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17 results on '"Maurizio Mattia"'

1. A geometrical solution underlies general neural principle for serial ordering

Author

Gabriele Di Antonio, Sofia Raglio, and Maurizio Mattia

Subjects
Science
Abstract

Abstract A general mathematical description of how the brain sequentially encodes knowledge remains elusive. We propose a linear solution for serial learning tasks, based on the concept of mixed selectivity in high-dimensional neural state spaces. In our framework, neural representations of items in a sequence are projected along a “geometric” mental line learned through classical conditioning. The model successfully solves serial position tasks and explains behaviors observed in humans and animals during transitive inference tasks amidst noisy sensory input and stochastic neural activity. This approach extends to recurrent neural networks performing motor decision tasks, where the same geometric mental line correlates with motor plans and modulates network activity according to the symbolic distance between items. Serial ordering is thus predicted to emerge as a monotonic mapping between sensory input and behavioral output, highlighting a possible pivotal role for motor-related associative cortices in transitive inference tasks.

Published
2024
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4. Slow waves form expanding, memory-rich mesostates steered by local excitability in fading anesthesia

Author

Antonio Pazienti, Andrea Galluzzi, Miguel Dasilva, Maria V. Sanchez-Vives, and Maurizio Mattia

Subjects
Neuroscience, Experimental models in systems biology, Science
Abstract

Summary: In the arousal process, the brain restores its integrative activity from the synchronized state of slow wave activity (SWA). The mechanisms underpinning this state transition remain, however, to be elucidated. Here we simultaneously probed neuronal assemblies throughout the whole cortex with micro-electrocorticographic recordings in mice. We investigated the progressive shaping of propagating SWA at different levels of isoflurane. We found a form of memory of the wavefront shapes at deep anesthesia, tightly alternating posterior-anterior-posterior patterns. At low isoflurane, metastable patterns propagated in more directions, reflecting an increased complexity. The wandering across these mesostates progressively increased its randomness, as predicted by simulations of a network of spiking neurons, and confirmed in our experimental data. The complexity increase is explained by the elevated excitability of local assemblies with no modifications of the network connectivity. These results shed new light on the functional reorganization of the cortical network as anesthesia fades out.

Published
2022
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5. Binocular rivalry reveals an out-of-equilibrium neural dynamics suited for decision-making

Author

Robin Cao, Alexander Pastukhov, Stepan Aleshin, Maurizio Mattia, and Jochen Braun

Subjects
binocular rivalry, Levelt's propositions, dominance distribution, attractor dynamics, discrete stochastic, decision making, Medicine, Science, Biology (General), QH301-705.5
Abstract

In ambiguous or conflicting sensory situations, perception is often ‘multistable’ in that it perpetually changes at irregular intervals, shifting abruptly between distinct alternatives. The interval statistics of these alternations exhibits quasi-universal characteristics, suggesting a general mechanism. Using binocular rivalry, we show that many aspects of this perceptual dynamics are reproduced by a hierarchical model operating out of equilibrium. The constitutive elements of this model idealize the metastability of cortical networks. Independent elements accumulate visual evidence at one level, while groups of coupled elements compete for dominance at another level. As soon as one group dominates perception, feedback inhibition suppresses supporting evidence. Previously unreported features in the serial dependencies of perceptual alternations compellingly corroborate this mechanism. Moreover, the proposed out-of-equilibrium dynamics satisfies normative constraints of continuous decision-making. Thus, multistable perception may reflect decision-making in a volatile world: integrating evidence over space and time, choosing categorically between hypotheses, while concurrently evaluating alternatives.

Published
2021
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6. Up and Down States During Slow Oscillations in Slow-Wave Sleep and Different Levels of Anesthesia

Author

Melody Torao-Angosto, Arnau Manasanch, Maurizio Mattia, and Maria V. Sanchez-Vives

Subjects
Up states, Down states, slow oscillations, sleep, anesthesia, cerebral cortex, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Slow oscillations are a pattern of synchronized network activity generated by the cerebral cortex. They consist of Up and Down states, which are periods of activity interspersed with periods of silence, respectively. However, even when this is a unique dynamic regime of transitions between Up and Down states, this pattern is not constant: there is a range of oscillatory frequencies (0.1–4 Hz), and the duration of Up vs. Down states during the cycles is variable. This opens many questions. Is there a constant relationship between the duration of Up and Down states? How much do they vary across conditions and oscillatory frequencies? Are there different sub regimes within the slow oscillations? To answer these questions, we aimed to explore a concrete aspect of slow oscillations, Up and Down state durations, across three conditions: deep anesthesia, light anesthesia, and slow-wave sleep (SWS), in the same chronically implanted rats. We found that light anesthesia and SWS have rather similar properties, occupying a small area of the Up and Down state duration space. Deeper levels of anesthesia occupy a larger region of this space, revealing that a large variety of Up and Down state durations can emerge within the slow oscillatory regime. In a network model, we investigated the network parameters that can explain the different points within our bifurcation diagram in which slow oscillations are expressed.

