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2. Good scientific practice in EEG and MEG research: Progress and perspectives

Author

Niso, Guiomar, Krol, Laurens R, Combrisson, Etienne, Dubarry, A Sophie, Elliott, Madison A, François, Clément, Héjja-Brichard, Yseult, Herbst, Sophie K, Jerbi, Karim, Kovic, Vanja, Lehongre, Katia, Luck, Steven J, Mercier, Manuel, Mosher, John C, Pavlov, Yuri G, Puce, Aina, Schettino, Antonio, Schön, Daniele, Sinnott-Armstrong, Walter, Somon, Bertille, Šoškić, Anđela, Styles, Suzy J, Tibon, Roni, Vilas, Martina G, van Vliet, Marijn, and Chaumon, Maximilien

Subjects
Biomedical and Clinical Sciences, Health Sciences, Neurosciences, Electroencephalography, Humans, Magnetoencephalography, Good scientific practice, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences
Abstract

Good scientific practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce work that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization. For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be regularly revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research. This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges. Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today's prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons.

Published
2022

3. 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. Neural interactions in the human frontal cortex dissociate reward and punishment learning.

Author

Combrisson, Etienne, Basanisi, Ruggero, Gueguen, Maelle C. M., Rheims, Sylvain, Kahane, Philippe, Bastin, Julien, and Brovelli, Andrea

Subjects
*FRONTAL lobe, *SOCIAL interaction, *PUNISHMENT, *INSULAR cortex
Abstract

How human prefrontal and insular regions interact while maximizing rewards and minimizing punishments is unknown. Capitalizing on human intracranial recordings, we demonstrate that the functional specificity toward reward or punishment learning is better disentangled by interactions compared to local representations. Prefrontal and insular cortices display non-selective neural populations to rewards and punishments. Non-selective responses, however, give rise to context-specific interareal interactions. We identify a reward subsystem with redundant interactions between the orbitofrontal and ventromedial prefrontal cortices, with a driving role of the latter. In addition, we find a punishment subsystem with redundant interactions between the insular and dorsolateral cortices, with a driving role of the insula. Finally, switching between reward and punishment learning is mediated by synergistic interactions between the two subsystems. These results provide a unifying explanation of distributed cortical representations and interactions supporting reward and punishment learning. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Neural shape mediation analysis

Author

Brochard, Jules, primary, Combrisson, Etienne, additional, Chatard, Benoit, additional, Lachaux, Jean-Philippe, additional, Brovelli, Andrea, additional, and Daunizeau, Jean, additional

Published
2023
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11. Class imbalance should not throw you off balance: Choosing the right classifiers and performance metrics for brain decoding with imbalanced data

Author

Thölke, Philipp, primary, Mantilla-Ramos, Yorguin-Jose, additional, Abdelhedi, Hamza, additional, Maschke, Charlotte, additional, Dehgan, Arthur, additional, Harel, Yann, additional, Kemtur, Anirudha, additional, Mekki Berrada, Loubna, additional, Sahraoui, Myriam, additional, Young, Tammy, additional, Bellemare Pépin, Antoine, additional, El Khantour, Clara, additional, Landry, Mathieu, additional, Pascarella, Annalisa, additional, Hadid, Vanessa, additional, Combrisson, Etienne, additional, O’Byrne, Jordan, additional, and Jerbi, Karim, additional

Published
2023
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16. Cholinergic interneuron inhibition potentiates corticostriatal transmission in direct medium spiny neurons and rescues motor learning in parkinsonism

Author

Laverne, Gwenaëlle, Pesce, Jonathan, Reynders, Ana, Combrisson, Etienne, Gascon, Eduardo, Melon, Christophe, Kerkerian-Le Goff, Lydia, Maurice, Nicolas, Beurrier, Corinne, Institut de Biologie du Développement de Marseille (IBDM), Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Centre National de la Recherche Scientifique (CNRS), Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), and ANR-17-EURE-0029,nEURo*AMU,Marseille NeuroSchool, une formation d'excellence(2017)

Subjects
[SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]
Abstract

International audience; Striatal cholinergic interneurons (CINs) respond to salient or reward prediction-related stimuli after conditioning with brief pauses in their activity, implicating them in learning and action selection. This pause is lost in animal models of Parkinson’s disease. How this signal regulates the striatal network remains an open question. Here, we examine the impact of CIN firing inhibition on glutamatergic transmission between the cortex and the medium spiny neurons expressing dopamine D1 receptor (D1 MSNs). Brief interruption of CIN activity has no effect in control conditions, whereas it increases glutamatergic responses in D1 MSNs after dopamine denervation. This potentiation depends upon M4 muscarinic receptor and protein kinase A. Decreasing CIN firing by optogenetics/chemogenetics in vivo partially rescues long-term potentiation in MSNs and motor learning deficits in parkinsonian mice. Our findings demonstrate that the control exerted by CINs on corticostriatal transmission and striatal-dependent motor-skill learning depends on the integrity of dopaminergic inputs.

