Roberto D. Pascual-Marqui

Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain

This paper presents a new method for localizing the electric activity in the brain based on multichannel surface EEG recordings. In contrast to the models presented up to now the new method does not assume a limited number of dipolar point sources nor a distribution on a given known surface, but directly computes a current distribution throughout the full brain volume. In order to find a unique solution for the 3-dimensional distribution among the infinite set of different possible solutions, the method assumes that neighboring neurons are simultaneously and synchronously activated. The basic assumption rests on evidence from single cell recordings in the brain that demonstrates strong synchronization of adjacent neurons. In view of this physiological consideration the computational task is to select the smoothest of all possible 3-dimensional current distributions, a task that is a common procedure in generalized signal processing. The result is a true 3-dimensional tomography with the characteristic that localization is preserved with a certain amount of dispersion, i.e., it has a relatively low spatial resolution. The new method, which we call Low Resolution Electromagnetic Tomography (LORETA) is illustrated with two different sets of evoked potential data, the first showing the tomography of the P100 component to checkerboard stimulation of the left, right, upper and lower hemiretina, and the second showing the results for the auditory N100 component and the two cognitive components CNV and P300. A direct comparison of the tomography results with those obtained from fitting one and two dipoles illustrates that the new method provides physiologically meaningful results while dipolar solutions fail in many situations. In the case of the cognitive components, the method offers new hypotheses on the location of higher cognitive functions in the brain.

Low resolution brain electromagnetic tomography (LORETA) functional imaging in acute, neuroleptic-naive, first-episode, productive schizophrenia.

Functional imaging of brain electrical activity was performed in nine acute, neuroleptic-naive, first-episode, productive patients with schizophrenia and 36 control subjects. Low-resolution electromagnetic tomography (LORETA, three-dimensional images of cortical current density) was computed from 19-channel electroencephalographic (EEG) activity obtained under resting conditions, separately for the different EEG frequencies. Three patterns of activity were evident in the patients: (1) an anterior, near-bilateral excess of delta frequency activity; (2) an anterior-inferior deficit of theta frequency activity coupled with an anterior-inferior left-sided deficit of alpha-1 and alpha-2 frequency activity; and (3) a posterior-superior right-sided excess of beta-1, beta-2 and beta-3 frequency activity. Patients showed deviations from normal brain activity as evidenced by LORETA along an anterior-left-to-posterior-right spatial axis. The high temporal resolution of EEG makes it possible to specify the deviations not only as excess or deficit, but also as inhibitory, normal and excitatory. The patients showed a dis-coordinated brain functional state consisting of inhibited prefrontal/frontal areas and simultaneously overexcited right parietal areas, while left anterior, left temporal and left central areas lacked normal routine activity. Since all information processing is brain-state dependent, this dis-coordinated state must result in inadequate treatment of (externally or internally generated) information.

Segmentation of brain electrical activity into microstates: model estimation and validation

A brain microstate is defined as a functional/physiological state of the brain during which specific neural computations are performed. It is characterized uniquely by a fixed spatial distribution of active neuronal generators with time varying intensity. Brain electrical activity is modeled as being composed of a time sequence of nonoverlapping microstates with variable duration. A precise mathematical formulation of the model for evoked potential recordings is presented, where the microstates are represented as normalized vectors constituted by scalp electric potentials due to the underlying generators. An algorithm is developed for estimating the microstates, based on a modified version of the classical k-means clustering method, in which cluster orientations are estimated, Consequently, each instantaneous multichannel evoked potential measurement is classified as belonging to some microstate, thus producing a natural segmentation of brain activity. Use is made of statistical image segmentation techniques for obtaining smooth continuous segments. Time varying intensities are estimated by projecting the measurements onto their corresponding microstates. A goodness of fit statistic for the model is presented. Finally, a method is introduced for estimating the number of microstates, based on nonparametric data-driven statistical resampling techniques.<<ETX>>

Three-dimensional tomography of event-related potentials during response inhibition: evidence for phasic frontal lobe activation

