Micah M. Murray

EEG source imaging

OBJECTIVE Electroencephalography (EEG) is an important tool for studying the temporal dynamics of the human brains large-scale neuronal circuits. However, most EEG applications fail to capitalize on all of the datas available information, particularly that concerning the location of active sources in the brain. Localizing the sources of a given scalp measurement is only achieved by solving the so-called inverse problem. By introducing reasonable a priori constraints, the inverse problem can be solved and the most probable sources in the brain at every moment in time can be accurately localized. METHODS AND RESULTS Here, we review the different EEG source localization procedures applied during the last two decades. Additionally, we detail the importance of those procedures preceding and following source estimation that are intimately linked to a successful, reliable result. We discuss (1) the number and positioning of electrodes, (2) the varieties of inverse solution models and algorithms, (3) the integration of EEG source estimations with MRI data, (4) the integration of time and frequency in source imaging, and (5) the statistical analysis of inverse solution results. CONCLUSIONS AND SIGNIFICANCE We show that modern EEG source imaging simultaneously details the temporal and spatial dimensions of brain activity, making it an important and affordable tool to study the properties of cerebral, neural networks in cognitive and clinical neurosciences.

Topographic ERP Analyses: A Step-by-Step Tutorial Review

In this tutorial review, we detail both the rationale for as well as the implementation of a set of analyses of surface-recorded event-related potentials (ERPs) that uses the reference-free spatial (i.e. topographic) information available from high-density electrode montages to render statistical information concerning modulations in response strength, latency, and topography both between and within experimental conditions. In these and other ways these topographic analysis methods allow the experimenter to glean additional information and neurophysiologic interpretability beyond what is available from canonical waveform analyses. In this tutorial we present the example of somatosensory evoked potentials (SEPs) in response to stimulation of each hand to illustrate these points. For each step of these analyses, we provide the reader with both a conceptual and mathematical description of how the analysis is carried out, what it yields, and how to interpret its statistical outcome. We show that these topographic analysis methods are intuitive and easy-to-use approaches that can remove much of the guesswork often confronting ERP researchers and also assist in identifying the information contained within high-density ERP datasets.

Multisensory auditory–somatosensory interactions in early cortical processing revealed by high-density electrical mapping.

We investigated the time-course and scalp topography of multisensory interactions between simultaneous auditory and somatosensory stimulation in humans. Event-related potentials (ERPs) were recorded from 64 scalp electrodes while subjects were presented with auditory-alone stimulation (1000-Hz tones), somatosensory-alone stimulation (median nerve electrical pulses), and simultaneous auditory-somatosensory (AS) combined stimulation. Interaction effects were assessed by comparing the responses to combined stimulation with the algebraic sum of responses to the constituent auditory and somatosensory stimuli when they were presented alone. Spatiotemporal analysis of ERPs and scalp current density (SCD) topographies revealed AS interaction over the central/postcentral scalp which onset at approximately 50 ms post-stimulus presentation. Both the topography and timing of these interactions are consistent with multisensory integration early in the cortical processing hierarchy, in brain regions traditionally held to be unisensory.

Electrical neuroimaging based on biophysical constraints

This paper proposes and implements biophysical constraints to select a unique solution to the bioelectromagnetic inverse problem. It first shows that the brains electric fields and potentials are predominantly due to ohmic currents. This serves to reformulate the inverse problem in terms of a restricted source model permitting noninvasive estimations of Local Field Potentials (LFPs) in depth from scalp-recorded data. Uniqueness in the solution is achieved by a physically derived regularization strategy that imposes a spatial structure on the solution based upon the physical laws that describe electromagnetic fields in biological media. The regularization strategy and the source model emulate the properties of brain activitys actual generators. This added information is independent of both the recorded data and head model and suffices for obtaining a unique solution compatible with and aimed at analyzing experimental data. The inverse solutions features are evaluated with event-related potentials (ERPs) from a healthy subject performing a visuo-motor task. Two aspects are addressed: the concordance between available neurophysiological evidence and inverse solution results, and the functional localization provided by fMRI data from the same subject under identical experimental conditions. The localization results are spatially and temporally concordant with experimental evidence, and the areas detected as functionally activated in both imaging modalities are similar, providing indices of localization accuracy. We conclude that biophysically driven inverse solutions offer a novel and reliable possibility for studying brain function with the temporal resolution required to advance our understanding of the brains functional networks.

Spatiotemporal analysis of multichannel EEG: CARTOOL

This paper describes methods to analyze the brains 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.

Towards the utilization of EEG as a brain imaging tool.

Recent advances in signal analysis have engendered EEG with the status of a true brain mapping and brain imaging method capable of providing spatio-temporal information regarding brain (dys)function. Because of the increasing interest in the temporal dynamics of brain networks, and because of the straightforward compatibility of the EEG with other brain imaging techniques, EEG is increasingly used in the neuroimaging community. However, the full capability of EEG is highly underestimated. Many combined EEG-fMRI studies use the EEG only as a spike-counter or an oscilloscope. Many cognitive and clinical EEG studies use the EEG still in its traditional way and analyze grapho-elements at certain electrodes and latencies. We here show that this way of using the EEG is not only dangerous because it leads to misinterpretations, but it is also largely ignoring the spatial aspects of the signals. In fact, EEG primarily measures the electric potential field at the scalp surface in the same way as MEG measures the magnetic field. By properly sampling and correctly analyzing this electric field, EEG can provide reliable information about the neuronal activity in the brain and the temporal dynamics of this activity in the millisecond range. This review explains some of these analysis methods and illustrates their potential in clinical and experimental applications.

