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1. brainlife.io: a decentralized and open-source cloud platform to support neuroscience research

Author

Hayashi, Soichi, Caron, Bradley A., Heinsfeld, Anibal Sólon, Vinci-Booher, Sophia, McPherson, Brent, Bullock, Daniel N., Bertò, Giulia, Niso, Guiomar, Hanekamp, Sandra, Levitas, Daniel, Ray, Kimberly, MacKenzie, Anne, Avesani, Paolo, Kitchell, Lindsey, Leong, Josiah K., Nascimento-Silva, Filipi, Koudoro, Serge, Willis, Hanna, Jolly, Jasleen K., Pisner, Derek, Zuidema, Taylor R., Kurzawski, Jan W., Mikellidou, Kyriaki, Bussalb, Aurore, Chaumon, Maximilien, George, Nathalie, Rorden, Christopher, Victory, Conner, Bhatia, Dheeraj, Aydogan, Dogu Baran, Yeh, Fang-Cheng F., Delogu, Franco, Guaje, Javier, Veraart, Jelle, Fischer, Jeremy, Faskowitz, Joshua, Fabrega, Ricardo, Hunt, David, McKee, Shawn, Brown, Shawn T., Heyman, Stephanie, Iacovella, Vittorio, Mejia, Amanda F., Marinazzo, Daniele, Craddock, R. Cameron, Olivetti, Emanuale, Hanson, Jamie L., Garyfallidis, Eleftherios, Stanzione, Dan, Carson, James, Henschel, Robert, Hancock, David Y., Stewart, Craig A., Schnyer, David, Eke, Damian O., Poldrack, Russell A., Bollmann, Steffen, Stewart, Ashley, Bridge, Holly, Sani, Ilaria, Freiwald, Winrich A., Puce, Aina, Port, Nicholas L., and Pestilli, Franco

Published
2024
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2. Author Correction: brainlife.io: a decentralized and open-source cloud platform to support neuroscience research

Author

Hayashi, Soichi, Caron, Bradley A., Heinsfeld, Anibal Sólon, Vinci-Booher, Sophia, McPherson, Brent, Bullock, Daniel N., Bertò, Giulia, Niso, Guiomar, Hanekamp, Sandra, Levitas, Daniel, Ray, Kimberly, MacKenzie, Anne, Avesani, Paolo, Kitchell, Lindsey, Leong, Josiah K., Nascimento-Silva, Filipi, Koudoro, Serge, Willis, Hanna, Jolly, Jasleen K., Pisner, Derek, Zuidema, Taylor R., Kurzawski, Jan W., Mikellidou, Kyriaki, Bussalb, Aurore, Chaumon, Maximilien, George, Nathalie, Rorden, Christopher, Victory, Conner, Bhatia, Dheeraj, Aydogan, Dogu Baran, Yeh, Fang-Cheng F., Delogu, Franco, Guaje, Javier, Veraart, Jelle, Fischer, Jeremy, Faskowitz, Joshua, Fabrega, Ricardo, Hunt, David, McKee, Shawn, Brown, Shawn T., Heyman, Stephanie, Iacovella, Vittorio, Mejia, Amanda F., Marinazzo, Daniele, Craddock, R. Cameron, Olivetti, Emanuale, Hanson, Jamie L., Garyfallidis, Eleftherios, Stanzione, Dan, Carson, James, Henschel, Robert, Hancock, David Y., Stewart, Craig A., Schnyer, David, Eke, Damian O., Poldrack, Russell A., Bollmann, Steffen, Stewart, Ashley, Bridge, Holly, Sani, Ilaria, Freiwald, Winrich A., Puce, Aina, Port, Nicholas L., and Pestilli, Franco

Published
2024
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5. Further characterisation of late somatosensory evoked potentials using electroencephalogram and magnetoencephalogram source imaging.

Author

Hssain‐Khalladi, Sahar, Giron, Alain, Huneau, Clément, Gitton, Christophe, Schwartz, Denis, George, Nathalie, Le Van Quyen, Michel, Marrelec, Guillaume, and Marchand‐Pauvert, Véronique

Subjects
SOMATOSENSORY evoked potentials, ELECTROENCEPHALOGRAPHY, SOMATOSENSORY cortex, MAGNETIC resonance imaging, ELECTRIC stimulation, WRIST, MEDIAN nerve, TRANSCRANIAL magnetic stimulation
Abstract

Beside the well‐documented involvement of secondary somatosensory area, the cortical network underlying late somatosensory evoked potentials (P60/N60 and P100/N100) is still unknown. Electroencephalogram and magnetoencephalogram source imaging were performed to further investigate the origin of the brain cortical areas involved in late somatosensory evoked potentials, using sensory inputs of different strengths and by testing the correlation between cortical sources. Simultaneous high‐density electroencephalograms and magnetoencephalograms were performed in 19 participants, and electrical stimulation was applied to the median nerve (wrist level) at intensity between 1.5 and 9 times the perceptual threshold. Source imaging was undertaken to map the stimulus‐induced brain cortical activity according to each individual brain magnetic resonance imaging, during three windows of analysis covering early and late somatosensory evoked potentials. Results for P60/N60 and P100/N100 were compared with those for P20/N20 (early response). According to literature, maximal activity during P20/N20 was found in central sulcus contralateral to stimulation site. During P60/N60 and P100/N100, activity was observed in contralateral primary sensorimotor area, secondary somatosensory area (on both hemispheres) and premotor and multisensory associative cortices. Late responses exhibited similar characteristics but different from P20/N20, and no significant correlation was found between early and late generated activities. Specific clusters of cortical activities were activated with specific input/output relationships underlying early and late somatosensory evoked potentials. Cortical networks, partly common to and distinct from early somatosensory responses, contribute to late responses, all participating in the complex somatosensory brain processing. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Resting-state posterior alpha rhythms are abnormal in subjective memory complaint seniors with preclinical Alzheimer's neuropathology and high education level: the INSIGHT-preAD study

