We develop machine learning and statistical tools to study cooperative phenomena occurring in brain activity at multiple scales.
Biological neural networks are characterized by strong recurrence, and widespread, bidirectional connectivity at multiple scales. From this structure emerges a complex dynamics where elements of this network cooperate at different levels to give rise, for example, to coherent behaviors and percepts. This complexity manifests itself as collective oscillations as well as more complex dymamical patterns such as Sharp-wave ripple complexes, that can be observed in electrical brain activity. These neural events are believed to play a key role in information processing, learning and behavior. Our research aims at designing better techniques to detect these events and understand their underlying mechanisms and computational role.
Ramirez-Villegas, J., Logothetis, N., Besserve, M.
Diversity of sharp wave-ripples in the CA1 of the macaque hippocampus and their brain wide signatures
45th Annual Meeting of the Society for Neuroscience (Neuroscience 2015), October 2015 (poster)
Besserve, M.
Causal Inference for Empirical Time Series Based on the Postulate of Independence of Cause and Mechanism
53rd Annual Allerton Conference on Communication, Control, and Computing, September 2015 (talk)
Besserve, M.
Independence of cause and mechanism in brain networks
DALI workshop on Networks: Processes and Causality, April 2015 (talk)
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 U.S.A, 112(46):E6379-E6387, November 2015 (article)
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):e1002257, September 2015 (article)
Shajarisales, N., Janzing, D., Schölkopf, B., Besserve, M.
Telling cause from effect in deterministic linear dynamical systems
In Proceedings of the 32nd International Conference on Machine Learning, 37, pages: 285–294, JMLR Workshop and Conference Proceedings, (Editors: F. Bach and D. Blei), JMLR, ICML, 2015 (inproceedings)
Besserve, M.
Quantifying statistical dependency
Research Network on Learning Systems Summer School, 2014 (talk)
Besserve, M., Schölkopf, B., Logothetis, N.
Unsupervised identification of neural events in local field potentials
44th Annual Meeting of the Society for Neuroscience (Neuroscience), 2014 (talk)
Ramirez-Villegas, J., Logothetis, N., Besserve, M.
Dynamical source analysis of hippocampal sharp-wave ripple episodes
Bernstein Conference, 2014 (poster)
Ramirez-Villegas, J., Logothetis, N., Besserve, M.
Cluster analysis of sharp-wave ripple field potential signatures in the macaque hippocampus
Computational and Systems Neuroscience Meeting (COSYNE), 2014 (poster)
Safavi, S., Panagiotaropoulos, T., Kapoor, V., Logothetis, N., Besserve, M.
Coupling between spiking activity and beta band spatio-temporal patterns in the macaque PFC
43rd Annual Meeting of the Society for Neuroscience (Neuroscience), 2013 (poster)
Safavi, S., Panagiotaropoulos, T., Kapoor, V., Logothetis, N., Besserve, M.
Analyzing locking of spikes to spatio-temporal patterns in the macaque prefrontal cortex
Bernstein Conference, 2013 (poster)
Logothetis, N., Eschenko, O., Murayama, Y., Augath, M., Steudel, T., Evrard, H., Besserve, M., Oeltermann, A.
Studying large-scale brain networks: electrical stimulation and neural-event-triggered fMRI
Twenty-Second Annual Computational Neuroscience Meeting (CNS*2013), July 2013, journal = {BMC Neuroscience},
year = {2013},
month = {7},
volume = {14},
number = {Supplement 1},
pages = {A1}, (talk)
Ramirez-Villegas, J., Logothetis, N., Besserve, M.
Characterization of different types of sharp-wave ripple signatures in the CA1 of the macaque hippocampus
4th German Neurophysiology PhD Meeting Networks, 2013 (poster)
Balduzzi, D., Ortega, P., Besserve, M.
Metabolic cost as an organizing principle for cooperative learning
Advances in Complex Systems, 16(02n03):1350012, 2013 (article)
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, pages: 2535-2543, (Editors: C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)
Laurent, F., Valderrama, M., Besserve, M., Guillard, M., Lachaux, J., Martinerie, J., Florence, G.
Multimodal information improves the rapid detection of mental fatigue
Biomedical Signal Processing and Control, 8(4):400 - 408, 2013 (article)
Besserve, M., Panagiotaropoulos, T., Crocker, B., Kapoor, V., Tolias, A., Panzeri, S., Logothetis, N.
Identifying endogenous rhythmic spatio-temporal patterns in micro-electrode array recordings
9th annual Computational and Systems Neuroscience meeting (Cosyne), 2012 (poster)
Besserve, M., Bartels, A., Murayama, Y., Logothetis, N.
Centrality of the Mammalian Functional Brain Network
42nd Annual Meeting of the Society for Neuroscience (Neuroscience), 2012 (poster)
Balduzzi, D., Besserve, M.
Towards a learning-theoretic analysis of spike-timing dependent plasticity
In Advances in Neural Information Processing Systems 25, pages: 2465-2473, (Editors: P Bartlett and FCN Pereira and CJC. Burges and L Bottou and KQ Weinberger), Curran Associates Inc., 26th Annual Conference on Neural Information Processing Systems (NIPS), 2012 (inproceedings)
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