans, Neuroanatomy, Software, Chemical Sciences, Biological Sciences, Medical and Health Sciences, Bioinformatics
Abstract

Human intracranial electroencephalography (iEEG) recordings provide data with much greater spatiotemporal precision than is possible from data obtained using scalp EEG, magnetoencephalography (MEG), or functional MRI. Until recently, the fusion of anatomical data (MRI and computed tomography (CT) images) with electrophysiological data and their subsequent analysis have required the use of technologically and conceptually challenging combinations of software. Here, we describe a comprehensive protocol that enables complex raw human iEEG data to be converted into more readily comprehensible illustrative representations. The protocol uses an open-source toolbox for electrophysiological data analysis (FieldTrip). This allows iEEG researchers to build on a continuously growing body of scriptable and reproducible analysis methods that, over the past decade, have been developed and used by a large research community. In this protocol, we describe how to analyze complex iEEG datasets by providing an intuitive and rapid approach that can handle both neuroanatomical information and large electrophysiological datasets. We provide a worked example using an example dataset. We also explain how to automate the protocol and adjust the settings to enable analysis of iEEG datasets with other characteristics. The protocol can be implemented by a graduate student or postdoctoral fellow with minimal MATLAB experience and takes approximately an hour to execute, excluding the automated cortical surface extraction.

Published
2018

16. The Human Connectome Project: A retrospective

Author

Elam, Jennifer Stine, Glasser, Matthew F., Harms, Michael P., Sotiropoulos, Stamatios N., Andersson, Jesper L.R., Burgess, Gregory C., Curtiss, Sandra W., Oostenveld, Robert, Larson-Prior, Linda J., Schoffelen, Jan-Mathijs, Hodge, Michael R., Cler, Eileen A., Marcus, Daniel M., Barch, Deanna M., Yacoub, Essa, Smith, Stephen M., Ugurbil, Kamil, and Van Essen, David C.

Published
2021
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17. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author

Poldrack, R, Markiewicz, C, Appelhoff, S, Ashar, Y, Auer, T, Baillet, S, Bansal, S, Beltrachini, L, Benar, C, Bertazzoli, G, Bhogawar, S, Blair, R, Bortoletto, M, Boudreau, M, Brooks, T, Calhoun, V, Castelli, F, Clement, P, Cohen, A, Cohen-Adad, J, D'Ambrosio, S, de Hollander, G, de la Iglesia-Vayá, M, de la Vega, A, Delorme, A, Devinsky, O, Draschkow, D, Duff, E, Dupre, E, Earl, E, Esteban, O, Feingold, F, Flandin, G, Galassi, A, Gallitto, G, Ganz, M, Gau, R, Gholam, J, Ghosh, S, Giacomel, A, Gillman, A, Gleeson, P, Gramfort, A, Guay, S, Guidali, G, Halchenko, Y, Handwerker, D, Hardcastle, N, Herholz, P, Hermes, D, Honey, C, Innis, R, Ioanas, H, Jahn, A, Karakuzu, A, Keator, D, Kiar, G, Kincses, B, Laird, A, Lau, J, Lazari, A, Legarreta, J, Li, A, Li, X, Love, B, Lu, H, Marcantoni, E, Maumet, C, Mazzamuto, G, Meisler, S, Mikkelsen, M, Mutsaerts, H, Nichols, T, Nikolaidis, A, Nilsonne, G, Niso, G, Norgaard, M, Okell, T, Oostenveld, R, Ort, E, Park, P, Pawlik, M, Pernet, C, Pestilli, F, Petr, J, Phillips, C, Poline, J, Pollonini, L, Raamana, P, Ritter, P, Rizzo, G, Robbins, K, Rockhill, A, Rogers, C, Rokem, A, Rorden, C, Routier, A, Saborit-Torres, J, Salo, T, Schirner, M, Smith, R, Spisak, T, Sprenger, J, Swann, N, Szinte, M, Takerkart, S, Thirion, B, Thomas, A, Torabian, S, Varoquaux, G, Voytek, B, Welzel, J, Wilson, M, Yarkoni, T, Gorgolewski, K, Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L., Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la Iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G., Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Marcantoni, Eleonora, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W., Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, Gorgolewski, Krzysztof J., Poldrack, R, Markiewicz, C, Appelhoff, S, Ashar, Y, Auer, T, Baillet, S, Bansal, S, Beltrachini, L, Benar, C, Bertazzoli, G, Bhogawar, S, Blair, R, Bortoletto, M, Boudreau, M, Brooks, T, Calhoun, V, Castelli, F, Clement, P, Cohen, A, Cohen-Adad, J, D'Ambrosio, S, de Hollander, G, de la Iglesia-Vayá, M, de la Vega, A, Delorme, A, Devinsky, O, Draschkow, D, Duff, E, Dupre, E, Earl, E, Esteban, O, Feingold, F, Flandin, G, Galassi, A, Gallitto, G, Ganz, M, Gau, R, Gholam, J, Ghosh, S, Giacomel, A, Gillman, A, Gleeson, P, Gramfort, A, Guay, S, Guidali, G, Halchenko, Y, Handwerker, D, Hardcastle, N, Herholz, P, Hermes, D, Honey, C, Innis, R, Ioanas, H, Jahn, A, Karakuzu, A, Keator, D, Kiar, G, Kincses, B, Laird, A, Lau, J, Lazari, A, Legarreta, J, Li, A, Li, X, Love, B, Lu, H, Marcantoni, E, Maumet, C, Mazzamuto, G, Meisler, S, Mikkelsen, M, Mutsaerts, H, Nichols, T, Nikolaidis, A, Nilsonne, G, Niso, G, Norgaard, M, Okell, T, Oostenveld, R, Ort, E, Park, P, Pawlik, M, Pernet, C, Pestilli, F, Petr, J, Phillips, C, Poline, J, Pollonini, L, Raamana, P, Ritter, P, Rizzo, G, Robbins, K, Rockhill, A, Rogers, C, Rokem, A, Rorden, C, Routier, A, Saborit-Torres, J, Salo, T, Schirner, M, Smith, R, Spisak, T, Sprenger, J, Swann, N, Szinte, M, Takerkart, S, Thirion, B, Thomas, A, Torabian, S, Varoquaux, G, Voytek, B, Welzel, J, Wilson, M, Yarkoni, T, Gorgolewski, K, Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Blair, Ross W., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L., Cohen-Adad, Julien, D'Ambrosio, Sasha, de Hollander, Gilles, de la Iglesia-Vayá, María, de la Vega, Alejandro, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Duff, Eugene Paul, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G., Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Ioanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Marcantoni, Eleonora, Maumet, Camille, Mazzamuto, Giacomo, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nikolaidis, Aki, Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W., Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Pollonini, Luca, Raamana, Pradeep Reddy, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Spisak, Tamas, Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Welzel, Julius, Wilson, Martin, Yarkoni, Tal, and Gorgolewski, Krzysztof J.

