Distributed current estimates using cortical orientation constraints

Numbers are not like words: Different pathways for literacy and numeracy

Literacy and numeracy are two fundamental cognitive skills that require mastering culturally-invented symbolic systems for representing spoken language and quantities. How numbers and words are processed in the human brain and their temporal dynamics remain unclear. Using MEG (magnetoencephalography), we find brain activation differences for literacy and numeracy from early stages of processing in the temporal-occipital and temporal-parietal regions. Native speakers of Spanish were exposed to visually presented words, pseudowords, strings of numbers, strings of letters and strings of symbols while engaged in a go/no-go task. Results showed more evoked neuromagnetic activity for words and pseudowords compared to symbols at ~120-130ms in the left occipito-temporal and temporal-parietal cortices (angular gyrus and intra-parietal sulcus) and at ~200ms in the left inferior frontal gyrus and left temporal areas. In contrast, numbers showed more activation than symbols at similar time windows in homologous regions of the right hemisphere: occipito-temporal and superior and middle temporal cortices at ~100-130ms. A direct comparison between the responses to words and numbers confirmed this distinct lateralization for the two stimulus types. These results suggest that literacy and numeracy follow distinct processing streams through the left and right hemispheres, respectively, and that the temporal-parietal and occipito-temporal regions may interact during processing alphanumeric stimuli.

Attention drives synchronization of alpha and beta rhythms between right inferior frontal and primary sensory neocortex

The right inferior frontal cortex (rIFC) is specifically associated with attentional control via the inhibition of behaviorally irrelevant stimuli and motor responses. Similarly, recent evidence has shown that alpha (7-14 Hz) and beta (15-29 Hz) oscillations in primary sensory neocortical areas are enhanced in the representation of non-attended stimuli, leading to the hypothesis that allocation of these rhythms plays an active role in optimal inattention. Here, we tested the hypothesis that selective synchronization between rIFC and primary sensory neocortex occurs in these frequency bands during inattention. We used magnetoencephalography to investigate phase synchrony between primary somatosensory (SI) and rIFC regions during a cued-attention tactile detection task that required suppression of response to uncertain distractor stimuli. Attentional modulation of synchrony between SI and rIFC was found in both the alpha and beta frequency bands. This synchrony manifested as an increase in the alpha-band early after cue between non-attended SI representations and rIFC, and as a subsequent increase in beta-band synchrony closer to stimulus processing. Differences in phase synchrony were not found in several proximal control regions. These results are the first to reveal distinct interactions between primary sensory cortex and rIFC in humans and suggest that synchrony between rIFC and primary sensory representations plays a role in the inhibition of irrelevant sensory stimuli and motor responses.

Voxel-based dipole orientation constraints for distributed current estimation

Distributed electroencephalography source localization is a highly ill-posed problem. With measurements on the order of 10(2), and unknowns in the range of 10(4)-10(5), the range of feasible solutions is quite large. One approach to reducing ill-posedness is to intelligently reduce the number of unknowns. Restricting solutions to gray matter is one approach. A further step is to use the anatomy of each patient to identify and constrain the orientation of the dipole within each voxel. While dipole orientation constraints for cortical patch-based approaches have been proposed, to our knowledge, no solutions for full volumetric localizations have been presented. Patch techniques account for patch surface area, but place dipoles only on the surface, rather than throughout the cortex. Variability in human cortical thickness means that thicker regions of cortex will potentially contribute more to the EEG signal, and should be accounted for in modeling. Additionally, patch models require cortical surface identification techniques, which can separate them from the extensive literature on voxel-based MR image processing, and require additional adaptation to incorporate more complex information. We present a volumetric approach for computing voxel-based distributed estimates of cortical activity with constrained dipole orientations. Using a tissue thickness estimation approach, we obtain estimates of the cortical surface normal at each voxel. These let us constrain the inverse problem, and yield localizations with reduced spatial blurring and better identification of signal magnitude within the cortex. This is demonstrated for a series of simulated and experimental data using patient-specific bioelectric models.

Localizing movement-related primary sensorimotor cortices with multi-band EEG frequency changes and functional MRI

Electroencephalographic (EEG) oscillations in multiple frequency bands can be observed during functional activity of the cerebral cortex. An important question is whether activity of focal areas of cortex, such as during finger movements, is tracked by focal oscillatory EEG changes. Although a number of studies have compared EEG changes to functional MRI hemodynamic responses, we can find no previous research that relates the fMRI hemodynamic activity to localization of the multiple EEG frequency changes observed in motor tasks. In the present study, five participants performed similar thumb and finger movement tasks in parallel EEG and functional MRI studies. We examined changes in five frequency bands (from 5–120 Hz) and localized them using 256 dense-array EEG (dEEG) recordings and high-resolution individual head models. These localizations were compared with fMRI localizations in the same participants. Results showed that beta-band (14–30 Hz) desynchronizations (power decreases) were the most robust effects, appearing in all individuals, consistently localized to the hand region of the primary motor cortex, and consistently aligned with fMRI localizations.