Published
2021
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7. Modulation of cortical slow oscillations and complexity across anesthesia levels

Author

Miguel Dasilva, Alessandra Camassa, Alvaro Navarro-Guzman, Antonio Pazienti, Lorena Perez-Mendez, Gorka Zamora-López, Maurizio Mattia, and Maria V. Sanchez-Vives

Subjects
Slow waves, PCI, Wave propagation, Emergent activity, Cortical connectivity, Up states, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

The ability of different groups of cortical neurons to engage in causal interactions that are at once differentiated and integrated results in complex dynamic patterns. Complexity is low during periods of unconsciousness (deep sleep, anesthesia, unresponsive wakefulness syndrome) in which the brain tends to generate a stereotypical pattern consisting of alternating active and silent periods of neural activity—slow oscillations— and is high during wakefulness. But how is cortical complexity built up? Is it a continuum? An open question is whether cortical complexity can vary within the same brain state. Here we recorded with 32-channel multielectrode arrays from the cortical surface of the mouse and used both spontaneous dynamics (wave propagation entropy and functional complexity) and a perturbational approach (a variation of the perturbation complexity index) to measure complexity at different anesthesia levels. Variations in anesthesia level within the bistable regime of slow oscillations (0.1–1.5 Hz) resulted in a modulation of the slow oscillation frequency. Both perturbational and spontaneous complexity increased with decreasing anesthesia levels, in correlation with the decrease in coherence of the underlying network. Changes in complexity level are related to, but not dependent on, changes in excitability. We conclude that cortical complexity can vary within a single brain state dominated by slow oscillations, building up to the higher complexity associated with consciousness.

Published
2021
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8. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3

