Lesions in deep gray nuclei after severe traumatic brain injury predict neurologic outcome.

Purpose: This study evaluates the correlation between injuries to deep gray matter nuclei, as quantitated by lesions in these nuclei on MR T2 Fast Spin Echo (T2 FSE) images, with 6-month neurological outcome after severe traumatic brain injury (TBI).

Materials And Methods: Ninety-five patients (80 males, mean age = 36.7y) with severe TBI were prospectively enrolled.

Riemannian Geometry Applied to Detection of Respiratory States From EEG Signals: The Basis for a Brain-Ventilator Interface.

Goal: During mechanical ventilation, patient-ventilator disharmony is frequently observed and may result in increased breathing effort, compromising the patient's comfort and recovery. This circumstance requires clinical intervention and becomes challenging when verbal communication is difficult. In this study, we propose a brain-computer interface (BCI) to automatically and noninvasively detect patient-ventilator disharmony from electroencephalographic (EEG) signals: a brain-ventilator interface (BVI).

Neurophysiological Evidence for a Cortical Contribution to the Wakefulness-Related Drive to Breathe Explaining Hypocapnia-Resistant Ventilation in Humans.

Unlabelled: Spontaneous ventilation in mammals is driven by automatic brainstem networks that generate the respiratory rhythm and increase ventilation in the presence of increased carbon dioxide production. Hypocapnia decreases the drive to breathe and induces apnea. In humans, this occurs during sleep but not during wakefulness.

Electroencephalographic detection of respiratory-related cortical activity in humans: from event-related approaches to continuous connectivity evaluation.

The presence of a respiratory-related cortical activity during tidal breathing is abnormal and a hallmark of respiratory difficulties, but its detection requires superior discrimination and temporal resolution. The aim of this study was to validate a computational method using EEG covariance (or connectivity) matrices to detect a change in brain activity related to breathing. In 17 healthy subjects, EEG was recorded during resting unloaded breathing (RB), voluntary sniffs, and breathing against an inspiratory threshold load (ITL).

Revisiting mu suppression in autism spectrum disorder.

Two aspects of the EEG literature lead us to revisit mu suppression in Autism Spectrum Disorder (ASD). First and despite the fact that the mu rhythm can be functionally segregated in two discrete sub-bands, 8-10 Hz and 10-12/13 Hz, mu-suppression in ASD has been analyzed as a homogeneous phenomenon covering the 8-13 Hz frequency. Second and although alpha-like activity is usually found across the entire scalp, ASD studies of action observation have focused on the central electrodes (C3/C4).

Beta, but not gamma, band oscillations index visual form-motion integration.

Electrophysiological oscillations in different frequency bands co-occur with perceptual, motor and cognitive processes but their function and respective contributions to these processes need further investigations. Here, we recorded MEG signals and seek for percept related modulations of alpha, beta and gamma band activity during a perceptual form/motion integration task. Participants reported their bound or unbound perception of ambiguously moving displays that could either be seen as a whole square-like shape moving along a Lissajou's figure (bound percept) or as pairs of bars oscillating independently along cardinal axes (unbound percept).

Response-specific slowing in older age revealed through differential stimulus and response effects on P300 latency and reaction time.

Older age produces numerous changes in cognitive processes, including slowing in the rate of mental processing speed. There has been controversy over the past three decades about whether this slowing is generalized or process-specific. A growing literature indicates that it is process-specific and suggests it is most dramatic at the interface where a stimulus input is translated into a response output.

Anatomical connectivity influences both intra- and inter-brain synchronizations.

Recent development in diffusion spectrum brain imaging combined to functional simulation has the potential to further our understanding of how structure and dynamics are intertwined in the human brain. At the intra-individual scale, neurocomputational models have already started to uncover how the human connectome constrains the coordination of brain activity across distributed brain regions. In parallel, at the inter-individual scale, nascent social neuroscience provides a new dynamical vista of the coupling between two embodied cognitive agents.

Does the brain know who is at the origin of what in an imitative interaction?

Brain correlates of the sense of agency have recently received increased attention. However, the explorations remain largely restricted to the study of brains in isolation. The prototypical paradigm used so far consists of manipulating visual perception of own action while asking the subject to draw a distinction between self- versus externally caused action.

Human gamma oscillations during slow wave sleep.

Neocortical local field potentials have shown that gamma oscillations occur spontaneously during slow-wave sleep (SWS). At the macroscopic EEG level in the human brain, no evidences were reported so far. In this study, by using simultaneous scalp and intracranial EEG recordings in 20 epileptic subjects, we examined gamma oscillations in cerebral cortex during SWS.

Improving quantification of functional networks with EEG inverse problem: evidence from a decoding point of view.

Decoding experimental conditions from single trial Electroencephalographic (EEG) signals is becoming a major challenge for the study of brain function and real-time applications such as Brain Computer Interface. EEG source reconstruction offers principled ways to estimate the cortical activities from EEG signals. But to what extent it can enhance informative brain signals in single trial has not been addressed in a general setting.

[Seizure prediction: from myth to reality].

Introduction: Clinical, metabolic and electrophysiologic studies suggest the existence of a preictal state, a transition between the interictal state and seizure.

State Of The Art: Analysis of the intracranial EEG by mathematical methods shows changes of the brain dynamics several minutes before the occurrence of partial seizures. These modifications can be widespread and not restricted to the epileptogenic focus, which would explain why they can also be detected from scalp EEG.

Ten years of Nature Reviews Neuroscience: insights from the highly cited.

To celebrate the first 10 years of Nature Reviews Neuroscience, we invited the authors of the most cited article of each year to look back on the state of their field of research at the time of publication and the impact their article has had, and to discuss the questions that might be answered in the next 10 years. This selection of highly cited articles provides interesting snapshots of the progress that has been made in diverse areas of neuroscience. They show the enormous influence of neuroimaging techniques and highlight concepts that have generated substantial interest in the past decade, such as neuroimmunology, social neuroscience and the 'network approach' to brain function.