Temporal dynamics of the knowledge-mediated visual disambiguation process in humans: a magnetoencephalography study

Disambiguation of a noisy visual scene with prior knowledge is an indispensable task of the visual system. To adequately adapt to a dynamically changing visual environment full of noisy visual scenes, the implementation of knowledge-mediated disambiguation in the brain is imperative and essential for proceeding as fast as possible under the limited capacity of visual image processing. However, the temporal profile of the disambiguation process has not yet been fully elucidated in the brain. The present study attempted to determine how quickly knowledge-mediated disambiguation began to proceed along visual areas after the onset of a two-tone ambiguous image using magnetoencephalography with high temporal resolution. Using the predictive coding framework, we focused on activity reduction for the two-tone ambiguous image as an index of the implementation of disambiguation. Source analysis revealed that a significant activity reduction was observed in the lateral occipital area at approximately 120 ms after the onset of the ambiguous image, but not in preceding activity (about 115 ms) in the cuneus when participants perceptually disambiguated the ambiguous image with prior knowledge. These results suggested that knowledge-mediated disambiguation may be implemented as early as approximately 120 ms following an ambiguous visual scene, at least in the lateral occipital area, and provided an insight into the temporal profile of the disambiguation process of a noisy visual scene with prior knowledge.

Investigations of sensitivity and resolution of ECG and MCG in a realistically shaped thorax model

Solving the inverse problem of electrocardiography (ECG) and magnetocardiography (MCG) is often referred to as cardiac source imaging. Spatial properties of ECG and MCG as imaging systems are, however, not well known. In this modelling study, we investigate the sensitivity and point-spread function (PSF) of ECG, MCG, and combined ECG+MCG as a function of source position and orientation, globally around the ventricles: signal topographies are modelled using a realistically-shaped volume conductor model, and the inverse problem is solved using a distributed source model and linear source estimation with minimal use of prior information. The results show that the sensitivity depends not only on the modality but also on the location and orientation of the source and that the sensitivity distribution is clearly reflected in the PSF. MCG can better characterize tangential anterior sources (with respect to the heart surface), while ECG excels with normally-oriented and posterior sources. Compared to either modality used alone, the sensitivity of combined ECG+MCG is less dependent on source orientation per source location, leading to better source estimates. Thus, for maximal sensitivity and optimal source estimation, the electric and magnetic measurements should be combined.

Visualizing simulated electrical fields from electroencephalography and transcranial electric brain stimulation: a comparative evaluation

Electrical activity of neuronal populations is a crucial aspect of brain activity. This activity is not measured directly but recorded as electrical potential changes using head surface electrodes (electroencephalogram - EEG). Head surface electrodes can also be deployed to inject electrical currents in order to modulate brain activity (transcranial electric stimulation techniques) for therapeutic and neuroscientific purposes. In electroencephalography and noninvasive electric brain stimulation, electrical fields mediate between electrical signal sources and regions of interest (ROI). These fields can be very complicated in structure, and are influenced in a complex way by the conductivity profile of the human head. Visualization techniques play a central role to grasp the nature of those fields because such techniques allow for an effective conveyance of complex data and enable quick qualitative and quantitative assessments. The examination of volume conduction effects of particular head model parameterizations (e.g., skull thickness and layering), of brain anomalies (e.g., holes in the skull, tumors), location and extent of active brain areas (e.g., high concentrations of current densities) and around current injecting electrodes can be investigated using visualization. Here, we evaluate a number of widely used visualization techniques, based on either the potential distribution or on the current-flow. In particular, we focus on the extractability of quantitative and qualitative information from the obtained images, their effective integration of anatomical context information, and their interaction. We present illustrative examples from clinically and neuroscientifically relevant cases and discuss the pros and cons of the various visualization techniques.

Cortical organization of language pathways in children with non-localized cryptogenic epilepsy

Children with a history of epilepsy are almost six times more likely than their unaffected siblings to be referred for speech or language therapy. However, the abnormalities in neural pathway that cause these delays are poorly understood. We recorded evoked fields using whole-head magnetoencephalography during real and non-word visual and auditory rhyme tasks in 15 children with non-localized cryptogenic epilepsy. Basic phonological and orthographic language skills were assessed using Woodcock–Johnson Test of Achievement subtests. Dynamic statistical parameter mapping was used with individual participant magnetic resonance images. Significant cortical activity was visualized on average and performance weighted maps. For the auditory rhyme tasks, bilateral primary and secondary auditory cortices, the superior temporal sulcus, and insular cortex were activated early with later increases in left hemisphere activity. Visual rhyme tasks evoked early bilateral primary and secondary occipital cortical and angular gyri activity followed by later activation of the planum temporale and supramarginal gyri and the left ventral occipitotemporal area. For the auditory rhyme tasks, performance weighted maps demonstrated that early right hemisphere activation was associated with poorer reading skills while later activity was associated with better reading skills; for the left hemisphere, greater early activation of the secondary auditory cortex, including the planum temporale, was related to better reading skills while relatively later activation of these areas was associated with poorer reading skills. For the visual rhyme tasks, greater activity in the bilateral ventral occipitotemporal and insular areas and angular and supramarginal gyri were associated with better performance. These data suggest that spatiotemporal cortical activation patterns are associated with variations in language performance in non-localized cryptogenic epilepsy.