Author

Adam J. H. Newton, Alexandra H. Seidenstein, Robert A. McDougal, Alberto Pérez-Cervera, Gemma Huguet, Tere M-Seara, Caroline Haimerl, David Angulo-Garcia, Alessandro Torcini, Rosa Cossart, Arnaud Malvache, Kaoutar Skiker, Mounir Maouene, Gianmarco Ragognetti, Letizia Lorusso, Andrea Viggiano, Angelo Marcelli, Rosa Senatore, Antonio Parziale, S. Stramaglia, M. Pellicoro, L. Angelini, E. Amico, H. Aerts, J. Cortés, S. Laureys, D. Marinazzo, I. Bassez, L. Faes, Hannes Almgren, Adeel Razi, Frederik Van de Steen, Ruth Krebs, Hannelore Aerts, Lida Kanari, Pawel Dlotko, Martina Scolamiero, Ran Levi, Julian Shillcock, Christiaan P.J. de Kock, Kathryn Hess, Henry Markram, Cheng Ly, Gary Marsat, Tom Gillespie, Malin Sandström, Mathew Abrams, Jeffrey S. Grethe, Maryann Martone, Robin De Gernier, Sergio Solinas, Christian Rössert, Marc Haelterman, Serge Massar, Valentina Pasquale, Vito Paolo Pastore, Sergio Martinoia, Paolo Massobrio, Cristiano Capone, Núria Tort-Colet, Maria V. Sanchez-Vives, Maurizio Mattia, Ali Almasi, Shaun L. Cloherty, David B. Grayden, Yan T. Wong, Michael R. Ibbotson, Hamish Meffin, Luke Y. Prince, Krasimira Tsaneva-Atanasova, Jack R. Mellor, Alberto Mazzoni, Manuela Rosa, Jacopo Carpaneto, Luigi M. Romito, Alberto Priori, Silvestro Micera, Rosanna Migliore, Carmen Alina Lupascu, Francesco Franchina, Luca Leonardo Bologna, Armando Romani, Sára Saray, Werner Van Geit, Szabolcs Káli, Alex Thomson, Audrey Mercer, Sigrun Lange, Joanne Falck, Eilif Muller, Felix Schürmann, Dmitrii Todorov, Robert Capps, William Barnett, Yaroslav Molkov, Federico Devalle, Diego Pazó, Ernest Montbrió, Gabriela Mochol, Habiba Azab, Benjamin Y. Hayden, Rubén Moreno-Bote, Pragathi Priyadharsini Balasubramani, Srinivasa V. Chakravarthy, Vignayanandam R. Muddapu, Medorian D. Gheorghiu, Bartul Mimica, Jonathan Withlock, Raul C. Mureșan, Jennifer L. Zick, Kelsey Schultz, Rachael K. Blackman, Matthew V. Chafee, Theoden I. Netoff, Nicholas Roberts, Vivek Nagaraj, Andrew Lamperski, Logan L. Grado, Matthew D. Johnson, David P. Darrow, Davide Lonardoni, Hayder Amin, Stefano Di Marco, Alessandro Maccione, Luca Berdondini, Thierry Nieus, Marcel Stimberg, Dan F. M. Goodman, Thomas Nowotny, Veronika Koren, Valentin Dragoi, Klaus Obermayer, Samy Castro, Mariano Fernandez, Wael El-Deredy, Kesheng Xu, Jean Paul Maidana, Patricio Orio, Weiliang Chen, Iain Hepburn, Francesco Casalegno, Adrien Devresse, Aleksandr Ovcharenko, Fernando Pereira, Fabien Delalondre, Erik De Schutter, Peter Bratby, Andrew R. Gallimore, Guido Klingbeil, Criseida Zamora, Yunliang Zang, Patrick Crotty, Eric Palmerduca, Alberto Antonietti, Claudia Casellato, Csaba Erö, Egidio D’Angelo, Marc-Oliver Gewaltig, Alessandra Pedrocchi, Ilja Bytschok, Dominik Dold, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici, Hui-An Shen, Simone Carlo Surace, Jean-Pascal Pfister, Baptiste Lefebvre, Olivier Marre, Pierre Yger, Athanasia Papoutsi, Jiyoung Park, Ryan Ash, Stelios Smirnakis, Panayiota Poirazi, Richard A. Felix, Alexander G. Dimitrov, Christine Portfors, Silvia Daun, Tibor I. Toth, Joanna Jędrzejewska-Szmek, Nadine Kabbani, Kim T. Blackwel, Bahar Moezzi, Natalie Schaworonkow, Lukas Plogmacher, Mitchell R. Goldsworthy, Brenton Hordacre, Mark D. McDonnell, Nicolangelo Iannella, Michael C. Ridding, Jochen Triesch, Reinoud Maex, Karen Safaryan, Volker Steuber, Rongxiang Tang, Yi-Yuan Tang, Darya V. Verveyko, Alexey R. Brazhe, Andrey Yu Verisokin, Dmitry E. Postnov, Cengiz Günay, Gabriella Panuccio, Michele Giugliano, Astrid A. Prinz, Pablo Varona, Mikhail I. Rabinovich, Jack Denham, Thomas Ranner, Netta Cohen, Maria Reva, Nelson Rebola, Tekla Kirizs, Zoltan Nusser, David DiGregorio, Eirini Mavritsaki, Panos Rentzelas, Nikul H. Ukani, Adam Tomkins, Chung-Heng Yeh, Wesley Bruning, Allison L. Fenichel, Yiyin Zhou, Yu-Chi Huang, Dorian Florescu, Carlos Luna Ortiz, Paul Richmond, Chung-Chuan Lo, Daniel Coca, Ann-Shyn Chiang, Aurel A. Lazar, Jennifer L. Creaser, Congping Lin, Peter Ashwin, Jonathan T. Brown, Thomas Ridler, Daniel Levenstein, Brendon O. Watson, György Buzsáki, John Rinzel, Rodica Curtu, Anh Nguyen, Sahand Assadzadeh, Peter A. Robinson, Paula Sanz-Leon, Caroline G. Forlim, Lírio O. B. de Almeida, Reynaldo D. Pinto, Francisco B. Rodríguez, Ángel Lareo, Caroline Garcia Forlim, Aaron Montero, Thiago Mosqueiro, Ramon Huerta, Francisco B. Rodriguez, Vinicio Changoluisa, Vinícius L. Cordeiro, César C. Ceballos, Nilton L. Kamiji, Antonio C. Roque, William W. Lytton, Andrew Knox, Joshua J. C. Rosenthal, Svitlana Popovych, Liqing