Author

Babiloni, Claudio, Lopez, Susanna, Del Percio, Claudio, Noce, Giuseppe, Pascarelli, Maria Teresa, Lizio, Roberta, Teipel, Stefan J., González-Escamilla, Gabriel, Bakardjian, Hovagim, George, Nathalie, Cavedo, Enrica, Lista, Simone, Chiesa, Patrizia Andrea, Vergallo, Andrea, Lemercier, Pablo, Spinelli, Giuseppe, Grothe, Michel J., Potier, Marie-Claude, Stocchi, Fabrizio, Ferri, Raffaele, Habert, Marie-Odile, Fraga, Francisco J., Dubois, Bruno, and Hampel, Harald

Published
2020
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14. The Memory Binding Test Detects Early Subtle Episodic Memory Decline in Preclinical Alzheimer's Disease: A Longitudinal Study.

Author

Rapos Pereira, Filipa, George, Nathalie, Dalla Barba, Gianfranco, Dubois, Bruno, and La Corte, Valentina

Subjects
*ALZHEIMER'S disease, *EPISODIC memory, *MEMORY testing, *RECOLLECTION (Psychology), *LAND title registration & transfer
Abstract

Background: The asymptomatic at-risk phase might be the optimal time-window to establish clinically meaningful endpoints in Alzheimer's disease (AD). Objective: We investigated whether, compared with the Free and Cued Selective Reminding Test (FCSRT), the Memory Binding Test (MBT) can anticipate the diagnosis of emergent subtle episodic memory (EM) deficits to an at-risk phase. Methods: Five-year longitudinal FCSRT and MBT scores from 45 individuals matched for age, education, and gender, were divided into 3 groups of 15 subjects: Aβ-/controls, Aβ+/stable, and Aβ+/progressors (preclinical-AD). The MBT adds an associative memory component (binding), particularly sensitive to subtle EM decline. Results: In the MBT, EM decline started in the Aβ+/progressors (preclinical-AD) up to 4 years prior to diagnosis in delayed free recall (FR), followed by decline in binding-associated scores 1 year later. Conversely, in the FCSRT, EM-decline began later, up to 3 years prior to diagnosis, in the same group on both immediate and delayed versions of FR, while on total recall (TR) and intrusions decline started only 1 year prior to diagnosis. Conclusions: The MBT seems more sensitive than the FCSRT for early EM-decline detection, regarding the year of diagnosis and the number of scores showing AD-linked EM deficits (associated with the AD-characteristic amnesic hippocampal syndrome). Considering the MBT as a detection tool of early subtle EM-decline in an asymptomatic at-risk phase, and the FCSRT as a classification tool of stages of EM-decline from a preclinical phase, these tests ought to potentially become complementary diagnostic tools that can foster therapies to delay cognitive decline. Clinical trial registration title: Electrophysiological markers of the progression to clinical Alzheimer disease in asymptomatic at-risk individuals: a longitudinal event-related potential study of episodic memory in the INSIGHT pre-AD cohort (acronym: ePARAD). [ABSTRACT FROM AUTHOR]

Published
2024
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15. Time course of EEG power during creative problem‐solving with insight or remote thinking.

Author

Bieth, Théophile, Ovando‐Tellez, Marcela, Lopez‐Persem, Alizée, Garcin, Béatrice, Hugueville, Laurent, Lehongre, Katia, Levy, Richard, George, Nathalie, and Volle, Emmanuelle

Subjects
PROBLEM solving, ELECTROENCEPHALOGRAPHY, LEXICAL access, WORD recognition
Abstract

Problem‐solving often requires creativity and is critical in everyday life. However, the neurocognitive mechanisms underlying creative problem‐solving remain poorly understood. Two mechanisms have been highlighted: the formation of new connections among problem elements and insight solving, characterized by sudden realization of a solution. In this study, we investigated EEG activity during a modified version of the remote associates test, a classical insight problem task that requires finding a word connecting three unrelated words. This allowed us to explore the brain correlates associated with the semantic remoteness of connections (by varying the remoteness of the solution word across trials) and with insight solving (identified as a Eurêka moment reported by the participants). Semantic remoteness was associated with power increase in the alpha band (8–12 Hz) in a left parieto‐temporal cluster, the beta band (13–30 Hz) in a right fronto‐temporal cluster in the early phase of the task, and the theta band (3–7 Hz) in a bilateral frontal cluster just prior to participants' responses. Insight solving was associated with power increase preceding participants' responses in the alpha and gamma (31–60 Hz) bands in a left temporal cluster and the theta band in a frontal cluster. Source reconstructions revealed the brain regions associated with these clusters. Overall, our findings shed new light on some of the mechanisms involved in creative problem‐solving. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Sex differences in functional and molecular neuroimaging biomarkers of Alzheimer's disease in cognitively normal older adults with subjective memory complaints