Abstract

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Published
2024

22. Independent EEG sources are dipolar.

Author

Delorme, Arnaud, Palmer, Jason, Onton, Julie, Oostenveld, Robert, and Makeig, Scott

Subjects
Scalp, Brain, Humans, Electroencephalography, Brain Mapping, Algorithms, Principal Component Analysis, Computer Simulation, Signal Processing, Computer-Assisted, Signal Processing, Computer-Assisted, General Science & Technology
Abstract

Independent component analysis (ICA) and blind source separation (BSS) methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG) and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI) in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR) effected by each decomposition, and decomposition 'dipolarity' defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA); best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison).

Published
2012

23. How to assess the accuracy of volume conduction models? A validation study with stereotactic EEG data.

Author

Piastra, Maria Carla, Oostenveld, Robert, Homölle, Simon, Biao Han, Qi Chen, and Oostendorp, Thom

Subjects
ELECTROENCEPHALOGRAPHY, ELECTRIC stimulation, DEEP brain stimulation, FINITE element method, BRAIN stimulation, MATHEMATICAL models
Abstract

Introduction: Volume conductionmodels of the human head are used in various neuroscience fields, such as for source reconstruction in EEG and MEG, and for modeling the effects of brain stimulation. Numerous studies have quantified the accuracy and sensitivity of volume conductionmodels by analyzing the effects of the geometrical and electrical features of the head model, the sensor model, the sourcemodel, and the numericalmethod. Most studies are based on simulations as it is hard to obtain sufficiently detailed measurements to compare to models. The recording of stereotactic EEG during electric stimulation mapping provides an opportunity for such empirical validation. Methods: In the study presented here, we used the potential distribution of volume-conducted artifacts that are due to cortical stimulation to evaluate the accuracy of finite element method (FEM) volume conduction models. We adopted a widely used strategy for numerical comparison, i.e., we fixed the geometrical description of the head model and the mathematical method to performsimulations, and we gradually altered the headmodels, by increasing the level of detail of the conductivity profile. We compared the simulated potentials at different levels of refinement with the measured potentials in three epilepsy patients. Results: Our results show that increasing the level of detail of the volume conduction head model only marginally improves the accuracy of the simulated potentials when compared to in-vivo sEEG measurements. The mismatch between measured and simulated potentials is, throughout all patients and models, maximally 40 microvolts (i.e., 10% relative error) in 80% of the stimulation-recording combination pairs and it is modulated by the distance between recording and stimulating electrodes. Discussion: Our study suggests that commonly used strategies used to validate volume conduction models based solely on simulations might give an overly optimistic idea about volume conduction model accuracy. We recommend more empirical validations to be performed to identify those factors in volume conduction models that have the highest impact on the accuracy of simulated potentials. We share the dataset to allow researchers to further investigate the mismatch between measurements and FEM models and to contribute to improving volume conduction models. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Heterogeneous Cortical Effects of Spinal Cord Stimulation

Author

Witjes, Bart, Baillet, Sylvain, Roy, Mathieu, Oostenveld, Robert, Huygen, Frank J.P.M., de Vos, Cecile C., Witjes, Bart, Baillet, Sylvain, Roy, Mathieu, Oostenveld, Robert, Huygen, Frank J.P.M., and de Vos, Cecile C.

