3D Statistical Parametric Mapping of EEG Source Spectra by Means of Variable Resolution Electromagnetic Tomography (VARETA)

Attentional bias of competitive interactions in neuronal networks of early visual processing in the human brain

Multiple objects in a visual scene compete for neuronal representation. We investigated competitive neuronal dynamics in cortical networks of early visual processing in the human brain. Coloured picture streams flickered at 7.42 Hz, evoking the steady-state visual evoked potential (SSVEP), an electrophysiological response of neuronal populations in early visual areas synchronised by the external pacemaker. While these picture streams were at a fixed location in the upper left and right quadrant, respectively, additional competing picture streams flickering at a different frequency were continuously changing the distance to the stationary streams by slow motion. Analysis of the 7.42 Hz SSVEP amplitude revealed significant amplitude decreases when the competing stimulus was closer than about 4.5 degrees of visual angle. Sources of the SSVEP suppression effect were found in early visual areas of the ventral and dorsal processing streams. Attending the stationary stimulus resulted in no difference in 7.42 Hz SSVEP amplitude regardless of spatial separation to the competing stimulus. Contrary to the predictions of the model, we found co-amplification of the competing stimulus at close spatial proximity accompanied by an increase of an intermodulation frequency, suggesting integrated neuronal processing of target and competing stimuli when both streams are close together.

Bayesian M/EEG source reconstruction with spatio-temporal priors

This article proposes a Bayesian spatio-temporal model for source reconstruction of M/EEG data. The usual two-level probabilistic model implicit in most distributed source solutions is extended by adding a third level which describes the temporal evolution of neuronal current sources using time-domain General Linear Models (GLMs). These comprise a set of temporal basis functions which are used to describe event-related M/EEG responses. This places M/EEG analysis in a statistical framework that is very similar to that used for PET and fMRI. The experimental design can be coded in a design matrix, effects of interest characterized using contrasts and inferences made using posterior probability maps. Importantly, as is the case for single-subject fMRI analysis, trials are treated as fixed effects and the approach takes into account between-trial variance, allowing valid inferences to be made on single-subject data. The proposed probabilistic model is efficiently inverted by using the Variational Bayes framework under a convenient mean-field approximation (VB-GLM). The new method is tested with biophysically realistic simulated data and the results are compared to those obtained with traditional spatial approaches like the popular Low Resolution Electromagnetic TomogrAphy (LORETA) and minimum variance Beamformer. Finally, the VB-GLM approach is used to analyze an EEG data set from a face processing experiment.

Sources of synchronized induced Gamma-Band responses during a simple object recognition task: a replication study in human MEG

Natural stimuli are compiled of numerous features, which are cortically represented in dispersed structures. Synchronized oscillations in the Gamma-Band (>30 Hz; induced Gamma-Band Responses, iGBRs), are regarded as a plausible mechanism to re-integrate these regions into a meaningful cortical object representation. Using electroencephalography (EEG) it was demonstrated that the generators of iGBRs can be localized to temporal, parietal, posterior, and frontal areas. The present magnetoencephalogram (MEG) study intended to replicate these findings in order contribute to the ongoing debate regarding the possible functional difference of high-frequency signals as measured by both techniques. During a standard object recognition task we found an augmentation of the iGBR after the presentation of meaningful as opposed to meaningless stimuli at approximately 160-440 ms after stimulus onset. This peak was localized to inferior temporal gyri, superior parietal lobules and the right middle frontal gyrus. Importantly, most of these brain structures were significantly phase-locked to each other. The implications of these results are twofold: (1) they present further evidence for the view that iGBRs signify neuronal activity in a broadly distributed network during object recognition. (2) MEG is well suited to detect induced high-frequency oscillations with a very similar morphology as revealed by EEG recordings, thereby eliminating known problems with electroencephalographical methods (e.g. reference confounds). In contrast to the iGBR, the localization of event-related fields (ERFs) and evoked Gamma-Band Response (eGBRs) revealed generators in focal visual areas, and thus, seem to mirror early sensory processing.

Processing of abstract rule violations in audition

The ability to encode rules and to detect rule-violating events outside the focus of attention is vital for adaptive behavior. Our brain recordings reveal that violations of abstract auditory rules are processed even when the sounds are unattended. When subjects performed a task related to the sounds but not to the rule, rule violations impaired task performance and activated a network involving supratemporal, parietal and frontal areas although none of the subjects acquired explicit knowledge of the rule or became aware of rule violations. When subjects tried to behaviorally detect rule violations, the brain's automatic violation detection facilitated intentional detection. This shows the brain's capacity for abstraction – an important cognitive function necessary to model the world. Our study provides the first evidence for the task-independence (i.e. automaticity) of this ability to encode abstract rules and for its immediate consequences for subsequent mental processes.

Directed cortical information flow during human object recognition: analyzing induced EEG gamma-band responses in brain's source space

The increase of induced gamma-band responses (iGBRs; oscillations >30 Hz) elicited by familiar (meaningful) objects is well established in electroencephalogram (EEG) research. This frequency-specific change at distinct locations is thought to indicate the dynamic formation of local neuronal assemblies during the activation of cortical object representations. As analytically power increase is just a property of a single location, phase-synchrony was introduced to investigate the formation of large-scale networks between spatially distant brain sites. However, classical phase-synchrony reveals symmetric, pair-wise correlations and is not suited to uncover the directionality of interactions. Here, we investigated the neural mechanism of visual object processing by means of directional coupling analysis going beyond recording sites, but rather assessing the directionality of oscillatory interactions between brain areas directly. This study is the first to identify the directionality of oscillatory brain interactions in source space during human object recognition and suggests that familiar, but not unfamiliar, objects engage widespread reciprocal information flow. Directionality of cortical information-flow was calculated based upon an established Granger-Causality coupling-measure (partial-directed coherence; PDC) using autoregressive modeling. To enable comparison with previous coupling studies lacking directional information, phase-locking analysis was applied, using wavelet-based signal decompositions. Both, autoregressive modeling and wavelet analysis, revealed an augmentation of iGBRs during the presentation of familiar objects relative to unfamiliar controls, which was localized to inferior-temporal, superior-parietal and frontal brain areas by means of distributed source reconstruction. The multivariate analysis of PDC evaluated each possible direction of brain interaction and revealed widespread reciprocal information-transfer during familiar object processing. In contrast, unfamiliar objects entailed a sparse number of only unidirectional connections converging to parietal areas. Considering the directionality of brain interactions, the current results might indicate that successful activation of object representations is realized through reciprocal (feed-forward and feed-backward) information-transfer of oscillatory connections between distant, functionally specific brain areas.