Glutathione Precursor, N-Acetyl-Cysteine, Improves Mismatch Negativity in Schizophrenia Patients

In schizophrenia patients, glutathione dysregulation at the gene, protein and functional levels, leads to N-methyl-D-aspartate (NMDA) receptor hypofunction. These patients also exhibit deficits in auditory sensory processing that manifests as impaired mismatch negativity (MMN), which is an auditory evoked potential (AEP) component related to NMDA receptor function. N-acetyl-cysteine (NAC), a glutathione precursor, was administered to patients to determine whether increased levels of brain glutathione would improve MMN and by extension NMDA function. A randomized, double-blind, cross-over protocol was conducted, entailing the administration of NAC (2g/day) for 60 days and then placebo for another 60 days (or vice versa). 128-channel AEPs were recorded during a frequency oddball discrimination task at protocol onset, at the point of cross-over, and at the end of the study. At the onset of the protocol, the MMN of patients was significantly impaired compared to sex- and age- matched healthy controls (p=0.003), without any evidence of concomitant P300 component deficits. Treatment with NAC significantly improved MMN generation compared with placebo (p=0.025) without any measurable effects on the P300 component. MMN improvement was observed in the absence of robust changes in assessments of clinical severity, though the latter was observed in a larger and more prolonged clinical study. This pattern suggests that MMN enhancement may precede changes to indices of clinical severity, highlighting the possible utility AEPs as a biomarker of treatment efficacy. The improvement of this functional marker may indicate an important pathway towards new therapeutic strategies that target glutathione dysregulation in schizophrenia.

Activation Timecourse of Ventral Visual Stream Object-recognition Areas: High Density Electrical Mapping of Perceptual Closure Processes

Object recognition is achieved even in circumstances when only partial information is available to the observer. Perceptual closure processes are essential in enabling such recognitions to occur. We presented successively less fragmented images while recording high-density event-related potentials (ERPs), which permitted us to monitor brain activity during the perceptual closure processes leading up to object recognition. We reveal a bilateral ERP component (Ncl) that tracks these processes (onsets 230 msec, maximal at 290 msec). Scalp-current density mapping of the Ncl revealed bilateral occipito-temporal scalp foci, which are consistent with generators in the human ventral visual stream, and specifically the lateral-occipital or LO complex as defined by hemodynamic studies of object recognition.

Rapid discrimination of visual and multisensory memories revealed by electrical neuroimaging.

Though commonly held that multisensory experiences enrich our memories and that memories influence ongoing sensory processes, their neural mechanisms remain unresolved. Here, electrical neuroimaging shows that auditory-visual multisensory experiences alter subsequent processing of unisensory visual stimuli during the same block of trials at early stages poststimulus onset and within visual object recognition areas. We show this with a stepwise analysis of scalp-recorded event-related potentials (ERPs) that statistically tested (1) ERP morphology and amplitude, (2) global electric field power, (3) topographic stability of and changes in the electric field configuration, and (4) intracranial distributed linear source estimations. Subjects performed a continuous recognition task, discriminating repeated vs. initial image presentations. Corresponding, but task-irrelevant, sounds accompanied half of the initial presentations during a given block of trials. On repeated presentations within a block of trials, only images appeared, yielding two situations-the images prior presentation was only visual or with a sound. Image repetitions that had been accompanied by sounds yielded improved memory performance accuracy (old or new discrimination) and were differentiated as early as approximately 60-136 ms from images that had not been accompanied by sounds through generator changes in areas of the right lateral-occipital complex (LOC). It thus appears that unisensory percepts trigger multisensory representations associated with them. The collective data support the hypothesis that perceptual or memory traces for multisensory auditory-visual events involve a distinct cortical network that is rapidly activated by subsequent repetition of just the unisensory visual component.

Electrical neuroimaging reveals early generator modulation to emotional words

Functional electrical neuroimaging investigated incidental emotional word processing. Previous research suggests that the brain may differentially respond to the emotional content of linguistic stimuli pre-lexically (i.e., before distinguishing that these stimuli are words). We investigated the spatiotemporal brain mechanisms of this apparent paradox and in particular whether the initial differentiation of emotional stimuli is marked by different brain generator configurations using high-density, event-related potentials. Such would support the existence of specific cerebral resources dedicated to emotional word processing. A related issue concerns the possibility of right-hemispheric specialization in the processing of emotional stimuli. Thirteen healthy men performed a go/no-go lexical decision task with bilateral word/non-word or non-word/non-word stimulus pairs. Words included equal numbers of neutral and emotional stimuli, but subjects made no explicit discrimination along this dimension. Emotional words appearing in the right visual field (ERVF) yielded the best overall performance, although the difference between emotional and neutral words was larger for left than for right visual field presentations. Electrophysiologically, ERVF presentations were distinguished from all other conditions over the 100-140 ms period by a distinct scalp topography, indicative of different intracranial generator configurations. A distributed linear source estimation (LAURA) of this distinct scalp potential field revealed bilateral lateral-occipital sources with a right hemisphere current density maximum. These data support the existence of a specialized brain network triggered by the emotional connotation of words at a very early processing stage.