Abstract

Objectives: The understanding of the cortical effects of spinal cord stimulation (SCS) remains limited. Multiple studies have investigated the effects of SCS in resting-state electroencephalography. However, owing to the large variation in reported outcomes, we aimed to describe the differential cortical responses between two types of SCS and between responders and nonresponders using magnetoencephalography (MEG). Materials and Methods: We conducted 5-minute resting-state MEG recordings in 25 patients with chronic pain with active SCS in three sessions, each after a one-week exposure to tonic, burst, or sham SCS. We extracted six spectral features from the measured neurophysiological signals: the alpha peak frequency; alpha power ratio (power 7–9 Hz/power 9–11 Hz); and average power in the theta (4–7.5 Hz), alpha (8–12.5 Hz), beta (13–30 Hz), and low-gamma (30.5–60 Hz) frequency bands. We compared these features (using nonparametric permutation t-tests) for MEG sensor and cortical map effects across stimulation paradigms, between participants who reported low (< 5, responders) vs high (≥ 5, nonresponders) pain scores, and in three representative participants. Results: We found statistically significant (p < 0.05, false discovery rate corrected) increased MEG sensor signal power below 3 Hz in response to burst SCS compared with tonic and sham SCS. We did not find statistically significant differences (all p > 0.05) between the power spectra of responders and nonresponders. Our data did not show statistically significant differences in the spectral features of interest among the three stimulation paradigms or between responders and nonresponders. These results were confirmed by the MEG cortical maps. However, we did identify certain trends in the MEG source maps for all comparisons and several features, with substantial variation across participants. Conclusions: The considerable variation in cortical responses to the various SC

Published
2023

25. ARTEM-IS for ERP: Agreed Reporting Template for EEG Methodology -International Standard for documenting studies on Event-Related Potentials

Author

Stekić, Katarina, Šoškić, Anđela, Vanja, Ković, Algermissen, Johannes, Fischer, Nastassja L., Ganis, Giorgio, Gau, Remi, Niso, Guiomar, Oostenveld, Robert, Pajić, Dejan, Paul, Mariella, Pavlov, Yuri, Yang, Yu-Fang, Styles, Suzy J, Stekić, Katarina, Šoškić, Anđela, Vanja, Ković, Algermissen, Johannes, Fischer, Nastassja L., Ganis, Giorgio, Gau, Remi, Niso, Guiomar, Oostenveld, Robert, Pajić, Dejan, Paul, Mariella, Pavlov, Yuri, Yang, Yu-Fang, and Styles, Suzy J

Abstract

Given that the choices made during recording, preprocessing and analysis of event-related potentials (ERP) data can affect study outcomes, it is critical that they are transparently reported to allow for reproducibility and replicability. Yet, systematic reviews of reporting practices in the field have shown that journal articles do not meet this goal and that guidelines for writing them better have not resulted in a sufficient improvement to reporting transparency.ARTEM-IS aims to address this issue by building dynamic, interactive web applications that support documenting information required by existing publication guidelines in the form of a standardised metadata template. Completing an ARTEM-IS form results in a human-reader-friendly PDF and a machine-readable JSON summary of methodological information, which allows for a level of reporting precision higher than what is typically found in journal articles. These can be used as supplements to a publication, as a memory aid when writing a paper, or as records that allow easier metadata extraction in comparison to verbal descriptions in papers.Here, we present the ARTEM-IS for ERP, which supports describing a typical ERP study, including most of its core methodological aspects (study description, experimental design, hardware, data acquisition, pre-processing, measurement, visualisation, additional comments). We discuss the current contents of the form, web application functionalities, current limitations, and potential directions for future developments. In addition, the process of building the form contents and the web application through a collaborative grassroots initiative is described. Finally, we argue that a wider adoption of ARTEM-IS can bring benefits to different stakeholders: researchers themselves or their collaborators, especially on large-scale projects, reviewers, readers of a paper, and the scientific community at large.