Recognizing a mother's voice in the persistent vegetative state

We studied an 8-year-old boy after a near-drowning left him in a vegetative state (VS) for 4 years before the study. Findings fulfilled all clinical criteria for the diagnosis of VS. The purpose of this study was to investigate whether there was significant differential activation of the brain in response to hearing his mother's voice compared with the voices of unknown women. The data were assessed using quantitative electric tomography (QEEGt), a technique that combines anatomical information of the brain by MRI with EEG patterns to estimate the sources of the EEG within the brain. We found significant differences for EEG frequencies from 14-58 Hz, with a peak at 33.2 Hz (gamma band). The 3D reconstruction showed that these statistical differences were localized in the lateral and posterior regions of the left hemisphere. No significant differences were found between unknown women vs. basal conditions. These results demonstrate recognition of the mother's voice and indicate high-level residual linguistic processing in a patient meeting clinical criteria for VS. These findings launch new ethical and practical implications for the management of VS patients.

Electrophysiological subtypes of psychotic states

OBJECTIVE

This research sought neurobiological features common to psychotic states displayed by patients with different clinical diagnoses.

METHOD

Cluster analysis with quantitative electroencephalographic (QEEG) variables was used to subtype drug-naïve, non-medicated, and medicated schizophrenic, depressed and alcoholic patients with psychotic symptoms, from the USA and Germany. QEEG source localization brain images were computed for each cluster.

RESULTS

Psychotic patients with schizophrenia, depression and alcoholism, and drug- naïve schizophrenic patients, were distributed among six clusters. QEEG images revealed one set of brain regions differentially upregulated in each cluster and another group of structures downregulated in the same way in every cluster.

CONCLUSION

Subtypes previously found among 94 schizophrenic patients were replicated in a sample of 390 non-schizophrenic as well as schizophrenic psychotics, and displayed common neurobiological abnormalities. Collaborative longitudinal studies using these economical methods might improve differential understanding and treatment of patients based upon these features rather than clinical symptoms.

Toward a better understanding of the pathophysiology of OCD SSRI responders: QEEG source localization

OBJECTIVE

To demonstrate the utility of three-dimensional source localization of the scalp-recorded electroencephalogram (EEG) for the identification of the most probable underlying brain dysfunction in patients with obsessive-compulsive disorder (OCD).

METHOD

Eyes-closed resting EEG data was recorded from the scalp locations of the International 10/20 System. Variable resolution electromagnetic tomography (VARETA) was applied to artifact-free EEG data. This mathematical algorithm estimates the source generators of EEG recorded from the scalp.

RESULTS

An excess in the alpha range was found with sources in the corpus striatum, in the orbito-frontal and temporo-frontal regions in untreated OCD patients. This abnormality was seen to decrease following successful treatment with paroxetine.

CONCLUSION

The VARETA findings of an activation/deactivation pattern in cortical and subcortical structures in paroxetine-responsive patients are in good accordance with data obtained in previously published positron emission tomography studies related to current hypotheses of a thalamo-striatal-frontal feedback loop being relevant for understanding the pathophysiology of OCD.

Sustained spatial attention to vibration is mediated in primary somatosensory cortex

Focusing attention to a specific body location has been shown to improve processing of events presented at this body location. One important debate concerns the stage in the somatosensory pathway at which the neural response is modulated when one attends to a tactile stimulus. Previous studies focused on components of the somatosensory evoked potential to transient stimuli, and demonstrated an early cortical attentional modulation. The neural basis of sustained spatial stimulus processing with continuous stimulation remains, however, largely unexplored. A way to approach this topic is to present vibrating stimuli with different frequencies for several seconds simultaneously to different body locations while subjects have to attend to the one or the other location. The amplitude of the somatosensory steady-state evoked potential (SSSEP) elicited by these vibrating stimuli increases with attention. On the basis of 128 electrode recordings, we investigated the topographical distribution and the underlying cortical sources by means of a VARETA approach of this attentional amplitude modulation of the SSSEP. Sustained spatial attention was found to be mediated in primary somatosensory cortex with no differences in SSSEP amplitude topographies between attended and unattended body locations. These result patterns were seen as evidence for a low-level sensory gain control mechanism in tactile spatial attention.

Repetition suppression of induced gamma band responses is eliminated by task switching

The formation of cortical object representations requires the activation of cell assemblies, correlated by induced oscillatory bursts of activity > 20 Hz (induced gamma band responses; iGBRs). One marker of the functional dynamics within such cell assemblies is the suppression of iGBRs elicited by repeated stimuli. This effect is commonly interpreted as a signature of 'sharpening' processes within cell-assemblies, which are behaviourally mirrored in repetition priming effects. The present study investigates whether the sharpening of primed objects is an automatic consequence of repeated stimulus processing, or whether it depends on task demands. Participants performed either a 'living/non-living' or a 'bigger/smaller than a shoebox' classification on repeated pictures of everyday objects. We contrasted repetition-related iGBR effects after the same task was used for initial and repeated presentations (no-switch condition) with repetitions after a task-switch occurred (switch condition). Furthermore, we complemented iGBR analysis by examining other brain responses known to be modulated by repetition-related memory processes (evoked gamma oscillations and event-related potentials; ERPs). The results obtained for the 'no-switch' condition replicated previous findings of repetition suppression of iGBRs at 200-300 ms after stimulus onset. Source modelling showed that this effect was distributed over widespread cortical areas. By contrast, after a task-switch no iGBR suppression was found. We concluded that iGBRs reflect the sharpening of a cell assembly only within the same task. After a task switch the complete object representation is reactivated. The ERP (220-380 ms) revealed suppression effects independent of task demands in bilateral posterior areas and might indicate correlates of repetition priming in perceptual structures.

Mechanisms for detecting auditory temporal and spectral deviations operate over similar time windows but are divided differently between the two hemispheres

In order to keep track of potentially relevant information in the acoustic environment, the human brain processes sounds to a high extent even when they are not attended: it extracts basic features, encodes regularities, and detects deviances. Here, we deliver evidence that the initial 300 ms of a sound contribute more to this preattentive processing than the sound's later parts. We directly compared the influence of the temporal distance relative to sound onset on the processing of the sound's duration and frequency information. The mismatch negativity (MMN), an event-related potential indicator for preattentive feature encoding and deviance detection, was measured for infrequent duration deviants and frequency modulation deviants. The onset of either deviancy was at 100, 200, 300, or 400 ms relative to sound onset. MMN was only elicited for deviations occurring within the first 300 ms after sound onset for both types of deviants. Its neural sources were localized in supra-temporal cortices with source current density analyses (SCD) and variable resolution electromagnetic tomography (VARETA), revealing a right-hemispheric preponderance for frequency modulations but not for duration shortenings. This suggests that preattentive deviance detection is based upon partly diverging functional memory registers for temporal and dynamic spectral information. The influence of temporal distance on MMN in both conditions supports the view that temporal and spectral sound properties are integrated into an auditory object representation prior to preattentive deviance detection. Importantly, the decline of MMN to unattended sounds with larger temporal distance suggests that parts beyond 300 ms are less important for preattentive auditory object representation.