Author

Bakardjian, Hovagim, Benali, Habib, Bertin, Hugo, Bonheur, Joel, Boukadida, Laurie, Boukerrou, Nadia, Cavedo, Enrica, Chiesa, Patrizia, Colliot, Olivier, Dubois, Bruno, Dubois, Marion, Epelbaum, Stéphane, Gagliardi, Geoffroy, Genthon, Remy, Habert, Marie-Odile, Hampel, Harald, Houot, Marion, Kas, Aurélie, Lamari, Foudil, Levy, Marcel, Lista, Simone, Metzinger, Christiane, Mochel, Fanny, Nyasse, Francis, Poisson, Catherine, Potier, Marie-Claude, Revillon, Marie, Santos, Antonio, Andrade, Katia Santos, Sole, Marine, Surtee, Mohmed, de Schotten, Michel Thiebaud, Vergallo, Andrea, Younsi, Nadjia, Aguilar, Lisi Flores, Babiloni, Claudio, Baldacci, Filippo, Benda, Norbert, Black, Keith L., Bokde, Arun L.W., Bonuccelli, Ubaldo, Broich, Karl, Bun, René S., Cacciola, Francesco, Castrillo, Juan, Ceravolo, Roberto, Chiesa, Patrizia A., Coman, Cristina-Maria, Corvol, Jean-Christophe, Cuello, Augusto Claudio, Cummings, Jeffrey L., Depypere, Herman, Duggento, Andrea, Durrleman, Stanley, Escott-Price, Valentina, Federoff, Howard, Ferretti, Maria Teresa, Fiandaca, Massimo, Frank, Richard A., Garaci, Francesco, George, Nathalie, Giorgi, Filippo S., Graziani, Manuela, Haberkamp, Marion, Herholz, Karl, Karran, Eric, Kim, Seung H., Koronyo, Yosef, Koronyo-Hamaoui, Maya, Langevin, Todd, Lehéricy, Stéphane, Lorenceau, Jean, Mapstone, Mark, Neri, Christian, Nisticò, Robert, Nyasse-Messene, Francis, O'bryant, Sid E., Perry, George, Ritchie, Craig, Rojkova, Katrine, Rossi, Simone, Saidi, Amira, Santarnecchi, Emiliano, Schneider, Lon S., Sporns, Olaf, Toschi, Nicola, Verdooner, Steven R., Villain, Nicolas, Welikovitch, Lindsay A., Woodcock, Janet, Younesi, Erfan, Grothe, Michel J., and Teipel, Stefan J.

Published
2018
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21. Using critical dynamics to capture processes underlying Brain-Computer Interface performance

Author

Corsi, Marie-Constance, Sorrentino, Pierpaolo, Schwartz, Denis P, George, Nathalie, Hugueville, Laurent, Kahn, Ari, Dupont, Sophie, Bassett, Danielle, Jirsa, Viktor, de Vico Fallani, Fabrizio, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), University of Pennsylvania, and Société des Neurosciences

Subjects
[SCCO.NEUR]Cognitive science/Neuroscience, [NLIN]Nonlinear Sciences [physics]
Abstract

International audience; Despite being a promising tool for establishing direct communication and control from the brain over external effectors, non-invasive Brain-computer interface (BCI) systems yield suboptimal performance in ~30% of users. Measuring the dynamical features that are relevant to the execution of a task to improve BCI performance remains an open challenge. Functional imaging is dominated by aperiodic and scale-free perturbations called “Neuronal Avalanches”, spreading across the whole brain. The sequence of regions recruited by avalanches could convey the processes underpinning BCI performance. To test our hypothesis, we used source-reconstructed magnetoencephalography signals in a BCI framework, where 20 healthy subjects were compared in resting-state and while performing a motor imagery (MI) task, in order to track the dynamical features related to motor imagery. Each signal was z-scored over time. For each condition, we estimated the avalanche transition matrix (ATM), containing the probability that regions j would be active at time t+1, given region i was active at time t. We computed the difference between the ATMs obtained from the two conditions in each subject, and validated them via permutation analysis. Then, we correlated the difference of the probabilities to BCI performance. All the significantly different edges cluster upon the premotor areas, involved during the MI task, and the cunei, involved during visual processing. The differences in the probabilities associated with edges incident upon areas such as the right paracentral lobule and the caudal middle frontal bilaterally directly correlate with the BCI scores. Our results suggest that avalanches capture functionally-relevant processes which are of interest for alternative BCI designing. Future work will consist of investigating the use of avalanche transition matrices as potential alternative features for classification in BCI.

