Neurocognitive pattern analysis of a visuospatial task: rapidly-shifting foci of evoked correlations between electrodes

Magnetoencephalography: physics, techniques, and applications in the basic and clinical neurosciences

Magnetoencephalography (MEG) is a technique used to measure the magnetic fields generated from neuronal activity in the brain. MEG has a high temporal resolution on the order of milliseconds and provides a more direct measure of brain activity when compared with hemodynamic-based neuroimaging methods such as magnetic resonance imaging and positron emission tomography. The current review focuses on basic features of MEG such as the instrumentation and the physics that are integral to the signals that can be measured, and the principles of source localization techniques, particularly the physics of beamforming and the techniques that are used to localize the signal of interest. In addition, we review several metrics that can be used to assess functional coupling in MEG and describe the advantages and disadvantages of each approach. Lastly, we discuss the current and future applications of MEG.

Neural Plasticity and Memory: Is Memory Encoded in Hydrogen Bonding Patterns?

Current models of memory storage recognize posttranslational modification vital for short-term and mRNA translation for long-lasting information storage. However, at the molecular level things are quite vague. A comprehensive review of the molecular basis of short and long-lasting synaptic plasticity literature leads us to propose that the hydrogen bonding pattern at the molecular level may be a permissive, vital step of memory storage. Therefore, we propose that the pattern of hydrogen bonding network of biomolecules (glycoproteins and/or DNA template, for instance) at the synapse is the critical edifying mechanism essential for short- and long-term memories. A novel aspect of this model is that nonrandom impulsive (or unplanned) synaptic activity functions as a synchronized positive-feedback rehearsal mechanism by revising the configurations of the hydrogen bonding network by tweaking the earlier tailored hydrogen bonds. This process may also maintain the elasticity of the related synapses involved in memory storage, a characteristic needed for such networks to alter intricacy and revise endlessly. The primary purpose of this review is to stimulate the efforts to elaborate the mechanism of neuronal connectivity both at molecular and chemical levels.

The molecular basis of memory

We propose a tripartite biochemical mechanism for memory. Three physiologic components are involved, namely, the neuron (individual and circuit), the surrounding neural extracellular matrix, and the various trace metals distributed within the matrix. The binding of a metal cation affects a corresponding nanostructure (shrinking, twisting, expansion) and dielectric sensibility of the chelating node (address) within the matrix lattice, sensed by the neuron. The neural extracellular matrix serves as an electro-elastic lattice, wherein neurons manipulate multiple trace metals (n > 10) to encode, store, and decode coginive information. The proposed mechanism explains brains low energy requirements and high rates of storage capacity described in multiples of Avogadro number (N(A) = 6 × 10(23)). Supportive evidence correlates memory loss to trace metal toxicity or deficiency, or breakdown in the delivery/transport of metals to the matrix, or its degradation. Inherited diseases revolving around dysfunctional trace metal metabolism and memory dysfunction, include Alzheimer's disease (Al, Zn, Fe), Wilson's disease (Cu), thalassemia (Fe), and autism (metallothionein). The tripartite mechanism points to the electro-elastic interactions of neurons with trace metals distributed within the neural extracellular matrix, as the molecular underpinning of "synaptic plasticity" affecting short-term memory, long-term memory, and forgetting.

Maximum multiple-correlation beamformer for estimating source connectivities in electromagnetic brain activities

Synchrony is a phenomenon of local-scale and long-range integrations within a brain circuit. Synchronous activities manifest themselves in similar temporal structures that can be statistically quantified by temporal correlation. In previous studies, synchronous activities were estimated by calculating the correlation coefficient or coherence between a single reference signal and the activity in a brain region. However, a brain circuit may involve multiple brain regions and these regions may communicate to each other through different temporal patterns. Therefore, temporal correlation to multiple reference signals is effective in quantify the source connectivities in the brain. This paper proposes a novel algorithm to calculate the maximum multiple-correlation for each brain region which has an activity estimated by a beamformer. Furthermore, this algorithm can accommodate various latencies of activities in a circuit. Experimental results demonstrate that the proposed method can accurately detect source activities correlated to the given multiple reference signals, even when unknown latencies exist between the source and references.