Published
2022

17. Good scientific practice in EEG and MEG research: Progress and perspectives

Author

Niso, Guiomar, primary, Krol, Laurens R., additional, Combrisson, Etienne, additional, Dubarry, A. Sophie, additional, Elliott, Madison A., additional, François, Clément, additional, Héjja-Brichard, Yseult, additional, Herbst, Sophie K., additional, Jerbi, Karim, additional, Kovic, Vanja, additional, Lehongre, Katia, additional, Luck, Steven J., additional, Mercier, Manuel, additional, Mosher, John C., additional, Pavlov, Yuri G., additional, Puce, Aina, additional, Schettino, Antonio, additional, Schön, Daniele, additional, Sinnott-Armstrong, Walter, additional, Somon, Bertille, additional, Šoškić, Anđela, additional, Styles, Suzy J., additional, Tibon, Roni, additional, Vilas, Martina G., additional, van Vliet, Marijn, additional, and Chaumon, Maximilien, additional

Published
2022
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18. Class imbalance should not throw you off balance: Choosing the right classifiers and performance metrics for brain decoding with imbalanced data

Author

Thölke, Philipp, primary, Mantilla-Ramos, Yorguin-Jose, additional, Abdelhedi, Hamza, additional, Maschke, Charlotte, additional, Dehgan, Arthur, additional, Harel, Yann, additional, Kemtur, Anirudha, additional, Berrada, Loubna Mekki, additional, Sahraoui, Myriam, additional, Young, Tammy, additional, Bellemare Pépin, Antoine, additional, El Khantour, Clara, additional, Landry, Mathieu, additional, Pascarella, Annalisa, additional, Hadid, Vanessa, additional, Combrisson, Etienne, additional, O’Byrne, Jordan, additional, and Jerbi, Karim, additional

Published
2022
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21. 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

22. Decoding the neural dynamics of oculomotor decision making in humans

Author

Thiery, Thomas, Saive, Anne-Lise, Combrisson, Etienne, Dehgan, Arthur, Bastin, Julien, Kahane, Philippe, Berthoz, Alain, Lachaux, Jean-Philippe, and Jerbi, Karim

Abstract

Summary Freely choosing an action between alternatives activates a widely distributed decision circuit in the brain. Primate studies suggest that oculomotor decision processes are encoded by high-frequency components of local field potentials (LFPs) recorded in frontal and parietal areas. To what extent these LFP observations extend to oculomotor decision-making in humans is unknown. Here, we address this question using intracerebral EEG recordings from 778 sites across six surgical epilepsy patients. Free saccade choices were associated with sustained high gamma (60-140 Hz) activity during the delay period in prefrontal and parietal areas. Importantly, employing single-trial signal classification to contrast free, instructed and control trials, we were able to isolate decision-related activity from sensory and motor processes. Our findings provide the first direct electrophysiological evidence in humans for the role of high gamma activity in parietal and prefrontal areas in the intrinsically driven process of choosing among competing behavioral alternatives during free choice. Highlights First LFP recordings in humans performing an oculomotor decision-making task Free-choice saccade trials exhibit sustained frontoparietal high gamma activity Machine learning analytics unravel underlying spectral and temporal brain dynamics Single-trial saccade-locked gamma distinguish planning and execution processes

Published
2019
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23. Decoding the neural dynamics of free choice in humans

Author

Thiery, Thomas, primary, Saive, Anne-Lise, additional, Combrisson, Etienne, additional, Dehgan, Arthur, additional, Bastin, Julien, additional, Kahane, Philippe, additional, Berthoz, Alain, additional, Lachaux, Jean-Philippe, additional, and Jerbi, Karim, additional

Published
2020
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25. NeuroPycon: An open-source Python toolbox for fast multi-modal and reproducible brain connectivity pipelines

Author

Meunier, David, primary, Pascarella, Annalisa, additional, Altukhov, Dmitrii, additional, Jas, Mainak, additional, Combrisson, Etienne, additional, Lajnef, Tarek, additional, Bertrand-Dubois, Daphné, additional, Hadid, Vanessa, additional, Alamian, Golnoush, additional, Alves, Jordan, additional, Barlaam, Fanny, additional, Saive, Anne-Lise, additional, Dehgan, Arthur, additional, and Jerbi, Karim, additional

