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508 results on '"Mitsis, Georgios"'

1. Neurovascular coupling methods in healthy individuals using transcranial doppler ultrasonography: A systematic review and consensus agreement

Author

Ball, James D, Hills, Eleanor, Altaf, Afzaa, Ramesh, Pranav, Green, Matthew, Surti, Farhaana BS, Minhas, Jatinder S, Robinson, Thompson G, Bond, Bert, Lester, Alice, Hoiland, Ryan, Klein, Timo, Liu, Jia, Nasr, Nathalie, Junejo, Rehan T, Müller, Martin, Lecchini-Visintini, Andrea, Mitsis, Georgios, Burma, Joel S, Smirl, Jonathan D, Pizzi, Michael A, Manquat, Elsa, Lucas, Samuel JE, Mullinger, Karen J, Mayhew, Steve, Bailey, Damian M, Rodrigues, Gabriel, Soares, Pedro Paulo, Phillips, Aaron A, Prokopiou, Prokopis C, and C Beishon, Lucy

Published
2024
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7. Deep Semantic Architecture with discriminative feature visualization for neuroimage analysis

Author

Ghosh, Arna, Maso, Fabien dal, Roig, Marc, Mitsis, Georgios D, and Boudrias, Marie-Hélène

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Artificial Intelligence, Quantitative Biology - Quantitative Methods
Abstract

Neuroimaging data analysis often involves \emph{a-priori} selection of data features to study the underlying neural activity. Since this could lead to sub-optimal feature selection and thereby prevent the detection of subtle patterns in neural activity, data-driven methods have recently gained popularity for optimizing neuroimaging data analysis pipelines and thereby, improving our understanding of neural mechanisms. In this context, we developed a deep convolutional architecture that can identify discriminating patterns in neuroimaging data and applied it to electroencephalography (EEG) recordings collected from 25 subjects performing a hand motor task before and after a rest period or a bout of exercise. The deep network was trained to classify subjects into exercise and control groups based on differences in their EEG signals. Subsequently, we developed a novel method termed the cue-combination for Class Activation Map (ccCAM), which enabled us to identify discriminating spatio-temporal features within definite frequency bands (23--33 Hz) and assess the effects of exercise on the brain. Additionally, the proposed architecture allowed the visualization of the differences in the propagation of underlying neural activity across the cortex between the two groups, for the first time in our knowledge. Our results demonstrate the feasibility of using deep network architectures for neuroimaging analysis in different contexts such as, for the identification of robust brain biomarkers to better characterize and potentially treat neurological disorders.

Published
2018

9. The Modulatory Effects of Transcranial Alternating Current Stimulation on Brain Oscillatory Patterns in the Beta Band in Healthy Older Adults.

Author

Morales Fajardo, Kenya, Yan, Xuanteng, Lungoci, George, Casado Sánchez, Monserrat, Mitsis, Georgios D., and Boudrias, Marie-Hélène

Subjects
TRANSCRANIAL alternating current stimulation, BRAIN stimulation, FREQUENCIES of oscillating systems, OLDER people, YOUNG adults
Abstract

Background: In the last few years, transcranial alternating current stimulation (tACS) has attracted attention as a promising approach to interact with ongoing oscillatory cortical activity and, consequently, to enhance cognitive and motor processes. While tACS findings are limited by high variability in young adults' responses, its effects on brain oscillations in older adults remain largely unexplored. In fact, the modulatory effects of tACS on cortical oscillations in healthy aging participants have not yet been investigated extensively, particularly during movement. This study aimed to examine the after-effects of 20 Hz and 70 Hz High-Definition tACS on beta oscillations both during rest and movement. Methods: We recorded resting state EEG signals and during a handgrip task in 15 healthy older participants. We applied 10 min of 20 Hz HD-tACS, 70 Hz HD-tACS or Sham stimulation for 10 min. We extracted resting-state beta power and movement-related beta desynchronization (MRBD) values to compare between stimulation frequencies and across time. Results: We found that 20 Hz HD-tACS induced a significant reduction in beta power for electrodes C3 and CP3, while 70 Hz did not have any significant effects. With regards to MRBD, 20 Hz HD-tACS led to more negative values, while 70 Hz HD-tACS resulted in more positive ones for electrodes C3 and FC3. Conclusions: These findings suggest that HD-tACS can modulate beta brain oscillations with frequency specificity. They also highlight the focal impact of HD-tACS, which elicits effects on the cortical region situated directly beneath the stimulation electrode. [ABSTRACT FROM AUTHOR]

