High-frequency deep brain stimulation of the subthalamic nucleus can be used to treat severe obsessive-compulsive disorders that are refractory to conventional treatments. The mechanisms of action of this approach possibly rely on the modulation of associative-limbic subcortical-cortical loops, but remain to be fully elucidated. Here in 12 patients, we report the effects of high-frequency stimu...

Template-based signal detection most often relies on computing a correlation, or a dot product, between an incoming data stream and a signal template. While such a correlation results in an ongoing estimate of the magnitude of the signal in the data stream, it does not directly indicate the presence or absence of a signal. Instead, the problem of signal detection is one of model-selection. Here...

OBJECTIVE Intracranial electroencephalographic (iEEG) recordings contain "bad channels", which show non-neuronal signals. Here, we developed a new method that automatically detects iEEG bad channels using machine learning of seven signal features. METHODS The features quantified signals' variance, spatial-temporal correlation and nonlinear properties. Because the number of bad channels is usu...

In this study, we quantified performance variations of motor imagery (MI)-based brain–computer interface (BCI) systems induced by practice. Two experimental sessions were recorded from ten healthy subjects while playing a BCI-oriented video game for 2 weeks. The analysis focused on the exploration electroencephalographic (EEG) changes during mental preparation between novice and practiced subje...

Individuals are able to discriminate visual stimuli they report not consciously seeing. This phenomenon is known as “subliminal perception.” Such capacity often assumed be relatively automatic in nature and rely on stimulus-driven activity low-level cortical areas. Instead, here we asked what extent neural before stimulus presentation influences subliminal perception. We participants the locati...

OF THESIS SIGNAL FRACTION ANALYSIS AND ARTIFACT REMOVAL IN EEG The presence of artifacts, such as eye blinks, in electroencephalographic (EEG) recordings obscures the underlying processes and makes analysis difficult. Large amounts of data must often be discarded because of contamination by eye blinks, muscle activity, line noise, and pulse signals. To overcome this difficulty, signal separatio...

Predicting recovery of consciousness in patients who survive their coma but evolve to a vegetative state (recently coined unresponsive wakefulness syndrome) remains a challenge. Most previous prognostic studies have focused on the acute coma phase. A novel outcome scale (combining behavioural, aetiology, electroencephalographic, sleep electroencephalographic and somatosensory evoked potential d...