The challenge of controlling an auditory BCI in the case of severe motor disability.

Background: The locked-in syndrome (LIS), due to a lesion in the pons, impedes communication. This situation can also be met after some severe brain injury or in advanced Amyotrophic Lateral Sclerosis (ALS). In the most severe condition, the persons cannot communicate at all because of a complete oculomotor paralysis (Complete LIS or CLIS).

Active inference as a unifying, generic and adaptive framework for a P300-based BCI.

Objective: Going adaptive is a major challenge for the field of brain-computer interface (BCI). This entails a machine that optimally articulates inference about the user's intentions and its own actions. Adaptation can operate over several dimensions which calls for a generic and flexible framework.

EEG artifact correction strategies for online trial-by-trial analysis.

Unlabelled: Brain-machine interfaces (BMIs) use brain signals to control closed-loop systems in real-time. This comes with substantial challenges, such as having to remove artifacts in order to extract reliable features, especially when using electroencephalography (EEG). Some approaches have been described in the literature to address online artifact correction.

Incorporation of recent waking-life experiences in dreams correlates with frontal theta activity in REM sleep.

Rapid eye movement (REM) sleep and its main oscillatory feature, frontal theta, have been related to the processing of recent emotional memories. As memories constitute much of the source material for our dreams, we explored the link between REM frontal theta and the memory sources of dreaming, so as to elucidate the brain activities behind the formation of dream content. Twenty participants were woken for dream reports in REM and slow wave sleep (SWS) while monitored using electroencephalography.

Active SAmpling Protocol (ASAP) to Optimize Individual Neurocognitive Hypothesis Testing: A BCI-Inspired Dynamic Experimental Design.

The relatively young field of Brain-Computer Interfaces has promoted the use of electrophysiology and neuroimaging in real-time. In the meantime, cognitive neuroscience studies, which make extensive use of functional exploration techniques, have evolved toward model-based experiments and fine hypothesis testing protocols. Although these two developments are mostly unrelated, we argue that, brought together, they may trigger an important shift in the way experimental paradigms are being designed, which should prove fruitful to both endeavors.

Improving BCI performance through co-adaptation: applications to the P300-speller.

A well-known neurophysiological marker that can easily be captured with electroencephalography (EEG) is the so-called P300: a positive signal deflection occurring at about 300 ms after a relevant stimulus. This brain response is particularly salient when the target stimulus is rare among a series of distracting stimuli, whatever the type of sensory input. Therefore, it has been proposed and extensively studied as a possible feature for direct brain-computer communication.

Toward a new application of real-time electrophysiology: online optimization of cognitive neurosciences hypothesis testing.

Brain-computer interfaces (BCIs) mostly rely on electrophysiological brain signals. Methodological and technical progress has largely solved the challenge of processing these signals online. The main issue that remains, however, is the identification of a reliable mapping between electrophysiological measures and relevant states of mind.

Impaired pitch perception and memory in congenital amusia: the deficit starts in the auditory cortex.

Congenital amusia is a lifelong disorder of music perception and production. The present study investigated the cerebral bases of impaired pitch perception and memory in congenital amusia using behavioural measures, magnetoencephalography and voxel-based morphometry. Congenital amusics and matched control subjects performed two melodic tasks (a melodic contour task and an easier transposition task); they had to indicate whether sequences of six tones (presented in pairs) were the same or different.

Adaptive training session for a P300 speller brain-computer interface.

With a brain-computer interface (BCI), it is nowadays possible to achieve a direct pathway between the brain and computers thanks to the analysis of some particular brain activities. The detection of even-related potentials, like the P300 in the oddball paradigm exploited in P300-speller, provides a way to create BCIs by assigning several detected ERP to a command. Due to the noise present in the electroencephalographic signal, the detection of an ERP and its different components requires efficient signal processing and machine learning techniques.

EEG sensor selection by sparse spatial filtering in P300 speller brain-computer interface.

A Brain-Computer Interface (BCI) is a specific type of human-machine interface that enables communication between a subject/patient and a computer by direct control from decoding of brain activity. This paper deals with the P300-speller application that enables to write a text based on the oddball paradigm. To improve the ergonomics and minimize the cost of such a BCI, reducing the number of electrodes is mandatory.

Topographical dynamics of brain connections for the design of asynchronous brain-computer interfaces.

This article presents a new processing method to design brain-computer interfaces (BCIs). It shows how to use the perturbations of the communication between different cortical areas due to a cognitive task. For this, the network of the cerebral connections is built from correlations between cortical areas at specific frequencies and is analyzed using graph theory.

Short-term effects of GSM mobiles phones on spectral components of the human electroencephalogram.

The aim of the study was to investigate whether the GSM (global system for mobile) signals affect the electrical activity of the human brain. Nine healthy subjects and six temporal epileptic patients were exposed to radiofrequencies emitted by a GSM mobile phone signals. Electroencephalographic (EEG) signals were recorded using surface electrodes with and without radiofrequency.

Scalp localization of human auditory cortical activity modified by GSM electromagnetic fields.

Purpose: This study attempted to determine whether there is a localized effect of GSM (Global System for Mobile communications) microwaves by studying the Auditory Evoked Potentials (AEP) recorded at the scalp of nine healthy subjects and six epileptic patients.

Materials And Methods: We determined the influence of GSM RadioFrequency (RF) on parameters characterizing the AEP in time or/and frequency domains. A parameter selection method using SVM (Support Vector Machines)-based criteria allowed us to estimate those most altered by the radiofrequencies.