Spatiotemporal Signatures of Lexical-Semantic Prediction

Although there is broad agreement that top-down expectations can facilitate lexical-semantic processing, the mechanisms driving these effects are still unclear. In particular, while previous electroencephalography (EEG) research has demonstrated a reduction in the N400 response to words in a supportive context, it is often challenging to dissociate facilitation due to bottom-up spreading activation from facilitation due to top-down expectations. The goal of the current study was to specifically determine the cortical areas associated with facilitation due to top-down prediction, using magnetoencephalography (MEG) recordings supplemented by EEG and functional magnetic resonance imaging (fMRI) in a semantic priming paradigm. In order to modulate expectation processes while holding context constant, we manipulated the proportion of related pairs across 2 blocks (10 and 50% related). Event-related potential results demonstrated a larger N400 reduction when a related word was predicted, and MEG source localization of activity in this time-window (350-450 ms) localized the differential responses to left anterior temporal cortex. fMRI data from the same participants support the MEG localization, showing contextual facilitation in left anterior superior temporal gyrus for the high expectation block only. Together, these results provide strong evidence that facilitatory effects of lexical-semantic prediction on the electrophysiological response 350-450 ms postonset reflect modulation of activity in left anterior temporal cortex.

Cortical somatosensory reorganization in children with spastic cerebral palsy: a multimodal neuroimaging study

Although cerebral palsy (CP) is among the most common causes of physical disability in early childhood, we know little about the functional and structural changes of this disorder in the developing brain. Here, we investigated with three different neuroimaging modalities [magnetoencephalography (MEG), diffusion tensor imaging (DTI), and resting-state fMRI] whether spastic CP is associated with functional and anatomical abnormalities in the sensorimotor network. Ten children participated in the study: four with diplegic CP (DCP), three with hemiplegic CP (HCP), and three typically developing (TD) children. Somatosensory (SS)-evoked fields (SEFs) were recorded in response to pneumatic stimuli applied to digits D1, D3, and D5 of both hands. Several parameters of water diffusion were calculated from DTI between the thalamus and the pre-central and post-central gyri in both hemispheres. The sensorimotor resting-state networks (RSNs) were examined by using an independent component analysis method. Tactile stimulation of the fingers elicited the first prominent cortical response at ~50 ms, in all except one child, localized over the primary SS cortex (S1). In five CP children, abnormal somatotopic organization was observed in the affected (or more affected) hemisphere. Euclidean distances were markedly different between the two hemispheres in the HCP children, and between DCP and TD children for both hemispheres. DTI analysis revealed decreased fractional anisotropy and increased apparent diffusion coefficient for the thalamocortical pathways in the more affected compared to less affected hemisphere in CP children. Resting-state functional MRI results indicated absent and/or abnormal sensorimotor RSNs for children with HCP and DCP consistent with the severity and location of their lesions. Our findings suggest an abnormal SS processing mechanism in the sensorimotor network of children with CP possibly as a result of diminished thalamocortical projections.

Producing Speech with a Newly Learned Morphosyntax and Vocabulary: An Magnetoencephalography Study

Ten participants learned a miniature language (Anigram), which they later employed to verbally describe a pictured event. Using magnetoencephalography, the cortical dynamics of sentence production in Anigram was compared with that in the native tongue from the preparation phase up to the production of the final word. At the preparation phase, a cartoon image with two animals prompted the participants to plan either the corresponding simple sentence (e.g., “the bear hits the lion”) or a grammar-free list of the two nouns (“the bear, the lion”). For the newly learned language, this stage induced stronger left angular and adjacent inferior parietal activations than for the native language, likely reflecting a higher load on lexical retrieval and STM storage. The preparation phase was followed by a cloze task where the participants were prompted to produce the last word of the sentence or word sequence. Production of the sentence-final word required retrieval of rule-based inflectional morphology and was accompanied by increased activation of the left middle superior temporal cortex that did not differ between the two languages. Activation of the right temporal cortex during the cloze task suggested that this area plays a role in integrating word meanings into the sentence frame. The present results indicate that, after just a few days of exposure, the newly learned language harnesses the neural resources for multiword production much the same way as the native tongue and that the left and right temporal cortices seem to have functionally different roles in this processing.