Revealing neuronal functional organization through the relation between multi-scale oscillatory extracellular signals

The spatial organization of neuronal elements and their connectivity make up the substrate underlying the information processing carried out in the networks they form. Conventionally, anatomical findings make the initial structure which later combines with superimposed neurophysiological information to create a functional organization map. The most common neurophysiological measure is the single neuron spike train extracted from an extracellular recording. This single neuron firing pattern provides valuable clues on information processing in a given brain area; however, it only gives a sparse and focal view of this process. Even with the increase in number of simultaneously recorded neurons, inference on their large-scale functional organization remains problematic. We propose a method of utilizing additional information derived from the same extracellular recording to generate a more comprehensive picture of neuronal functional organization. This analysis is based on the relationship between the oscillatory activity of single neurons and their neighboring neuronal populations. Two signals that reflect the multiple scales of neuronal populations are used to complement the single neuron spike train: (1) the high-frequency background unit activity representing the spiking activity of small localized sub-populations and (2) the low-frequency local field potential that represents the synaptic input to a larger global population. The three coherences calculated between pairs of these three signals arising from a single source of extracellular recording are then used to infer mosaic representations of the functional neuronal organization. We demonstrate this methodology on experimental data and on simulated leaky integrate-and-fire neurons.

Functional connectivity in the brain--is it an elusive concept?

Even though functional brain connectivity is an influential concept in modern cognitive neuroscience, it is a very controversial notion. This is why further theoretical and methodological clarification are needed to help define precisely what is meant by functional connectivity and to help frame-associated issues. In this review we present the neurophysiological concept of functional connectivity, which utilizes in a plausible manner the notion of neural assemblies, as well as local and large-scale levels of description. Here functional connectivity is the mechanism for the coordination of activity between different neural assemblies in order to achieve a complex cognitive task or perceptual process. Our theoretical and empirical findings offer new insights into possible implications of the concept of functional connectivity for cognitive neuroscience.

The elusive concept of brain connectivity

Neurons and neural populations do not function as islands onto themselves. Rather, they interact with other such elements through their afferent and efferent connections in an orchestrated manner so as to enable different sensorimotor and cognitive tasks to be performed. The concept of functional connectivity and the allied notion of effective connectivity were introduced to designate the functional strengths of such interactions. Functional neuroimaging methods, especially PET and fMRI, have been used extensively to evaluate the functional connectivity between different brain regions. After providing a brief historical review of these notions of brain connectivity, I argue that the conceptual formulations of functional and effective connectivity are far from clear. Specifically, the terms functional and effective connectivity are applied to quantities computed on types of functional imaging data (e.g., PET, fMRI, EEG) that vary in spatial, temporal, and other features, using different definitions (even for data of the same modality) and employing different computational algorithms. Until it is understood what each definition means in terms of an underlying neural substrate, comparisons of functional and/or effective connectivity across studies may appear inconsistent and should be performed with great caution.

Brain electrical microstates in subjects with panic disorder

Brain electrical microstates represent spatial configurations of scalp recorded brain electrical activity and are considered to be the basic elements of stepwise processing of information in the brain. In the present study, the hypothesis of a temporo-limbic dysfunction in panic disorder (PD) was tested by investigating the topographic descriptors of brain microstates, in particular the one corresponding to the Late Positive Complex (LPC), an event-related potential (ERP) component with generators in these regions. ERPs were recorded in PD patients and matched healthy subjects during a target detection task, in a central (CC) and a lateral condition (LC). In the CC, a leftward shift of the LPC microstate positive centroid was observed in the patients with PD versus the healthy control subjects. In the LC, the topographic descriptor of the first microstate showed a rightward shift, while those of both the second and the fourth microstate, corresponding to the LPC, revealed a leftward shift in the PD patients versus the healthy control subjects. These findings indicate an overactivation of the right hemisphere networks involved in early visual processing and a hypoactivation of the right hemisphere circuits involved in LPC generators in PD. In line with this interpretation, the abnormal topography of the LPC microstate, observed in the CC, was associated with a worse performance on a test exploring right temporo-hippocampal functioning. Topographical abnormalities found for the LPC microstate in the LC were associated with a higher number of panic attacks, suggesting a pathogenetic role of the right temporo-hippocampal dysfunction in PD.

Neural modeling and functional brain imaging: an overview

This article gives an overview of the different functional brain imaging methods, the kinds of questions these methods try to address and some of the questions associated with functional neuroimaging data for which neural modeling must be employed to provide reasonable answers.

