Combined EEG/MEG Can Outperform Single Modality EEG or MEG Source Reconstruction in Presurgical Epilepsy Diagnosis

We investigated two important means for improving source reconstruction in presurgical epilepsy diagnosis. The first investigation is about the optimal choice of the number of epileptic spikes in averaging to (1) sufficiently reduce the noise bias for an accurate determination of the center of gravity of the epileptic activity and (2) still get an estimation of the extent of the irritative zone. The second study focuses on the differences in single modality EEG (80-electrodes) or MEG (275-gradiometers) and especially on the benefits of combined EEG/MEG (EMEG) source analysis. Both investigations were validated with simultaneous stereo-EEG (sEEG) (167-contacts) and low-density EEG (ldEEG) (21-electrodes). To account for the different sensitivity profiles of EEG and MEG, we constructed a six-compartment finite element head model with anisotropic white matter conductivity, and calibrated the skull conductivity via somatosensory evoked responses. Our results show that, unlike single modality EEG or MEG, combined EMEG uses the complementary information of both modalities and thereby allows accurate source reconstructions also at early instants in time (epileptic spike onset), i.e., time points with low SNR, which are not yet subject to propagation and thus supposed to be closer to the origin of the epileptic activity. EMEG is furthermore able to reveal the propagation pathway at later time points in agreement with sEEG, while EEG or MEG alone reconstructed only parts of it. Subaveraging provides important and accurate information about both the center of gravity and the extent of the epileptogenic tissue that neither single nor grand-averaged spike localizations can supply.     

Intracranial EEG and human brain mapping

This review is an attempt to highlight the value of human intracranial recordings (intracranial electro-encephalography, iEEG) for human brain mapping, based on their technical characteristics and based on the corpus of results they have already yielded. The advantages and limitations of iEEG recordings are introduced in detail, with an estimation of their spatial and temporal resolution for both monopolar and bipolar recordings. The contribution of iEEG studies to the general field of human brain mapping is discussed through a review of the effects observed in the iEEG while patients perform cognitive tasks. Those effects range from the generation of well-localized evoked potentials to the formation of large-scale interactions between distributed brain structures, via long-range synchrony in particular. A framework is introduced to organize those iEEG studies according to the level of complexity of the spatio-temporal patterns of neural activity found to correlate with cognition. This review emphasizes the value of iEEG for the study of large-scale interactions, and describes in detail the few studies that have already addressed this point.     

Replicability of MEG and EEG measures of the auditory N1/N1m-response

We investigated the replicability of the source location, amplitude and latency measures of the auditory evoked N1 (EEG) and N1m (MEG) responses. Each of the 5 subjects was measured 6 times in two recording sessions. Responses to monaural stimuli were recorded from 122 MEG and 64 EEG channels simultaneously. The EEG data were modeled with a symmetrically-located dipole pair. For the MEG data, one dipole in each hemisphere was located independently using a subset of channels. Standard deviation (SD) was used as a measure for replicability. The average SD of the x, y and z coordinates of the contralateral N1m dipole was about 2 mm, whereas the corresponding figures for the ipsilateral N1m and the contra- and ipsilateral N1 were about twice as large. The SDs of the dipole amplitudes and latencies were almost equal with MEG and EEG. The amplitude and latency measures of the MEG field gradient waveforms were almost as replicable as those of the dipole models. The results suggest that both MEG and EEG can be used for investigating the simultaneous activity of the left and right auditory cortices independently, MEG being superior in certain experimental setups.     

Functional Mapping with Simultaneous MEG and EEG

We use magnetoencephalography (MEG) and electroencephalography (EEG) to locate and determine the temporal evolution in brain areas involved in the processing of simple sensory stimuli. We will use somatosensory stimuli to locate the hand somatosensory areas, auditory stimuli to locate the auditory cortices, visual stimuli in four quadrants of the visual field to locate the early visual areas. These type of experiments are used for functional mapping in epileptic and brain tumor patients to locate eloquent cortices. In basic neuroscience similar experimental protocols are used to study the orchestration of cortical activity. The acquisition protocol includes quality assurance procedures, subject preparation for the combined MEG/EEG study, and acquisition of evoked-response data with somatosensory, auditory, and visual stimuli. We also demonstrate analysis of the data using the equivalent current dipole model and cortically-constrained minimum-norm estimates. Anatomical MRI data are employed in the analysis for visualization and for deriving boundaries of tissue boundaries for forward modeling and cortical location and orientation constraints for the minimum-norm estimates.Download video file.^{(69M, mp4)}     