Published
2023

26. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

Author

National Institutes of Health (US), National Science Foundation (US), Novo Nordisk Foundation, European Research Council, German Research Foundation, Charité - Universitätsmedizin Berlin, Agence Nationale de la Recherche (France), Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Maumet, Camille, Mazzamuto, Giacomo, Nikolaidis, Aki, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W, Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pollonini, Luca, Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Reddy Raamana, Pradeep, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Spisak, Tamas, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Blair, Ross W., Welzel, Julius, Wilson, Martin, Yarkoni, Tal, Gorgolewski, Krzysztof J., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L, Cohen-Adad, Julien, D'Ambrosio, Sasha, Hollander, D'Ambrosio, iglesia-Vayá, María de la, Vega, Alejandro de la, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Paul Duff, Eugene, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G, Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Loanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, Kincses, Balint, National Institutes of Health (US), National Science Foundation (US), Novo Nordisk Foundation, European Research Council, German Research Foundation, Charité - Universitätsmedizin Berlin, Agence Nationale de la Recherche (France), Poldrack, Russell A., Markiewicz, Christopher J., Appelhoff, Stefan, Ashar, Yoni K., Auer, Tibor, Baillet, Sylvain, Bansal, Shashank, Beltrachini, Leandro, Benar, Christian G., Bertazzoli, Giacomo, Bhogawar, Suyash, Laird, Angela R., Lau, Jonathan C., Lazari, Alberto, Legarreta, Jon Haitz, Li, Adam, Li, Xiangrui, Love, Bradley C., Lu, Hanzhang, Maumet, Camille, Mazzamuto, Giacomo, Nikolaidis, Aki, Meisler, Steven L., Mikkelsen, Mark, Mutsaerts, Henk, Nichols, Thomas E., Nilsonne, Gustav, Niso, Guiomar, Norgaard, Martin, Okell, Thomas W, Oostenveld, Robert, Ort, Eduard, Park, Patrick J., Pawlik, Mateusz, Pernet, Cyril R., Pollonini, Luca, Pestilli, Franco, Petr, Jan, Phillips, Christophe, Poline, Jean-Baptiste, Reddy Raamana, Pradeep, Ritter, Petra, Rizzo, Gaia, Robbins, Kay A., Rockhill, Alexander P., Rogers, Christine, Rokem, Ariel, Rorden, Chris, Routier, Alexandre, Spisak, Tamas, Saborit-Torres, Jose Manuel, Salo, Taylor, Schirner, Michael, Smith, Robert E., Sprenger, Julia, Swann, Nicole C., Szinte, Martin, Takerkart, Sylvain, Thirion, Bertrand, Thomas, Adam G., Torabian, Sajjad, Varoquaux, Gael, Voytek, Bradley, Blair, Ross W., Welzel, Julius, Wilson, Martin, Yarkoni, Tal, Gorgolewski, Krzysztof J., Bortoletto, Marta, Boudreau, Mathieu, Brooks, Teon L., Calhoun, Vince D., Castelli, Filippo Maria, Clement, Patricia, Cohen, Alexander L, Cohen-Adad, Julien, D'Ambrosio, Sasha, Hollander, D'Ambrosio, iglesia-Vayá, María de la, Vega, Alejandro de la, Delorme, Arnaud, Devinsky, Orrin, Draschkow, Dejan, Paul Duff, Eugene, DuPre, Elizabeth, Earl, Eric, Esteban, Oscar, Feingold, Franklin W., Flandin, Guillaume, Galassi, Anthony, Gallitto, Giuseppe, Ganz, Melanie, Gau, Rémi, Gholam, James, Ghosh, Satrajit S., Giacomel, Alessio, Gillman, Ashley G, Gleeson, Padraig, Gramfort, Alexandre, Guay, Samuel, Guidali, Giacomo, Halchenko, Yaroslav O., Handwerker, Daniel A., Hardcastle, Nell, Herholz, Peer, Hermes, Dora, Honey, Christopher J., Innis, Robert B., Loanas, Horea-Ioan, Jahn, Andrew, Karakuzu, Agah, Keator, David B., Kiar, Gregory, and Kincses, Balint

Abstract

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Published
2023

29. Introduction to the shared near infrared spectroscopy format

Author

Tucker, Stephen, primary, Dubb, Jay, additional, Kura, Sreekanth, additional, von Lühmann, Alexander, additional, Franke, Robert, additional, Horschig, Jörn M., additional, Powell, Samuel, additional, Oostenveld, Robert, additional, Lührs, Michael, additional, Delaire, Édouard, additional, Aghajan, Zahra M., additional, Yun, Hanseok, additional, Yücel, Meryem A., additional, Fang, Qianqian, additional, Huppert, Theodore J., additional, Frederick, Blaise B., additional, Pollonini, Luca, additional, Boas, David, additional, and Luke, Robert, additional

Published
2022
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36. Editorial: From Raw MEG/EEG to Publication: How to Perform MEG/EEG Group Analysis With Free Academic Software

Author

Delorme, Arnaud, Oostenveld, Robert, Tadel, Francois, Gramfort, Alexandre, Nagarajan, Srikantan, Litvak, Vladimir, Centre de recherche cerveau et cognition (CERCO UMR5549), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, University of California [San Diego] (UC San Diego), University of California (UC), Radboud University [Nijmegen], Karolinska Institutet [Stockholm], University of Southern California (USC), Modèles et inférence pour les données de Neuroimagerie (MIND), IFR49 - Neurospin - CEA, Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université Paris-Saclay, CEA- Saclay (CEA), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), University of California [San Francisco] (UC San Francisco), University College of London [London] (UCL), Delorme, Arnaud, Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)

