Bernhard Schoelkopf
Max Planck Society
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Featured researches published by Bernhard Schoelkopf.
Electronic Journal of Statistics | 2012
Bharath K. Sriperumbudur; Kenji Fukumizu; Arthur Gretton; Bernhard Schoelkopf; Gert R. G. Lanckriet
Given two probability measures, P and Q defined on a measurable space, S, the integral probability metric (IPM) is defined as γF(P,Q) = sup {∣∣∣∣ ∫
Frontiers in Human Neuroscience | 2014
Suzanne Martens; Michael Bensch; Sebastian Halder; Jeremy Hill; Femke Nijboer; Ander Ramos-Murguialday; Bernhard Schoelkopf; Niels Birbaumer; Alireza Gharabaghi
Electroencephalography (EEG) often fails to assess both the level (i.e., arousal) and the content (i.e., awareness) of pathologically altered consciousness in patients without motor responsiveness. This might be related to a decline of awareness, to episodes of low arousal and disturbed sleep patterns, and/or to distorting and attenuating effects of the skull and intermediate tissue on the recorded brain signals. Novel approaches are required to overcome these limitations. We introduced epidural electrocorticography (ECoG) for monitoring of cortical physiology in a late-stage amytrophic lateral sclerosis patient in completely locked-in state (CLIS). Despite long-term application for a period of six months, no implant-related complications occurred. Recordings from the left frontal cortex were sufficient to identify three arousal states. Spectral analysis of the intrinsic oscillatory activity enabled us to extract state-dependent dominant frequencies at <4, ~7 and ~20 Hz, representing sleep-like periods, and phases of low and elevated arousal, respectively. In the absence of other biomarkers, ECoG proved to be a reliable tool for monitoring circadian rhythmicity, i.e., avoiding interference with the patient when he was sleeping and exploiting time windows of responsiveness. Moreover, the effects of interventions addressing the patient’s arousal, e.g., amantadine medication, could be evaluated objectively on the basis of physiological markers, even in the absence of behavioral parameters. Epidural ECoG constitutes a feasible trade-off between surgical risk and quality of recorded brain signals to gain information on the patient’s present level of arousal. This approach enables us to optimize the timing of interactions and medical interventions, all of which should take place when the patient is in a phase of high arousal. Furthermore, avoiding low-responsiveness periods will facilitate measures to implement alternative communication pathways involving brain-computer interfaces (BCI).
Archive | 2002
Jason Weston; André Elisseeff; Bernhard Schoelkopf; Fernando Pérez-Cruz
international conference on machine learning | 2014
David Lopez-Paz; Suvrit Sra; Alexander J. Smola; Zoubin Ghahramani; Bernhard Schoelkopf
international conference on machine learning | 2014
Hadi Daneshmand; Manuel Gomez-Rodriguez; Le Song; Bernhard Schoelkopf
Archive | 2002
Peter L. Bartlett; André Elisseeff; Bernhard Schoelkopf
In: ACM Press (2009) | 2009
Jonas Peters; Dominik Janzing; Arthur Gretton; Bernhard Schoelkopf
international conference on artificial intelligence and statistics | 2005
Arthur Gretton; Alexander J. Smola; Olivier Bousquet; Ralf Herbrich; Andrei Belitski; M Augath; Yusuke Murayama; J Pauls; Bernhard Schoelkopf; Nk Logothetis
international conference on learning representations | 2018
Ilya O. Tolstikhin; Olivier Bousquet; Sylvain Gelly; Bernhard Schoelkopf
international conference on machine learning | 2015
Mingming Gong; Kun Zhang; Bernhard Schoelkopf; Dacheng Tao; Philipp Geiger