The relevance of QEEG to the evaluation of behavioral disorders and pharmacological interventions

It has become apparent that the electrical signals recorded from the scalp of healthy individuals under standardized conditions are predictable, and that patients with a wide variety of brain disorders display activity with unusual features. It also early became apparent that centrally active medications produced striking changes in this activity. The application of computerized signal analysis to EEG recordings collected using standardized procedures has made it possible to obtain quantitative descriptions of brain electrical activity (QEEG) in normal individuals and patients with disorders of brain function or structure, as well as quantitative description of the ways in which centrally active medications alter this activity (Pharmaco-EEG or "PEEG"). With the emergence of three-dimensional EEG source localization techniques, it has recently become possible to visualize the mathematically most probable generators of QEEG abnormalities within the brain as well as the neuroanatomical regions where abnormal activity is most altered by efficacious medication. As QEEG and PEEG have evolved, a vast body of facts has been accumulated, describing changes in the EEG or event-related potentials (ERPs). observed in a variety of brain disorders or after administration of a variety of medications. With some notable exceptions, these studies have tended to be phenomenological rather than analytic. There has not been a systematic attempt to integrate these phenomena in order to build better understanding of how the abnormal behaviors of a particular psychiatric patient might be related to the specific pattern of the deviant electrical activity, nor just how pharmacological reduction of that deviant activity may have resulted in more normal behavior. This article is an endeavor to provide a more specific theoretical framework for understanding the relationships between the neuroanatomy and neurochemistry of the homeostatic system underlying the regulation of the QEEG, and the mechanisms revealed by Pharmaco-EEG that aid in correcting these illnesses.

Brain electrical tomography (BET) analysis of induced gamma band responses during a simple object recognition task

The formation of cortical object representations requires the activation of cell assemblies, correlated by induced oscillatory bursts above 20 Hz (gamma band), which are characterized by trial-by-trial latency fluctuations around a mean of approximately 300 ms after stimulus onset. The present electroencephalogram (EEG) study was intended to uncover to the generators of induced gamma band responses (GBRs) and to analyze phase-synchronization between these sources. A standard object recognition task was used to elicit gamma activity. At the scalp surface (electrode space), we found an augmentation of induced GBRs after the presentation of meaningful (familiar) as opposed to meaningless (unfamiliar) stimuli, which was accompanied by a dense pattern of significant phase-locking values between distant recording sites. Subsequently, intracranial current density distributions compatible with the observed scalp voltage topographies were estimated by means of VARETA (Variable Resolution Electromagnetic Tomography). In source space brain electrical tomographies (BETs) revealed widespread generators of induced GBRs at temporal, parietal, posterior, and frontal areas. Phase-locking analysis was calculated between re-constructed electrode signals based on separate forward solutions of the observed generators, thereby eliminating the possibly confounding influence of activity from areas not under observation. The results support the view that induced GBRs signify synchronous neuronal activity in a broadly distributed network during object recognition. The localization of the generators of event-related potentials (ERPs), evoked gamma activity, and induced alpha activity revealed different sources as compared to the induced GBR and, thus, seem to mirror complementary functions during the present task as compared to induced high-frequency brain dynamics.

Activity of left inferior frontal gyrus related to word repetition effects: LORETA imaging with 128-channel EEG and individual MRI

We investigated the brain substrate of word repetition effects on the implicit memory task using low-resolution electromagnetic tomography (LORETA) with high-density 128-channel EEG and individual MRI as a realistic head model. Thirteen right-handed, healthy subjects performed a word/non-word discrimination task, in which the words and non-words were presented visually, and some of the words appeared twice with a lag of one or five items. All of the subjects exhibited word repetition effects with respect to the behavioral data, in which a faster reaction time was observed to the repeated word (old word) than to the first presentation of the word (new word). The old words elicited more positive-going potentials than the new words, beginning at 200 ms and lasting until 500 ms post-stimulus. We conducted source reconstruction using LORETA at a latency of 400 ms with the peak mean global field potentials and used statistical parametric mapping for the statistical analysis. We found that the source elicited by the old words exhibited a statistically significant current density reduction in the left inferior frontal gyrus. This is the first study to investigate the generators of word repetition effects using voxel-by-voxel statistical mapping of the current density with individual MRI and high-density EEG.

Sensory suppression during shifts of attention between surfaces in transparent motion

During transparent motion, attention to changes in the direction of one illusory surface will impede recognition of a similar event affecting the other surface if both are close together in time. This is a form of object-based attentional blink (AB). Here, we show that this AB is related to a smaller N200 response to the change in direction and that the response is even smaller for trials on which the subject makes mistakes compared to those with correct responses consistent with signal detection theory models. The variation of N200 associated with the AB can be modeled by an attenuation of current sources estimated in visual extrastriate cortex. These results suggest that the AB in the transparent motion paradigm is due to the suppression of sensory signals in early visual areas.

Multichannel matching pursuit and EEG inverse solutions

We present a new approach to the preprocessing of the electroencephalographic time series for EEG inverse solutions. As the first step, EEG recordings are decomposed by multichannel matching pursuit algorithm--in this study we introduce a computationally efficient, suboptimal solution. Then, based upon the parameters of the waveforms fitted to the EEG (frequency, amplitude and duration), we choose those corresponding to the the phenomena of interest, like e.g. sleep spindles. For each structure, the corresponding weights of each channel define a topographic signature, which can be subject to an inverse solution procedure, like e.g. Loreta, used in this work. As an example, we present an automatic detection and parameterization of sleep spindles, appearing in overnight polysomnographic recordings. Inverse solutions obtained for single sleep spindles are coherent with the averages obtained for 20 overnight EEG recordings analyzed in this study, as well as with the results reported previously in literature as inter-subject averages of solutions for spectral integrals, computed on visually selected spindles.

From genes to brain oscillations: Is the visual pathway the epigenetic clue to schizophrenia?