How to use fMRI functional localizers to improve EEG/MEG source estimation

EEG and MEG have excellent temporal resolution, but the estimation of the neural sources that generate the signals recorded by the sensors is a difficult, ill-posed problem. The high spatial resolution of functional MRI makes it an ideal tool to improve the localization of the EEG/MEG sources using data fusion. However, the combination of the two techniques remains challenging, as the neural generators of the EEG/MEG and BOLD signals might in some cases be very different. Here we describe a data fusion approach that was developed by our team over the last decade in which fMRI is used to provide source constraints that are based on functional areas defined individually for each subject. This mini-review describes the different steps that are necessary to perform source estimation using this approach. It also provides a list of pitfalls that should be avoided when doing fMRI-informed EEG/MEG source imaging. Finally, it describes the advantages of using a ROI-based approach for group-level analysis and for the study of sensory systems.

Dissociable genetic contributions to error processing: a multimodal neuroimaging study

BACKGROUND

Neuroimaging studies reliably identify two markers of error commission: the error-related negativity (ERN), an event-related potential, and functional MRI activation of the dorsal anterior cingulate cortex (dACC). While theorized to reflect the same neural process, recent evidence suggests that the ERN arises from the posterior cingulate cortex not the dACC. Here, we tested the hypothesis that these two error markers also have different genetic mediation.

METHODS

We measured both error markers in a sample of 92 comprised of healthy individuals and those with diagnoses of schizophrenia, obsessive-compulsive disorder or autism spectrum disorder. Participants performed the same task during functional MRI and simultaneously acquired magnetoencephalography and electroencephalography. We examined the mediation of the error markers by two single nucleotide polymorphisms: dopamine D4 receptor (DRD4) C-521T (rs1800955), which has been associated with the ERN and methylenetetrahydrofolate reductase (MTHFR) C677T (rs1801133), which has been associated with error-related dACC activation. We then compared the effects of each polymorphism on the two error markers modeled as a bivariate response.

RESULTS

We replicated our previous report of a posterior cingulate source of the ERN in healthy participants in the schizophrenia and obsessive-compulsive disorder groups. The effect of genotype on error markers did not differ significantly by diagnostic group. DRD4 C-521T allele load had a significant linear effect on ERN amplitude, but not on dACC activation, and this difference was significant. MTHFR C677T allele load had a significant linear effect on dACC activation but not ERN amplitude, but the difference in effects on the two error markers was not significant.

CONCLUSIONS

DRD4 C-521T, but not MTHFR C677T, had a significant differential effect on two canonical error markers. Together with the anatomical dissociation between the ERN and error-related dACC activation, these findings suggest that these error markers have different neural and genetic mediation.

Enhanced neural synchrony between left auditory and premotor cortex is associated with successful phonetic categorization

The cortical dorsal auditory stream has been proposed to mediate mapping between auditory and articulatory-motor representations in speech processing. Whether this sensorimotor integration contributes to speech perception remains an open question. Here, magnetoencephalography was used to examine connectivity between auditory and motor areas while subjects were performing a sensorimotor task involving speech sound identification and overt repetition. Functional connectivity was estimated with inter-areal phase synchrony of electromagnetic oscillations. Structural equation modeling was applied to determine the direction of information flow. Compared to passive listening, engagement in the sensorimotor task enhanced connectivity within 200 ms after sound onset bilaterally between the temporoparietal junction (TPJ) and ventral premotor cortex (vPMC), with the left-hemisphere connection showing directionality from vPMC to TPJ. Passive listening to noisy speech elicited stronger connectivity than clear speech between left auditory cortex (AC) and vPMC at ~100 ms, and between left TPJ and dorsal premotor cortex (dPMC) at ~200 ms. Information flow was estimated from AC to vPMC and from dPMC to TPJ. Connectivity strength among the left AC, vPMC, and TPJ correlated positively with the identification of speech sounds within 150 ms after sound onset, with information flowing from AC to TPJ, from AC to vPMC, and from vPMC to TPJ. Taken together, these findings suggest that sensorimotor integration mediates the categorization of incoming speech sounds through reciprocal auditory-to-motor and motor-to-auditory projections.

EEG/MEG source reconstruction with spatial-temporal two-way regularized regression

In this work, we propose a spatial-temporal two-way regularized regression method for reconstructing neural source signals from EEG/MEG time course measurements. The proposed method estimates the dipole locations and amplitudes simultaneously through minimizing a single penalized least squares criterion. The novelty of our methodology is the simultaneous consideration of three desirable properties of the reconstructed source signals, that is, spatial focality, spatial smoothness, and temporal smoothness. The desirable properties are achieved by using three separate penalty functions in the penalized regression framework. Specifically, we impose a roughness penalty in the temporal domain for temporal smoothness, and a sparsity-inducing penalty and a graph Laplacian penalty in the spatial domain for spatial focality and smoothness. We develop a computational efficient multilevel block coordinate descent algorithm to implement the method. Using a simulation study with several settings of different spatial complexity and two real MEG examples, we show that the proposed method outperforms existing methods that use only a subset of the three penalty functions.