Published
2024
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15. Time-domain methods for quantifying dynamic cerebral blood flow autoregulation: Review and recommendations. A white paper from the Cerebrovascular Research Network (CARNet).

Author

Kostoglou, Kyriaki, Bello-Robles, Felipe, Brassard, Patrice, Chacon, Max, Claassen, Jurgen AHR, Czosnyka, Marek, Elting, Jan-Willem, Hu, Kun, Labrecque, Lawrence, Liu, Jia, Marmarelis, Vasilis Z, Payne, Stephen J, Shin, Dae Cheol, Simpson, David, Smirl, Jonathan, Panerai, Ronney B, and Mitsis, Georgios D

Abstract

Cerebral Autoregulation (CA) is an important physiological mechanism stabilizing cerebral blood flow (CBF) in response to changes in cerebral perfusion pressure (CPP). By maintaining an adequate, relatively constant supply of blood flow, CA plays a critical role in brain function. Quantifying CA under different physiological and pathological states is crucial for understanding its implications. This knowledge may serve as a foundation for informed clinical decision-making, particularly in cases where CA may become impaired. The quantification of CA functionality typically involves constructing models that capture the relationship between CPP (or arterial blood pressure) and experimental measures of CBF. Besides describing normal CA function, these models provide a means to detect possible deviations from the latter. In this context, a recent white paper from the Cerebrovascular Research Network focused on Transfer Function Analysis (TFA), which obtains frequency domain estimates of dynamic CA. In the present paper, we consider the use of time-domain techniques as an alternative approach. Due to their increased flexibility, time-domain methods enable the mitigation of measurement/physiological noise and the incorporation of nonlinearities and time variations in CA dynamics. Here, we provide practical recommendations and guidelines to support researchers and clinicians in effectively utilizing these techniques to study CA. [ABSTRACT FROM AUTHOR]

Published
2024
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18. Variability in the analysis of a single neuroimaging dataset by many teams

