Neural activity underlying the detection of an object movement by an observer during forward self-motion: Dynamic decoding and temporal evolution of directional cortical connectivity.

Relatively little is known about how the human brain identifies movement of objects while the observer is also moving in the environment. This is, ecologically, one of the most fundamental motion processing problems, critical for survival. To study this problem, we used a task which involved nine textured spheres moving in depth, eight simulating the observer's forward motion while the ninth, the target, moved independently with a different speed towards or away from the observer. Capitalizing on the high temporal resolution of magnetoencephalography (MEG) we trained a Support Vector Classifier (SVC) using the sensor-level data to identify correct and incorrect responses. Using the same MEG data, we addressed the dynamics of cortical processes involved in the detection of the independently moving object and investigated whether we could obtain confirmatory evidence for the brain activity patterns used by the classifier. Our findings indicate that response correctness could be reliably predicted by the SVC, with the highest accuracy during the blank period after motion and preceding the response. The spatial distribution of the areas critical for the correct prediction was similar but not exclusive to areas underlying the evoked activity. Importantly, SVC identified frontal areas otherwise not detected with evoked activity that seem to be important for the successful performance in the task. Dynamic connectivity further supported the involvement of frontal and occipital-temporal areas during the task periods. This is the first study to dynamically map cortical areas using a fully data-driven approach in order to investigate the neural mechanisms involved in the detection of moving objects during observer's self-motion.

Toward noninvasive monitoring of ongoing electrical activity of human uterus and fetal heart and brain.

OBJECTIVE: To evaluate whether a full-coverage fetal-maternal scanner can noninvasively monitor ongoing electrophysiological activity of maternal and fetal organs. METHODS: A simulation study was carried out for a scanner with an array of magnetic field sensors placed all around the torso from the chest to the hip within a horizontal magnetic shielding enclosure. The magnetic fields from internal organs and an external noise source were computed for a pregnant woman with a 35-week old fetus. Signal processing methods were used to reject the external and internal interferences, to visualize uterine activity, and to detect activity of fetal heart and brain. RESULTS: External interference was reduced by a factor of 1000, sufficient for detecting signals from internal organs when combined with passive and active shielding. The scanner rejects internal interferences better than partial-coverage arrays. It can be used to estimate currents around the uterus. It clearly detects spontaneous activity from the fetal heart and brain without averaging and weaker evoked brain activity at all fetal head positions after averaging. CONCLUSION: The simulated device will be able to monitor the ongoing activity of the fetal and maternal organs. SIGNIFICANCE: This type of scanner may become a novel tool in fetal medicine.

Time-frequency mixed-norm estimates: sparse M/EEG imaging with non-stationary source activations.

Magnetoencephalography (MEG) and electroencephalography (EEG) allow functional brain imaging with high temporal resolution. While solving the inverse problem independently at every time point can give an image of the active brain at every millisecond, such a procedure does not capitalize on the temporal dynamics of the signal. Linear inverse methods (minimum-norm, dSPM, sLORETA, beamformers) typically assume that the signal is stationary: regularization parameter and data covariance are independent of time and the time varying signal-to-noise ratio (SNR). Other recently proposed non-linear inverse solvers promoting focal activations estimate the sources in both space and time while also assuming stationary sources during a time interval. However such a hypothesis holds only for short time intervals. To overcome this limitation, we propose time-frequency mixed-norm estimates (TF-MxNE), which use time-frequency analysis to regularize the ill-posed inverse problem. This method makes use of structured sparse priors defined in the time-frequency domain, offering more accurate estimates by capturing the non-stationary and transient nature of brain signals. State-of-the-art convex optimization procedures based on proximal operators are employed, allowing the derivation of a fast estimation algorithm. The accuracy of the TF-MxNE is compared with recently proposed inverse solvers with help of simulations and by analyzing publicly available MEG datasets.

Language lateralization represented by spatiotemporal mapping of magnetoencephalography.