Potential Use of MEG to Understand Abnormalities in Auditory Function in Clinical Populations

Magnetoencephalography (MEG) provides a direct, non-invasive view of neural activity with millisecond temporal precision. Recent developments in MEG analysis allow for improved source localization and mapping of connectivity between brain regions, expanding the possibilities for using MEG as a diagnostic tool. In this paper, we first describe inverse imaging methods (e.g., minimum-norm estimation) and functional connectivity measures, and how they can provide insights into cortical processing. We then offer a perspective on how these techniques could be used to understand and evaluate auditory pathologies that often manifest during development. Here we focus specifically on how MEG inverse imaging, by providing anatomically based interpretation of neural activity, may allow us to test which aspects of cortical processing play a role in (central) auditory processing disorder [(C)APD]. Appropriately combining auditory paradigms with MEG analysis could eventually prove useful for a hypothesis-driven understanding and diagnosis of (C)APD or other disorders, as well as the evaluation of the effectiveness of intervention strategies.

Comparison of minimum-norm estimation and beamforming in electrocardiography with acute ischemia

In the electrocardiographic (ECG) inverse problem, the electrical activity of the heart is estimated from measured electrocardiogram. A model of thorax conductivities and a model of the cardiac generator is required for the ECG inverse problem. Limitations and errors in methods, models, and data will lead to errors in the estimates. However, in experimental applications, the use of limited or erroneous models is often inevitable due to necessary model simplifications and the difficulty of obtaining accurate 3D anatomical imaging data. In this work, we focus on two methods for solving the inverse problem of ECG in the case of acute ischemia: minimum-norm (MN) estimation and linearly constrained minimum-variance beamforming. We study how these methods perform with different sizes of ischemia and with erroneous conductivity models. The results indicate that the beamformer can localize small ischemia given an accurate model, but it cannot be used for estimating the size of ischemia. The MN estimator is tolerant to geometry errors and excels in estimating the size of ischemia, although the beamformer performs better with accurate model and small ischemia.

MNE software for processing MEG and EEG data

Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals originating from neural currents in the brain. Using these signals to characterize and locate brain activity is a challenging task, as evidenced by several decades of methodological contributions. MNE, whose name stems from its capability to compute cortically-constrained minimum-norm current estimates from M/EEG data, is a software package that provides comprehensive analysis tools and workflows including preprocessing, source estimation, time-frequency analysis, statistical analysis, and several methods to estimate functional connectivity between distributed brain regions. The present paper gives detailed information about the MNE package and describes typical use cases while also warning about potential caveats in analysis. The MNE package is a collaborative effort of multiple institutes striving to implement and share best methods and to facilitate distribution of analysis pipelines to advance reproducibility of research. Full documentation is available at http://martinos.org/mne.

Automatic semantic facilitation in anterior temporal cortex revealed through multimodal neuroimaging

A core property of human semantic processing is the rapid, facilitatory influence of prior input on extracting the meaning of what comes next, even under conditions of minimal awareness. Previous work has shown a number of neurophysiological indices of this facilitation, but the mapping between time course and localization-critical for separating automatic semantic facilitation from other mechanisms-has thus far been unclear. In the current study, we used a multimodal imaging approach to isolate early, bottom-up effects of context on semantic memory, acquiring a combination of electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) measurements in the same individuals with a masked semantic priming paradigm. Across techniques, the results provide a strikingly convergent picture of early automatic semantic facilitation. Event-related potentials demonstrated early sensitivity to semantic association between 300 and 500 ms; MEG localized the differential neural response within this time window to the left anterior temporal cortex, and fMRI localized the effect more precisely to the left anterior superior temporal gyrus, a region previously implicated in semantic associative processing. However, fMRI diverged from early EEG/MEG measures in revealing semantic enhancement effects within frontal and parietal regions, perhaps reflecting downstream attempts to consciously access the semantic features of the masked prime. Together, these results provide strong evidence that automatic associative semantic facilitation is realized as reduced activity within the left anterior superior temporal cortex between 300 and 500 ms after a word is presented, and emphasize the importance of multimodal neuroimaging approaches in distinguishing the contributions of multiple regions to semantic processing.