Author

Botvinik-Nezer, R., Holzmeister, F., Camerer, C. F., Dreber, A., Huber, J., Johannesson, M., Kirchler, M., Iwanir, R., Mumford, J. A., Adcock, R. A., Avesani, P., Baczkowski, B. M., Bajracharya, A., Bakst, L., Ball, S., Barilari, M., Bault, N., Beaton, D., Beitner, J., Benoit, R. G., Berkers, R. M. W. J., Bhanji, J. P., Biswal, B. B., Bobadilla-Suarez, S., Bortolini, T., Bottenhorn, K. L., Bowring, A., Braem, S., Brooks, H. R., Brudner, E. G., Calderon, C. B., Camilleri, J. A., Castrellon, J. J., Cecchetti, L., Cieslik, E. C., Cole, Z. J., Collignon, O., Cox, R. W., Cunningham, W. A., Czoschke, S., Dadi, K., Davis, C. P., Luca, A. D., Delgado, M. R., Demetriou, L., Dennison, J. B., Di, X., Dickie, E. W., Dobryakova, E., Donnat, C. L., Dukart, J., Duncan, N. W., Durnez, J., Eed, A., Eickhoff, S. B., Erhart, A., Fontanesi, L., Fricke, G. M., Fu, S., Galván, A., Gau, R., Genon, S., Glatard, T., Glerean, E., Goeman, J. J., Golowin, S. A. E., González-García, C., Gorgolewski, K. J., Grady, C. L., Green, M. A., Guassi Moreira, J. F., Guest, O., Hakimi, S., Hamilton, J. P., Hancock, R., Handjaras, G., Harry, B.B., Hawco, C., Herholz, P., Herman, G., Heunis, S., Hoffstaedter, F., Hogeveen, J., Holmes, S., Hu, C. P., Huettel, S. A., Hughes, M. E., Iacovella, V., Iordan, A. D., Isager, P. M., Isik, A. I., Jahn, Andrew, Johnson, Matthew R., Johnstone, Tom, Joseph, Michael J. E., Juliano, Anthony C., Kable, Joseph W., Kassinopoulos, Michalis, Koba, Cemal, Kong, Xiang-Zhen, Koscik, Timothy R., Kucukboyaci, Nuri Erkut, Kuhl, Brice A., Kupek, Sebastian, Laird, Angela R., Lamm, Claus, Langner, Robert, Lauharatanahirun, Nina, Lee, Hongmi, Lee, Sangil, Leemans, Alexander, Leo, Andrea, Lesage, Elise, Li, Flora, Li, Monica Y. C., Lim, Cheng Phui, Lintz, Evan N., Liphardt, Schuyler W., Losecaat Vermeer, Annabel B., Love, Bradley C., Mack, Michael L., Malpica, Norberto, Marins, Theo, Maumet, Camille, McDonald, Kelsey, McGuire, Joseph T., Méndez Leal, Adriana S., Meyer, Benjamin, Meyer, Kristin N., Mihai, Glad, Mitsis, Georgios D., Moll, Jorge, Nielson, Dylan M., Nilsonne, Gustav, Notter, Michael P., Olivetti, Emanuele, Onicas, Adrian I., Papale, Paolo, Patil, Kaustubh R., Peelle, Jonathan E., Pérez, Alexandre, Pischedda, Doris, Poline, Jean-Baptiste, Prystauka,Yanina, Ray, Shruti, Reuter-Lorenz, Patricia A., Reynolds, Richard C., Ricciardi, Emiliano, Rieck, Jenny R., Rodriguez-Thompson, Anais M., Romyn, Anthony, Salo, Taylor, Samanez-Larkin, Gregory R., Sanz-Morales, Emilio, Schlichting, Margaret L., Schultz, Douglas H., Shen, Qiang, Sheridan, Margaret A., Silvers, Jennifer A., Skagerlund, Kenny, Smith, Alec, Smith, David V., Sokol-Hessner, Peter, Steinkamp, Simon R., Tashjian, Sarah M., Thirion, Bertrand, Thorp, John N., Tinghög, Gustav, Tisdall, Loreen, Tompson, Steven H., Toro-Serey, Claudio, Torre Tresols, Juan Jesus, Tozzi, Leonardo, Truong, Vuong, Turella, Luca, van ‘t Veer, Anna E., Verguts, Tom, Vettel, Jean M., Vijayarajah, Sagana, Vo, Khoi, Wall, Matthew B., Weeda, Wouter D., Weis, Susanne, White, David J., Wisniewski, David, Xifra-Porxas, Alba, Yearling, Emily A., Yoon, Sangsuk, Yuan, Rui, Yuen, Kenneth S. L., Lei Zhang, Zhang, Xu, Zosky, Joshua E., Thomas E. Nichols, Poldrack, Rusell A., Schonberg, Tom, Melero