BACKGROUND AND PURPOSE: Determination of hemispheric language dominance is critical for planning epilepsy surgery. We assess the usefulness of spatiotemporal source analysis of magnetoencephalography for determining language laterality. MATERIALS AND METHODS: Thirty-five patients with epilepsy were studied. The patients performed a semantic word-processing task during MEG recording. Epochs containing language-related neuromagnetic activity were averaged after preprocessing. The averaged data between 250 and 550 ms after stimulus were analyzed by using dynamic statistical parametric mapping. ROIs were obtained in the opercular and triangular parts of the inferior frontal gyrus, superior temporal gyrus, and supramarginal gyrus in both hemispheres. We calculated laterality indices according to 1) dSPM-amplitude method, based on the amplitude of activation in the ROIs, and 2) dSPM-counting method, based on the number of unit dipoles with activation over a threshold in the ROIs. The threshold was determined as half of the maximum value in all ROIs for each patient. A LI ≥0.10 or ≤-0.10 was considered left- or right-hemisphere dominance, respectively; a LI between -0.10 and 0.10 was considered bilateral. All patients underwent an intracarotid amobarbital procedure as part of presurgical evaluation. RESULTS: The dSPM-counting method demonstrated laterality consistent with the IAP in 32 of 35 patients (91.4%), the remaining 3 (8.6%) demonstrated bilateral language representation, whereas the dSPM-amplitude method showed 18 (51.4%) concordant and 17 (48.6%) bilateral. No laterality opposite to the IAP was found. CONCLUSIONS: Spatiotemporal mapping of language lateralization with the dSPM-counting method may reduce the necessity for an IAP in as many as 90% of patients.

Multimodal imaging of spike propagation: a technical case report.

We report an 11-year-old boy with intractable epilepsy, who had cortical dysplasia in the right superior frontal gyrus. Spatiotemporal source analysis of MEG and EEG spikes demonstrated a similar time course of spike propagation from the superior to inferior frontal gyri, as observed on intracranial EEG. The tractography reconstructed from DTI showed a fiber connection between these areas. Our multimodal approach demonstrates spike propagation and a white matter tract guiding the propagation.

Quantification of the benefit from integrating MEG and EEG data in minimum l2-norm estimation.

Source current estimation from electromagnetic (MEG and EEG) signals is an ill-posed problem that often produces blurry or inaccurately positioned estimates. The two modalities have distinct factors limiting the resolution, e.g., MEG cannot detect radially oriented sources, while EEG is sensitive to accuracy of the head model. This makes combined EEG+MEG estimation techniques desirable, but different acquisition noise statistics, complexity of the head models, and lack of pertinent metrics all complicate the assessment of the resulting improvements. We investigated analytically the effect of including EEG recordings in MEG studies versus the addition of new MEG channels when computing noise-normalized minimum l(2)-norm estimates. Three-compartment boundary-element forward models were constructed using structural MRI scans for four subjects. Singular value analysis of the resulting forward models predicted better performance of the EEG+MEG case in the form of higher matrix rank. MNE inverse operators for EEG, MEG and EEG+MEG were constructed using the sensor noise covariance estimated from data. Metrics derived from the resolution matrices predicted higher spatial resolution in EEG+MEG as compared to MEG due to decreased spread (lower spatial dispersion, higher resolution index) with no reduction in dipole localization error. The effect was apparent in all source locations, with increased magnitude for deep areas such as the cingulate cortex. We were also able to corroborate the results for the somatosensory cortex using median nerve responses.

PARAMETER ESTIMATION AND DYNAMIC SOURCE LOCALIZATION FOR THE MAGNETOENCEPHALOGRAPHY (MEG) INVERSE PROBLEM.

Dynamic estimation methods based on linear state-space models have been applied to the inverse problem of magnetoencephalography (MEG), and can improve source localization compared with static methods by incorporating temporal continuity as a constraint. The efficacy of these methods is influenced by how well the state-space model approximates the dynamics of the underlying brain current sources. While some components of the state-space model can be inferred from brain anatomy and knowledge of the MEG instrument noise structure, parameters governing the temporal evolution of underlying current sources are unknown and must be selected on an ad-hoc basis or estimated from data. In this work, we apply the Expectation-Maximization (EM) algorithm to estimate parameters and sources in an MEG state-space model, and demonstrate in simulation studies that the resulting source estimates are superior to those provided by static methods or dynamic methods employing ad hoc parameter selection.

The value of multichannel MEG and EEG in the presurgical evaluation of 70 epilepsy patients.

OBJECTIVE: To evaluate the sensitivity of a simultaneous whole-head 306-channel magnetoencephalography (MEG)/70-electrode EEG recording to detect interictal epileptiform activity (IED) in a prospective, consecutive cohort of patients with medically refractory epilepsy that were considered candidates for epilepsy surgery. METHODS: Seventy patients were prospectively evaluated by simultaneously recorded MEG/EEG. All patients were surgical candidates or were considered for invasive EEG monitoring and had undergone an extensive presurgical evaluation at a tertiary epilepsy center. MEG and EEG raw traces were analysed individually by two independent reviewers. RESULTS: MEG data could not be evaluated due to excessive magnetic artefacts in three patients (4%). In the remaining 67 patients, the overall sensitivity to detect IED was 72% (48/67 patients) for MEG and 61% for EEG (41/67 patients) analysing the raw data. In 13% (9/67 patients), MEG-only IED were recorded, whereas in 3% (2/67 patients) EEG-only IED were recorded. The combined sensitivity was 75% (50/67 patients). CONCLUSION: Three hundred and six-channel MEG has a similarly high sensitivity to record IED as EEG and appears to be complementary. In one-third of the EEG-negative patients, MEG can be expected to record IED, especially in the case of lateral neocortical epilepsy and/or cortical dysplasia.