Published
2023

22. Informing motor imagery-based brain-computer interface via neuronal avalanches

Author

Sorrentino, Pierpaolo, Corsi, Marie-Constance, Schwartz, Denis P, George, Nathalie, Kahn, Ari, Dupont, Sophie, Bassett, Danielle, de Vico Fallani, Fabrizio, Jirsa, Viktor, Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), University of Pennsylvania, The authors acknowledge support from European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No. 864729), from the program 'Investissements d’avenir' ANR-10-IAIHU-06, from European Union’s Horizon 2020 research and innovation programme under grant agreement No. 945539 (SGA3) Human Brain Project, and from VirtualBrainCloud No.826421., ANR-10-IAHU-0006,IHU-A-ICM,Institut de Neurosciences Translationnelles de Paris(2010), European Project: 945539,H2020,H2020-SGA-FETFLAG-HBP-2019,HBP SGA3(2020), European Project: 826421,TVB-Cloud (2018), and European Project: 864729,H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC),BCINET(2020)

Subjects
[SCCO.NEUR]Cognitive science/Neuroscience, [NLIN]Nonlinear Sciences [physics]
Abstract

International audience; Brain-Computer Interfaces (BCIs) constitute a promising tool for communication and control. However, mastering non-invasive BCI systems remains a learned skill difficult to develop for a non-negligible proportion of users. Even though similarities have been shown between MI-based BCI learning and motor sequence learning our understanding of the dynamical processes, and their reflection on brain signals during BCI performance is still incomplete. In particular, whole-brain functional imaging is dominated by a 'bursty' dynamics, "neuronal avalanches", with fast, fat-tailed distributed, aperiodic perturbations spreading across the whole brain. Neuronal avalanches evolve over a manifold during resting-state, generating a rich functional connectivity dynamics. In this work, we evaluated to which extent neuronal avalanches can be used as a tool to differentiate mental states in the context of BCI experiments.

Published
2023

27. A neuroscientific approach to increase gender equality

Author

Schreiweis, Christiane, Volle, Emmanuelle, Durr, Alexandra, Auffret, Alexandra, Delarasse, Cécile, George, Nathalie, Dumont, Magali, Hassan, Bassem A., Renier, Nicolas, Rosso, Charlotte, Thiebaut de Schotten, Michel, Burguière, Eric, and Zujovic, Violetta

Published
2019
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28. Exploiting brain critical dynamics to inform Brain-Computer Interfaces performance

Author

Corsi, Marie-Constance, Sorrentino, Pierpaolo, Schwartz, Denis P, George, Nathalie, Hugueville, Laurent, Kahn, Ari, Dupont, Sophie, Bassett, Danielle, Jirsa, Viktor, de Vico Fallani, Fabrizio, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Pennsylvania, European Project: 826421,TVB-Cloud (2018), European Project: 945539,H2020,H2020-SGA-FETFLAG-HBP-2019,HBP SGA3(2020), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), and University of Pennsylvania [Philadelphia]

Subjects
[SCCO]Cognitive science, [INFO]Computer Science [cs], [MATH]Mathematics [math], ComputingMilieux_MISCELLANEOUS
Abstract

International audience; The reconfiguration of large-scale interactions among multiple brain regions is characterized by aperiodic perturbations, called “Neuronal Avalanches”, which can be tracked non-invasively as they expand across the brain. As such, learning a new task might affect the path of propagation of neuronal avalanches. Brain-Computer Interfaces (BCIs) constitute a promising tool for establishing direct communication and control from the brain over external effectors but mastering them remains a poorly-understood learned skill. Therefore, neuronal avalanche measures may constitute natural candidates to inform the underlying brain processes and their reflection on brain signals. To test this hypothesis, we used source-reconstructed magneto/electroencephalography, comparing resting-state to motor imagery conditions during a BCI protocol. For each experimental condition, we computed an individual avalanche transition matrix, to track the probability that an avalanche would spread across any two regions. We found a robust topography of the edges that were affected by the execution of the task, which mainly hinge upon the premotor regions. Finally, we related the individual differences to the task performance, showing that significant correlations are predominantly positive and involve edges connecting pre/motor regions to parietal ones. Our findings suggest that avalanches capture functionally-relevant processes crucial for alternative BCI designing.

Published
2022

30. Functional connectivity predicts MI-based BCI learning

Author

Corsi, Marie-Constance, Chavez, Mario, Schwartz, Denis, George, Nathalie, Hugueville, Laurent, Kahn, Ari E., Dupont, Sophie, Bassett, Danielle, de Vico Fallani, Fabrizio, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), University of Pennsylvania, This work was partially supported by the program 'Investissements d'avenir' ANR-10-IAIHU-06, 'ANR-NIH CRCNS' ANR-15-NEUC-0006-02 and by NICHD 1R01HD086888-01, ANR-10-IAHU-0006,IHU-A-ICM,Institut de Neurosciences Translationnelles de Paris(2010), ANR-15-NEUC-0006,NETBCI,US-France Research Proposal- Modeling and Predicting Brain-Computer Interface Learning from Dynamic Networks(2015), Corsi, Marie-Constance, Institut de Neurosciences Translationnelles de Paris - - IHU-A-ICM2010 - ANR-10-IAHU-0006 - IAHU - VALID, and US-France Research Proposal- Modeling and Predicting Brain-Computer Interface Learning from Dynamic Networks - - NETBCI2015 - ANR-15-NEUC-0006 - CRCNS - VALID

Subjects
[SDV] Life Sciences [q-bio], [SPI]Engineering Sciences [physics], [SPI] Engineering Sciences [physics], [SDV]Life Sciences [q-bio], [MATH] Mathematics [math], [MATH]Mathematics [math]
Abstract

International audience; Non-invasive Brain-Computer Interfaces (BCIs) can exploit the ability of subjects to voluntary modulate their brain activity through mental imagery. Despite its clinical applications, controlling a BCI appears to be a learned skill that requires several weeks to reach relatively high-performance in control, without being sufficient for 15 to 30 % of the users. This gap has motivated a deeper understanding of mechanisms associated with motor imagery (MI) tasks. Here, we investigated dynamical changes in terms of cortical activations and network recruitment. We hypothesized that the associated characteristics would be able to predict the success of learning.