Liu, Bin A. Wang, Tibor I. Tóth, Christian Grefkes, Gereon R. Fink, Nils Rosjat, Abraham Perez-Trujillo, Andres Espinal, Marco A. Sotelo-Figueroa, Ivan Cruz-Aceves, Horacio Rostro-Gonzalez, Martin Zapotocky, Martina Hoskovcová, Jana Kopecká, Olga Ulmanová, Evžen Růžička, Matthias Gärtner, Sevil Duvarci, Jochen Roeper, Gaby Schneider, Stefan Albert, Katharina Schmack, Michiel Remme, Susanne Schreiber, Michele Migliore, Carmen A. Lupascu, Luca L. Bologna, Stefano M. Antonel, Jean-Denis Courcol, Sami Utku Çelikok, Eva M. Navarro-López, Neslihan Serap Şengör, Rahmi Elibol, Neslihan Serap Sengor, Mustafa Yasir Özdemir, Tianyi Li, Angelo Arleo, Denis Sheynikhovich, Akihiro Nakamura, Masanori Shimono, Youngjo Song, Sol Park, Ilhwan Choi, Jaeseung Jeong, Hee-sup Shin, Sadra Sadeh, Padraig Gleeson, R. Angus Silver, Alexandra Pierri Chatzikalymniou, Frances K. Skinner, Lazaro M. Sanchez-Rodriguez, Roberto C. Sotero, Loreen Hertäg, Owen Mackwood, Henning Sprekeler, Steffen Puhlmann, Simon N. Weber, David Higgins, Laura B. Naumann, Ramakrisnan Iyer, Stefan Mihalas, Valentina Ticcinelli, Tomislav Stankovski, Peter V. E. McClintock, Aneta Stefanovska, Predrag Janjić, Dimitar Solev, Gerald Seifert, Ljupčo Kocarev, Christian Steinhäuser, Mehrdad Salmasi, Stefan Glasauer, Martin Stemmler, Danke Zhang, Chi Zhang, Armen Stepanyants, Julia Goncharenko, Lieke Kros, Neil Davey, Chris de Zeeuw, Freek Hoebeek, Ankur Sinha, Roderick Adams, Michael Schmuker, Maria Psarrou, Maria Schilstra, Benjamin Torben-Nielsen, Christoph Metzner, Achim Schweikard, Tuomo Mäki-Marttunen, Bartosz Zurowski, Daniele Marinazzo, Luca Faes, Sebastiano Stramaglia, Henry O. C. Jordan, Simon M. Stringer, Elżbieta Gajewska-Dendek, Piotr Suffczyński, Nicoladie Tam, George Zouridakis, Luca Pollonini, Mojtaba Madadi Asl, Alireza Valizadeh, Peter A. Tass, Andreas Nold, Wei Fan, Sara Konrad, Heiko Endle, Johannes Vogt, Tatjana Tchumatchenko, Juliane Herpich, Christian Tetzlaff, Jannik Luboeinski, Timo Nachstedt, Manuel Ciba, Andreas Bahmer, Christiane Thielemann, Eric S. Kuebler, Joseph S. Tauskela, Jean-Philippe Thivierge, Rembrandt Bakker, María García-Amado, Marian Evangelio, Francisco Clascá, Paul Tiesinga, Christopher L. Buckley, Taro Toyoizumi, Alexis M. Dubreuil, Rémi Monasson, Alessandro Treves, Davide Spalla, Sophie Rosay, Florence I. Kleberg, Willy Wong, Bruno de Oliveira Floriano, Toshihiko Matsuo, Tetsuya Uchida, Domenica Dibenedetto, Kâmil Uludağ, Abdorreza Goodarzinick, Maximilian Schmidt, Claus C. Hilgetag, Markus Diesmann, Sacha J. van Albada, Michael Fauth, Mark van Rossum, Manuel Reyes-Sánchez, Rodrigo Amaducci, Carlos Muñiz, Irene Elices, David Arroyo, Rafael Levi, Ben Cohen, Carson Chow, Shashaank Vattikuti, Elena Bertolotti, Raffaella Burioni, Matteo di Volo, Alessandro Vezzani, Bayar Menzat, Tim P. Vogels, Nobuhiko Wagatsuma, Susmita Saha, Reena Kapoor, Robert Kerr, John Wagner, Luis C. Garcia del Molino, Guangyu Robert Yang, Jorge F. Mejias, Xiao-Jing Wang, Hanbing Song, Joseph Goodliffe, Jennifer Luebke, Christina M. Weaver, John Thomas, Nishant Sinha, Nikhita Shaju, Tomasz Maszczyk, Jing Jin, Sydney S. Cash, Justin Dauwels, M. Brandon Westover, Maryam Karimian, Michelle Moerel, Peter De Weerd, Thomas Burwick, Ronald L. Westra, Romesh Abeysuriya, Jonathan Hadida, Stamatios Sotiropoulos, Saad Jbabdi, Mark Woolrich, Chama Bensmail, Borys Wrobel, Xiaolong Zhou, Zilong Ji, Xiao Liu, Yan Xia, Si Wu, Xiao Wang, Mingsha Zhang, Netanel Ofer, Orit Shefi, Gur Yaari, Ted Carnevale, Amit Majumdar, Subhashini Sivagnanam, Kenneth Yoshimoto, Elena Y. Smirnova, Dmitry V. Amakhin, Sergey L. Malkin, Aleksey V. Zaitsev, Anton V. Chizhov, Margarita Zaleshina, Alexander Zaleshin, Victor J. Barranca, George Zhu, Quinton M. Skilling, Daniel Maruyama, Nicolette Ognjanovski, Sara J. Aton, Michal Zochowski, Jiaxing Wu, Sara Aton, Scott Rich, Victoria Booth, Maral Budak, Salvador Dura-Bernal, Samuel A. Neymotin, Benjamin A. Suter, Gordon M. G. Shepherd, Melvin A. Felton, Alfred B. Yu, David L. Boothe, Kelvin S. Oie, Piotr J. Franaszczuk, Sergey A. Shuvaev, Batuhan Başerdem, Anthony Zador, Alexei A. Koulakov, Víctor J. López-Madrona, Ernesto Pereda, Claudio R. Mirasso, Santiago Canals, Stefano Masoli, Udaya B. Rongala, Anton Spanne, Henrik Jorntell, Calogero M. Oddo, Alexander V. Vartanov, Anastasia K. Neklyudova, Stanislav A. Kozlovskiy, Andrey A. Kiselnikov, Julia A. Marakshina, Maria Teleńczuk, Bartosz Teleńczuk, Alain Destexhe, Paula T. Kuokkanen, Anna Kraemer, Thomas McColgan, Catherine E. Carr, and Richard Kempter

Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurophysiology and neuropsychology, QP351-495
Published
2017
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9. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2

Author

Leonid L. Rubchinsky, Sungwoo Ahn, Wouter Klijn, Ben Cumming, Stuart Yates, Vasileios Karakasis, Alexander Peyser, Marmaduke Woodman, Sandra Diaz-Pier, James Deraeve, Eliana Vassena, William Alexander, David Beeman, Pawel Kudela, Dana Boatman-Reich, William S. Anderson, Niceto R. Luque, Francisco Naveros, Richard R. Carrillo, Eduardo Ros, Angelo Arleo, Jacob Huth, Koki Ichinose, Jihoon Park, Yuji Kawai, Junichi Suzuki, Hiroki Mori, Minoru Asada, Sorinel A. Oprisan, Austin I. Dave, Tahereh Babaie, Peter Robinson, Alejandro Tabas, Martin Andermann, André Rupp, Emili Balaguer-Ballester, Henrik Lindén, Rasmus K. Christensen, Mari Nakamura, Tania R. Barkat, Zach Tosi, John Beggs, Davide Lonardoni, Fabio Boi, Stefano Di Marco, Alessandro Maccione, Luca Berdondini, Joanna Jędrzejewska-Szmek, Daniel B. Dorman, Kim T. Blackwell, Christoph Bauermeister, Hanna Keren, Jochen Braun, João V. Dornas, Eirini Mavritsaki, Silvio Aldrovandi, Emma Bridger, Sukbin Lim, Nicolas Brunel, Anatoly Buchin, Clifford Charles Kerr, Anton Chizhov, Gilles Huberfeld, Richard Miles, Boris Gutkin, Martin J. Spencer, Hamish Meffin, David B. Grayden, Anthony N. Burkitt, Catherine E. Davey, Liangyu Tao, Vineet Tiruvadi, Rehman Ali, Helen Mayberg, Robert Butera, Cengiz Gunay, Damon Lamb, Ronald L. Calabrese, Anca Doloc-Mihu, Víctor J. López-Madrona, Fernanda S. Matias, Ernesto Pereda, Claudio R. Mirasso, Santiago Canals, Alice Geminiani, Alessandra Pedrocchi, Egidio D’Angelo, Claudia Casellato, Ankur Chauhan, Karthik Soman, V. Srinivasa Chakravarthy, Vignayanandam R. Muddapu, Chao-Chun Chuang, Nan-yow Chen, Mehdi Bayati, Jan Melchior, Laurenz Wiskott, Amir Hossein Azizi, Kamran Diba, Sen Cheng, Elena Y. Smirnova, Elena G. Yakimova, Anton V. Chizhov, Nan-Yow Chen, Chi-Tin Shih, Dorian Florescu, Daniel Coca, Julie Courtiol, Viktor K. Jirsa, Roberto J. M. Covolan, Bartosz Teleńczuk, Richard Kempter, Gabriel Curio, Alain Destexhe, Jessica Parker, Alexander N. Klishko, Boris I. Prilutsky, Gennady Cymbalyuk, Felix Franke, Andreas Hierlemann, Rava Azeredo da Silveira, Stefano Casali, Stefano Masoli, Martina Rizza, Martina Francesca Rizza, Yinming Sun, Willy Wong, Faranak Farzan, Daniel M. Blumberger, Zafiris J. Daskalakis, Svitlana Popovych, Shivakumar Viswanathan, Nils Rosjat, Christian Grefkes, Silvia Daun, Damiano Gentiletti, Piotr Suffczynski, Vadym Gnatkovski, Marco De Curtis, Hyeonsu Lee, Se-Bum Paik, Woochul Choi, Jaeson Jang, Youngjin Park, Jun Ho Song, Min Song, Vicente Pallarés, Matthieu Gilson, Simone Kühn, Andrea Insabato, Gustavo Deco, Katharina Glomb, Adrián Ponce-Alvarez, Petra Ritter, Adria Tauste Campo, Alexander Thiele, Farah Deeba, P. A. Robinson, Sacha J. van Albada, Andrew Rowley, Michael Hopkins, Maximilian Schmidt, Alan B. Stokes, David R. Lester, Steve Furber, Markus Diesmann, Alessandro Barri, Martin T. Wiechert, David A. DiGregorio, Alexander G. Dimitrov, Catalina Vich, Rune W. Berg, Antoni Guillamon, Susanne Ditlevsen, Romain D. Cazé, Benoît Girard, Stéphane Doncieux, Nicolas Doyon, Frank Boahen, Patrick Desrosiers, Edward Laurence, Louis J. Dubé, Russo Eleonora, Daniel Durstewitz, Dominik Schmidt, Tuomo Mäki-Marttunen, Florian Krull, Francesco Bettella, Christoph Metzner, Anna Devor, Srdjan Djurovic, Anders M. Dale, Ole A. Andreassen, Gaute T. Einevoll, Solveig Næss, Torbjørn V. Ness, Geir Halnes, Eric Halgren, Klas H. Pettersen, Marte J. Sætra, Espen Hagen, Alina Schiffer, Axel Grzymisch, Malte Persike, Udo Ernst, Daniel Harnack, Udo A. Ernst, Nergis Tomen, Stefano Zucca, Valentina Pasquale, Giuseppe Pica, Manuel Molano-Mazón, Michela Chiappalone, Stefano Panzeri, Tommaso Fellin, Kelvin S. Oie, David L. Boothe, Joshua C. Crone, Alfred B. Yu, Melvin A. Felton, Isma Zulfiqar, Michelle