Suchergebnisse

Kapoor, V.; Besserve, M.; Logothetis, N.; Panagiotaropoulos, T.: Parallel and functionally segregated processing of task phase and conscious content in the prefrontal cortex. Communications Biology 1, 215, S. 1 - 12 (2018)

Ramirez-Villegas, J.; Willeke, K.; Logothetis, N.; Besserve, M.: Dissecting the Synapse- and Frequency-Dependent Network Mechanisms of In Vivo Hippocampal Sharp Wave-Ripples. Neuron 100 (5), S. 1224 - 1240 (2018)

Ramirez-Villegas, J. F.; Willeke, K.; Logothetis, N. K.; Besserve, M.: Dissecting the frequency-dependent network mechanisms of in vivo hippocampal sharp wave-ripples. (eingereicht)

Hindriks, R.; Arsiwalla, X.; Panagiotaropoulos, T.; Besserve, M.; Verschure, P.; Logothetis, N.; Deco, G.: Discrepancies between multi-electrode LFP and CSD phase-patterns: A forward modeling study. Frontiers in Neural Circuits 10, 51, S. 1 - 18 (2016)

Ramirez-Villegas, J.; Logothetis, N.; Besserve, M.: Diversity of sharp-wave–ripple LFP signatures reveals differentiated brain-wide dynamical events. Proceedings of the National Academy of Sciences of the United States of America 112 (46), S. E6379 - E6387 (2015)

Besserve, M.; Lowe, S.; Logothetis, N.; Schölkopf, B.; Panzeri, S.: Shifts of Gamma Phase across Primary Visual Cortical Sites Reflect Dynamic Stimulus-Modulated Information Transfer. PLoS Biology 13 (9), S. 1 - 29 (2015)

Laurent, F.; Valderrama, M.; Besserve, M.; Guillard , M.; Lachaux, J.-P.; Martinerie, J.; Forence, G.: Multimodal information improves the rapid detection of mental fatigue. Biomedical Signal Processing and Control 8 (4), S. 400 - 408 (2013)

Laurent, F.; Valderrama, M.; Besserve, M.; Guillard, M.; Lachaux, J.-P.; Martinerie, J.; Forence, G.: Multimodal information improves the rapid detection of mental fatigue. Biomedical Signal Processing and Control 8 (4), S. 400 - 408 (2013)

Balduzzi, D.; Ortega, P.; Besserve, M.: Metabolic cost as an organizing principle for cooperative learning. Advances in Complex Systems 16 (02n03), 1350012, S. 1 - 18 (2013)

Logothetis, N.; Eschenko, O.; Murayama, Y.; Augath, M.; Steudel, T.; Evrard, H.; Besserve, M.; Oeltermann, A.: Hippocampal-cortical interaction during periods of subcortical silence. Nature 491 (7425), S. 547 - 553 (2012)

Chavez, M.; Besserve, M.; Le Van Quyen, M.: Dynamics of excitable neural networks with heterogeneous connectivity. Progress in Biophysics and Molecular Biology 105 (1-2), S. 29 - 33 (2011)

Besserve, M.; Martinerie, J.: Extraction of functional information from ongoing brain electrical activity: Extraction en temps-réel d'informations fonctionnelles à partir de l'activité électrique cérébrale. IRBM 32 (1), S. 27 - 34 (2011)

Besserve, M.; Schölkopf, B.; Logothetis, N.; Panzeri, S.: Causal relationships between frequency bands of extracellular signals in visual cortex revealed by an information theoretic analysis. Journal of Computational Neuroscience 29 (3), S. 547 - 566 (2010)

Geiger, P.; Besserve, M.; Winkelmann, J.; Proissl, C.; Schölkopf, B.: Coordinating Users of Shared Facilities via Data-driven Predictive Assistants and Game Theory. In: 35th Conference on Uncertainty in Artificial Intelligence (UAI 2019), 49, S. 286 - 295. 35th Conference on Uncertainty in Artificial Intelligence (UAI 2019), Tel Aviv, Israel, 22. Juli 2019 - 25. Juli 2019. Curran, Red Hook, NY, USA (2019)

Besserve, M.; Shajarisales, N.; Schölkopf, B.; Janzing, D.: Group invariance principles for causal generative models. In: International Conference on Artificial Intelligence and Statistics, 9-11 April 2018, Playa Blanca, Lanzarote, Canary Islands, S. 557 - 565 (Hg. Storkey , A.; Perez-Cruz, F.). 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018), Playa Blanca, Spain, 09. April 2018 - 11. April 2018. International Machine Learning Society, Madison, WI, USA (2018)

Shajarisales, N.; Janzing, D.; Schölkopf, B.; Besserve, M.: Telling Cause from Effect in Deterministic Linear Dynamical Systems. In: International Conference on Machine Learning, 7-9 July 2015, Lille, France, S. 285 - 294 (Hg. Bach , F.; Blei, D.). 32nd International Conference on Machine Learning (ICML 2015), Lille, France. International Machine Learning Society, Madison, WI, USA (2015)

Besserve, M.; Logothetis, N.; Schölkopf, B.: Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators. In: Advances in Neural Information Processing Systems 26, S. 2535 - 2543 (Hg. Burges, C.; Bottou, L.; Welling, M.; Ghahramani, Z.; Weinberger, K.Q.). Twenty-Seventh Annual Conference on Neural Information Processing Systems (NIPS 2013), Lake Tahoe, NV, USA. Curran, Red Hook, NY, USA (2014)

Balduzzi, D.; Besserve, M.: Towards a learning-theoretic analysis of spike-timing dependent plasticity. In: Advances in Neural Information Processing Systems 25, S. 2465 - 2473 (Hg. Bartlett, P.; Pereira, F.; Bottou, L.; Burges, C.; Weinberger, K.). Twenty-Sixth Annual Conference on Neural Information Processing Systems (NIPS 2012), Lake Tahoe, Nevada, USA, 03. Dezember 2012 - 06. Dezember 2012. Curran, Red Hook, NY, USA (2013)

Besserve, M.; Janzing, D.; Logothetis, N.; Schölkopf, B.: Finding dependencies between frequencies with the kernel cross-spectral density. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), S. 2080 - 2083. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), Praha, Czech Republic, 22. Mai 2011 - 27. Mai 2011. IEEE, Piscataway, NJ, USA (2011)

Logothetis, N.; Murayama, Y.; Ramirez-Villegas, J.; Besserve, M.; Evrard, H.: PGO wave-triggered functional MRI: mapping the networks underlying synaptic consolidation. In 46th Annual Meeting of the Society for Neuroscience (Neuroscience 2016), 670.12. 46th Annual Meeting of the Society for Neuroscience (Neuroscience 2016), San Diego, CA, USA, 12. November 2016 - 16. November 2016. (2016)