Top-down facilitation of visual recognition.

Cortical analysis related to visual object recognition is traditionally thought to propagate serially along a bottom-up hierarchy of ventral areas. Recent proposals gradually promote the role of top-down processing in recognition, but how such facilitation is triggered remains a puzzle. We tested a specific model, proposing that low spatial frequencies facilitate visual object recognition by initiating top-down processes projected from orbitofrontal to visual cortex. The present study combined magnetoencephalography, which has superior temporal resolution, functional magnetic resonance imaging, and a behavioral task that yields successful recognition with stimulus repetitions. Object recognition elicited differential activity that developed in the left orbitofrontal cortex 50 ms earlier than it did in recognition-related areas in the temporal cortex. This early orbitofrontal activity was directly modulated by the presence of low spatial frequencies in the image. Taken together, the dynamics we revealed provide strong support for the proposal of how top-down facilitation of object recognition is initiated, and our observations are used to derive predictions for future research.

Partial signal space projection for artefact removal in MEG measurements: a theoretical analysis.

Standard methods for artefact removal in MEG or EEG measurements consist of rejection of either corrupted epochs or signal space projection (SSP). We propose to combine the two methods by applying SSP only in corrupted epochs and thus using both temporal and spatial information. This partial signal space projection necessarily results in smaller variances for the source localization. Formulae for dipole localization errors as a function of fraction of corrupted epochs are derived and verified in Monte Carlo simulations of MEG measurements corrupted with eye artefacts. A theoretical analysis of various measuring devices, classes of artefact and locations of dipole of interest shows that the proposed method leads to significant improvement for frontal signal dipoles and for 30-80% corrupted epochs.

Effects of intensity variation on human auditory evoked magnetic fields.

We recorded auditory evoked magnetic fields from 6 healthy subjects with a 122-channel whole-head neuromagnetometer. The stimuli were 200-ms 1-kHz tones delivered at 4 different intensities (40, 50, 60, and 65 dB HL). The tones were given once every second, binaurally in the first session, and monaurally to each ear in the second one. The four intensities were presented randomly and equiprobably within a single sequence. In both stimulus conditions, the 100-ms response (N100m) decreased in latency and increased in amplitude as a function of intensity in both hemispheres. No systematic dependence was found between stimulus intensity and the N100m source location in the auditory cortex. Our study illustrates a noninvasive method to examine the functional properties of human auditory cortex, allowing simultaneous comparison between signals arising from both hemispheres.

Functional localization based on measurements with a whole-head magnetometer system.

Whole-cortex magnetometers represent a significant methodological breakthrough in noninvasive studies of the brain's electrical activity. This paper describes our 122-channel instrument with planar gradiometers, methods to interpret its data, and gives a few examples of neuromagnetic studies.

Dipole modelling of MEG rhythms in time and frequency domains.

Local generators of spontaneous brain rhythms can be identified from the measured magnetic field pattern both in the time and frequency domains when the sources are dipolar. The dipole assumption is most efficient when only a few sources contribute to the signal at one time or frequency. We have quantified the effects of different filters and spectral transformation sizes in the analysis of spontaneous magnetic activity measured simultaneously over the whole head to determine the optimal values for maximum identification probability of localized (dipolar) activity. The criteria employed were (i) the percentage of dipolar sources, (ii) the goodness-of-fit of the dipole model, (iii) the confidence volumes and (iv) spatial distributions of the source sites, and (v) the effective spectral resolving power of the various Fast Fourier transform (FFT) sizes. The systematic changes of (i-v) suggested the use of 3-5 Hz passbands around the major spectral peaks and FFT lengths of 2-3 s for extraction of the maximum amount of information from this data set. The most successful choices of filter passband and spectral transformation length for source localization simultaneously provide estimates for the inherent spectral fluctuation of cortical rhythms (0.5 Hz) and for the activation lifetime of individual sources (0.3 s).

Visual cortex activation in blind humans during sound discrimination.

