ERP correlates of word production before and after stroke in an aphasic patient

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State-Dependent Visual Processing

The temporal dynamics and anatomical correlates underlying human visual cognition are traditionally assessed as a function of stimulus properties and task demands. Any non-stimulus related activity is commonly dismissed as noise and eliminated to extract an evoked signal that is only a small fraction of the magnitude of the measured signal. We review studies that challenge this view by showing that non-stimulus related activity is not mere noise but that it has a well-structured organization which can largely determine the processing of upcoming stimuli. We review recent evidence from human electrophysiology that shows how different aspects of pre-stimulus activity such as pre-stimulus EEG frequency power and phase and pre-stimulus EEG microstates can determine qualitative and quantitative properties of both lower and higher-level visual processing. These studies show that low-level sensory processes depend on the momentary excitability of sensory cortices whereas perceptual processes leading to stimulus awareness depend on momentary pre-stimulus activity in higher-level non-visual brain areas. Also speed and accuracy of stimulus identification have likewise been shown to be modulated by pre-stimulus brain states

Right Parietal Brain Activity Precedes Perceptual Alternation of Bistable Stimuli

Momentary fluctuations of baseline activity have been shown to influence responses to sensory stimulation both behaviorally and neurophysiologically. This suggests that perceptual awareness does not solely arise from physical stimulus properties. Here we studied whether the momentary state of the brain immediately before stimulus presentation indicates how a physically unique but perceptually ambiguous stimulus will be perceived. A complex Necker cube was intermittently presented and subjects indicated whether their perception changed with respect to the preceding presentation. EEG was recorded from 256 channels. The prestimulus brain-state was defined as the spatial configuration of the scalp potential map within the 50 ms before stimulus arrival, representing the sum of all momentary ongoing brain processes. Two maps were found that doubly dissociated perceptual reversals from perceptual stability. For EEG sweeps classified as either map, distributed inverse solutions were computed and statistically compared. This yielded activity confined to a region in right inferior parietal cortex that was significantly more active before a perceptual reversal. In contrast, no significant topographic differences of the evoked potentials elicited by stable vs. reversed Necker cubes were found. This indicates that prestimulus activity in right inferior parietal cortex is associated with the perceptual chang

Spatiotemporal Analysis of Multichannel EEG: CARTOOL

This paper describes methods to analyze the brain's electric fields recorded with multichannel Electroencephalogram (EEG) and demonstrates their implementation in the software CARTOOL. It focuses on the analysis of the spatial properties of these fields and on quantitative assessment of changes of field topographies across time, experimental conditions, or populations. Topographic analyses are advantageous because they are reference independents and thus render statistically unambiguous results. Neurophysiologically, differences in topography directly indicate changes in the configuration of the active neuronal sources in the brain. We describe global measures of field strength and field similarities, temporal segmentation based on topographic variations, topographic analysis in the frequency domain, topographic statistical analysis, and source imaging based on distributed inverse solutions. All analysis methods are implemented in a freely available academic software package called CARTOOL. Besides providing these analysis tools, CARTOOL is particularly designed to visualize the data and the analysis results using 3-dimensional display routines that allow rapid manipulation and animation of 3D images. CARTOOL therefore is a helpful tool for researchers as well as for clinicians to interpret multichannel EEG and evoked potentials in a global, comprehensive, and unambiguous way