Lateralized parietotemporal oscillatory phase synchronization during auditory selective attention

Based on the infamous left-lateralized neglect syndrome, one might hypothesize that the dominating right parietal cortex has a bilateral representation of space, whereas the left parietal cortex represents only the contralateral right hemispace. Whether this principle applies to human auditory attention is not yet fully clear. Here, we explicitly tested the differences in cross-hemispheric functional coupling between the intraparietal sulcus (IPS) and auditory cortex (AC) using combined magnetoencephalography (MEG), EEG, and functional MRI (fMRI). Inter-regional pairwise phase consistency (PPC) was analyzed from data obtained during dichotic auditory selective attention task, where subjects were in 10-s trials cued to attend to sounds presented to one ear and to ignore sounds presented in the opposite ear. Using MEG/EEG/fMRI source modeling, parietotemporal PPC patterns were (a) mapped between all AC locations vs. IPS seeds and (b) analyzed between four anatomically defined AC regions-of-interest (ROI) vs. IPS seeds. Consistent with our hypothesis, stronger cross-hemispheric PPC was observed between the right IPS and left AC for attended right-ear sounds, as compared to PPC between the left IPS and right AC for attended left-ear sounds. In the mapping analyses, these differences emerged at 7-13Hz, i.e., at the theta to alpha frequency bands, and peaked in Heschl's gyrus and lateral posterior non-primary ACs. The ROI analysis revealed similarly lateralized differences also in the beta and lower theta bands. Taken together, our results support the view that the right parietal cortex dominates auditory spatial attention.

Targeting of white matter tracts with transcranial magnetic stimulation

BACKGROUND

TMS activations of white matter depend not only on the distance from the coil, but also on the orientation of the axons relative to the TMS-induced electric field, and especially on axonal bends that create strong local field gradient maxima. Therefore, tractography contains potentially useful information for TMS targeting.

OBJECTIVE/METHODS

Here, we utilized 1-mm resolution diffusion and structural T1-weighted MRI to construct large-scale tractography models, and localized TMS white matter activations in motor cortex using electromagnetic forward modeling in a boundary element model (BEM).

RESULTS

As expected, in sulcal walls, pyramidal cell axonal bends created preferred sites of activation that were not found in gyral crowns. The model agreed with the well-known coil orientation sensitivity of motor cortex, and also suggested unexpected activation distributions emerging from the E-field and tract configurations. We further propose a novel method for computing the optimal coil location and orientation to maximally stimulate a pre-determined axonal bundle.

CONCLUSIONS

Diffusion MRI tractography with electromagnetic modeling may improve spatial specificity and efficacy of TMS.

Different cortical dynamics in face and body perception: an MEG study

Evidence from functional neuroimaging indicates that visual perception of human faces and bodies is carried out by distributed networks of face and body-sensitive areas in the occipito-temporal cortex. However, the dynamics of activity in these areas, needed to understand their respective functional roles, are still largely unknown. We monitored brain activity with millisecond time resolution by recording magnetoencephalographic (MEG) responses while participants viewed photographs of faces, bodies, and control stimuli. The cortical activity underlying the evoked responses was estimated with anatomically-constrained noise-normalised minimum-norm estimate and statistically analysed with spatiotemporal cluster analysis.

Our findings point to distinct spatiotemporal organization of the neural systems for face and body perception. Face-selective cortical currents were found at early latencies (120–200 ms) in a widespread occipito-temporal network including the ventral temporal cortex (VTC). In contrast, early body-related responses were confined to the lateral occipito-temporal cortex (LOTC). These were followed by strong sustained body-selective responses in the orbitofrontal cortex from 200–700 ms, and in the lateral temporal cortex and VTC after 500 ms latency. Our data suggest that the VTC region has a key role in the early processing of faces, but not of bodies. Instead, the LOTC, which includes the extra-striate body area (EBA), appears the dominant area for early body perception, whereas the VTC contributes to late and post-perceptual processing.

Dynamic oscillatory processes governing cued orienting and allocation of auditory attention

In everyday listening situations, we need to constantly switch between alternative sound sources and engage attention according to cues that match our goals and expectations. The exact neuronal bases of these processes are poorly understood. We investigated oscillatory brain networks controlling auditory attention using cortically constrained fMRI-weighted magnetoencephalography/EEG source estimates. During consecutive trials, participants were instructed to shift attention based on a cue, presented in the ear where a target was likely to follow. To promote audiospatial attention effects, the targets were embedded in streams of dichotically presented standard tones. Occasionally, an unexpected novel sound occurred opposite to the cued ear to trigger involuntary orienting. According to our cortical power correlation analyses, increased frontoparietal/temporal 30-100 Hz gamma activity at 200-1400 msec after cued orienting predicted fast and accurate discrimination of subsequent targets. This sustained correlation effect, possibly reflecting voluntary engagement of attention after the initial cue-driven orienting, spread from the TPJ, anterior insula, and inferior frontal cortices to the right FEFs. Engagement of attention to one ear resulted in a significantly stronger increase of 7.5-15 Hz alpha in the ipsilateral than contralateral parieto-occipital cortices 200-600 msec after the cue onset, possibly reflecting cross-modal modulation of the dorsal visual pathway during audiospatial attention. Comparisons of cortical power patterns also revealed significant increases of sustained right medial frontal cortex theta power, right dorsolateral pFC and anterior insula/inferior frontal cortex beta power, and medial parietal cortex and posterior cingulate cortex gamma activity after cued versus novelty-triggered orienting (600-1400 msec). Our results reveal sustained oscillatory patterns associated with voluntary engagement of auditory spatial attention, with the frontoparietal and temporal gamma increases being best predictors of subsequent behavioral performance.