Moerel, Peter De Weerd, Elia Formisano, Kelvin Oie, Piotr Franaszczuk, Roland Diggelmann, Michele Fiscella, Domenico Guarino, Jan Antolík, Andrew P. Davison, Yves Frègnac, Benjamin Xavier Etienne, Flavio Frohlich, Jérémie Lefebvre, Encarni Marcos, Maurizio Mattia, Aldo Genovesio, Leonid A. Fedorov, Tjeerd M.H. Dijkstra, Louisa Sting, Howard Hock, Martin A. Giese, Laure Buhry, Clément Langlet, Francesco Giovannini, Christophe Verbist, Stefano Salvadé, Michele Giugliano, James A. Henderson, Hendrik Wernecke, Bulcsú Sándor, Claudius Gros, Nicole Voges, Paulina Dabrovska, Alexa Riehle, Thomas Brochier, Sonja Grün, Yifan Gu, Pulin Gong, Grégory Dumont, Nikita A. Novikov, Boris S. Gutkin, Parul Tewatia, Olivia Eriksson, Andrei Kramer, Joao Santos, Alexandra Jauhiainen, Jeanette H. Kotaleski, Jovana J. Belić, Arvind Kumar, Jeanette Hellgren Kotaleski, Masanori Shimono, Naomichi Hatano, Subutai Ahmad, Yuwei Cui, Jeff Hawkins, Johanna Senk, Karolína Korvasová, Tom Tetzlaff, Moritz Helias, Tobias Kühn, Michael Denker, PierGianLuca Mana, David Dahmen, Jannis Schuecker, Sven Goedeke, Christian Keup, Katja Heuer, Rembrandt Bakker, Paul Tiesinga, Roberto Toro, Wei Qin, Alex Hadjinicolaou, Michael R. Ibbotson, Tatiana Kameneva, William W. Lytton, Lealem Mulugeta, Andrew Drach, Jerry G. Myers, Marc Horner, Rajanikanth Vadigepalli, Tina Morrison, Marlei Walton, Martin Steele, C. Anthony Hunt, Nicoladie Tam, Rodrigo Amaducci, Carlos Muñiz, Manuel Reyes-Sánchez, Francisco B. Rodríguez, Pablo Varona, Joseph T. Cronin, Matthias H. Hennig, Elisabetta Iavarone, Jane Yi, Ying Shi, Bas-Jan Zandt, Werner Van Geit, Christian Rössert, Henry Markram, Sean Hill, Christian O’Reilly, Rodrigo Perin, Huanxiang Lu, Alexander Bryson, Michal Hadrava, Jaroslav Hlinka, Ryosuke Hosaka, Mark Olenik, Conor Houghton, Nicolangelo Iannella, Thomas Launey, Rebecca Kotsakidis, Jaymar Soriano, Takatomi Kubo, Takao Inoue, Hiroyuki Kida, Toshitaka Yamakawa, Michiyasu Suzuki, Kazushi Ikeda, Samira Abbasi, Amber E. Hudson, Detlef H. Heck, Dieter Jaeger, Joel Lee, Skirmantas Janušonis, Maria Luisa Saggio, Andreas Spiegler, William C. Stacey, Christophe Bernard, Davide Lillo, Spase Petkoski, Mark Drakesmith, Derek K. Jones, Ali Sadegh Zadeh, Chandra Kambhampati, Jan Karbowski, Zeynep Gokcen Kaya, Yair Lakretz, Alessandro Treves, Lily W. Li, Joseph Lizier, Cliff C. Kerr, Timothée Masquelier, Saeed Reza Kheradpisheh, Hojeong Kim, Chang Sub Kim, Julia A. Marakshina, Alexander V. Vartanov, Anastasia A. Neklyudova, Stanislav A. Kozlovskiy, Andrey A. Kiselnikov, Kanako Taniguchi, Katsunori Kitano, Oliver Schmitt, Felix Lessmann, Sebastian Schwanke, Peter Eipert, Jennifer Meinhardt, Julia Beier, Kanar Kadir, Adrian Karnitzki, Linda Sellner, Ann-Christin Klünker, Lena Kuch, Frauke Ruß, Jörg Jenssen, Andreas Wree, Paula Sanz-Leon, Stuart A. Knock, Shih-Cheng Chien, Burkhard Maess, Thomas R. Knösche, Charles C. Cohen, Marko A. Popovic, Jan Klooster, Maarten H.P. Kole, Erik A. Roberts, Nancy J. Kopell, Daniel Kepple, Hamza Giaffar, Dima Rinberg, Alex Koulakov, Caroline Garcia Forlim, Leonie Klock, Johanna Bächle, Laura Stoll, Patrick Giemsa, Marie Fuchs, Nikola Schoofs, Christiane Montag, Jürgen Gallinat, Ray X. Lee, Greg J. Stephens, Bernd Kuhn, Luiz Tauffer, Philippe Isope, Katsuma Inoue, Yoshiyuki Ohmura, Shogo Yonekura, Yasuo Kuniyoshi, Hyun Jae Jang, Jeehyun Kwag, Marc de Kamps, Yi Ming Lai, Filipa dos Santos, K. P. Lam, Peter Andras, Julia Imperatore, Jessica Helms, Tamas Tompa, Antonieta Lavin, Felicity H. Inkpen, Michael C. Ashby, Nathan F. Lepora, Aaron R. Shifman, John E. Lewis, Zhong Zhang, Yeqian Feng, Christian Tetzlaff, Tomas Kulvicius, Yinyun Li, Rodrigo F. O. Pena, Davide Bernardi, Antonio C. Roque, Benjamin Lindner, Sebastian Vellmer, Ausra Saudargiene, Tiina Maninen, Riikka Havela, Marja-Leena Linne, Arthur Powanwe, Andre Longtin, Jesús A. Garrido, Joe W. Graham, Salvador Dura-Bernal, Sergio L. Angulo, Samuel A. Neymotin, and Srdjan D. Antic

Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurophysiology and neuropsychology, QP351-495
Published
2017
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10. Analysis Pipeline for Extracting Features of Cortical Slow Oscillations

Author

Giulia De Bonis, Miguel Dasilva, Antonio Pazienti, Maria V. Sanchez-Vives, Maurizio Mattia, and Pier Stanislao Paolucci

Subjects
slow-wave activity, slow oscillations, analysis pipeline, software tools, cortical areas, multi-electrode arrays (MEAs), Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Cortical slow oscillations (≲1 Hz) are an emergent property of the cortical network that integrate connectivity and physiological features. This rhythm, highly revealing of the characteristics of the underlying dynamics, is a hallmark of low complexity brain states like sleep, and represents a default activity pattern. Here, we present a methodological approach for quantifying the spatial and temporal properties of this emergent activity. We improved and enriched a robust analysis procedure that has already been successfully applied to both in vitro and in vivo data acquisitions. We tested the new tools of the methodology by analyzing the electrocorticography (ECoG) traces recorded from a custom 32-channel multi-electrode array in wild-type isoflurane-anesthetized mice. The enhanced analysis pipeline, named SWAP (Slow Wave Analysis Pipeline), detects Up and Down states, enables the characterization of the spatial dependency of their statistical properties, and supports the comparison of different subjects. The SWAP is implemented in a data-independent way, allowing its application to other data sets (acquired from different subjects, or with different recording tools), as well as to the outcome of numerical simulations. By using the SWAP, we report statistically significant differences in the observed slow oscillations (SO) across cortical areas and cortical sites. Computing cortical maps by interpolating the features of SO acquired at the electrode positions, we give evidence of gradients at the global scale along an oblique axis directed from fronto-lateral toward occipito-medial regions, further highlighting some heterogeneity within cortical areas. The results obtained using the SWAP will be essential for producing data-driven brain simulations. A spatial characterization of slow oscillations will also trigger a discussion on the role of, and the interplay between, the different regions in the cortex, improving our understanding of the mechanisms of generation and propagation of delta rhythms and, more generally, of cortical properties.

Published
2019
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11. Dimensional reduction in networks of non-Markovian spiking neurons: Equivalence of synaptic filtering and heterogeneous propagation delays.

Author

Maurizio Mattia, Matteo Biggio, Andrea Galluzzi, and Marco Storace

Subjects
Biology (General), QH301-705.5
Abstract

Message passing between components of a distributed physical system is non-instantaneous and contributes to determine the time scales of the emerging collective dynamics. In biological neuron networks this is due in part to local synaptic filtering of exchanged spikes, and in part to the distribution of the axonal transmission delays. How differently these two kinds of communication protocols affect the network dynamics is still an open issue due to the difficulties in dealing with the non-Markovian nature of synaptic transmission. Here, we develop a mean-field dimensional reduction yielding to an effective Markovian dynamics of the population density of the neuronal membrane potential, valid under the hypothesis of small fluctuations of the synaptic current. Within this limit, the resulting theory allows us to prove the formal equivalence between the two transmission mechanisms, holding for any synaptic time scale, integrate-and-fire neuron model, spike emission regimes and for different network states even when the neuron number is finite. The equivalence holds even for larger fluctuations of the synaptic input, if white noise currents are incorporated to model other possible biological features such as ionic channel stochasticity.

Published
2019
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12. Scaling of a Large-Scale Simulation of Synchronous Slow-Wave and Asynchronous Awake-Like Activity of a Cortical Model With Long-Range Interconnections

Author

Elena Pastorelli, Cristiano Capone, Francesco Simula, Maria V. Sanchez-Vives, Paolo Del Giudice, Maurizio Mattia, and Pier Stanislao Paolucci

Subjects
spiking neural network, slow wave activity, asynchronous activity, long range interconnections, distributed simulation, strong scaling, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Cortical synapse organization supports a range of dynamic states on multiple spatial and temporal scales, from synchronous slow wave activity (SWA), characteristic of deep sleep or anesthesia, to fluctuating, asynchronous activity during wakefulness (AW). Such dynamic diversity poses a challenge for producing efficient large-scale simulations that embody realistic metaphors of short- and long-range synaptic connectivity. In fact, during SWA and AW different spatial extents of the cortical tissue are active in a given timespan and at different firing rates, which implies a wide variety of loads of local computation and communication. A balanced evaluation of simulation performance and robustness should therefore include tests of a variety of cortical dynamic states. Here, we demonstrate performance scaling of our proprietary Distributed and Plastic Spiking Neural Networks (DPSNN) simulation engine in both SWA and AW for bidimensional grids of neural populations, which reflects the modular organization of the cortex. We explored networks up to 192 × 192 modules, each composed of 1,250 integrate-and-fire neurons with spike-frequency adaptation, and exponentially decaying inter-modular synaptic connectivity with varying spatial decay constant. For the largest networks the total number of synapses was over 70 billion. The execution platform included up to 64 dual-socket nodes, each socket mounting 8 Intel Xeon Haswell processor cores @ 2.40 GHz clock rate. Network initialization time, memory usage, and execution time showed good scaling performances from 1 to 1,024 processes, implemented using the standard Message Passing Interface (MPI) protocol. We achieved simulation speeds of between 2.3 × 109 and 4.1 × 109 synaptic events per second for both cortical states in the explored range of inter-modular interconnections.