We used a whole-scalp magnetometer with 122 planar gradiometers to study the activity of the visual cortex of five blind humans deprived of visual input since early infancy. Magnetic responses were recorded to pitch changes in a sound sequence when the subjects were either counting these changes or ignoring the stimuli. In two of the blind subjects, magnetic resonance images were also obtained, showing normal visual cortex macroanatomy. In these subjects, the magnetic responses to counted pitch changes were located at visual and temporal cortices whereas ignored pitch changes activated the temporal cortices almost exclusively. Also in two of the other three blind, the visual-cortex activation was detectable in the auditory counting task. Our results suggest that the visual cortex of blind humans can participate in auditory discrimination.

Interpreting magnetic fields of the brain: minimum norm estimates.

The authors have applied estimation theory to the problem of determining primary current distributions from measured neuromagnetic fields. In this procedure, essentially nothing is assumed about the source currents, except that they are spatially restricted to a certain region. Simulation experiments show that the results can describe the structure of the current flow fairly well. By increasing the number of measurements, the estimate can be made more localised. The current distributions may be also used as an interpolation and an extrapolation for the measured field patterns.

Minimum-norm estimation in a boundary-element torso model.

The paper deals with the bioelectric and biomagnetic inverse problems. The authors present a method to estimate primary-current distributions in a homogeneous, realistically shaped boundary-element torso model. The reconstruction surface is triangulated to keep the procedure computationally feasible. The minimum-norm estimate is computed on the basis of separate electric and magnetic signals, as well as from combined data. The method can be used both for heart and brain studies. Simulation results for current-dipole sources in a homogeneous realistic torso are discussed.

Use of a computerized brain atlas in magnetoencephalographic activation studies.

A pilot study was carried out to test the feasibility of an adjustable computerized brain atlas, adapted to the individual anatomy for localizing current dipoles by means of magnetoencephalography (MEG). The atlas can be adapted to individual computed tomography (CT) or magnetic resonance (MR) images. Position information is transferred between these imaging methods and MEG using a stereotactic technique. For this purpose, a special non-magnetic helmet was designed to be used together with the ordinary head fixation system. It seems likely that the proposed combination of the brain atlas with MEG, CT and MRI methods will become a powerful tool in exploring different brain functions.

Sampling theory for neuromagnetic detector arrays.

The sampling theorem for wave-number-limited multivariable functions is applied to the problem of neuromagnetic field mapping. The wave-number spectrum and other relevant properties of these fields are estimated. A theory is derived for reconstructing neuromagnetic fields from measurements using sensor arrays which sample either the field component Bz perpendicular to the planar grid of measurement points, or the two components delta Bz/delta x and delta Bz/delta y of its gradient in the xy plane. The maximum sensor spacing consistent with a unique reconstruction is determined for both cases. It is shown that, when two orthogonal components of the gradient are measured at every site of the measurement grid, the density of these sensor-pair units can be reduced, without risk of aliasing, to half of what is necessary for single-channel sensors in an array sampling Bz alone. Thus the planar and axial gradiometer arrays are equivalent in the sampling sense provided that the number of independent measurements per unit area is equal.

Estimates of visually evoked cortical currents.

We have measured magnetic fields evoked by the onset of checkerboard-like sectorial patterns presented at 16 locations near the center of the visual field. Small stimuli (less than 2 degrees), which, nevertheless, gave sufficiently strong responses to enable source localization, were used to limit cortical activation to a small area, thus simplifying the analysis of the magnetic field data. We focused on optimizing the experimental design: cortical sources could be located from measurements at just one position of our 24-channel magnetometer and with as few as 15-20 repetitions of the stimulus. Minimum-norm-estimate maps calculated from even a single response showed reproducible features of the current distribution, which was, 80-100 msec after the pattern onset, retinotopically organized in the occipital lobe. Since magnetoencephalography can reveal cortical locations with a precision of 2-3 mm, our procedure appears promising for further studies of cortical retinotopy and visual field defects.

Magnetoencephalography: a tool for functional brain imaging.

At present, one of the most promising windows to the functional organization of the human brain is magnetoencephalography (MEG). By mapping the magnetic field distribution outside the head the sites of neural events can be located with an accuracy of a few millimeters and the temporal evolution of the activation can be traced with a millisecond resolution. This paper reviews some forward field calculation approaches suitable for the interpretation of the brain's electromagnetic signals. Inverse modelling with multiple dipoles is described in detail. An example of the analysis of the somatosensory evoked-responses illustrates the potential of multiple signal classification (MUSIC) algorithm in finding optimal dipole positions.