Published
2019
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26. Decoding the neural dynamics of free choice in humans

Author

Thiery, Thomas, primary, Saive, Anne-Lise, additional, Combrisson, Etienne, additional, Dehgan, Arthur, additional, Bastin, Julien, additional, Kahane, Philippe, additional, Berthoz, Alain, additional, Lachaux, Jean-Philippe, additional, and Jerbi, Karim, additional

Published
2019
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28. Visbrain: A multi-purpose GPU-accelerated open-source suite for brain data visualization

Author

Combrisson, Etienne, Vallat, Raphael, O'Reilly, Christian, Pascarella, Annalisa, Saive, Anne-Lise, Thiery, Thomas, Meunier, David, Althukov, Dmitri, Lajnef, Tarek, Ruby, Perrine, Guillot, Aymeric, and Jerbi, Karim

Subjects
Neuroinformatics, python, meg, data analysis, eeg, visualization
Abstract

We present a Python open-source package called Visbrain that offers a coherent visualization suite for multi-modal brain data (intracranial and scalp EEG, MEG, structural and functional MRI). The current version of Visbrain is essentially articulated around four modules dedicated to 1) 3D visualization of functional and/or connectivity results (Brain), 2) polysomnographic data visualization and sleep analysis (Sleep, [1]), 3) data mining and basic plotting functions (Signal), 4) topographic representation (Topo). We also included functions for page layout and export of paper-ready high-quality figure. Those modules come with a modular and powerful graphical user interfaces built with PyQt. Each module has been developed in collaboration with neuroscientists and experts in the field and provides a comprehensive set of functionalities. Visbrain is developed on top of VisPy [2], a Python package providing high performance 2D and 3D visualization by leveraging the computational power of the graphic card. This package is available on Github and comes with an extensive documentation, examples and datasets (see http://visbrain.org).

Published
2018

29. Visbrain: A Multi-Purpose GPU-Accelerated Open-Source Suite for Multimodal Brain Data Visualization

Author

Combrisson, Etienne, primary, Vallat, Raphael, additional, O'Reilly, Christian, additional, Jas, Mainak, additional, Pascarella, Annalisa, additional, Saive, Anne-lise, additional, Thiery, Thomas, additional, Meunier, David, additional, Altukhov, Dmitrii, additional, Lajnef, Tarek, additional, Ruby, Perrine, additional, Guillot, Aymeric, additional, and Jerbi, Karim, additional

Published
2019
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34. Direct Recordings from Human Anterior Insula Reveal its Leading Role within the Error-Monitoring Network

Author

Bastin, Julien, primary, Deman, Pierre, additional, David, Olivier, additional, Gueguen, Maëlle, additional, Benis, Damien, additional, Minotti, Lorella, additional, Hoffman, Dominique, additional, Combrisson, Etienne, additional, Kujala, Jan, additional, Perrone-Bertolotti, Marcela, additional, Kahane, Philippe, additional, Lachaux, Jean-Philippe, additional, and Jerbi, Karim, additional

Published
2016
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35. Decoding cognitive states and motor intentions from intracranial EEG: How promising is high-frequency brain activity for brain-machine interfaces?

Author

Jerbi, Karim, Combrisson, Etienne, Dalal, Sarang, Vidal, Juan, Hamame, Carlos, Bertrand, Olivier, Berthoz, Alain, Kahane, Philippe, Lachaux, Jean-Philippe, Centre de recherche en neurosciences de Lyon (CRNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Zukunftskolleg & Department of Psychology, University of Konstanz, Laboratoire de psychologie cognitive (LPC), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), Dynamique Cérébrale et Cognition, Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire de Physiologie de la Perception et de l'Action (LPPA), Collège de France (CdF (institution))-Centre National de la Recherche Scientifique (CNRS), INSERM U836, équipe 9, Dynamique des réseaux synchrones épileptiques, Grenoble Institut des Neurosciences (GIN), Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center (CRNL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), and Jerbi, Karim

Subjects
MESH: Humans, gamma band, intention decoding, [SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, [SDV.NEU.NB] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, real-time electrophysiology, [SDV.NEU.SC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive Sciences, Brain-computer Interfaces, MESH: Cognition, MESH: Neuropsychiatry, High frequency activity, MESH: Brain, MESH: Cognition Disorders, MESH: Epilepsy, intracranial electroencephalography, [SDV.NEU.SC] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive Sciences, electrocorticography, cognitive BCI
Abstract

International audience; We provide a brief overview of our recent research into decoding cognitive states and motor intentions from intracranial EEG using high-frequency brain activity for brain-machine interfaces. Appears in: Korczyn AD et al. Epilepsy, cognition, and neuropsychiatry (Epilepsy, Brain, and Mind, part 2), Epilepsy Behav (in press), doi: 10.1016/j.yebeh.2013.03.012

Published
2013

37. Meet Spinky: An Open-Source Spindle and K-Complex Detection Toolbox Validated on the Open-Access Montreal Archive of Sleep Studies (MASS).