Published
2022

31. Exploiting brain critical dynamics to inform Brain-Computer Interfaces

Author

Sorrentino, Pierpaolo, Corsi, Marie-Constance, Schwartz, Denis P, George, Nathalie, Hugueville, Laurent, Kahn, Ari, Dupont, Sophie, Bassett, Danielle, de Vico Fallani, Fabrizio, Jirsa, Viktor, Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), University of Pennsylvania, European Project: 864729,H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC),BCINET(2020), European Project: 826421,TVB-Cloud (2018), European Project: 945539,H2020,H2020-SGA-FETFLAG-HBP-2019,HBP SGA3(2020), Corsi, Marie-Constance, Non-invasive decoding of brain communication patterns to ease motor restoration after stroke - BCINET - - H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)2020-10-01 - 2025-09-30 - 864729 - VALID, VirtualBrainCloud - TVB-Cloud - 2018-12-01 - 2022-11-30 - 826421 - VALID, and Human Brain Project Specific Grant Agreement 3 - HBP SGA3 - - H20202020-01-01 - 2023-09-30 - 945539 - VALID

Subjects
[SCCO]Cognitive science, [INFO]Computer Science [cs], [MATH] Mathematics [math], [SCCO] Cognitive science, [MATH]Mathematics [math], [INFO] Computer Science [cs]
Abstract

International audience; Brain-Computer Interfaces (BCIs) constitute a promising tool for communication and control. However, mastering non-invasive BCI systems remains a learned skill difficult to develop for a non-negligible proportion of users. Even though similarities have been shown between MI-based BCI learning and motor sequence learning our understanding of the dynamical processes, and their reflection on brain signals during BCI performance is still incomplete. In particular, whole-brain functional imaging is dominated by a ‘bursty’ dynamics, “neuronal avalanches”, with fast, fat-tailed distributed, aperiodic perturbations spreading across the whole brain. Neuronal avalanches evolve over a manifold during resting-state, generating a rich functionalconnectivity dynamics. In this work, we evaluated to which extent neuronal avalanches can be used as a tool to differentiate mental states in the context of BCI experiments.

Published
2022

32. M/EEG networks integration to elicit patters of motor imagery-based Brain-Computer Interface (BCI) training

Author

Corsi, Marie-Constance, Chavez, Mario, Schwartz, Denis P, George, Nathalie, Hugueville, Laurent, Kahn, Ari, Dupont, Sophie, Bassett, Danielle, de Vico Fallani, Fabrizio, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), University of Pennsylvania, This work was partially supported by the program 'Investissements d'avenir' ANR-10-IAIHU-06, 'ANR-NIH CRCNS' ANR-15-NEUC-0006-02 and by NICHD 1R01HD086888-01., ANR-15-NEUC-0006,NETBCI,US-France Research Proposal- Modeling and Predicting Brain-Computer Interface Learning from Dynamic Networks(2015), ANR-10-IAHU-0006,IHU-A-ICM,Institut de Neurosciences Translationnelles de Paris(2010), Corsi, Marie-Constance, US-France Research Proposal- Modeling and Predicting Brain-Computer Interface Learning from Dynamic Networks - - NETBCI2015 - ANR-15-NEUC-0006 - CRCNS - VALID, and Institut de Neurosciences Translationnelles de Paris - - IHU-A-ICM2010 - ANR-10-IAHU-0006 - IAHU - VALID

Subjects
[SCCO]Cognitive science, [INFO]Computer Science [cs], [MATH] Mathematics [math], [SCCO] Cognitive science, [INFO] Computer Science [cs], [MATH]Mathematics [math]
Abstract

International audience; Non-invasive Brain-Computer Interfaces (BCIs) can exploit the ability of subjects to voluntary modulate their brain activity through mental imagery. Despite its clinical applications, controlling a BCI appears to be a learned skill that requires several weeks to reach relatively high-performance in control, without being sufficient for 15 to 30 % of the users [1]. This gap has motivated a deeper understanding of mechanisms associated with motor imagery (MI) tasks. Here, we investigated dynamical changes in multimodal network recruitment. We hypothesized that integrating information from EEG and MEG data, show a better description of the core-periphery changes occurring during a motor imagery-based BCI training. Such an enriched description could reveal fresh insights into learning processes that are difficult to observe at the signle layer level and eventually improve the prediction of future BCI performance.multimodal brain network properties could be considered as a potential marker of BCI learning.

Published
2022

33. M/EEG networks integration to elicit patterns of motor imagery-based BCI training

Author

Corsi, Marie-Constance, Chavez, Mario, Schwartz, Denis P, George, Nathalie, Hugueville, Laurent, Kahn, Ari, Dupont, Sophie, Bassett, Danielle, de Vico Fallani, Fabrizio, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), University of Pennsylvania, This work was partially supported by the program 'Investissements d'avenir' ANR-10-IAIHU-06, 'ANR-NIH CRCNS' ANR-15-NEUC-0006-02 and by NICHD 1R01HD086888-01., ANR-15-NEUC-0006,NETBCI,US-France Research Proposal- Modeling and Predicting Brain-Computer Interface Learning from Dynamic Networks(2015), Corsi, Marie-Constance, and US-France Research Proposal- Modeling and Predicting Brain-Computer Interface Learning from Dynamic Networks - - NETBCI2015 - ANR-15-NEUC-0006 - CRCNS - VALID