Classification methods for ongoing EEG and MEG signals

Classification algorithms help predict the qualitative properties of a subject's mental state by extracting useful information from the highly multivariate non-invasive recordings of his brain activity. In particular, applying them to Magneto-encephalography (MEG) and electro-encephalography (EEG) is a challenging and promising task with prominent practical applications to e.g. Brain Computer Interface (BCI). In this paper, we first review the principles of the major classification techniques and discuss their application to MEG and EEG data classification. Next, we investigate the behavior of classification methods using real data recorded during a MEG visuomotor experiment. In particular, we study the influence of the classification algorithm, of the quantitative functional variables used in this classifier, and of the validation method. In addition, our findings suggest that by investigating the distribution of classifier coefficients, it is possible to infer knowledge and construct functional interpretations of the underlying neural mechanisms of the performed tasks. Finally, the promising results reported here (up to 97% classification accuracy on 1-second time windows) reflect the considerable potential of MEG for the continuous classification of mental states.     

A review of EEG and MEG for brainnetome research

The majority of brain activities are performed by functionally integrating separate regions of the brain. Therefore, the synchronous operation of the brain’s multiple regions or neuronal assemblies can be represented as a network with nodes that are interconnected by links. Because of the complexity of brain interactions and their varying effects at different levels of complexity, one of the corresponding authors of this paper recently proposed the brainnetome as a new –ome to explore and integrate the brain network at different scales. Because electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive and have outstanding temporal resolution and because they are the primary clinical techniques used to capture the dynamics of neuronal connections, they lend themselves to the analysis of the neural networks comprising the brainnetome. Because of EEG/MEG’s applicability to brainnetome analyses, the aim of this review is to identify the procedures that can be used to form a network using EEG/MEG data in sensor or source space and to promote EEG/MEG network analysis for either neuroscience or clinical applications. To accomplish this aim, we show the relationship of the brainnetome to brain networks at the macroscale and provide a systematic review of network construction using EEG and MEG. Some potential applications of the EEG/MEG brainnetome are to use newly developed methods to associate the properties of a brainnetome with indices of cognition or disease conditions. Associations based on EEG/MEG brainnetome analysis may improve the comprehension of the functioning of the brain in neuroscience research or the recognition of abnormal patterns in neurological disease.     

Topographical EEG maps of human responses to odors

The physiological response to seven odors (birch tar, galbanum,heliotropine, jasmine, lavender, lemon and peppermint) was assessedby EEG recordings from 19 scalp loci from 16 young adult females.Topographic maps were constructed from the amplitude spectrain four frequency bands: delta (1–4 Hz), theta (4–8Hz), alpha (8–13 Hz) and beta (13–30 Hz). Eightseconds of representative and artifact-free EEG were selectedfor FFT analysis before onset of odor delivery, and at threetimes after stimulus onset. EEG was also quantified at 30 safter stimulus termination. Subjects differed in their subjective responses to the odors,with the most consistently arousing and strong odors being galbanum,lavender, lemon and peppermint. Heliotropine was notably weak.The most pleasant odors were lemon and peppermint, while birchtar, galbanum and lavender were consistently unpleasant. EEGmap changes occurred in one or more frequency bands in eachsubject in response to one or more of the odors. EEG map changessometimes occurred even with weak odors and even when the subjectseemed unaware of the odor's presence. This was most notablewith heliotropine. Across subjects, the most consistent responses to odors werein the theta band. Analysis of variance confirmed that certainodors caused statistically significant theta increases overthe left anterior group of electrodes. Both right hemispheregroups tended to have significant theta increases. The odorsthat caused the greatest increase in theta were birch tar, jasmine,lavender and lemon. On the other hand, during blank controltrials, theta activity diminished. There was also a significantodor by epoch interaction over the right posterior set of electrodes.Several of the odors caused increased theta at one or more epochs.Lemon caused an immediate increase in theta that abated withtime. Birch tar induced a delayed response that persisted afterthe stimulus was turned off. Jasmine and lavender tended toinduce theta sooner than birch tar, but the effect did not outlastthe stimulus. Increased theta was not associated with EEG signsof drowsiness. We conclude that all odors affected the EEG in at least somesubjects, and all subjects responded to at least some odors.Widespread increase in theta occurred in most subjects duringstimulation with such odors as birch tar, jasmine, lavenderand lemon.     