Carrasco, Helena, Botvinik-Nezer, R., Holzmeister, F., Camerer, C. F., Dreber, A., Huber, J., Johannesson, M., Kirchler, M., Iwanir, R., Mumford, J. A., Adcock, R. A., Avesani, P., Baczkowski, B. M., Bajracharya, A., Bakst, L., Ball, S., Barilari, M., Bault, N., Beaton, D., Beitner, J., Benoit, R. G., Berkers, R. M. W. J., Bhanji, J. P., Biswal, B. B., Bobadilla-Suarez, S., Bortolini, T., Bottenhorn, K. L., Bowring, A., Braem, S., Brooks, H. R., Brudner, E. G., Calderon, C. B., Camilleri, J. A., Castrellon, J. J., Cecchetti, L., Cieslik, E. C., Cole, Z. J., Collignon, O., Cox, R. W., Cunningham, W. A., Czoschke, S., Dadi, K., Davis, C. P., Luca, A. D., Delgado, M. R., Demetriou, L., Dennison, J. B., Di, X., Dickie, E. W., Dobryakova, E., Donnat, C. L., Dukart, J., Duncan, N. W., Durnez, J., Eed, A., Eickhoff, S. B., Erhart, A., Fontanesi, L., Fricke, G. M., Fu, S., Galván, A., Gau, R., Genon, S., Glatard, T., Glerean, E., Goeman, J. J., Golowin, S. A. E., González-García, C., Gorgolewski, K. J., Grady, C. L., Green, M. A., Guassi Moreira, J. F., Guest, O., Hakimi, S., Hamilton, J. P., Hancock, R., Handjaras, G., Harry, B.B., Hawco, C., Herholz, P., Herman, G., Heunis, S., Hoffstaedter, F., Hogeveen, J., Holmes, S., Hu, C. P., Huettel, S. A., Hughes, M. E., Iacovella, V., Iordan, A. D., Isager, P. M., Isik, A. I., Jahn, Andrew, Johnson, Matthew R., Johnstone, Tom, Joseph, Michael J. E., Juliano, Anthony C., Kable, Joseph W., Kassinopoulos, Michalis, Koba, Cemal, Kong, Xiang-Zhen, Koscik, Timothy R., Kucukboyaci, Nuri Erkut, Kuhl, Brice A., Kupek, Sebastian, Laird, Angela R., Lamm, Claus, Langner, Robert, Lauharatanahirun, Nina, Lee, Hongmi, Lee, Sangil, Leemans, Alexander, Leo, Andrea, Lesage, Elise, Li, Flora, Li, Monica Y. C., Lim, Cheng Phui, Lintz, Evan N., Liphardt, Schuyler W., Losecaat Vermeer, Annabel B., Love, Bradley C., Mack, Michael L., Malpica, Norberto, Marins, Theo, Maumet, Camille, McDonald, Kelsey, McGuire, Joseph T., Méndez Leal, Adriana S., Meyer, Benjamin, Meyer, Kristin N., Mihai, Glad, Mitsis, Georgios D., Moll, Jorge, Nielson, Dylan M., Nilsonne, Gustav, Notter, Michael P., Olivetti, Emanuele, Onicas, Adrian I., Papale, Paolo, Patil, Kaustubh R., Peelle, Jonathan E., Pérez, Alexandre, Pischedda, Doris, Poline, Jean-Baptiste, Prystauka,Yanina, Ray, Shruti, Reuter-Lorenz, Patricia A., Reynolds, Richard C., Ricciardi, Emiliano, Rieck, Jenny R., Rodriguez-Thompson, Anais M., Romyn, Anthony, Salo, Taylor, Samanez-Larkin, Gregory R., Sanz-Morales, Emilio, Schlichting, Margaret L., Schultz, Douglas H., Shen, Qiang, Sheridan, Margaret A., Silvers, Jennifer A., Skagerlund, Kenny, Smith, Alec, Smith, David V., Sokol-Hessner, Peter, Steinkamp, Simon R., Tashjian, Sarah M., Thirion, Bertrand, Thorp, John N., Tinghög, Gustav, Tisdall, Loreen, Tompson, Steven H., Toro-Serey, Claudio, Torre Tresols, Juan Jesus, Tozzi, Leonardo, Truong, Vuong, Turella, Luca, van ‘t Veer, Anna E., Verguts, Tom, Vettel, Jean M., Vijayarajah, Sagana, Vo, Khoi, Wall, Matthew B., Weeda, Wouter D., Weis, Susanne, White, David J., Wisniewski, David, Xifra-Porxas, Alba, Yearling, Emily A., Yoon, Sangsuk, Yuan, Rui, Yuen, Kenneth S. L., Lei Zhang, Zhang, Xu, Zosky, Joshua E., Thomas E. Nichols, Poldrack, Rusell A., Schonberg, Tom, and Melero Carrasco, Helena