Published
2019
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13. A Network Activity Reconfiguration Underlies the Transition from Goal to Action

Author

Encarni Marcos, Satoshi Tsujimoto, Maurizio Mattia, and Aldo Genovesio

Subjects
Biology (General), QH301-705.5
Abstract

Summary: Neurons in prefrontal cortex (PF) represent mnemonic information about current goals until the action can be selected and executed. However, the neuronal dynamics underlying the transition from goal into specific actions are poorly understood. Here, we show that the goal-coding PF network is dynamically reconfigured from mnemonic to action selection states and that such reconfiguration is mediated by cell assemblies with heterogeneous excitability. We recorded neuronal activity from PF while monkeys selected their actions on the basis of memorized goals. Many PF neurons encoded the goal, but only a minority of them did so across both memory retention and action selection stages. Interestingly, about half of this minority of neurons switched their goal preference across the goal-action transition. Our computational model led us to propose a PF network composed of heterogeneous cell assemblies with single-state and bistable local dynamics able to produce both dynamical stability and input susceptibility simultaneously. : Marcos et al. find a sudden activity reconfiguration of the PF network during the transition from goal in memory to action. Using a computational model, the authors propose a PF network, capable of reproducing the stability and susceptibility required for such process, composed of neurons with heterogeneous connection strengths. Keywords: neurophysiology, prefrontal cortex, goal, action, activity reconfiguration, neural circuits, computational neuroscience, cortical networks, attractor metastable dynamics

Published
2019
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14. Bistable perception modeled as competing stochastic integrations at two levels.

Author

Guido Gigante, Maurizio Mattia, Jochen Braun, and Paolo Del Giudice

Subjects
Biology (General), QH301-705.5
Abstract

We propose a novel explanation for bistable perception, namely, the collective dynamics of multiple neural populations that are individually meta-stable. Distributed representations of sensory input and of perceptual state build gradually through noise-driven transitions in these populations, until the competition between alternative representations is resolved by a threshold mechanism. The perpetual repetition of this collective race to threshold renders perception bistable. This collective dynamics - which is largely uncoupled from the time-scales that govern individual populations or neurons - explains many hitherto puzzling observations about bistable perception: the wide range of mean alternation rates exhibited by bistable phenomena, the consistent variability of successive dominance periods, and the stabilizing effect of past perceptual states. It also predicts a number of previously unsuspected relationships between observable quantities characterizing bistable perception. We conclude that bistable perception reflects the collective nature of neural decision making rather than properties of individual populations or neurons.

Published
2009
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15. A fluctuation-driven mechanism for slow decision processes in reverberant networks.

Author

Daniel Martí, Gustavo Deco, Maurizio Mattia, Guido Gigante, and Paolo Del Giudice

Subjects
Medicine, Science
Abstract

The spike activity of cells in some cortical areas has been found to be correlated with reaction times and behavioral responses during two-choice decision tasks. These experimental findings have motivated the study of biologically plausible winner-take-all network models, in which strong recurrent excitation and feedback inhibition allow the network to form a categorical choice upon stimulation. Choice formation corresponds in these models to the transition from the spontaneous state of the network to a state where neurons selective for one of the choices fire at a high rate and inhibit the activity of the other neurons. This transition has been traditionally induced by an increase in the external input that destabilizes the spontaneous state of the network and forces its relaxation to a decision state. Here we explore a different mechanism by which the system can undergo such transitions while keeping the spontaneous state stable, based on an escape induced by finite-size noise from the spontaneous state. This decision mechanism naturally arises for low stimulus strengths and leads to exponentially distributed decision times when the amount of noise in the system is small. Furthermore, we show using numerical simulations that mean decision times follow in this regime an exponential dependence on the amplitude of noise. The escape mechanism provides thus a dynamical basis for the wide range and variability of decision times observed experimentally.

Published
2008
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16. Qualitative-Modeling-Based Silicon Neurons and Their Networks.

Author

Takashi Kohno, Munehisa Sekikawa, Jing Li, Takuya Nanami, Kazuyuki Aihara, Alberto Mazzoni, and Maurizio Mattia

Subjects
NEURAL physiology, SILICON, DIFFERENTIAL equations
Abstract

The ionic conductance models of neuronal cells can finely reproduce a wide variety of complex neuronal activities. However, the complexity of these models has prompted the development of qualitative neuron models. They are described by differential equations with a reduced number of variables and their low-dimensional polynomials, which retain the core mathematical structures. Such simple models form the foundation of a bottom-up approach in computational and theoretical neuroscience. We proposed a qualitative-modeling-based approach for designing silicon neuron circuits, in which the mathematical structures in the polynomial-based qualitative models are reproduced by differential equations with silicon-native expressions. This approach can realize low-power-consuming circuits that can be configured to realize various classes of neuronal cells. In this article, our qualitative-modeling-based silicon neuron circuits for analog and digital implementations are quickly reviewed. One of our CMOS analog silicon neuron circuits can realize a variety of neuronal activities with a power consumption less than 72 nW. The square-wave bursting mode of this circuit is explained. Another circuit can realize Class I and II neuronal activities with about 3 nW. Our digital silicon neuron circuit can also realize these classes. An auto-associative memory realized on an all-to-all connected network of these silicon neurons is also reviewed, in which the neuron class plays important roles in its performance. [ABSTRACT FROM AUTHOR]

Published
2016
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