Source Reconstruction Accuracy of MEG and EEG Bayesian Inversion Approaches

Electro- and magnetoencephalography allow for non-invasive investigation of human brain activation and corresponding networks with high temporal resolution. Still, no correct network detection is possible without reliable source localization. In this paper, we examine four different source localization schemes under a common Variational Bayesian framework. A Bayesian approach to the Minimum Norm Model (MNM), an Empirical Bayesian Beamformer (EBB) and two iterative Bayesian schemes (Automatic Relevance Determination (ARD) and Greedy Search (GS)) are quantitatively compared. While EBB and MNM each use a single empirical prior, ARD and GS employ a library of anatomical priors that define possible source configurations. The localization performance was investigated as a function of (i) the number of sources (one vs. two vs. three), (ii) the signal to noise ratio (SNR; 5 levels) and (iii) the temporal correlation of source time courses (for the cases of two or three sources). We also tested whether the use of additional bilateral priors specifying source covariance for ARD and GS algorithms improved performance. Our results show that MNM proves effective only with single source configurations. EBB shows a spatial accuracy of few millimeters with high SNRs and low correlation between sources. In contrast, ARD and GS are more robust to noise and less affected by temporal correlations between sources. However, the spatial accuracy of ARD and GS is generally limited to the order of one centimeter. We found that the use of correlated covariance priors made no difference to ARD/GS performance.     

Modelling and detecting deep brain activity with MEG and EEG

We introduce an anatomical and electrophysiological model of deep brain structures dedicated to magnetoencephalography (MEG) and electroencephalography (EEG) source imaging. So far, most imaging inverse models considered that MEG/EEG surface signals were predominantly produced by cortical, hence superficial, neural currents. Here we question whether crucial deep brain structures such as the basal ganglia and the hippocampus may also contribute to distant, scalp MEG and EEG measurements. We first design a realistic anatomical and electrophysiological model of these structures and subsequently run Monte-Carlo experiments to evaluate the respective sensitivity of the MEG and EEG to signals from deeper origins. Results indicate that MEG/EEG may indeed localize these deeper generators, which is confirmed here from experimental MEG data reporting on the modulation of alpha (10–12 Hz) brain waves.     

Accounting for Linear Transformations of EEG and MEG Data in Source Analysis

Analyses of electro- and magnetoencephalography (EEG, MEG) data often involve a linear modification of signals at the sensor level. Examples include re-referencing of the EEG, computation of synthetic gradiometer in MEG, or the removal of artifactual independent components to clean EEG and MEG data. A question of practical relevance is, if such modifications must be accounted for by adapting the physical forward model (leadfield) before subsequent source analysis. Here, we show that two scenarios need to be differentiated. In the first scenario, which corresponds to re-referencing the EEG and synthetic gradiometer computation in MEG, the leadfield must be adapted before source analysis. In the second scenario, which corresponds to removing artifactual components to ‘clean’ the data, the leadfield must not be changed. We demonstrate and discuss the consequences of wrongly modifying the leadfield in the latter case for an example. Future EEG and MEG studies employing source analyses should carefully consider whether and, if so, how the leadfield must be modified as explicated here.     

Coupled oscillators for modeling and analysis of EEG/MEG oscillations.

This study presents three EEG/MEG applications in which the modeling of oscillatory signal components offers complementary analysis and an improved explanation of the underlying generator structures. Coupled oscillator networks were used for modeling. Parameters of the corresponding ordinary coupled differential equation (ODE) system are identified using EEG/MEG data and the resulting solution yields the modeled signals. This model-related analysis strategy provides information about the coupling quantity and quality between signal components (example 1, neonatal EEG during quiet sleep), allows identification of the possible contribution of hidden generator structures (example 2, 600-Hz MEG oscillations in somatosensory evoked magnetic fields), and can explain complex signal characteristics such as amplitude-frequency coupling and frequency entrainment (example 3, EEG burst patterns in sedated patients).     

Extensive cochleotopic mapping of human auditory cortical fields obtained with phase-encoding FMRI

The primary sensory cortices are characterized by a topographical mapping of basic sensory features which is considered to deteriorate in higher-order areas in favor of complex sensory features. Recently, however, retinotopic maps were also discovered in the higher-order visual, parietal and prefrontal cortices. The discovery of these maps enabled the distinction between visual regions, clarified their function and hierarchical processing. Could such extension of topographical mapping to high-order processing regions apply to the auditory modality as well? This question has been studied previously in animal models but only sporadically in humans, whose anatomical and functional organization may differ from that of animals (e.g. unique verbal functions and Heschl''s gyrus curvature). Here we applied fMRI spectral analysis to investigate the cochleotopic organization of the human cerebral cortex. We found multiple mirror-symmetric novel cochleotopic maps covering most of the core and high-order human auditory cortex, including regions considered non-cochleotopic, stretching all the way to the superior temporal sulcus. These maps suggest that topographical mapping persists well beyond the auditory core and belt, and that the mirror-symmetry of topographical preferences may be a fundamental principle across sensory modalities.     