Author

Lajnef, Tarek, O'Reilly, Christian, Combrisson, Etienne, Chaibi, Sahbi, Eichenlaub, Jean-Baptiste, Ruby, Perrine M., Aguera, Pierre-Emmanuel, Samet, Mounir, Kachouri, Abdennaceur, Frenette, Sonia, Carrier, Julie, and Jerbi, Karim

Subjects
SOMNOLOGY, ELECTROENCEPHALOGRAPHY, OPEN source software, WAVELET transforms, SLEEP disorders, PATIENTS
Abstract

Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencephalographic (EEG) recordings during sleep. These EEG microstructures are thought to be hallmarks of sleep-related cognitive processes. Although tedious and time-consuming, their identification and quantification is important for sleep studies in both healthy subjects and patients with sleep disorders. Therefore, procedures for automatic detection of spindles and K-complexes could provide valuable assistance to researchers and clinicians in the field. Recently, we proposed a framework for joint spindle and K-complex detection (Lajnef et al., 2015a) based on a Tunable Q-factor Wavelet Transform (TQWT; Selesnick, 2011a) and morphological component analysis (MCA). Using a wide range of performance metrics, the present article provides critical validation and benchmarking of the proposed approach by applying it to open-access EEG data from the Montreal Archive of Sleep Studies (MASS; O'Reilly et al., 2014). Importantly, the obtained scores were compared to alternative methods that were previously tested on the same database. With respect to spindle detection, our method achieved higher performance than most of the alternative methods. This was corroborated with statistic tests that took into account both sensitivity and precision (i.e., Matthew's coefficient of correlation (MCC), F1, Cohen k). Our proposed method has been made available to the community via an open-source tool named Spinky (for spindle and K-complex detection). Thanks to a GUI implementation and access to Matlab and Python resources, Spinky is expected to contribute to an open-science approach that will enhance replicability and reliable comparisons of classifier performances for the detection of sleep EEG microstructure in both healthy and patient populations. [ABSTRACT FROM AUTHOR]

Published
2017
Full Text
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38. Sleep: An Open-Source Python Software for Visualization, Analysis, and Staging of Sleep Data

Author

Combrisson, Etienne, Vallat, Raphael, Eichenlaub, Jean-Baptiste, O'Reilly, Christian, Lajnef, Tarek, Guillot, Aymeric, Ruby, Perrine, Jerbi, Karim, Centre de recherche en neurosciences de Lyon (CRNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Dynamique Cérébrale et Cognition, Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire scribens, École Polytechnique de Montréal (EPM), Université de Montréal (UdeM), Laboratoire Interuniversitaire de Biologie de la Motricité (LIBM ), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)

Subjects
opengl, hypnogram, [SDV]Life Sciences [q-bio], graphoelements, scoring, graphical user interface, Biomedical Engineering, Neuroscience (miscellaneous), automatic detection, Computer Science Applications, polysomnography, Methods, ComputingMilieux_MISCELLANEOUS, electroencephalography, Neuroscience
Abstract

We introduce Sleep, a new Python open-source graphical user interface (GUI) dedicated to visualization, scoring and analyses of sleep data. Among its most prominent features are: (1) Dynamic display of polysomnographic data, spectrogram, hypnogram and topographic maps with several customizable parameters, (2) Implementation of several automatic detection of sleep features such as spindles, K-complexes, slow waves, and rapid eye movements (REM), (3) Implementation of practical signal processing tools such as re-referencing or filtering, and (4) Display of main descriptive statistics including publication-ready tables and figures. The software package supports loading and reading raw EEG data from standard file formats such as European Data Format, in addition to a range of commercial data formats. Most importantly, Sleep is built on top of the VisPy library, which provides GPU-based fast and high-level visualization. As a result, it is capable of efficiently handling and displaying large sleep datasets. Sleep is freely available (http://visbrain. org/sleep) and comes with sample datasets and an extensive documentation. Novel functionalities will continue to be added and open-science community efforts are expected to enhance the capacities of this module.

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