Inter-brain synchronization during social interaction.

During social interaction, both participants are continuously active, each modifying their own actions in response to the continuously changing actions of the partner. This continuous mutual adaptation results in interactional synchrony to which both members contribute. Freely exchanging the role of imitator and model is a well-framed example of interactional synchrony resulting from a mutual behavioral negotiation.

Shifting visual attention away from fixation is specifically associated with alpha band activity over ipsilateral parietal regions.

We studied brain activity during the displacement of attention in a modified visuo-spatial orienting paradigm. Using a behaviorally relevant no-shift condition as a control, we asked whether ipsi- or contralateral parietal alpha band activity is specifically related to covert shifts of attention. Cue-related event-related potentials revealed an attention directing anterior negativity (ADAN) contralateral to the shift of attention and P3 and contingent negative variation waveforms that were enhanced in both shift conditions as compared to the no-shift task.

Functional modularity of background activities in normal and epileptic brain networks.

We analyze the connectivity structure of weighted brain networks extracted from spontaneous magnetoencephalographic signals of healthy subjects and epileptic patients (suffering from absence seizures) recorded at rest. We find that, for the activities in the 5-14 Hz range, healthy brains exhibit a sparse connectivity, whereas the brain networks of patients display a rich connectivity with a clear modular structure. Our results suggest that modularity plays a key role in the functional organization of brain areas during normal and pathological neural activities at rest.

Mapping interictal oscillations greater than 200 Hz recorded with intracranial macroelectrodes in human epilepsy.

Interictal high-frequency oscillations over 200 Hz have been recorded with microelectrodes in the seizure onset zone of epileptic patients suffering from mesial temporal lobe epilepsy. Recent work suggests that similar high-frequency oscillations can be detected in the seizure onset zone using standard diagnostic macroelectrodes. However, only a few channels were examined in these studies, so little information is available on the spatial extent of high-frequency oscillations.

Complex modular structure of large-scale brain networks.

Modular structure is ubiquitous among real-world networks from related proteins to social groups. Here we analyze the modular organization of brain networks at a large scale (voxel level) extracted from functional magnetic resonance imaging signals. By using a random-walk-based method, we unveil the modularity of brain webs and show modules with a spatial distribution that matches anatomical structures with functional significance.

Assessment of bursting activity and interspike intervals variability: a case study for methodological comparison.

The detection and characterization of bursting activity remains a topic where no consensual definition has been reached so far. We compare here three different approaches of spike trains variability: statistical characterization (average frequency, coefficient of variation), burst detection (Poisson and rank surprise) and multi-scale analysis (detrended fluctuations analysis). Using both real and simulated data, we show that Poisson surprise provides information closely related to the coefficient of variation and that rank surprise detects significant bursts which are associated with long-range correlations.

Simultaneous MEG and intracranial EEG recordings during attentive reading.

The relationship between neural oscillations recorded at various spatial scales remains poorly understood partly due to an overall dearth of studies utilizing simultaneous measurements. In an effort to study quantitative markers of attention during reading, we performed simultaneous magnetoencephalography (MEG) and intracranial electroencephalography (iEEG) recordings in four epileptic patients. Patients were asked to attend to a specific color when presented with an intermixed series of red words and green words, with words of a given color forming a cohesive story.

Cortical local and long-range synchronization interplay in human absence seizure initiation.

Brain activity relies on transient, fluctuating interactions between segregated neuronal populations. Synchronization within a single and between distributed neuronal clusters reflects the dynamics of these cooperative patterns. Thus absence epilepsy can be used as a model for integrated, large-scale investigation of the emergence of pathological collective dynamics in the brain.

Enter feelings: somatosensory responses following early stages of visual induction of emotion.

In a MEG experiment, we imaged the early dynamics of the human cerebral cortex during the induction of emotion by visual stimuli. We tested the hypothesis that early cortical responses would correlate with the emotional competence of visual stimuli and subsequent subjective ratings of feeling in a set of specific target regions important for somatosensory, attentional, and motivational functions, just after initial visual and appraisal related cortical responses to picture presentation. Relative to the neutral condition, cortical responses, during the 350-500 ms phase of the MEG evoked response, were stronger for both pleasant and unpleasant stimuli in the orbitofrontal cortex, ventromedial prefrontal cortex, anterior cingulate and somatosensory cortices.

Dynamic small-world behavior in functional brain networks unveiled by an event-related networks approach.

There is growing interest in studying the role of connectivity patterns in brain functions. In recent years, functional brain networks were found to exhibit small-world properties during different brain states. In previous studies, time-independent networks were recovered from long time periods of brain activity.

Classification methods for ongoing EEG and MEG signals.

Classification algorithms help predict the qualitative properties of a subject's mental state by extracting useful information from the highly multivariate non-invasive recordings of his brain activity. In particular, applying them to Magneto-encephalography (MEG) and electro-encephalography (EEG) is a challenging and promising task with prominent practical applications to e.g.

Rapid interactions between the ventral visual stream and emotion-related structures rely on a two-pathway architecture.

Visual attention can be driven by the affective significance of visual stimuli before full-fledged processing of the stimuli. Two kinds of models have been proposed to explain this phenomenon: models involving sequential processing along the ventral visual stream, with secondary feedback from emotion-related structures ("two-stage models"); and models including additional short-cut pathways directly reaching the emotion-related structures ("two-pathway models"). We tested which type of model would best predict real magnetoencephalographic responses in subjects presented with arousing visual stimuli, using realistic models of large-scale cerebral architecture and neural biophysics.