Abstract

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2–5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed., Depto. de Psicobiología y Metodología en Ciencias del Comportamiento, Fac. de Psicología, TRUE, pub

Published
2024

19. Variability in the analysis of a single neuroimaging dataset by many teams

Author

Botvinik-Nezer, Rotem, Holzmeister, Felix, Camerer, Colin F., Dreber, Anna, Huber, Juergen, Johannesson, Magnus, Kirchler, Michael, Iwanir, Roni, Mumford, Jeanette A., Adcock, R. Alison, Avesani, Paolo, Baczkowski, Blazej M., Bajracharya, Aahana, Bakst, Leah, Ball, Sheryl, Barilari, Marco, Bault, Nadège, Beaton, Derek, Beitner, Julia, Benoit, Roland G., Berkers, Ruud M. W. J., Bhanji, Jamil P., Biswal, Bharat B., Bobadilla-Suarez, Sebastian, Bortolini, Tiago, Bottenhorn, Katherine L., Bowring, Alexander, Braem, Senne, Brooks, Hayley R., Brudner, Emily G., Calderon, Cristian B., Camilleri, Julia A., Castrellon, Jaime J., Cecchetti, Luca, Cieslik, Edna C., Cole, Zachary J., Collignon, Olivier, Cox, Robert W., Cunningham, William A., Czoschke, Stefan, Dadi, Kamalaker, Davis, Charles P., Luca, Alberto De, Delgado, Mauricio R., Demetriou, Lysia, Dennison, Jeffrey B., Di, Xin, Dickie, Erin W., Dobryakova, Ekaterina, Donnat, Claire L., Dukart, Juergen, Duncan, Niall W., Durnez, Joke, Eed, Amr, Eickhoff, Simon B., Erhart, Andrew, Fontanesi, Laura, Fricke, G. Matthew, Fu, Shiguang, Galván, Adriana, Gau, Remi, Genon, Sarah, Glatard, Tristan, Glerean, Enrico, Goeman, Jelle J., Golowin, Sergej A. E., González-García, Carlos, Gorgolewski, Krzysztof J., Grady, Cheryl L., Green, Mikella A., Guassi Moreira, João F., Guest, Olivia, Hakimi, Shabnam, Hamilton, J. Paul, Hancock, Roeland, Handjaras, Giacomo, Harry, Bronson B., Hawco, Colin, Herholz, Peer, Herman, Gabrielle, Heunis, Stephan, Hoffstaedter, Felix, Hogeveen, Jeremy, Holmes, Susan, Hu, Chuan-Peng, Huettel, Scott A., Hughes, Matthew E., Iacovella, Vittorio, Iordan, Alexandru D., Isager, Peder M., Isik, Ayse I., Jahn, Andrew, Johnson, Matthew R., Johnstone, Tom, Joseph, Michael J. E., Juliano, Anthony C., Kable, Joseph W., Kassinopoulos, Michalis, Koba, Cemal, Kong, Xiang-Zhen, Koscik, Timothy R., Kucukboyaci, Nuri Erkut, Kuhl, Brice A., Kupek, Sebastian, Laird, Angela R., Lamm, Claus, Langner, Robert, Lauharatanahirun, Nina, Lee, Hongmi, Lee, Sangil, Leemans, Alexander, Leo, Andrea, Lesage, Elise, Li, Flora, Li, Monica Y. C., Lim, Phui Cheng, Lintz, Evan N., Liphardt, Schuyler W., Losecaat Vermeer, Annabel B., Love, Bradley C., Mack, Michael L., Malpica, Norberto, Marins, Theo, Maumet, Camille, McDonald, Kelsey, McGuire, Joseph T., Melero, Helena, Méndez Leal, Adriana S., Meyer, Benjamin, Meyer, Kristin N., Mihai, Glad, Mitsis, Georgios D., Moll, Jorge, Nielson, Dylan M., Nilsonne, Gustav, Notter, Michael P., Olivetti, Emanuele, Onicas, Adrian I., Papale, Paolo, Patil, Kaustubh R., Peelle, Jonathan E., Pérez, Alexandre, Pischedda, Doris, Poline, Jean-Baptiste, Prystauka, Yanina, Ray, Shruti, Reuter-Lorenz, Patricia A., Reynolds, Richard C., Ricciardi, Emiliano, Rieck, Jenny R., Rodriguez-Thompson, Anais M., Romyn, Anthony, Salo, Taylor, Samanez-Larkin, Gregory R., Sanz-Morales, Emilio, Schlichting, Margaret L., Schultz, Douglas H., Shen, Qiang, Sheridan, Margaret A., Silvers, Jennifer A., Skagerlund, Kenny, Smith, Alec, Smith, David V., Sokol-Hessner, Peter, Steinkamp, Simon R., Tashjian, Sarah M., Thirion, Bertrand, Thorp, John N., Tinghög, Gustav, Tisdall, Loreen, Tompson, Steven H., Toro-Serey, Claudio, Torre Tresols, Juan Jesus, Tozzi, Leonardo, Truong, Vuong, Turella, Luca, van ‘t Veer, Anna E., Verguts, Tom, Vettel, Jean M., Vijayarajah, Sagana, Vo, Khoi, Wall, Matthew B., Weeda, Wouter D., Weis, Susanne, White, David J., Wisniewski, David, Xifra-Porxas, Alba, Yearling, Emily A., Yoon, Sangsuk, Yuan, Rui, Yuen, Kenneth S. L., Zhang, Lei, Zhang, Xu, Zosky, Joshua E., Nichols, Thomas E., Poldrack, Russell A., and Schonberg, Tom