Subjects
[SCCO]Cognitive science, [INFO]Computer Science [cs], [MATH] Mathematics [math], [SCCO] Cognitive science, [INFO] Computer Science [cs], [MATH]Mathematics [math]
Abstract

International audience; Non-invasive Brain-Computer Interfaces (BCIs) can exploit the ability of subjects to voluntary modulate their brain activity through mental imagery. Despite its clinical applications, controlling a BCI appears to be a learned skill that requires several weeks to reach relatively high-performance in control, without being sufficient for 15 to 30 % of the users [1]. This gap has motivated a deeper understanding of mechanisms associated with motor imagery (MI) tasks. Here, we investigated dynamical changes in multimodal network recruitment. We hypothesized that integrating information from EEG and MEG data, show a better description of the core-periphery changes occurring during a motor imagery-based BCI training. Such an enriched description could reveal fresh insights into learning processes that are difficult to observe at the signle layer level and eventually improve the prediction of future BCI performance.multimodal brain network properties could be considered as a potential marker of BCI learning.

Published
2022

35. The Memory Binding Test: a new tool to assess emerging episodic memory decline in asymptomatic at‐risk individuals to Alzheimer's disease.

Author

Pereira, Filipa Raposo, George, Nathalie, Barba, Gianfranco Dalla, Dubois, Bruno, and La Corte, Valentina

Abstract

Background: Episodic memory (EM) deficits are a hallmark of Alzheimer's disease (AD). The Free and Cued Selective Reminding Test (FCSRT) is the most specific official diagnostic tool detecting AD‐linked EM alterations in advanced preclinical stages (Grober et al., 2021). However, new tools that anticipate diagnosis to the at‐risk phase are needed, to reach more meaningful therapies. Based on existing research, we aim to investigate the Memory Binding Test (MBT) promising capacity to detect the appearance of subtle AD‐linked EM alterations and anticipate AD‐diagnosis to an at‐risk phase (Bushcke ey al., 2017; Mowrey et al., 2018). Methods: FCSRT and MBT scores were collected yearly during 5 years from the INSIGHT‐preAD cohort. We selected 3 groups controlled for age, education level, gender, beta‐amyloid burden (AB+), and neurodegeneration status based on 15 individuals who converted to prodromal‐AD during follow‐up, as follows: converters/AB+; non‐converters/AB+; controls/AB‐. Evaluation of both list‐learning tests is mainly based on free recall (FR) and total (cued) recall (TR) scores. The FCSRT uses 1‐list of words to remember while the MBT uses 2‐lists, introducing a binding component sensitive to subtle EM alterations. Data was analysed using mixed effect models including age, gender, and education as covariates. Results: When compared with the FCSRT, the MBT anticipated the detection of AD‐linked EM alterations in the converters/AB+ versus the other groups. In the MBT decline started up to 5 years prior to diagnosis, in delayed FR (mainly associated to executive dysfunction), followed by decline in 4 binding‐associated scores 1 year later (linked to storage deficits associated with the amnesic hippocampal syndrome characteristic of AD). Therefore, at an at‐risk phase, MBT outperformed FCSRT, both in the year of diagnosis and in the number of scores confirming AD‐linked EM deficits. Conclusion: We show the MBT capacity to detect the initial subtle EM alterations and to anticipate diagnosis to the at‐risk phase, while participants remain cognitively normal. We argue that the MBT (at‐risk phase detection) and the FCSRT (preclinical phase classification) could be complementary rather than concurrent tools, fostering meaningful innovative treatments to prolong quality of life in AD, a disease that remains without a cure. [ABSTRACT FROM AUTHOR]

Published
2023
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36. Salient Social Cues Are Prioritized in Autism Spectrum Disorders Despite Overall Decrease in Social Attention

Author

Chevallier, Coralie, Huguet, Pascal, Happé, Francesca, George, Nathalie, and Conty, Laurence

Abstract

Diminished social attention is often considered to be a central deficit in autism spectrum disorders (ASDs). We further investigate this hypothesis by measuring the distracting power of social and non-social stimuli in the context of a Stroop task among children with ASD and typically developing controls (TDCs). Our results show that Stroop interference increases with social versus non-social distracters in TDCs, whereas the opposite pattern occurs in ASD. Within social stimuli, however, the superiority of direct gaze previously reported in the literature did not differ between the groups. Our data thus suggest that ASD children assign less weight to social than non-social stimuli, but that within social signals, salient stimuli remain prioritized.

Published
2013
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37. The Role of Facial Expressions in Attention-Orienting in Adults and Infants

Author

Rigato, Silvia, Menon, Enrica, Di Gangi, Valentina, George, Nathalie, and Farroni, Teresa

Abstract

Faces convey many signals (i.e., gaze or expressions) essential for interpersonal interaction. We have previously shown that facial expressions of emotion and gaze direction are processed and integrated in specific combinations early in life. These findings open a number of developmental questions and specifically in this paper we address whether such emotional signals may modulate the behavior in a following gaze context. A classic spatial cueing paradigm was used to assess whether different facial expressions may cause differential orienting response times and modulate the visual response to a peripheral target in adults and in 4-month-old infants. Results showed that both adults and infants oriented towards a peripheral target when a central face was gazing in the direction of the target location. However, in adults this effect occurred regardless of the facial expression displayed by the face. In contrast, in infants, the emotional facial expressions used, at least in the current study, did not facilitate the attention shift but tended to hold infants' attention. (Contains 2 tables and 2 figures.)