Subjects
[SCCO]Cognitive science, MEG, General Neuroscience, iEEG, pipeline, EEG, [SCCO] Cognitive science, BIDS
Abstract

International audience

Published
2022

37. BIDScoin: A User-Friendly Application to Convert Source Data to Brain Imaging Data Structure

Author

Zwiers, Marcel Peter, Moia, Stefano, Oostenveld, Robert, Zwiers, Marcel Peter, Moia, Stefano, and Oostenveld, Robert

Abstract

Published: 13 January 2022, Analyses of brain function and anatomy using shared neuroimaging data is an important development, and have acquired the potential to be scaled up with the specification of a new Brain Imaging Data Structure (BIDS) standard. To date, a variety of software tools help researchers in converting their source data to BIDS but often require programming skills or are tailored to specific institutes, data sets, or data formats. In this paper, we introduce BIDScoin, a cross-platform, flexible, and user-friendly converter that provides a graphical user interface (GUI) to help users finding their way in BIDS standard. BIDScoin does not require programming skills to be set up and used and supports plugins to extend their functionality. In this paper, we show its design and demonstrate how it can be applied to a downloadable tutorial data set. BIDScoin is distributed as free and open-source software to foster the community-driven effort to promote and facilitate the use of BIDS standard.

Published
2022

38. Advances in human intracranial electroencephalography research, guidelines and good practices

Author

ZL Algemene en Acute Nec Medisch, Projectafdeling functional imaging, Brain, Mercier, Manuel R, Dubarry, Anne-Sophie, Tadel, François, Avanzini, Pietro, Axmacher, Nikolai, Cellier, Dillan, Vecchio, Maria Del, Hamilton, Liberty S, Hermes, Dora, Kahana, Michael J, Knight, Robert T, Llorens, Anais, Megevand, Pierre, Melloni, Lucia, Miller, Kai J, Piai, Vitória, Puce, Aina, Ramsey, Nick F, Schwiedrzik, Caspar M, Smith, Sydney E, Stolk, Arjen, Swann, Nicole C, Vansteensel, Mariska J, Voytek, Bradley, Wang, Liang, Lachaux, Jean-Philippe, Oostenveld, Robert, ZL Algemene en Acute Nec Medisch, Projectafdeling functional imaging, Brain, Mercier, Manuel R, Dubarry, Anne-Sophie, Tadel, François, Avanzini, Pietro, Axmacher, Nikolai, Cellier, Dillan, Vecchio, Maria Del, Hamilton, Liberty S, Hermes, Dora, Kahana, Michael J, Knight, Robert T, Llorens, Anais, Megevand, Pierre, Melloni, Lucia, Miller, Kai J, Piai, Vitória, Puce, Aina, Ramsey, Nick F, Schwiedrzik, Caspar M, Smith, Sydney E, Stolk, Arjen, Swann, Nicole C, Vansteensel, Mariska J, Voytek, Bradley, Wang, Liang, Lachaux, Jean-Philippe, and Oostenveld, Robert

Published
2022

39. Microscopy-BIDS: an extension to the brain imaging data structure for microscopy data

Author

Bourget, Marie-Hélène, Kamentsky, Lee, Ghosh, Satrajit S., Mazzamuto, Giacomo, Lazari, Alberto, Markiewicz, Christopher J., Oostenveld, Robert, Niso, Guiomar, Halchenko, Yaroslav O., Lipp, Ilona, Takerkart, Sylvain, Toussaint, Paule-Joanne, Khan, Ali R., Nilsonne, Gustav, Castelli, Filippo Maria, Cohen-Adad, Julien, Bourget, Marie-Hélène, Kamentsky, Lee, Ghosh, Satrajit S., Mazzamuto, Giacomo, Lazari, Alberto, Markiewicz, Christopher J., Oostenveld, Robert, Niso, Guiomar, Halchenko, Yaroslav O., Lipp, Ilona, Takerkart, Sylvain, Toussaint, Paule-Joanne, Khan, Ali R., Nilsonne, Gustav, Castelli, Filippo Maria, and Cohen-Adad, Julien

Abstract

The Brain Imaging Data Structure (BIDS) is a specification for organizing, sharing, and archiving neuroimaging data and metadata in a reusable way. First developed for magnetic resonance imaging (MRI) datasets, the community-led specification evolved rapidly to include other modalities such as magnetoencephalography, positron emission tomography, and quantitative MRI (qMRI). In this work, we present an extension to BIDS for microscopy imaging data, along with example datasets. Microscopy-BIDS supports common imaging methods, including 2D/3D, ex/in vivo, micro-CT, and optical and electron microscopy. Microscopy-BIDS also includes comprehensible metadata definitions for hardware, image acquisition, and sample properties. This extension will facilitate future harmonization efforts in the context of multi-modal, multi-scale imaging such as the characterization of tissue microstructure with qMRI.