Altered oscillation and synchronization of default-mode network activity in mild Alzheimer's disease compared to mild cognitive impairment: an electrophysiological study

Some researchers have suggested that the default mode network (DMN) plays an important role in the pathological mechanisms of Alzheimer’s disease (AD). To examine whether the cortical activities in DMN regions show significant difference between mild AD from mild cognitive impairment (MCI), electrophysiological responses were analyzed from 21 mild Alzheimer’s disease (AD) and 21 mild cognitive impairment (MCI) patients during an eyes closed, resting-state condition. The spectral power and functional connectivity of the DMN were estimated using a minimum norm estimate (MNE) combined with fast Fourier transform and imaginary coherence analysis. Our results indicated that source-based EEG maps of resting-state activity showed alterations of cortical spectral power in mild AD when compared to MCI. These alterations are characteristic of attenuated alpha or beta activities in the DMN, as are enhanced delta or theta activities in the medial temporal, inferior parietal, posterior cingulate cortex and precuneus. With regard to altered synchronization in AD, altered functional interconnections were observed as specific connectivity patterns of connection hubs in the precuneus, posterior cingulate cortex, anterior cingulate cortex and medial temporal regions. Moreover, posterior theta and alpha power and altered connectivity in the medial temporal lobe correlated significantly with scores obtained on the Mini-Mental State Examination (MMSE). In conclusion, EEG is a useful tool for investigating the DMN in the brain and differentiating early stage AD and MCI patients. This is a promising finding; however, further large-scale studies are needed.

Anomalous use of context during task preparation in schizophrenia: a magnetoencephalography study

BACKGROUND

Impaired ability to use contextual information to optimally prepare for tasks contributes to performance deficits in schizophrenia. We used magnetoencephalography and an antisaccade task to investigate the neural basis of this deficit.

METHODS

In schizophrenia patients and healthy control participants, we examined the difference in preparatory activation to cues indicating an impending antisaccade or prosaccade. We analyzed activation for correct trials only and focused on the network for volitional ocular motor control-frontal eye field (FEF), dorsal anterior cingulate cortex (dACC), and the ventrolateral and dorsolateral prefrontal cortex (VLPFC, DLPFC).

RESULTS

Compared with control subjects, patients made more antisaccade errors and showed reduced differential preparatory activation in the dACC and increased differential preparatory activation in the VLPFC. In patients only, antisaccade error rates correlated with preparatory activation in the FEF, DLPFC, and VLPFC.

CONCLUSIONS

In schizophrenia, reduced differential preparatory activation of the dACC may reflect reduced signaling of the need for control. Greater preparatory activation in the VLPFC and the correlations of error rate with FEF, DLPFC, and VLPFC activation may reflect that patients who are more error prone require stronger activation in these regions for correct performance. These findings provide the first evidence of abnormal task preparation, distinct from response generation, during volitional saccades in schizophrenia. We conclude that schizophrenia patients are impaired in using task cues to modulate cognitive control and that this contributes to deficits inhibiting prepotent but contextually inappropriate responses and to behavior that is stimulus bound and error prone rather than flexibly guided by context.

Minimum-norm cortical source estimation in layered head models is robust against skull conductivity error

The conductivity profile of the head has a major effect on EEG signals, but unfortunately the conductivity for the most important compartment, skull, is only poorly known. In dipole modeling studies, errors in modeled skull conductivity have been considered to have a detrimental effect on EEG source estimation. However, as dipole models are very restrictive, those results cannot be generalized to other source estimation methods. In this work, we studied the sensitivity of EEG and combined MEG + EEG source estimation to errors in skull conductivity using a distributed source model and minimum-norm (MN) estimation.

We used a MEG/EEG modeling set-up that reflected state-of-the-art practices of experimental research. Cortical surfaces were segmented and realistically-shaped three-layer anatomical head models were constructed, and forward models were built with Galerkin boundary element method while varying the skull conductivity. Lead-field topographies and MN spatial filter vectors were compared across conductivities, and the localization and spatial spread of the MN estimators were assessed using intuitive resolution metrics.

The results showed that the MN estimator is robust against errors in skull conductivity: the conductivity had a moderate effect on amplitudes of lead fields and spatial filter vectors, but the effect on corresponding morphologies was small. The localization performance of the EEG or combined MEG + EEG MN estimator was only minimally affected by the conductivity error, while the spread of the estimate varied slightly. Thus, the uncertainty with respect to skull conductivity should not prevent researchers from applying minimum norm estimation to EEG or combined MEG + EEG data. Comparing our results to those obtained earlier with dipole models shows that general judgment on the performance of an imaging modality should not be based on analysis with one source estimation method only.