Intention as a component of the alpha-rhythm response to mental activity

Many studies of alpha-rhythm reactivity conclude that alpha is selectively attenuated by attention accompanying mental activity. The topography of this attenuation is assumed to match the relevant functional topography of the cortex. But there are reports of apparent increased attention resulting in no change, or even enhanced alpha - the paradoxical response. It is proposed that in this case, alpha amplitude may be dependent on an intention component of behaviour. Some conflicting reports of alpha reactivity to mental processes may then be resolved. It is argued that the classical attention model of alpha is untenable, except for simple sensori-motor responses. Reasons are given to support this and the concept of intention as a neuropsychological variable is introduced. Evidence is presented for a generalisation of an oculomotor model of alpha activity proposed by Wertheim who demonstrated that alpha reduces during attentive, but not during intentive visual behaviour. The generalisation follows from reports of enhanced alpha in the few seconds prior to a skilled action in sport, and by neurophysiological evidence for a separate cortical organisation for perception and action. Varying proportions of attention and intention then add a dimension to the factors influencing alpha blocking which may explain its inconsistent response.

High resolution evoked potential imaging of the cortical dynamics of human working memory

High resolution evoked potentials (EPs), sampled from 115 channels and spatially sharpened with the finite element deblurring method, were recorded from 8 subjects during working memory (WM) and control tasks. The tasks required matching each stimulus with a preceding stimulus on either verbal or spatial attributes. All stimuli elicited a central P200 potential that was larger in the spatial tasks than in the verbal tasks, and larger in the WM tasks than in the control tasks. Frequent, non-matching stimuli elicited a frontal, positive peak at 305 msec that was larger in the spatial WM task relative to the other tasks. Irrespective of whether subjects attended to verbal or spatial stimulus attributes, non-matching stimuli in the WM tasks also elicited an enhanced P450 potential over the left frontal cortex, followed by a sustained potential over the superior parietal cortex. A posterior P390 potential elicited by infrequent, matching stimuli was smaller in amplitude for both spatial and verbal WM tasks compared to control tasks, as was a central prestimulus CNV. These results indicate that WM is a function of a distributed system with both task-specific and task-independent components. Lesion studies and course temporal resolution functional imaging methods, such as PET and fMRI, tend to paint a fairly static picture of the cortical regions which participate in the performance of WM tasks. In contrast, the fine-grain time resolution provided by imaging brain function with EP methods provides a dynamic picture of subsecond changes in the spatial distribution of WM effects over the course of individual trials, as well as evidence for differences in the activity elicited by matching and non-matching stimuli within sequences of trials. This information about the temporal dynamics of WM provides a critical complement to the fine-grain spatial resolution provided by other imaging modalities.

High resolution evoked potentials of cognition

The precision of four methods of quantifying neuroelectric signals has been improved by increasing EEG spatial sampling, using up to 124 electrodes, and by accurate anatomical registration of the EEG with Magnetic Resonance Images (MRIs). One such method, equivalent dipole modeling, is a well-known form of source localization which is useful when the generator of the scalp recorded signal approximates a simple dipolar source, as is usually the case with early and mid-latency Evoked Potentials (EPs). Two methods of enhancing spatial detail which benefit from increased spatial sampling include the Laplacian Derivation and the Finite Element Deblurring method. The latter is a new technique which estimates the EP distribution at the superficial cortical surface. The fourth method, Evoked Potential Covariance, characterizes the spatiotemporal relationships among EP segments at different recording sites. This is useful when studying "functional neural networks" underlying higher cognitive functions. These methods are reviewed and examples of results of their application in recent experiments are presented.

Relationships between EEG coherence and neuropsychological tests in dementia

Previous research has demonstrated differences in resting state EEG coherence among groups of subjects with dementia of the Alzheimer type (DAT), multi-infarct dementia (MID), and normal elderly controls. Since reduced coherence between brain sites has been thought to reflect functional disconnection between brain areas, we hypothesized that decreased coherence would be associated with cognitive dysfunction as assessed by neuropsychological tests. We correlated several neuropsychological tests with four coherence variables and found that reduced coherence was associated with impairment on specific neuropsychological tests in ways that conform to and supplement current knowledge about the localization of brain functions. The results are consistent with the hypothesis that coherence reflects a functional breakdown in communication between brain areas, and that coherence may be a more precise way to localize brain function than other EEG variables.