Published
2022

42. Microscopy-BIDS: An extension to the Brain Imaging Data Structure for microscopy data

Author

Bourget, Marie Hélène, Kamentsky, Lee, Ghosh, Satrajit S., Mazzamuto, Giacomo, Lazari, Alberto, Markiewicz, Christopher J., Oostenveld, Robert, Niso, Guiomar, Halchenko, Yaroslav O., Lipp, Ilona, Takerkart, Sylvain, Toussaint, Paule Joanne, Khan, Ali R., Nilsonne, Gustav, Castelli, Filippo Maria, Cohen-Adad, Julien, Appelhoff, Stefan, Blair, Ross, Earl, Eric, Feingold, Franklin, Galassi, Anthony, Gau, Rémi, and Salo, Taylor

Subjects
standardization, specification, data sharing, General Neuroscience, open science, microscopy, data structure, 310 000 MEG Methods
Abstract

The Brain Imaging Data Structure (BIDS) is a specification for organizing, sharing, and archiving neuroimaging data and metadata in a reusable way. First developed for magnetic resonance imaging (MRI) datasets, the community-led specification evolved rapidly to include other modalities such as magnetoencephalography, positron emission tomography, and quantitative MRI (qMRI). In this work, we present an extension to BIDS for microscopy imaging data, along with example datasets. Microscopy-BIDS supports common imaging methods, including 2D/3D, ex/in vivo, micro-CT, and optical and electron microscopy. Microscopy-BIDS also includes comprehensible metadata definitions for hardware, image acquisition, and sample properties. This extension will facilitate future harmonization efforts in the context of multi-modal, multi-scale imaging such as the characterization of tissue microstructure with qMRI.

Published
2022

44. Deep-Breathing Biofeedback Trainability in a Virtual-Reality Action Game: A Single-Case Design Study With Police Trainers

Author

Michela, Abele, primary, van Peer, Jacobien M., additional, Brammer, Jan C., additional, Nies, Anique, additional, van Rooij, Marieke M. J. W., additional, Oostenveld, Robert, additional, Dorrestijn, Wendy, additional, Smit, Annika S., additional, Roelofs, Karin, additional, Klumpers, Floris, additional, and Granic, Isabela, additional

Published
2022
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46. Pseudonymisation of neuroimages and data protection: Increasing access to data while retaining scientific utility

Author

Eke, Damian, primary, Aasebø, Ida E.J., additional, Akintoye, Simisola, additional, Knight, William, additional, Karakasidis, Alexandros, additional, Mikulan, Ezequiel, additional, Ochang, Paschal, additional, Ogoh, George, additional, Oostenveld, Robert, additional, Pigorini, Andrea, additional, Stahl, Bernd Carsten, additional, White, Tonya, additional, and Zehl, Lyuba, additional

Published
2021
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49. The Open Brain Consent

Author

Bannier, Elise, Barker, Gareth, Borghesani, Valentina, Broeckx, Nils, Clement, Patricia, Emblem, Kyrre E., Ghosh, Satrajit, Glerean, Enrico, Gorgolewski, Krzysztof J., Havu, Marko, Halchenko, Yaroslav O., Herholz, Peer, Hespel, Anne, Heunis, Stephan, Hu, Yue, Hu, Chuan Peng, Huijser, Dorien, de la Iglesia Vayá, María, Jancalek, Radim, Katsaros, Vasileios K., Kieseler, Marie Luise, Maumet, Camille, Moreau, Clara A., Mutsaerts, Henk Jan, Oostenveld, Robert, Ozturk-Isik, Esin, Pascual Leone Espinosa, Nicolas, Pellman, John, Pernet, Cyril R., Pizzini, Francesca Benedetta, Trbalić, Amira Šerifović, Toussaint, Paule Joanne, Visconti di Oleggio Castello, Matteo, Wang, Fengjuan, Wang, Cheng, Zhu, Hua, CHU de Rennes, King’s College London, University of California San Francisco, University of Antwerp, Ghent University, University of Oslo, Harvard Medical School, School services,SCI, Stanford University, Department of Neuroscience and Biomedical Engineering, Dartmouth College, McGill University, Eindhoven University of Technology, Heinrich Heine University Düsseldorf, Nanjing Normal University, Erasmus University Rotterdam, Centro de Investigacion Principe Felipe, Masaryk University, National and Kapodistrian University of Athens, Centre National de la Recherche Scientifique (CNRS), Institut Pasteur Paris, University of Amsterdam, Radboud University Nijmegen, Bogazici University, Columbia University, University of Edinburgh, University of Verona, University of Tuzla, University of California Berkeley, Nanyang Technological University, Fujian Medical University, Beihang University, Aalto-yliopisto, and Aalto University

Subjects
informed consent, ComputingMilieux_LEGALASPECTSOFCOMPUTING, brain imaging, general data protection regulation
Abstract