Molecular data and gene expression data and recently mitochondrial genes and possible epigenetic regulation by non-coding genes is revolutionizing our views on schizophrenia. Genes and epigenetic mechanisms are triggered by cell-cell interaction and by external stimuli. A number of recent clinical and molecular observations indicate that epigenetic factors may be operational in the origin of the illness. Based on the molecular insights, gene expression profiles and epigenetic regulation of gene, we went back to the neurophysiology (brain oscillations) and found a putative role of the visual experiences (i.e. visual stimuli) as epigenetic factor. The functional evidences provided here, establish a direct link between the striate and extrastriate unimodal visual cortex and the neurobiology of the schizophrenia. This result support the hypothesis that 'visual experience' has a potential role as epigenetic factor and contribute to trigger and/or to maintain the progression of the schizophrenia. In this case, candidate genes sensible for the visual 'insult' may be located within the visual cortex including associative areas, while the integrity of the visual pathway before reaching the primary visual cortex is preserved. The same effect can be perceived if target genes are localised within the visual pathway, which actually, is more sensitive for 'insult' during the early life than the cortex per se. If this process affects gene expression at these sites a stably sensory specific 'insult', i.e. distorted visual information, is entering the visual system and expanded to fronto-temporo-parietal multimodal areas even from early maturation periods. The difference in the timing of postnatal neuroanatomical events between such areas and the primary visual cortex in humans (with the formers reaching the same development landmarks later in life than the latter) is 'optimal' to establish an abnormal 'cell- communication' mediated by the visual system that may further interfere with the local physiology. In this context the strategy to search target genes need to be rearrangement and redirected to visual-related genes. Otherwise, psychophysics studies combining functional neuroimage, and electrophysiology are strongly recommended, for the search of epigenetic clues that will allow to carrier gene association studies in schizophrenia.

Interictal Regional Cerebral Blood Flow and Electrical Source Analysis in Patients with Complex Partial Seizures

BACKGROUND

Recently, new methods of EEG source analysis have been developed. Dipole modeling and brain distributed source analysis localize in three-dimensions the origin of the electrical source of spikes registered in EEG. With single photon emission computed tomography (SPECT), it is possible to detect hypo- and hyperperfusion zones. Our aim in this study is to compare the regions where the electrical sources are detected, with the hypoperfusion regions in patients with complex partial seizures (CPS).

METHODS

The concordance of localization with dipole analysis, brain distributed source analysis and regional cerebral flow blood in patients with CPS was studied. The hypoperfusion zones detected with interictal SPECT were compared with electrical sources localized with brain electric source analysis (BESA) and brain distributed source analysis with variable resolution electromagnetic tomography (VARETA).

RESULTS

Hypoperfusion zones were found to localize with the origin of dipoles in 18 cases (90%), between lobes in 17 (85%) and between mesial or lateral regions in the temporal lobe in 12 cases (60%). With VARETA, agreement between side of hypoperfusion and electrical current source localization was found in 18/20 cases (90%), with lobes in 17 (85%) and with mesial or lateral regions of the temporal lobe only in 2 cases (10%).

CONCLUSIONS

Hypoperfusion zones in interictal SPECT of patients with CPS are in agreement with the origin of dipoles in 85% of the cases, but in specifics zones of temporal lobe the agreement falls to 60%. The concordance of hypoperfusion zones was better with dipole analysis than with VARETA.

The neurophysiology of attention-deficit/hyperactivity disorder

Recent reviews of the neurobiology of Attention-Deficit/Hyperactivity Disorder (AD/HD) have concluded that there is no single pathophysiological profile underlying this disorder. Certainly, dysfunctions in the frontal/subcortical pathways that control attention and motor behavior are implicated. However, no diagnostic criteria or behavioral/neuroimaging techniques allow a clear discrimination among subtypes within this disorder, especially when problems with learning are also considered. Two major Quantitative EEG (QEEG) subtypes have been found to characterize AD/HD. Here we review the major findings in the neurophysiology of AD/HD, focusing on QEEG, and briefly present our previous findings using a source localization technique called Variable Resolution Electromagnetic Tomography (VARETA). These two techniques represent a possible objective method to identify specific patterns corresponding to EEG-defined subtypes of AD/HD. We then propose a model representing the distribution of the neural generators in these two major AD/HD subtypes, localized within basal ganglia and right anterior cortical regions, and hippocampal, para-hippocampal and temporal cortical regions, respectively. A comprehensive review of neurochemical, genetic, neuroimaging, pharmacological and neuropsychological evidence in support of this model is then presented. These results indicate the value of the neurophysiological model of AD/HD and support the involvement of different neuroanatomical systems, particularly the dopaminergic pathways.

A pre-task resting condition neither 'baseline' nor 'zero'

This study introduce the comparison of a 'reference state' versus a resting condition (zero), defined upon normative developmental equations. We compared pre-task 'resting' data from healthy individuals with the Normative Cuban digital resting EEG-database recently calculated for VARETA (qEEG/VARETA). The results allowed us to state that a 'pre-task resting conditions' exists as a state beyond the 'zero' or 'baseline' condition. The pre-task 'resting' condition is never truly 'at rest', however most of the previous published fMRI/PET studies assumed such a pre-task condition as reference/baseline condition. By defining different 'resting states' by qEEG/VARETA analyses, we have a potential methodology which can define resting state conditions and to be sure that they are consistent when comparing within group analyses across tasks or between groups either void of task or for task specific conditions.

Evaluation and validity of a LORETA normative EEG database

To evaluate the reliability and validity of a Z-score normative EEG database for Low Resolution Electromagnetic Tomography (LORETA), EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) were acquired from 106 normal subjects, and the cross-spectrum was computed and multiplied by the Key Institute's LORETA 2,394 gray matter pixel T Matrix. After a log10 transform or a Box-Cox transform the mean and standard deviation of the *.lor files were computed for each of the 2394 gray matter pixels, from 1 to 30 Hz, for each of the subjects. Tests of Gaussianity were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of a Z-score database was computed by measuring the approximation to a Gaussian distribution. The validity of the LORETA normative database was evaluated by the degree to which confirmed brain pathologies were localized using the LORETA normative database. Log10 and Box-Cox transforms approximated Gaussian distribution in the range of 95.64% to 99.75% accuracy. The percentage of normative Z-score values at 2 standard deviations ranged from 1.21% to 3.54%, and the percentage of Z-scores at 3 standard deviations ranged from 0% to 0.83%. Left temporal lobe epilepsy, right sensory motor hematoma and a right hemisphere stroke exhibited maximum Z-score deviations in the same locations as the pathologies. We conclude: (1) Adequate approximation to a Gaussian distribution can be achieved using LORETA by using a log10 transform or a Box-Cox transform and parametric statistics, (2) a Z-Score normative database is valid with adequate sensitivity when using LORETA, and (3) the Z-score LORETA normative database also consistently localized known pathologies to the expected Brodmann areas as an hypothesis test based on the surface EEG before computing LORETA.

Applications of random field theory to electrophysiology

The analysis of electrophysiological data often produces results that are continuous in one or more dimensions, e.g., time-frequency maps, peri-stimulus time histograms, and cross-correlation functions. Classical inferences made on the ensuing statistical maps must control family wise error (FWE) when searching across the map's dimensions. In this paper, we borrow multiple comparisons procedures, established in neuroimaging, and apply them to electrophysiological data. These procedures use random field theory (RFT) to adjust p-values from statistics that are functions of time and/or frequency. This RFT adjustment for continuous statistical processes plays the same role as a Bonnferonni adjustment in the context of discrete statistical tests. Here, by analysing the time-frequency decompositions of single channel EEG data we show that RFT adjustments can be used in the analysis of electrophysiological data and illustrate the advantages of this method over existing approaches.