EEG Source Imaging: A Practical Review of the Analysis Steps

The electroencephalogram (EEG) is one of the oldest technologies to measure neuronal activity of the human brain. It has its undisputed value in clinical diagnosis, particularly (but not exclusively) in the identification of epilepsy and sleep disorders and in the evaluation of dysfunctions in sensory transmission pathways. With the advancement of digital technologies, the analysis of EEG has moved from pure visual inspection of amplitude and frequency modulations over time to a comprehensive exploration of the temporal and spatial characteristics of the recorded signals. Today, EEG is accepted as a powerful tool to capture brain function with the unique advantage of measuring neuronal processes in the time frame in which these processes occur, namely in the sub-second range. However, it is generally stated that EEG suffers from a poor spatial resolution that makes it difficult to infer to the location of the brain areas generating the neuronal activity measured on the scalp. This statement has challenged a whole community of biomedical engineers to offer solutions to localize more precisely and more reliably the generators of the EEG activity. High-density EEG systems combined with precise information of the head anatomy and sophisticated source localization algorithms now exist that convert the EEG to a true neuroimaging modality. With these tools in hand and with the fact that EEG still remains versatile, inexpensive and portable, electrical neuroimaging has become a widely used technology to study the functions of the pathological and healthy human brain. However, several steps are needed to pass from the recording of the EEG to 3-dimensional images of neuronal activity. This review explains these different steps and illustrates them in a comprehensive analysis pipeline integrated in a stand-alone freely available academic software: Cartool. The information about how the different steps are performed in Cartool is only meant as a suggestion. Other EEG source imaging software may apply similar or different approaches to the different steps

Giant Optical Non-linearity induced by a Single Two-Level System interacting with a Cavity in the Purcell Regime

A two-level system that is coupled to a high-finesse cavity in the Purcell regime exhibits a giant optical non-linearity due to the saturation of the two-level system at very low intensities, of the order of one photon per lifetime. We perform a detailed analysis of this effect, taking into account the most important practical imperfections. Our conclusion is that an experimental demonstration of the giant non-linearity should be feasible using semiconductor micropillar cavities containing a single quantum dot in resonance with the cavity mode.Comment: 40 pages, 16 figures, accepted in Phys. Rev.

Electrical neuroimaging of music processing reveals mid-latency changes with level of musical expertise

This original research focused on the effect of training intensity on cerebral and behavioral processing of complex music using high-density event-related potential (ERP) approaches. Recently we have been able to show progressive changes with training in grey and white matter and higher order brain functioning using (f)MRI ((functional) Magnetic Resonance Imaging), as well as changes in musical and general cognitive functioning. The current study investigated the same population of non-musicians, amateur pianists and expert pianists using spatio-temporal ERP analysis, by means of microstate analysis, and ERP source imaging. The stimuli consisted of complex musical compositions containing three levels of transgression of musical syntax at closure that participants appraised. ERP waveforms, microstates and underlying brain sources revealed gradual differences according to expertise in a 300-500 ms window after the onset of the terminal chords of the pieces. Within this time-window, processing seemed to concern context-based memory updating, indicated by a P3b-like component or microstate for which underlying sources were localized in right middle temporal gyrus, anterior cingulate and right parahippocampal areas. Given that the 3 expertise groups were carefully matched for demographic factors, these results provide evidence of the progressive impact of training on brain and behavior

Functional Deficit and Recovery of Developing Sensorimotor Networks following Neonatal Hypoxic-Ischemic Injury in the Rat

Neonatal hypoxia-ischemia (HI) is the most important cause of brain injury in the newborn. Here we studied structural alterations and functional perturbations of developing large-scale sensorimotor cortical networks in a rat model of moderate HI at postnatal day 3 (P3). At the morphological level, HI led to a disorganized barrel pattern in the somatosensory cortex without detectable histological changes in the motor cortex. Functional effects were addressed by means of epicranial mapping of somatosensory-evoked potentials (SEPs) during the postischemic recovery period. At P10, SEPs were immature and evoked activity was almost restricted to the somatosensory and motor cortices of the contralateral hemisphere. Peak and topographic analyses of epicranial potentials revealed that responses were profoundly depressed in both sensory and motor areas of HI-lesioned animals. At the end of the postnatal period at P21, responses involved networks in both hemispheres. SEP amplitude was still depressed in the injured sensory region, but it completely recovered in the motor area. These results suggest a process of large-scale network plasticity in sensorimotor circuits after perinatal ischemic injury. The model provides new perspectives for investigating the temporal and spatial characteristics of the recovery process following HI and eventually developing therapeutic intervention