Having the means to share research data openly is essential to modern science. For human research, a key aspect in this endeavor is obtaining consent from participants, not just to take part in a study, which is a basic ethical principle, but also to share their data with the scientific community. To ensure that the participants' privacy is respected, national and/or supranational regulations and laws are in place. It is, however, not always clear to researchers what the implications of those are, nor how to comply with them. The Open Brain Consent (https://open-brain-consent.readthedocs.io) is an international initiative that aims to provide researchers in the brain imaging community with information about data sharing options and tools. We present here a short history of this project and its latest developments, and share pointers to consent forms, including a template consent form that is compliant with the EU general data protection regulation. We also share pointers to an associated data user agreement that is not only useful in the EU context, but also for any researchers dealing with personal (clinical) data elsewhere. Non

Published
2021

50. Unravelling the Neural Basis of Spatial Delusions After Stroke

Author

Thiebaut De Schotten, Michel, Noble, Stephanie, Heuer, Katja, Bottenhorn, Katherine, Bilgin, Isil, Yang, Yu-Fang, Huntenburg, Julia, Bayer, Johanna M.M., Bethlehem, Richard A.I., Rhoads, Shawn, Vogelbacher, Christoph, Borghesani, Valentina, Levitis, Elizabeth, Wang, Hao-Ting, Van Den Bossche, Sofie, Kobeleva, Xenia, Legarreta, Jon Haitz, Guay, Samuel, Atay, Selim Melvin, Varoquaux, Gael, Huijser, Dorien, Sandström, Malin, Herholz, Peer, Nastase, Samuel, Badhwar, AmanPreet, Dumas, Guillaume, Schwab, Simon, Moia, Stefano, Dayan, Michael, Bassil, Yasmine, Brooks, Paula, Mancini, Matteo, Shine, James, O’Connor, David, Xie, Xihe, Poggiali, Davide, Friedrich, Patrick, Heinsfeld, Anibal, Riedl, Lydia, Toro, Roberto, Caballero-Gaudes, César, Eklund, Anders, Garner, Kelly, Nolan, Christopher, Demeter, Damion, Barrios, Fernando, Merchant, Junaid, McDevitt, Elizabeth, Oostenveld, Robert, Craddock, R. Cameron, Rokem, Ariel, Doyle, Andrew, Ghosh, Satrajit, Nikolaidis, Aki, Stanley, Olivia, Uruñuela, Eneko, Anousheh, Nasim, Arnatkeviciute, Aurina, Auzias, Guillaume, Bachar, Dipankar, Bannier, Elise, Basanisi, Ruggero, Basavaraj, Arshitha, Bedini, Marco, Bellec, Pierre, Benn, R. Austin, Berluti, Kathryn, Bollmann, Steffen, Bollmann, Saskia, Bradley, Claire, Brown, Jesse, Buchweitz, Augusto, Callahan, Patrick, Chan, Micaela, Chandio, Bramsh, Cheng, Theresa, Chopra, Sidhant, Chung, Ai Wern, Close, Thomas, Combrisson, Etienne, Cona, Giorgia, Constable, R. Todd, Cury, Claire, Dadi, Kamalaker, Damasceno, Pablo, Das, Samir, De Vico Fallani, Fabrizio, DeStasio, Krista, Dickie, Erin, Dorfschmidt, Lena, Duff, Eugene, Dupre, Elizabeth, Dziura, Sarah, Esper, Nathalia, Esteban, Oscar, Fadnavis, Shreyas, Flandin, Guillaume, Flannery, Jessica, Flournoy, John, Franco, Alexandre, Ganesan, Saampras, Gao, Siyuan, García Alanis, José, Garyfallidis, Eleftherios, Glatard, Tristan, Glerean, Enrico, Gonzalez-Castillo, Javier, Gould van Praag, Cassandra, Greene, Abigail, Gupta, Geetika, Hahn, Catherine Alice, Halchenko, Yaroslav, Handwerker, Daniel, Hartmann, Thomas, Hayot-Sasson, Valérie, Heunis, Stephan, Hoffstaedter, Felix, Hohmann, Daniela, Horien, Corey, Ioanas, Horea-Ioan, Iordan, Alexandru, Jiang, Chao, Joseph, Michael, Kai, Jason, Karakuzu, Agah, KENNEDY, David, Keshavan, Anisha, Khan, Ali, Kiar, Gregory, Klink, P. Christiaan, Koppelmans, Vincent, Koudoro, Serge, Laird, Angela, Langs, Georg, Laws, Marissa, Licandro, Roxane, Liew, Sook-Lei, Lipic, Tomislav, Litinas, Krisanne, Lurie, Daniel, Lussier, Désirée, Madan, Christopher, Mais, Lea-Theresa, Mansour L, Sina, Manzano-Patron, J.P., Maoutsa, Dimitra, Marcon, Matheus, Margulies, Daniel, Marinato, Giorgio, Marinazzo, Daniele, Markiewicz, Christopher, Meneguzzi, Felipe, Meunier, David, Milham, Michael, Mills, Kathryn, Momi, Davide, Moreau, Clara, Motala, Aysha, Moxon-Emre, Iska, Nichols, Thomas, Nielson, Dylan, Nilsonne, Gustav, Novello, Lisa, O’Brien, Caroline, Olafson, Emily, Oliver, Lindsay, Onofrey, John, Orchard, Edwina, Oudyk, Kendra, Park, Patrick, Parsapoor, Mahboobeh, Pasquini, Lorenzo, Peltier, Scott, Pernet, Cyril, Pienaar, Rudolph, Pinheiro-Chagas, Pedro, Poline, Jean-Baptiste, Qiu, Anqi, Quendera, Tiago, Rice, Laura, Rocha-Hidalgo, Joscelin, Rutherford, Saige, Scharinger, Mathias, Scheinost, Dustin, Shariq, Deena, Shaw, Thomas, Siless, Viviana, Simmonite, Molly, Sirmpilatze, Nikoloz, Spence, Hayli, Sprenger, Julia, Stajduhar, Andrija, Szinte, Martin, Takerkart, Sylvain, Tam, Angela, Tejavibulya, Link, Thome, Ina, Tomaz da Silva, Laura, Traut, Nicolas, Uddin, Lucina, Vallesi, Antonino, VanMeter, John, Vijayakumar, Nandita, di Oleggio Castello, Matteo Visconti, Vohryzek, Jakub, Vukojević, Jakša, Whitaker, Kirstie Jane, Whitmore, Lucy, Wideman, Steve, Witt, Suzanne, Xie, Hua, Xu, Ting, Yan, Chao-Gan, Yeh, Fang-Cheng, Yeo, B.T. Thomas, Zuo, Xi-Nian, Alves, Pedro, Fonseca, Ana, Silva, Daniela, Andrade, Matilde, Pinho‐e‐Melo, Teresa, Martins, Isabel, Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), and Repositório da Universidade de Lisboa