Low-resolution electromagnetic tomography neurofeedback

Through continuous feedback of the electroencephalogram (EEG) humans can learn how to shape their brain electrical activity in a desired direction. The technique is known as EEG biofeedback, or neurofeedback, and has been used since the late 1960s in research and clinical applications. A major limitation of neurofeedback relates to the limited information provided by a single or small number of electrodes placed on the scalp. We establish a method for extracting and feeding back intracranial current density and we carry out an experimental study to ascertain the ability of the participants to drive their own EEG power in a desired direction. To derive current density within the brain volume, we used the low-resolution electromagnetic tomography (LORETA). Six undergraduate students (three males, three females) underwent tomographic neurofeedback (based on 19 electrodes placed according to the 10-20 system) to enhance the current density power ratio between the frequency bands beta (16-20 Hz) and alpha (8-10 Hz). According to LORETA modeling, the region of interest corresponded to the Anterior Cingulate (cognitive division). The protocol was designed to improve the performance of the subjects on the dimension of sustained attention. Two hypotheses were tested: 1) that the beta/alpha current density power ratio increased over sessions and 2) that by the end of the training subjects acquired the ability of increasing that ratio at will. Both hypotheses received substantial experimental support in this study. This is the first application of an EEG inverse solution to neurofeedback. Possible applications of the technique include the treatment of epileptic foci, the rehabilitation of specific brain regions damaged as a consequence of traumatic brain injury and, in general, the training of any spatial specific cortical electrical activity. These findings may also have relevant consequences for the development of brain-computer interfaces.

Parametric vs. non-parametric statistics of low resolution electromagnetic tomography (LORETA)

This study compared the relative statistical sensitivity of non-parametric and parametric statistics of 3-dimensional current sources as estimated by the EEG inverse solution Low Resolution Electromagnetic Tomography (LORETA). One would expect approximately 5% false positives (classification of a normal as abnormal) at the P < .025 level of probability (two tailed test) and approximately 1% false positives at the P < .005 level. EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) from 43 normal adult subjects were imported into the Key Institute's LORETA program. We then used the Key Institute's cross-spectrum and the Key Institute's LORETA output files (*.lor) as the 2,394 gray matter pixel representation of 3-dimensional currents at different frequencies. The mean and standard deviation *.lor files were computed for each of the 2,394 gray matter pixels for each of the 43 subjects. Tests of Gaussianity and different transforms were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of parametric vs. non-parametric statistics were compared using a "leave-one-out" cross validation method in which individual normal subjects were withdrawn and then statistically classified as being either normal or abnormal based on the remaining subjects. Log10 transforms approximated Gaussian distribution in the range of 95% to 99% accuracy. Parametric Z score tests at P < .05 cross-validation demonstrated an average misclassification rate of approximately 4.25%, and range over the 2,394 gray matter pixels was 27.66% to 0.11%. At P < .01 parametric Z score cross-validation false positives were 0.26% and ranged from 6.65% to 0% false positives. The non-parametric Key Institute's t-max statistic at P < .05 had an average misclassification error rate of 7.64% and ranged from 43.37% to 0.04% false positives. The nonparametric t-max at P < .01 had an average misclassification rate of 6.67% and ranged from 41.34% to 0% false positives of the 2,394 gray matter pixels for any cross-validated normal subject. In conclusion, adequate approximation to Gaussian distribution and high cross-validation can be achieved by the Key Institute's LORETA programs by using a log10 transform and parametric statistics, and parametric normative comparisons had lower false positive rates than the non-parametric tests.

A solution to the dynamical inverse problem of EEG generation using spatiotemporal Kalman filtering

We present a new approach for estimating solutions of the dynamical inverse problem of EEG generation. In contrast to previous approaches, we reinterpret this problem as a filtering problem in a state space framework; for the purpose of its solution, we propose a new extension of Kalman filtering to the case of spatiotemporal dynamics. The temporal evolution of the distributed generators of the EEG can be reconstructed at each voxel of a discretisation of the gray matter of brain. By fitting linear autoregressive models with neighbourhood interactions to EEG time series, new classes of inverse solutions with improved resolution and localisation ability can be explored. For the purposes of model comparison and parameter estimation from given data, we employ a likelihood maximisation approach. Both for instantaneous and dynamical inverse solutions, we derive estimators of the time-dependent estimation error at each voxel. The performance of the algorithm is demonstrated by application to simulated and clinical EEG recordings. It is shown that by choosing appropriate dynamical models, it becomes possible to obtain inverse solutions of considerably improved quality, as compared to the usual instantaneous inverse solutions.

Statistical parametric mapping for event-related potentials: I. Generic considerations

In this paper, we frame the strategy and motivations behind developments in statistical parametric mapping (SPM) for the analysis of electroencephalogram (EEG) data. This work deals specifically with SPM procedures for the analysis of event-related potentials (ERP). We place these developments in the larger context of integrating electrophysiological and hemodynamic measurements of evoked brain responses through the fusion of EEG and fMRI data. In this paper, we consider some fundamental issues when selecting an appropriate statistical model that enables diverse questions to be asked of the data and at the same time retains maximum sensitivity. The three key issues addressed in this paper are as follows: (i) should multivariate or mass univariate analyses be adopted, (ii) should time be treated as an experimental factor or as a dimension of the measured response variable, and (iii) how to form appropriate explanatory variables in a hierarchical observation model. We review the relative merits of the different options and explain the rationale for our choices. In brief, we motivate a mass univariate approach in terms of sensitivity to region-specific responses. This involves modeling responses at each voxel or space bin separately. In contradistinction, we treat time as an experimental factor to enable inferences about temporally distributed responses that encompass multiple time bins. In a companion paper, we develop statistical models of ERPs in the time domain that follow from the heuristics established here and illustrate the approach using simulated and real data.

Specific EEG frequencies signal general common cognitive processes as well as specific task processes in man

The EEG of 10 normal male young adults was recorded during the performance of three different tasks: mental calculation, verbal working memory (VWM) and spatial working memory (SWM). The stimuli used in the three tasks were the same, only the instructions to the subjects were different. Narrow band analysis of the EEG and distributed sources for each EEG frequency were calculated using variable resolution electromagnetic tomography (VARETA). At some frequencies (1.56, 4.68, 7.80 to 10.92 Hz) at least two tasks produced similar EEG patterns that were interpreted as the reflex of common cognitive processes, such as attention, inhibition of irrelevant stimuli, etc. Specific changes were also observed at 2.34, 3.12, 3.90, 5.46 and 6.24 Hz. The first three of these frequencies showed similar changes during VWM and calculus at the left frontal cortex, suggesting the activation of working memory (WM) processes. The interaction effect at these frequencies was mainly observed at the anterior cingulate cortex and frontal cortex. At 5.46 and 6.24 Hz, changes were only observed during mental calculation.