Published
2020
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40. Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure–flow relation: The CARNet study

Author

Meel-van den Abeelen, Aisha S.S., Simpson, David M., Wang, Lotte J.Y., Slump, Cornelis H., Zhang, Rong, Tarumi, Takashi, Rickards, Caroline A., Payne, Stephen, Mitsis, Georgios D., Kostoglou, Kyriaki, Marmarelis, Vasilis, Shin, Dae, Tzeng, Yu-Chieh, Ainslie, Philip N., Gommer, Erik, Müller, Martin, Dorado, Alexander C., Smielewski, Peter, Yelicich, Bernardo, Puppo, Corina, Liu, Xiuyun, Czosnyka, Marek, Wang, Cheng-Yen, Novak, Vera, Panerai, Ronney B., and Claassen, Jurgen A.H.R.

Published
2014
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42. Nonlinear Modeling of the Dynamic Effects of Arterial Pressure and Blood Gas Variations on Cerebral Blood Flow in Healthy Humans

Author

Mitsis, Georgios D., Ainslie, Philip N., Poulin, Marc J., Robbins, Peter A., Marmarelis, Vasilis Z., Back, Nathan, editor, Cohen, Irun R., editor, Kritchevsky, David, editor, Lajtha, Abel, editor, Paoletti, Rodolfo, editor, Champagnat, Jean, editor, Denavit-Saubié, Monique, editor, Fortin, Gilles, editor, Foutz, Arthur S., editor, and Thoby-Brisson, Muriel, editor

Published
2005
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