OBJECTIVES Spatial analysis of the evoked brain electrical fields during a cued continuous performance test (CPT) revealed an extremely robust anteriorization of the positivity of a P300 microstate in the NoGo compared to the Go condition (NoGo-anteriorization in a previous study). To allow a neuroanatomical interpretation the NoGo-anteriorization was investigated with a new three-dimensional source tomography method (LORETA) was applied. METHODS The CPT contains subsets of stimuli requiring the execution (Go) or the inhibition (NoGo) of a cued motor response which can be considered as mutual control conditions for the event-related potential (ERP) study of inhibitory brain functions 21-channel ERPs were obtained from 10 healthy subjects during a cued CPT, and analyzed with LORETA. RESULTS Topographic analyses revealed significantly different scalp distributions between the Go and the NoGo conditions in both P100 and P300 microstates, indicating that already at an early stage different neural assemblies are activated. LORETA disclosed a significant hyperactivity located in the right frontal lobe during the NoGo condition in the P300 microstate. CONCLUSIONS The results indicate that right frontal sources are responsible for the NoGo-anteriorization of the scalp P300 which is consistent with animal and human lesion studies of inhibitory brain functions. Furthermore, it demonstrates that frontal activation is confined to a brief microstate and time-locked to phasic inhibitory motor control. This adds important functional and chronometric specificity to findings of frontal activation obtained with PET and Near-Infrared-Spectroscopy studies during the cued CPT, and suggests that these metabolic results are not due to general task demands.

Affective Judgments of Faces Modulate Early Activity (160 ms) within the Fusiform Gyri

Functional neuroimaging studies have implicated the fusiform gyri (FG) in structural encoding of faces, while event-related potential (ERP) and magnetoen- cephalography studies have shown that such encoding occurs approximately 170 ms poststimulus. Behavioral and functional neuroimaging studies suggest that pro- cesses involved in face recognition may be strongly modulated by socially relevant information conveyed by faces. To test the hypothesis that affective informa- tion indeed modulates early stages of face processing, ERPs were recorded to individually assessed liked, neutral, and disliked faces and checkerboard-reversal stimuli. At the N170 latency, the cortical three-dimen- sional distribution of current density was computed in stereotactic space using a tomographic source local- ization technique. Mean activity was extracted from the FG, defined by structure-probability maps, and a meta-cluster delineated by the coordinates of the voxel with the strongest face-sensitive response from five published functional magnetic resonance imaging studies. In the FG, 160 ms poststimulus, liked faces elicited stronger activation than disliked and neutral faces and checkerboard-reversal stimuli. Further, confirming recent results, affect-modulated brain elec- trical activity started very early in the human brain (112 ms). These findings suggest that affective fea- tures conveyed by faces modulate structural face en- coding. Behavioral results from an independent study revealed that the stimuli were not biased toward par- ticular facial expressions and confirmed that liked faces were rated as more attractive. Increased FG ac- tivation for liked faces may thus be interpreted as reflecting enhanced attention due to their saliency.

Correspondence of event‐related potential tomography and functional magnetic resonance imaging during language processing

Combining event‐related potentials (ERP) and functional magnetic resonance imaging (fMRI) may provide sufficient temporal and spatial resolution to clarify the functional connectivity of neural processes, provided both methods represent the same neural networks. The current study investigates the statistical correspondence of ERP tomography and fMRI within the common activity volume and time range in a complex visual language task. The results demonstrate that both methods represent similar neural networks within the bilateral occipital gyrus, lingual gyrus, precuneus and middle frontal gyrus, and the left inferior and superior parietal lobe, middle and superior temporal gyrus, cingulate gyrus, superior frontal gyrus and precentral gyrus. The mean correspondence of both methods over subjects was significant. On an individual basis, only half of the subjects showed significantly corresponding activity patterns, suggesting that a one‐to‐one correspondence between individual fMRI activation patterns and ERP source tomographies integrated over microstates cannot be assumed in all cases. Hum. Brain Mapping 17:4–12, 2002.