Assessing acute middle cerebral artery ischemic stroke by quantitative electric tomography

This paper focuses on the application of quantitative electric tomography (qEEGT) to map changes in EEG generators for detection of early signs of ischemia in patients with acute middle cerebral artery stroke. Thirty-two patients were studied with the diagnosis of acute ischemic stroke of the left middle cerebral artery territory, within the first 24 hours of their clinical evolution. Variable Resolution Electrical Tomography was used for estimating EEG source generators. High resolution source Z-spectra and 3- dimensional images of Z values for all the sources at each frequency were obtained for all cases. To estimate statistically significant increments and decrements of brain electric activity within the frequency spectra, the t-Student vs. Zero test was performed. A significant increment of delta activity was observed on the affected vascular territory, and a more extensive increment of theta activity was detected. A significant alpha decrement was found in the parieto-occipital region of the affected cerebral hemisphere (left), and in the medial and posterior region of the right hemisphere. These findings suggest that qEEGT Z delta images are probably related to the main ischemic core within the affected arterial territory; penumbra, diaschisis, edema, might explain those observed theta and alpha abnormalities. It was concluded that qEEGT is useful for the detection of early signs of ischemia in acute ischemic stroke.

Random field-union intersection tests for EEG/MEG imaging

Electrophysiological (EEG/MEG) imaging challenges statistics by providing two views of the same spatiotemporal data: topographic and tomographic. Until now, statistical tests for these two situations have developed separately. This work introduces statistical tests for assessing simultaneously the significance of spatiotemporal event-related potential/event-related field (ERP/ERF) components and that of their sources. The test for detecting a component at a given time instant is provided by a Hotelling's T(2) statistic. This statistic is constructed in such a manner to be invariant to any choice of reference and is based upon a generalized version of the average reference transform of the data. As a consequence, the proposed test is a generalization of the well-known Global Field Power statistic. Consideration of tests at all time instants leads to a multiple comparison problem addressed by the use of Random Field Theory (RFT). The Union-Intersection (UI) principle is the basis for testing hypotheses about the topographic and tomographic distributions of such ERP/ERF components. The performance of the method is illustrated with actual EEG recordings obtained from a visual experiment of pattern reversal stimuli.

Statistical parametric mapping for event-related potentials (II): a hierarchical temporal model

In this paper, we describe a temporal model for event-related potentials (ERP) in the context of statistical parametric mapping (SPM). In brief, we project channel data onto a two-dimensional scalp surface or into three-dimensional brain space using some appropriate inverse solution. We then treat the spatiotemporal data in a mass-univariate fashion. This implicitly factorises the model into spatial and temporal components. The key contribution of this paper is the use of observation models that afford an explicit distinction between observation error and variation in the expression of ERPs. This distinction is created by employing a two-level hierarchical model, in which the first level models the ERP effects within-subject and trial type, while the second models differences in ERP expression among trial types and subjects. By bringing the analysis of ERP data into a classical hierarchical (i.e., mixed effects) framework, many apparently disparate approaches (e.g., conventional P300 analyses and time-frequency analyses of stimulus-locked oscillations) can be reconciled within the same estimation and inference procedure. Inference proceeds in the normal way using t or F statistics to test for effects that are localised in peristimulus time or in some time-frequency window. The use of F statistics is an important generalisation of classical approaches, because it allows one to test for effects that lie in a multidimensional subspace (i.e., of unknown but constrained form). We describe the analysis procedures, the underlying theory and compare its performance to established techniques.

Variable resolution electromagnetic tomography (VARETA) in evaluation of compression of cerebral arteries due to deep midline brain lesions

BACKGROUND

Hemispheric tumors produced electroencephalographic (EEG) delta activity mainly due to deafferentation of cerebral cortex. In small, deep midline lesions that compressed cerebral arteries, the most important abnormality should have been in EEG theta band that selectively responded to brain ischemia. Frequency domain-variable resolution electromagnetic tomography (FD-VARETA) has been applied satisfactorily to the study of brain tumors, cerebral infarcts, and brain hemorrhages and was shown to localize areas of hypoperfusion.

METHODS

Twelve patients with deep midline lesions compressing different cerebral arteries were studied. Computer tomography (CT) and/or magnetic resonance imaging (MRI) as well as quantitative EEG with source calculation in frequency domain were obtained. Brain electromagnetic tomographies (BETs) were calculated to evaluate localization and extension of functional abnormalities.

RESULTS

Ten of twelve cases presented abnormal sources in theta band as main abnormal source. In only two cases was the main source in delta band, but these cases also had abnormal Z values in theta band. In four patients there were only abnormal values in theta range. Sources of abnormal theta activity were observed in regions irrigated by the arteries compressed.

CONCLUSIONS

In deep midline lesions, compression of cerebral arteries producing relative ischemia may explain abnormal EEG sources in theta band. Patients with main source in theta band showed vascular compression and some patients exhibited vasogenic edema. Thus, theta might be due to relative ischemia produced by both hypoperfusion and edema. Once again, VARETA has found to be very useful in evaluation of functional abnormalities.

Bayesian model averaging in EEG/MEG imaging

In this paper, the Bayesian Theory is used to formulate the Inverse Problem (IP) of the EEG/MEG. This formulation offers a comparison framework for the wide range of inverse methods available and allows us to address the problem of model uncertainty that arises when dealing with different solutions for a single data. In this case, each model is defined by the set of assumptions of the inverse method used, as well as by the functional dependence between the data and the Primary Current Density (PCD) inside the brain. The key point is that the Bayesian Theory not only provides for posterior estimates of the parameters of interest (the PCD) for a given model, but also gives the possibility of finding posterior expected utilities unconditional on the models assumed. In the present work, this is achieved by considering a third level of inference that has been systematically omitted by previous Bayesian formulations of the IP. This level is known as Bayesian model averaging (BMA). The new approach is illustrated in the case of considering different anatomical constraints for solving the IP of the EEG in the frequency domain. This methodology allows us to address two of the main problems that affect linear inverse solutions (LIS): (a) the existence of ghost sources and (b) the tendency to underestimate deep activity. Both simulated and real experimental data are used to demonstrate the capabilities of the BMA approach, and some of the results are compared with the solutions obtained using the popular low-resolution electromagnetic tomography (LORETA) and its anatomically constraint version (cLORETA).