Subdural grid recordings of distributed neocortical networks involved with somatosensory discrimination

Previous studies suggest that evidence for the sub-second activation of distributed neural networks can be obtained by computing the covariance between segments of the scalp-recorded evoked potential. However, the cortical representation of such potentials is not known. Here we report a case study where the evoked potential covariance (EPC) measure was applied to data recorded from a 58-channel subdural grid implanted in an epilepsy patient. Recordings were made while the patient performed a task that required judging the somatosensory intensities of electrical stimuli and executing precise finger flexion responses in response to a subset of those stimuli. Post-stimulus EPC patterns involved covariances between somatosensory, motor, and temporal regions. Pre-stimulus EPC patterns involved these same regions, but only when it could be anticipated that the upcoming stimulus would likely require a response. The majority of the observed EPCs occurred with non-zero time-lags, and these EPCs often involved non-adjacent electrode pairs. Thus, the observed EPCs were unlikely to arise solely from volume conduction. Rather, they appeared to reflect the transient integration of activity across distinct cortical processing nodes.

Reduced EEG coherence in dementia: state or trait marker?

Recent work from our laboratory demonstrated that quantitative electroencephalographic (EEG) coherence between brain areas linked by long cortico-cortical fibers (termed "fascicle" coherence) was differentially reduced in subjects with Alzheimer's disease, whereas coherence between brain areas linked by short cortico-cortical and cortico-subcortical fibers in postcentral areas (termed "visual" coherence) was differentially reduced in subjects with multi-infarct dementia. In this study, we investigated whether these differences in coherence represent "trait" or "state" markers for dementia. Visual coherence demonstrated high stability in both demented groups as assessed by both one-year test-retest reliabilities and analysis of group mean change. Fascicle coherence demonstrated good stability in multi-infarct dementia and control subjects, but some variability was observed in Alzheimer's subjects, suggesting both state and trait factors may be involved. These findings complement neuropathologic studies, and suggest that decreases in coherence may serve as a diagnostic trait markers for these two types of dementia. The role of state factors in Alzheimer's disease requires further investigation.

Estimation of the spatio-temporal correlations of biological electrical sources from their magnetic fields

Quasi-static electromagnetic systems, such as those found in biological systems, produce electric and magnetic fields whose temporal and spatial correlations reflect the source correlations in a straightforward manner. These fields can be noninvasively measured, providing information about the coherence properties of the source, which may directly represent ordered physiological processes of the organism. The description "biocoherence" will be adopted here to refer to the manifestation of the coherence in the magnetic measurements of these sources due solely to physiological processes. In this paper a general formulation linking the spatial and temporal coherence of measurable magnetic fields with the corresponding spatial and temporal coherence of the inaccessible current sources is derived in the quasi-static model. A method for reconstructing the spatial and temporal coherence of the source distribution is then presented. Such coherence maps would be useful descriptors of physiological processes occurring over time and space, and would represent more information than an image of the current sources frozen in time, or even a temporal sequence of such images.

Interregional correlations of resting cerebral glucose metabolism in old and young women

A correlational analysis of normalized (regional to whole-brain) regional cerebral metabolic rates for glucose obtained in the 'resting' state (eyes covered, ears plugged) using [18F]fluorodeoxyglucose, demonstrated differences between old and young women in patterns of functional associations. Fifteen healthy young (age less than 40 years) and 17 healthy old women (age greater than 64 years) were scanned with a Scanditronix PC1024-7B tomograph. The brain was divided into 65 regions of interest. The old women had fewer and less positive correlations between pairs of metabolic ratios in the frontal and parietal cortices. The results suggest an age-related reduction in frontal and parietal functional interactions in the 'resting' state that is consistent with a prior correlation analysis using a low resolution ECAT II scanner on young and old men. Reduced functional interactions may reflect age-related cognitive changes.

Cognitive neuropsychophysiology of thought imagery versus imagination imagery

The present study was designed to measure patterns of cortical activation during two types of mental imagery: "thought imagery" and "imagination imagery." Topographic cortical power spectrum (CPS) analyses were conducted for 10 subjects during four experimental conditions. EEG was recorded from right and left hemispheres at frontal, temporal, parietal, and occipital leads. Subjects gave rating of visual vividness and quasisensory subjective experience after each imagery condition. Examination of subjects' ratings revealed that they reported significantly greater visual vividness and quasisensory experiences during the imagination imagery condition, as compared to the thought imagery condition. Topographic CPS analyses showed significant individual differences in patterns of brain activation, which were reliable across conditions. Individual differences in lateralization of brain activity were found in terms of an anterior-posterior gradient. Within-subject analyses showed CPS changes as a function of condition. Three major patterns of CPS changes across condition were delineated.