Published
2013
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38. Neuronal avalanches differentiate resting-state and task conditions in Brain-Computer Interfaces

Author

Corsi, Marie-Constance, Sorrentino, Pierpaolo, Schwartz, Denis P, George, Nathalie, Hugueville, Laurent, Kahn, Ari, Dupont, Sophie, Bassett, Danielle, Jirsa, Viktor, de Vico Fallani, Fabrizio, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Princeton Neuroscience Institute [Princeton], University of Pennsylvania [Philadelphia], Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and University of Pennsylvania

Subjects
[SCCO]Cognitive science, [INFO]Computer Science [cs], [MATH]Mathematics [math], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2022

39. Unveiling the role of beta activity in motor motivation: an EEG study of effort using neurofeedback and pupillometry

Author

Pierrieau, Emeline, Pillette, Léa, Dussard, Claire, George, Nathalie, Jeunet, Camille, Institut de Neurosciences cognitives et intégratives d'Aquitaine (INCIA), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-SFR Bordeaux Neurosciences-Centre National de la Recherche Scientifique (CNRS), 3D interaction with virtual environments using body and mind (Hybrid), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-RÉALITÉ VIRTUELLE, HUMAINS VIRTUELS, INTERACTIONS ET ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SCCO.NEUR]Cognitive science/Neuroscience, [SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, Effort, Beta power, EEG, Neurofeedback, Motor vigor
Abstract

International audience; A progressive desynchronization of beta-band power (β-desync; 13-30 Hz) has been consistently observed before movement initiation. Although mounting evidence demonstrate a significant relationship between this β-desync and subsequent motor vigor, a neurophysiological foundation to explain this finding is still lacking. In the present study, we proposed that this association might come from changes in motor motivation and perceived effort. This hypothesis will be tested by recording the signal from electroencephalography and using it as neurofeedback to decrease or increase β-desync in two distinct sessions, in an intra-subject and double-blinded design. First, participants will be screened based on their ability to up- and down-regulate their β-desync. The selected participants will then perform the experimental test, in which each trial comprised a neurofeedback phase directly followed by an effort phase. The effort will consist in squeezing a dynamometer with the right hand during an allocated time of 10 seconds. Participants will be asked to apply enough force to cross a defined threshold, and that the more time the exerted force would exceed the threshold, the more money they would earn. Subjective perception of effort will be evaluated afterwards using an analog scale. Because effort exertion is associated with increased pupil dilation, which is itself modulated by noradrenergic activity, we will further investigate the influence of noradrenergic activity on changes in β-desync due to neurofeedback and effort exertion. Besides the contribution to unraveling the neurophysiological and functional bases of beta activity, the present work is of special interest to the study of Parkinson’s disease by helping to better understand the association between beta activity and motor symptoms.

Published
2022

40. Can feedback transparency improve Motor-Imagery BCI performance?

Author

Dussard, Claire, Pillette, Léa, Jeunet, Camille, George, Nathalie, Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France, Institut de Neurosciences cognitives et intégratives d'Aquitaine (INCIA), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-SFR Bordeaux Neurosciences-Centre National de la Recherche Scientifique (CNRS), and Dussard, Claire

Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, feedback transparency, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, agency, neurofeedback, [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], [INFO.INFO-HC] Computer Science [cs]/Human-Computer Interaction [cs.HC], embodiment
Abstract

International audience; Motor Imagery-based BCI (MI-BCI) performances remain highly variable, with up to 30% of users unable to achieve control. Operating a BCI system requires users to learn to modulate their neural activity. This is a complex task, thus the training procedure is crucial. Our study draws on task-feedback transparency to improve the feedback given during training. MI-BCI protocols often feature abstract feedback (e.g., visual gauge) unrelated to the imagined movement. Transparent feedback, directly related to the task, may reinforce agency-the ability to self-attribute actions, such as feedback movements-and embodiment, facilitating kinesthetic MI. This could lessen complexity in BCI control and ultimately improve BCI performance.We tested this hypothesis in a beta-based MI neurofeedback task with electroencephalography (EEG). Twenty-three subjects participated in a single MIneurofeedback session that consisted in imagining clenching their right hand rhythmically. Feedback was based on online laplacian-filtered 8-30Hz power on C3 electrode computed with OpenViBE. There were 3 feedback conditions of expected increasing transparency: pendulum; virtual hand; virtual hand with additional motor illusion induced by vibrations to the participant's hand. The amplitude of the pendulum and virtual hand movements was proportional to beta desynchronisation. Each participant performed two runs of five 24s-trials per condition. Agency, embodiment, and user experience questionnaires were included. Repeated-measures ANOVA showed better BCI performance when using the virtual hand than the pendulum. However, participants had lower performance in the visuotactile condition compared to the virtual hand-only feedback. Agency showed a similar pattern.Feeling of success in the task did not vary with feedback conditions, but the virtual hand feedback felt easier to use. BCI performance correlated positively with agency for all conditions and with embodiment in conditions with a virtual hand.Thus, visual transparency—but not tactile feedback addition—increased BCI performance and this was associated with better agency and embodiment.