Functional coupling of simultaneous electrical and metabolic activity in the human brain

The relationships between brain electrical and metabolic activity are being uncovered currently in animal models using invasive methods; however, in the human brain this relationship remains not well understood. In particular, the relationship between noninvasive measurements of electrical activity and metabolism remains largely undefined. To understand better these relations, cerebral activity was measured simultaneously with electroencephalography (EEG) and positron emission tomography using [(18)f]-fluoro-2-deoxy-D-glucose (PET-FDG) in 12 normal human subjects during rest. Intracerebral distributions of current density were estimated, yielding tomographic maps for seven standard EEG frequency bands. The PET and EEG data were registered to the same space and voxel dimensions, and correlational maps were created on a voxel-by-voxel basis across all subjects. For each band, significant positive and negative correlations were found that are generally consistent with extant understanding of EEG band power function. With increasing EEG frequency, there was an increase in the number of positively correlated voxels, whereas the lower alpha band (8.5-10.0 Hz) was associated with the highest number of negative correlations. This work presents a method for comparing EEG signals with other more traditionally tomographic functional imaging data on a 3-D basis. This method will be useful in the future when it is applied to functional imaging methods with faster time resolution, such as short half-life PET blood flow tracers and functional magnetic resonance imaging.

N400 during lexical decision tasks: a current source localization study

OBJECTIVE

Our primary aim in the present study was to establish the anatomic and psychophysiological correlates of automatic and controlled semantic priming.

METHODS

Current sources were calculated on N400 component data from a previous study on lexical decision tasks [Clin Neurophysiol 1999;110:813] using the variable resolution electromagnetic tomography method (VARETA). In this study, two experiments were carried out, one using directly related pairs and the other one using mediated related pairs. Each experiment consisted of 3 tasks that required different levels of contribution from controlled processes.

RESULTS

Average source localization images showed the brain structures involved in lexical decision tasks. The automatic component of the N400 effect was related to activation of occipitotemporal and parahippocampal gyri and anterior temporal lobes bilaterally. The expectancy strategy was related to activation of the right posterior temporal and right frontal areas. The postlexical strategy was associated with activation of right frontal, anterior cingulate and bilateral superior parietal areas.

CONCLUSIONS

The findings indicated that the current sources of the N400 varied according to the relative contributions of automatic and controlled mechanisms. Moreover, the sources of the N400 effect depended on the type of strategy used.

LORETA imaging of P300 in schizophrenia with individual MRI and 128-channel EEG

We investigated the characteristics of P300 generators in schizophrenics by using voxel-based statistical parametric mapping of current density images. P300 generators, produced by a rare target tone of 1500 Hz (15%) under a frequent nontarget tone of 1000 Hz (85%), were measured in 20 right-handed schizophrenics and 21 controls. Low-resolution electromagnetic tomography (LORETA), using a realistic head model of the boundary element method based on individual MRI, was applied to the 128-channel EEG. Three-dimensional current density images were reconstructed from the LORETA intensity maps that covered the whole cortical gray matter. Spatial normalization and intensity normalization of the smoothed current density images were used to reduce anatomical variance and subject-specific global activity and statistical parametric mapping (SPM) was applied for the statistical analysis. We found that the sources of P300 were consistently localized at the left superior parietal area in normal subjects, while those of schizophrenics were diversely distributed. Upon statistical comparison, schizophrenics, with globally reduced current densities, showed a significant P300 current density reduction in the left medial temporal area and in the left inferior parietal area, while both left prefrontal and right orbitofrontal areas were relatively activated. The left parietotemporal area was found to correlate negatively with Positive and Negative Syndrome Scale total scores of schizophrenic patients. In conclusion, the reduced and increased areas of current density in schizophrenic patients suggest that the medial temporal and frontal areas contribute to the pathophysiology of schizophrenia, the frontotemporal circuitry abnormality.

Induced oscillations and the distributed cortical sources during the Wisconsin card sorting test performance in schizophrenic patients: new clues to neural connectivity

Prefrontal dysfunction has been associated with schizophrenia. Activation during Wisconsin card sorting test (WCST) is a common approach used in functional neuroimaging to address this failure. Equally, current knowledge states that oscillations are basic forms of cells-assembly communications during mental activity. Promising results were revealed in a previous study assessing healthy subjects, WCST and oscillations. However, those previous studies failed to meet the functional integration of the network during the WCST in schizophrenics, based on the induced oscillations and their distributed cortical sources. In this research, we utilized the brain electrical tomography (variable-resolution brain electromagnetic tomography) technique to accomplish this goal. Task specific delta, theta, alpha and beta-2 oscillations were induced and simultaneously synchronized over large extensions of cortex, encompassing prefrontal, temporal and posterior regions as in healthy subjects. Every frequency had a well-defined network involving a variable number of areas and sharing some of them. Oscillations at 11.5, 5.0 and 30 Hz seem to reflect an abnormal increase or decrease, being located at supplementary motor area (SMA), left occipitotemporal region (OT), and right frontotemporal subregions (RFT), respectively. Three cortical areas appeared to be critical, that may lead to difficulties either in coordinating/sequencing the input/output of the prefrontal networks-SMA, and retention of information in memory-RFT, both preceded or paralleled by a deficient visual information processing-OT.

Sources of EEG activity in learning disabled children

The sources of different EEG frequencies were studied in 25 normal children and 46 learning disabled (not otherwise specified) children between 7 and 11 years old. The EEG sources were computed using Frequency-domain Variable Resolution Electromagnetic Tomography which produces a three dimensional picture of the currents at each EEG frequency. Significant differences between groups were observed. LD children showed more theta activity (3.5 to 7.02 Hz) in the frontal lobes and control children more alpha (9.75 to 12.87 Hz) in occipital areas. These results may support the maturational lag hypothesis, as the neurobiological cause of learning deficiencies not otherwise specified.

Statistical parametric mapping of LORETA using high density EEG and individual MRI: application to mismatch negativities in schizophrenia

We describe a method for the statistical parametric mapping of low resolution electromagnetic tomography (LORETA) using high-density electroencephalography (EEG) and individual magnetic resonance images (MRI) to investigate the characteristics of the mismatch negativity (MMN) generators in schizophrenia. LORETA, using a realistic head model of the boundary element method derived from the individual anatomy, estimated the current density maps from the scalp topography of the 128-channel EEG. From the current density maps that covered the whole cortical gray matter (up to 20,000 points), volumetric current density images were reconstructed. Intensity normalization of the smoothed current density images was used to reduce the confounding effect of subject specific global activity. After transforming each image into a standard stereotaxic space, we carried out statistical parametric mapping of the normalized current density images. We applied this method to the source localization of MMN in schizophrenia. The MMN generators, produced by a deviant tone of 1,200 Hz (5% of 1,600 trials) under the standard tone of 1,000 Hz, 80 dB binaural stimuli with 300 msec of inter-stimulus interval, were measured in 14 right-handed schizophrenic subjects and 14 age-, gender-, and handedness-matched controls. We found that the schizophrenic group exhibited significant current density reductions of MMN in the left superior temporal gyrus and the left inferior parietal gyrus (P < 0. 0005). This study is the first voxel-by-voxel statistical mapping of current density using individual MRI and high-density EEG.

