Our project focuses on developing machine learning and statistical approached to anlayze 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.
M. Besserve, N. Logothetis, B. Schölkopf
(2013). Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators In: Advances in Neural Information Processing Systems 26, (Ed) C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger, 2535–2543, 27th Annual Conference on Neural Information Processing Systems (NIPS 2013)
NK. Logothetis, O. Eschenko, Y. Murayama, M. Augath, T. Steudel, HC. Evrard, M. Besserve, A. Oeltermann
(2013). Studying large-scale brain networks: electrical stimulation and neural-event-triggered fMRI Keynote Lecture, Twenty-Second Annual Computational Neuroscience Meeting (CNS*2013)
D. Balduzzi, M. Besserve
(2012). Towards a learning-theoretic analysis of spike-timing dependent plasticity In: Advances in Neural Information Processing Systems 25, (Ed) P Bartlett and FCN Pereira and CJC. Burges and L Bottou and KQ Weinberger, Curran Associates Inc., 2465–2473, 26th Annual Conference on Neural Information Processing Systems (NIPS 2012)
T. Panagiotaropoulos, M. Besserve, B. Crocker, V. Kapoor, AS. Tolias, S. Panzeri, NK. Logothetis
(2011). Spatiotemporal mapping of rhythmic activity in the inferior convexity of the macaque prefrontal cortex 41, (239.15), 41st Annual Meeting of the Society for Neuroscience (Neuroscience 2011)