Published
2022

41. Are Brain-Computer Interfaces and Neurofeedback acceptable?

Author

Pillette, Léa, Grevet, Elise, Dussard, Claire, Amadieu, Franck, Gasq, David, Pierrieau, Emeline, Py, Jacques, Si-Mohammed, Hakim, George, Nathalie, Jeunet, Camille, Pillette, Léa, Institut de Neurosciences cognitives et intégratives d'Aquitaine (INCIA), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-SFR Bordeaux Neurosciences-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Cognition, Langues, Langage, Ergonomie (CLLE), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Toulouse - Jean Jaurès (UT2J)-Centre National de la Recherche Scientifique (CNRS), INSERM, Univ. Toulouse 3, Université de Sherbrooke (UdeS), Université Toulouse - Jean Jaurès (UT2J), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-SFR Bordeaux Neurosciences-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Toulouse Mind & Brain Institut (TMBI), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT), and Université Toulouse III - Paul Sabatier (UT3)

Subjects
[SCCO]Cognitive science, Acceptability, Brain-Computer Interfaces, [SCCO] Cognitive science, Neurofeedback
Abstract

International audience; The adoption of a technology can be defined as the decision made by a person or a society to accept and use it. It is based on two phases during which the willingness to use that technology is assessed. The first phase corresponds to the evaluation of the acceptability of the technology and takes place before the use while the second phase, the technology acceptance, comes afterwards. Assessing the acceptability of BCIs/NF is of utmost importance as it could provide i) insights on the propensity of people to use these technologies and ii) leads to facilitate their adoption.We reviewed the literature dealing with the acceptability of BCIs/NF and using validated questionnaires and models. Through a reproducible search method, we retrieved a list of 55 main references of acceptability questionnaires and models. Then, we searched Scopus, PubMed, and Web of Science to identify the articles in the fields of BCIs/NF that cited these references. We included in our review all the articles reporting experimental results on the acceptability of BCIs/NF that were based on one or several validated acceptability questionnaire(s).Four articles were included in our review. Two of them assessed the acceptability while the others assessed the acceptance of the BCIs. While there are too few articles included to conclude on the acceptability of those technologies, the results are encouraging. BCIs were perceived as useful at 78% by motor impaired individuals who used BCIs for pain management and at 84% by neurotypical individuals who used BCIs to browse an instruction manual. The perceived ease of use varied from 30% to 80%, which could be related to differences in the protocols. Among other factors, the presence of social support appeared to influence the acceptability.

Published
2022

47. Theta Band-Power Shapes Amyloid-Driven Longitudinal EEG Changes in Elderly Subjective Memory Complainers At-Risk for Alzheimer's Disease.

Author

Spinelli, Giuseppe, Bakardjian, Hovagim, Schwartz, Denis, Potier, Marie-Claude, Habert, Marie-Odile, Levy, Marcel, Dubois, Bruno, George, Nathalie, and INSIGHT-preAD study group

Subjects
PROTEIN metabolism, BRAIN, PROTEINS, ALZHEIMER'S disease, AMYLOIDOSIS, ELECTROENCEPHALOGRAPHY, MAGNETIC resonance imaging, IMPACT of Event Scale, EMISSION-computed tomography
Abstract

Background: Alzheimer's disease (AD) includes progressive symptoms spread along a continuum of preclinical and clinical stages. Although numerous studies uncovered the neuro-cognitive changes of AD, very little is known on the natural history of brain lesions and modifications of brain networks in elderly cognitively-healthy memory complainers at risk of AD for carrying pathophysiological biomarkers (amyloidopathy and tauopathy).Objective: We analyzed resting-state electroencephalography (EEG) of 318 cognitively-healthy subjective memory complainers from the INSIGHT-preAD cohort at the time of their first visit (M0) and two-years later (M24).Methods: Using 18F-florbetapir PET-scanner, subjects were stratified between amyloid negative (A-; n = 230) and positive (A+; n = 88) groups. Differences between A+ and A- were estimated at source-level in each band-power of the EEG spectrum.Results: At M0, we found an increase of theta power in the mid-frontal cortex in A+ compared to A-. No significant association was found between mid-frontal theta and the individuals' cognitive performance. At M24, theta power increased in A+ relative to A- individuals in the posterior cingulate cortex and the pre-cuneus. Alpha band revealed a peculiar decremental trend in posterior brain regions in the A+ relative to the A- group only at M24. Theta power increase over the mid-frontal and mid-posterior cortices suggests an hypoactivation of the default-mode network in the A+ individuals and a non-linear longitudinal progression at M24.Conclusion: We provide the first source-level longitudinal evidence on the impact of brain amyloidosis on the EEG dynamics of a large-scale, monocentric cohort of elderly individuals at-risk for AD. [ABSTRACT FROM AUTHOR]

Published
2022
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50. Functional connectivity predicts MI-based BCI learning (oral presentation)

Author

Corsi, Marie-Constance, Chavez, Mario, Schwartz, Denis, George, Nathalie, Hugueville, Laurent, Kahn, Ari E., Dupont, Sophie, Bassett, Danielle, De Vico Fallani, Fabrizio, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), University of Pennsylvania, Corsi, Marie-Constance, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), University of Pennsylvania [Philadelphia], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDV] Life Sciences [q-bio], [SPI]Engineering Sciences [physics], [SPI] Engineering Sciences [physics], [SDV]Life Sciences [q-bio], [MATH] Mathematics [math], [MATH]Mathematics [math], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2021

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