Wisconsin Card Sorting Test synchronizes the prefrontal, temporal and posterior association cortex in different frequency ranges and extensions

Current findings show some brain regions consistently related to performance of the Wisconsin Card Sorting Test (WCST). An increase of local cerebral blood flow or metabolic demands has been detected in those regions. Functional integration of the neuronal circuits that subserve the task performance, based upon the identification of the oscillations and their distributed cerebral sources, has not been accomplished previously. The event-related tonic oscillations within a period of 2,000 msec after the stimulus onset and the probable neural substrate were evaluated in healthy volunteers by variable-resolution brain electrical tomography (VARETA). The WCST induced a significant increase of delta, theta, beta-2, and gamma oscillations, but decrease of alpha. Areas such as the frontal subregions, temporal, cingulate, parahippocampal, parietal, occipitotemporal cortex, and occipital poles showed modified activity during the task, with EEG spectral band selectivity as well as some overlapping among them. Frontal and temporal regions generated the delta/theta oscillations. Additionally, the occipitotemporal and parietal regions were the source of the delta activity, lacking theta activation. The parietal region also showed tonic alpha, beta-2 and gamma changes. These data imply that different processes have been simultaneously mediated during task performance. Relationships among the individual bands, the neural substrata and the specific cognitive process that support the task were established. The selectively distributed delta, theta, alpha, beta-2 and gamma oscillations reflect communication networks through variable populations of neurons, with functional relations to the working memory functions and the information processing that subserve the WCST performance.

The neurophysics of consciousness

Consciousness combines information about attributes of the present multimodal sensory environment with relevant elements of the past. Information from each modality is continuously fractionated into distinct features, processed locally by different brain regions relatively specialized for extracting these disparate components and globally by interactions among these regions. Information is represented by levels of synchronization within neuronal populations and of coherence among multiple brain regions that deviate from random fluctuations. Significant deviations constitute local and global negative entropy, or information. Local field potentials reflect the degree of synchronization among the neurons of the local ensembles. Large-scale integration, or 'binding', is proposed to involve oscillations of local field potentials that play an important role in facilitating synchronization and coherence, assessed by neuronal coincidence detectors, and parsed into perceptual frames by cortico-thalamo-cortical loops. The most probable baseline levels of local synchrony, coherent interactions among brain regions, and frame durations have been quantitatively described in large studies of their age-appropriate normative distributions and are considered as an approximation to a conscious 'ground state'. The level of consciousness during anesthesia can be accurately predicted by the magnitude and direction of reversible multivariate deviations from this ground state. An invariant set of changes takes place during anesthesia, independent of the particular anesthetic agent. Evidence from a variety of neuroscience areas supporting these propositions, together with the invariant reversible electrophysiological changes observed with loss and return of consciousness, are used to provide a foundation for this theory of consciousness. This paper illustrates the increasingly recognized need to consider global as well as local processes in the search for better explanations of how the brain accomplishes the transformation from synchronous and distributed neuronal discharges to seamless global subjective awareness.

Sources of abnormal EEG activity in spontaneous intracerebral hemorrhage

This report describes the results obtained with EEG source analysis in the frequency domain (FD-VARETA), in 14 patients with brain hemorrhages; 6 hemorrhages were located in the putaminal region, 1 was mesencephalic and 7 were lobar cerebral hemorrhages. Our goal was to evaluate FD-VARETA accuracy for the localization of fast growth expansive brain lesions. FD-VARETA produces brain electromagnetic tomography images of EEG sources in every frequency. The location of the most abnormal or the maximum Z value across all frequencies was compared with the location of spontaneous hemorrhages in computed tomographies (CT). In all patients the main source was within delta or theta bands. The spatial extent of the sources, in the brain atlas, at these frequency values was almost the same as the volume of hematoma in CT. Putaminal lesions produced larger regions of cortical deafferentation than lobar hematomas, with higher abnormal Z values. FD-VARETA was more accurate in locating the lesions than traditional maps of absolute and relative power in delta, theta, alpha and beta bands.

CONCLUSION

FD-VARETA is a valuable procedure for the functional evaluation of brain hemorrhages.

Outcome related electrophysiological subtypes of cocaine dependence

We previously described the existence of two quantitative EEG (QEEG) subtypes of cocaine dependent males, identified at baseline, displaying differential proneness to relapse. The current study expands the population to include females and enhances the measure set to include both QEEG and somatosensory EP (SEP) features. Fifty-seven cocaine dependent adults (16 F, 41 M) were evaluated 5-14 days after last cocaine use, while in residence at a drug-free therapeutic community. The median length of stay in treatment (continued abstinence) was 25 weeks. Using a small subset of QEEG and SEP baseline features, three subtypes (CLUS) were identified. CLUS 2 (n = 25) and CLUS 3 (n = 23) replicated the published subtypes, while CLUS 1 (n = 9) was previously undescribed. Cluster membership was significantly associated with length of stay in treatment (chi 2 = 13.789, P < 0.001), but not with length of exposure to crack cocaine or to any demographic or clinical features. Seventy-eight percent of CLUS 1 and 65% of CLUS 3 left treatment < or = 25 weeks, whereas 80% of CLUS 2 remained in treatment > 25 weeks. The existence of outcome related subtypes may reflect: [1] differential neurophysiological vulnerability, "traits," predisposing individuals to cocaine addiction; or [2] differential neurosensitivity, "states," due to the effects of chronic cocaine exposure, and associated differences in treatment outcome. Using Variable Resolution Electrical Tomographic Analysis (VARETA), the mathematically most probable neuroanatomical source of the scalp recorded EEG data was localized. Computation of VARETA on the baseline Cluster profiles suggest significant differences in the underlying pathophysiology of these subtypes.

EEG source localization of interictal epileptiform activity in patients with partial complex epilepsy: comparison between dipole modeling and brain distributed source models

The precision between dipole Brain Electric Source Analysis (BESA) and brain distributed Variable Resolution Electromagnetic Tomography (VARETA) models for the localization of brain sources of interictal epileptiform discharges in patients with partial complex epilepsy was compared. The localization of brain sources calculated with dipole analysis and variable resolution electromagnetic tomography in 20 interictal recordings was analyzed. The origin of the dipoles was temporal in 18 cases, frontal in 1 and occipital in another. One dipole was enough in 7 cases, whereas two dipoles were necessary in 13 cases. The localization of paroxysmal activity was the same with BESA and VARETA in 17 patients. BESA and VARETA are useful methods for EEG sources analysis; BESA has more precision for the localization of punctate epileptogenic regions, and VARETA provides more information concerning the extension of the epileptic zone.