Subjects
0301 basic medicine, Male, medicine.medical_specialty, Support Vector Machine, Reduplicative paramnesia, Audiology, Logistic regression, Delusions, 03 medical and health sciences, [SCCO]Cognitive science, 0302 clinical medicine, Neuroimaging, Image Interpretation, Computer-Assisted, medicine, Humans, Functional disconnection, Prospective Studies, Stroke, ComputingMilieux_MISCELLANEOUS, Aged, Aged, 80 and over, Brain Mapping, business.industry, Anosognosia, Confounding, 16. Peace & justice, medicine.disease, Magnetic Resonance Imaging, 030104 developmental biology, Neurology, Case-Control Studies, Female, Neurology (clinical), Disconnection, business, Tomography, X-Ray Computed, 030217 neurology & neurosurgery
Abstract

© 2021 American Neurological Association, Objective: Knowing explicitly where we are is an interpretation of our spatial representations. Reduplicative paramnesia is a disrupting syndrome in which patients present a firm belief of spatial mislocation. Here, we studied the largest sample of patients with delusional misidentifications of space (i.e. reduplicative paramnesia) after stroke to shed light on their neurobiology. Methods: In a prospective, cumulative, case-control study, we screened 400 patients with acute right-hemispheric stroke. We included 64 cases and 233 controls. First, lesions were delimited and normalized. Then, we computed structural and functional disconnection maps using methods of lesion-track and network-mapping. The maps were compared, controlling for confounders. Second, we built a multivariate logistic model including clinical, behavioural and neuroimaging data. Finally, we performed a nested cross-validation of the model with a support-vector machine analysis. Results: The most frequent misidentification subtype was confabulatory mislocation (56%), followed by place reduplication (19%) and chimeric assimilation (13%). Our results indicate that structural disconnection is the strongest predictor of the syndrome and included two distinct streams, connecting right fronto-thalamic and right occipito-temporal structures. In the multivariate model, the independent predictors of reduplicative paramnesia were the structural disconnection map, lesion sparing of right dorsal fronto-parietal regions, age and anosognosia. Good discrimination accuracy was demonstrated (area under the curve = 0.80[0.75-0.85]). Interpretation: Our results localize the anatomical circuits that may have a role in the abnormal spatial-emotional binding and in the defective updating of spatial representations underlying reduplicative paramnesia. This novel data may contribute to better understand the pathophysiology of delusional syndromes after stroke., The authors acknowledge our colleagues from the Department of Neurology and from the Language Research Laboratory for their contribution to patient screening. This work received funding from “PRÉMIO JOÃO LOBO ANTUNES” – SCML (grant to P.N.A.), from “Bolsa de Investigação em Doenças Vasculares Cerebrais 2017”–SPAVC (grant to P.N.A.) and from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No. 818521 to M.T.S.).“Data were provided in part bythe Human Connectome Project, WU-Minn Consortium(Principal Investigators: David Van Essen and KamilUgurbil; 1U54 MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University.

Published
2021

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