Spatial pattern of cerebral glucose metabolism (PET) correlates with localization of intracerebral EEG-generators in Alzheimer's disease

BACKGROUND Since the measurement of human cerebral glucose metabolism (GluM) by positron emission tomography (PET) and that of human cerebral electrical activity by EEG reflect synaptic activity, both methods should be related in their cerebral spatial distribution. Healthy subjects do indeed demonstrate similar metabolic and neuroelectric spatial patterns. OBJECTIVE The aim of the study was to show that this similarity of GluM and EEG spatial patterns holds true in a population with a high variability of glucose metabolism. METHODS We investigated healthy control subjects and patients with varying degrees of cognitive dysfunction and varying GluM patterns by applying [18F]FDG PET and EEG. RESULTS We demonstrated that the localization of intracerebral generators of EEG correlates with spatial indices of GluM. CONCLUSION These results indicates that EEG provides similar spatial information about brain function as GluM-PET. Since EEG is a non-invasive technique, which is more widely available and can be repeated more often than PET, this may have important implications both for neuropsychiatric research and for clinical diagnosis. However, further studies are required to determine whether equivalent EEG dipole generators can yield a diagnostic specificity and sensitivity similar to that of GluM-PET.

Assessing interactions in the brain with exact low-resolution electromagnetic tomography

Scalp electric potentials (electroencephalogram; EEG) are contingent to the impressed current density unleashed by cortical pyramidal neurons undergoing post-synaptic processes. EEG neuroimaging consists of estimating the cortical current density from scalp recordings. We report a solution to this inverse problem that attains exact localization: exact low-resolution brain electromagnetic tomography (eLORETA). This non-invasive method yields high time-resolution intracranial signals that can be used for assessing functional dynamic connectivity in the brain, quantified by coherence and phase synchronization. However, these measures are non-physiologically high because of volume conduction and low spatial resolution. We present a new method to solve this problem by decomposing them into instantaneous and lagged components, with the lagged part having almost pure physiological origin.

Mapping distributed sources of cortical rhythms in mild Alzheimer's disease. A multicentric EEG study

The study aimed at mapping (i) the distributed electroencephalographic (EEG) sources specific for mild Alzheimers disease (AD) compared to vascular dementia (VaD) or normal elderly people (Nold) and (ii) the distributed EEG sources sensitive to the mild AD at different stages of severity. Resting EEG (10-20 electrode montage) was recorded from 48 mild AD, 20 VaD, and 38 Nold subjects. Both AD and VaD patients had 24-17 of mini mental state examination (MMSE). EEG rhythms were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). Cortical EEG sources were modeled by low resolution brain electromagnetic tomography (LORETA). Regarding issue i, there was a decline of central, parietal, temporal, and limbic alpha 1 (low alpha) sources specific for mild AD group with respect to Nold and VaD groups. Furthermore, occipital alpha 1 sources showed a strong decline in mild AD compared to VaD group. Finally, distributed theta sources were largely abnormal in VaD but not in mild AD group. Regarding issue ii, there was a lower power of occipital alpha 1 sources in mild AD subgroup having more severe disease. Compared to previous field studies, this was the first investigation that illustrated the power spectrum profiles at the level of cortical (macroregions) EEG sources in mild AD patients having different severity of the disease with respect to VaD and normal subjects. Future studies should evaluate the clinical usefulness of this approach in early differential diagnosis, disease staging, and therapy monitoring.

Brain areas and time course of emotional processing

The aims of the present study were to identify brain regions involved in emotional processing as well as to follow the time sequence of these processes in the millisecond-range resolution using low resolution brain electromagnetic tomography (LORETA). Different emotional (happy, sad, angry, fearful, and disgust) and neutral faces were presented to 17 healthy, right-handed volunteers on a computer screen while 25-channel EEG data were recorded. Subjects were instructed to generate the same emotion as shown in the presented faces. Event-related potentials (ERPs) were computed for each emotion and neutral condition, and analyzed as sequences of potential distribution maps. Paired topographic analysis of variance tests of the ERP maps identified time segments of significant differences between responses to emotional and neutral faces. For these significant segments, statistical analyses of functional LORETA images were performed to identify active brain regions for the different emotions. Significant differences occurred in different time segments within the first 500 ms after stimulus onset. Each emotional condition showed specific activation patterns in different brain regions, changing over time. In the majority of significant time segments, activation was highest in the right frontal areas. Strongest activation was found in the happy, sad, and disgust conditions in extended fronto-temporal areas. Happy, sad, and disgust conditions also produced earlier and more widely distributed differences than anger and fear. Our findings are in good agreement with other brain-imaging studies (PET/fMRI). But unlike other imaging techniques, LORETA allows to follow the time sequence in the millisecond-range resolution.