Functional interactions in the brain: use of correlations between regional metabolic rates

Correlation coefficients between pairs of regional metabolic rates have been used to study patterns of functional associations among brain regions in humans and animals. An overview is provided concerning the additional information about brain functioning this type of analysis yields. A computer simulation model is presented for the purpose of giving a partial validation for correlational analysis. The model generates a set of simulated metabolic data upon which correlational analysis is performed. Because the underlying pattern of functional couplings in the model is known, these simulations demonstrate that the correlation coefficient between normalized metabolic rates is proportional to the strength of the functional coupling constant and that correlational analysis yields information on regional involvement in neural systems not evident in the pattern of absolute metabolic values.

Effects of prolonged mental work on functional brain topography

Topographic patterns of event-related covariance between electrodes were measured from subjects performing a difficult memory and fine-motor control task for 10-14 h. Striking changes occurred in the patterns after subjects performed the task for an average of 7-9 h, but before performance deteriorated. Pattern strength was reduced in a fraction-of-a-second-long response preparation interval over midline precentral areas and over the entire left hemisphere. By contrast, pattern strength in a succeeding response inhibition interval was reduced over all areas. The pattern changed least in an intervening interval associated with visual-stimulus processing. This suggests that, in addition to the well-known global reduction in neuroelectric signal strength, functional neural networks are selectively affected by sustained mental work in specific fraction-of-a-second task intervals.

Simulating functional interactions in the brain: a model for examining correlations between regional cerebral metabolic rates

A computer simulation model was developed to investigate the use of interregional correlations of cerebral metabolic rates to analyze functional interactions in the brain. The model generates simulated metabolic data for individual brain regions in a specified number of subjects, where there are defined functional couplings amongst the regions. Random numbers provide the variability seen in measured metabolic data. Correlational analysis is performed on these simulated data sets. The parameters of the model can be chosen so that simulated and actual metabolic data are very similar. The model demonstrates that the change in the correlation coefficient between normalized metabolic data in two brain regions is related to the change in the strength of the functional association between the two regions. The model also is used to explore the relations between patterns of correlations and the underlying sets of functional couplings. The results indicate that correlational analysis provides more information about regional involvement in neural systems than does region-by-region comparisons of absolute metabolic rates.

Emulation of somatosensory evoked potential (SEP) components with the 3-shell head model and the problem of 'ghost potential fields' when using an average reference in brain mapping

In brain topographic mapping, the putative location and orientation in the head space of neural generators are currently inferred from the features of negative and positive scalp potential fields. This procedure requires the use of a fairly neutral reference. The frequently advocated average reference creates problems because its effect is not merely to change a (steady) zero reference level, but to dynamically zero-center all scalp potentials at each latency. Ghost potential fields are thus created at the latencies for which the integral of scalp recorded potentials differs from zero. These distortions of brain mapping have been analyzed with a true 3-shell head model in conjunction with the emulation of SEP components. In the head model, surface potential fields generated by dipoles or dipole sheets of various depths and orientations were computed either over the north hemisphere, so as to emulate scalp recorded SEP components, or over the entire equivalent head sphere. The spurious effects of the average reference are shown to occur because it is computed from a limited number of (scalp) electrodes which fail to survey the bottom half of the head.

Event-related covariances during a bimanual visuomotor task. II. Preparation and feedback

Event-related covariance (ERC) patterns were computed from pre-stimulus and feedback intervals of a bimanual, visuomotor judgment task performed by 7 right-handed men. Late contingent negative variation (CNV) ERC patterns that preceded subsequently accurate right- or left-hand responses differed from patterns that preceded subsequently inaccurate responses. Recordings from electrodes placed at left frontal, midline antero-central, and appropriately contralateral central and parietal sites were prominent in ERC patterns of subsequently accurate performances. This suggests that a distributed cortical 'preparatory network,' composed of distinct cognitive, integrative motor, somesthetic, and motor components, is essential for accurate visuomotor performance. ERC patterns related to feedback about accurate and inaccurate responses were similar to each other in the interval immediately after feedback onset, but began to differ in an interval spanning an early P300 peak. The difference became even greater in an interval spanning a late P300 peak. For both early and late P300 peaks, ERC patterns following feedback about inaccurate performance involved more frontal sites than did those following feedback about accurate performance. Together with the stimulus- and response-locked results presented in part I, results of this study on the preparatory and feedback periods suggest that ERCs show salient features of the rapidly shifting, functional cortical networks that are responsible for simple cognitive tasks. ERCs thus provide a new perspective on information processing in the human brain in relation to behavior--a perspective that supplements conventional EEG and ERP procedures.