Discrimination of timbre in early auditory responses of the human brain

Background

The issue of how differences in timbre are represented in the neural response still has not been well addressed, particularly with regard to the relevant brain mechanisms. Here we employ phasing and clipping of tones to produce auditory stimuli differing to describe the multidimensional nature of timbre. We investigated the auditory response and sensory gating as well, using by magnetoencephalography (MEG).

Methodology/Principal Findings

Thirty-five healthy subjects without hearing deficit participated in the experiments. Two different or same tones in timbre were presented through conditioning (S1) – testing (S2) paradigm as a pair with an interval of 500 ms. As a result, the magnitudes of auditory M50 and M100 responses were different with timbre in both hemispheres. This result might support that timbre, at least by phasing and clipping, is discriminated in the auditory early processing. The second response in a pair affected by S1 in the consecutive stimuli occurred in M100 of the left hemisphere, whereas both M50 and M100 responses to S2 only in the right hemisphere reflected whether two stimuli in a pair were the same or not. Both M50 and M100 magnitudes were different with the presenting order (S1 vs. S2) for both same and different conditions in the both hemispheres.

Conclusions/Significances

Our results demonstrate that the auditory response depends on timbre characteristics. Moreover, it was revealed that the auditory sensory gating is determined not by the stimulus that directly evokes the response, but rather by whether or not the two stimuli are identical in timbre.     

Dynamic characteristics of the human resonance EEG responses to rhythmic photostimulation

The development of the resonance EEG responses of the left and right occipital areas was studied in right-handed men during prolonged (12 or 120 s) rhythmic, photostimulation with the intensity of 0.7 J and frequencies of 6, 10, and 16 Hz. Analysis of the EEG fine spectral structure was applied to compare the accumulated baseline EEG spectra and EEG spectra during photostimulation, to observe the dynamics of the short-term spectra and to detect power changes in the EEG narrow spectral band sharply coincident with the stimulation frequency. The more pronounced EEG responses to photostimulation were observed in subjects with the initially low EEG baseline, α-rhythm. Two-minute flash trains produced a substantial increase in the EEG power within the stimulation frequency with superposed oscillatory processes with different periods. These fluctuations are considered a reflection of intricate interaction between the adaptive and resonance EEG responses to the presented intermittent stimulation. Under 12-s stimulation the resonance EEG responses are steadily recorded within the first 3 s of stimulation and immediately after the flash cessation EEG power at the stimulation frequency returns to the initial level. The resonance EEG responses were more pronounced in the right hemisphere than in the left one, especially, at the stimulation frequencies of 6 and 16 Hz. With increasing the stimulation frequency, the maximum of resonance EEG responses was reached earlier. Under the stimulation frequency of 6 Hz, the maximal response was recorded 9–12 s after the beginning of flashes, at the frequencies of 10 and 16 Hz, it was recorded within 3–6 and 3 s, respectively.     

Experience-dependent modulation of tonotopic neural responses in human auditory cortex.

Experience-dependent plasticity of receptive fields in the auditory cortex has been demonstrated by electrophysiological experiments in animals. In the present study we used PET neuroimaging to measure regional brain activity in volunteer human subjects during discriminatory classical conditioning of high (8000 Hz) or low (200 Hz) frequency tones by an aversive 100 dB white noise burst. Conditioning-related, frequency-specific modulation of tonotopic neural responses in the auditory cortex was observed. The modulated regions of the auditory cortex positively covaried with activity in the amygdala, basal forebrain and orbitofrontal cortex, and showed context-specific functional interactions with the medial geniculate nucleus. These results accord with animal single-unit data and support neurobiological models of auditory conditioning and value-dependent neural selection.     

Gustatory evoked cortical activity in humans studied by simultaneous EEG and MEG recording

Evoked potentials are widely used in clinical medicine for objective evaluation of sensory disturbances. However, gustatory evoked potentials (GEPs) have not been extensively studied due to lack of agreement among investigators regarding the waveforms. In this study GEPs and gustatory magnetic fields (GEMfs) were simultaneously recorded from five subjects in response to 0.3 M NaCl in an attempt to establish GEP recording as an objective gustatometer. Each subject received a total of 240 stimulus presentations over six sessions. Three GEP components (P1, N1 and P2) were observed and correlated with their corresponding equivalent current dipoles (ECD1, ECD2 and ECD3, respectively). ECD1 was localized to area G in all subjects, P1 being the indicator of intact gustatory projection to area G. No significant GEP activity was detected during the time preceding P1, which suggests that there was no activity in cortical gyri other than that detected by magnetoencephalography. ECD2 and ECD3 were localized to various cortical structures, including the inferior insula and the superior temporal sulcus, indicating that N1 and P2 reflect higher order gustatory functions. The present results indicate that measurement of GEPs may be useful for objective evaluation of gustatory disturbance.