Event-related covariances during a bimanual visuomotor task. I. Methods and analysis of stimulus- and response-locked data

A new method that measures between-channel, event-related covariances (ERCs) from scalp-recorded brain signals has been developed. The method was applied to recordings of 26 EEG channels from 7 right-handed men performing a bimanual visuomotor judgment task that required fine motor control. Covariance and time-delay measures were derived from pairs of filtered, laplacian-derived, averaged wave forms, which were enhanced by rejection of outlying trials, in intervals spanning event-related potential components. Stimulus- and response-locked ERC patterns were consistent with functional neuroanatomical models of visual stimulus processing and response execution. In early post-stimulus intervals, ERC patterns differed according to the physical properties of the stimulus; in later intervals, the patterns differed according to the subjective interpretation of the stimulus. The response-locked ERC patterns suggested 4 major cortical generators for the voluntary fine motor control required by the task: motor, somesthetic, premotor and/or supplementary motor, and prefrontal. This new method may thus be an advancement toward characterizing, both spatially and temporally, functional cortical networks in the human brain responsible for perception and action.

Dynamic functional topography of cognitive tasks

Improved neuroelectric recording and analysis tools are yielding increasingly specific information about the spatial and temporal features of neurocognitive processes. Such tools include recordings with up to 125 channels, digital signal processing techniques, and correlation of neuroelectric measures with anatomical information from magnetic resonance images. These tools, and their application to the study of cognitive functions, are presented in this paper.

Trial-to-trial variability of single potentials: methodological concepts and results

Variability of single visual evoked potentials was investigated by means of three statistical tests sensitive to amplitude variations, gradual changes, and latency jitter, respectively. In a sample of (n = 78) normal children, a considerable number of inhomogeneous responders was found, and most prominent were gradual potential changes and latency jitter. Removal of latency jitter demonstrated that the gradual changes are not of latency type and only partly of the amplitude type. As found from empirical densities, there is strong indication that there were subpopulations differing in their response style. On the whole, however, it was concluded that there was no clear, interindividually stable type of response variation in these data.

Human neuroelectric patterns predict performance accuracy

In seven right-handed adults, the brain electrical patterns before accurate performance differed from the patterns before inaccurate performance. Activity overlying the left frontal cortex and the motor and parietal cortices contralateral to the performing hand preceded accurate left- or right-hand performance. Additional strong activity overlying midline motor and premotor cortices preceded left-hand performance. These measurements suggest that brief, spatially distributed neural activity patterns, or "preparatory sets," in distinct cognitive, somesthetic-motor, and integrative motor areas of the human brain may be essential precursors of accurate visuomotor performance.

Evoked potential maps in learning disabled children

Some childhood learning disabilities are associated with altered synchrony patterns of brain evoked potentials. Scalp recorded electrical synchrony between selected brain regions was measured in response to visual, auditory and somatosensory stimuli and compared between a group of learning disabled children and a group of normal children. Statistically significant inter-group differences revealed stimulus dependent greater inter-regional EP synchrony in the learning disabled group. These findings support the notion that some childhood learning disabilities reflect, in part, altered connections between selected brain regions.

Improved event-related potential estimation using statistical pattern classification

A new method of ERP estimation with minimal statistical assumptions is presented. A mathematical pattern classification procedure is used to select trials with discriminable event-related signals in a time interval of interest. A method of forming a reference 'baseline' is also presented. Stimulus-registered and response-registered 'enhanced' ERP averages computed from selected trials of a visuo-motor experiment show substantial enhancement of event-related signals, especially for channels with weak signals, while rejected trials have minimal event-related signals.

The brain's magnetic field: some effects of multiple sources on localization methods

The theoretical basis for magnetic field recording (MEG) methods is briefly summarized. Lines of constant radial magnetic field on a spherical surface, which are typically used in MEG applications to locate sources, are shown for various multiple dipole sources. It is shown that the usual localization methods are subject to relatively large error if only one additional dipole is present. New methods to improve spatial resolution are discussed.