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We tested EEG and MEG + EEG minimum-norm estimation with errors in skull models.

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Error in skull conductivity has only a small effect on morphology.

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Error in skull conductivity has moderate effect on amplitudes.

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Quality of minimum-norm estimates is minimally affected by skull conductivity error.

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Sensitivity to conductivity error depends on chosen source estimation method.

The effect of imagination on stimulation: the functional specificity of efference copies in speech processing

The computational role of efference copies is widely appreciated in action and perception research, but their properties for speech processing remain murky. We tested the functional specificity of auditory efference copies using magnetoencephalography recordings in an unconventional pairing: We used a classical cognitive manipulation (mental imagery--to elicit internal simulation and estimation) with a well-established experimental paradigm (one shot repetition--to assess neuronal specificity). Participants performed tasks that differentially implicated internal prediction of sensory consequences (overt speaking, imagined speaking, and imagined hearing) and their modulatory effects on the perception of an auditory (syllable) probe were assessed. Remarkably, the neural responses to overt syllable probes vary systematically, both in terms of directionality (suppression, enhancement) and temporal dynamics (early, late), as a function of the preceding covert mental imagery adaptor. We show, in the context of a dual-pathway model, that internal simulation shapes perception in a context-dependent manner.

A fast statistical significance test for baseline correction and comparative analysis in phase locking

Human perception, cognition, and action are supported by a complex network of interconnected brain regions. There is an increasing interest in measuring and characterizing these networks as a function of time and frequency, and inter-areal phase locking is often used to reveal these networks. This measure assesses the consistency of phase angles between the electrophysiological activity in two areas at a specific time and frequency. Non-invasively, the signals from which phase locking is computed can be measured with magnetoencephalography (MEG) and electroencephalography (EEG). However, due to the lack of spatial specificity of reconstructed source signals in MEG and EEG, inter-areal phase locking may be confounded by false positives resulting from crosstalk. Traditional phase locking estimates assume that no phase locking exists when the distribution of phase angles is uniform. However, this conjecture is not true when crosstalk is present. We propose a novel method to improve the reliability of the phase-locking measure by sampling phase angles from a baseline, such as from a prestimulus period or from resting-state data, and by contrasting this distribution against one observed during the time period of interest.

MEG source localization of spatially extended generators of epileptic activity: comparing entropic and hierarchical bayesian approaches

Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG) or Magneto-EncephaloGraphy (MEG) signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data. Source localization methods based on two types of realistic models have been investigated: (i) brain activity may be modeled using cortical parcels and (ii) brain activity is assumed to be locally smooth within each parcel. A Data Driven Parcellization (DDP) method was used to segment the cortical surface into non-overlapping parcels and diffusion-based spatial priors were used to model local spatial smoothness within parcels. These models were implemented within the Maximum Entropy on the Mean (MEM) and the Hierarchical Bayesian (HB) source localization frameworks. We proposed new methods in this context and compared them with other standard ones using Monte Carlo simulations of realistic MEG data involving sources of several spatial extents and depths. Detection accuracy of each method was quantified using Receiver Operating Characteristic (ROC) analysis and localization error metrics. Our results showed that methods implemented within the MEM framework were sensitive to all spatial extents of the sources ranging from 3 cm² to 30 cm², whatever were the number and size of the parcels defining the model. To reach a similar level of accuracy within the HB framework, a model using parcels larger than the size of the sources should be considered.

Neural correlates of somatosensory paired-pulse suppression: a MEG study using distributed source modeling and dynamic spectral power analysis

Paired-pulse stimulation has been used previously to evaluate cortical excitability and sensory gating. To help elucidate the neural network involved in paired-pulse suppression of somatosensory cortical processing, magnetoencephalographic (MEG) responses to paired-pulse electrical stimulation of the left median nerve of the wrists of 13 healthy males were recorded using an intra-pair interstimulus interval (ISI) of 500ms and an inter-pair ISI of 8s. Minimum norm estimates showed the presence of cortical activation in the bilateral primary somatosensory cortex, the post-central sulcus and the supplementary motor areas. Compared with the responses to the first stimulation, the responses to the second stimulation were attenuated in these areas with gating ratios (the amplitude ratios of the second response to the first response) of 0.54-0.69. By spectral power dynamic analysis, beta frequency oscillations were found to be associated with an early-latency (30-36ms) gating process in the contralateral primary somatosensory cortex and post-central sulcus, whereas theta and alpha oscillations were correlated with paired-pulse suppression of activations at 98-136ms in the ipsilateral primary somatosensory cortex, the bilateral post-central sulcus and the supplementary motor areas. In summary, it can be concluded that differential oscillatory activities are involved in the pair-pulse suppression in various somatosensory regions in response to repetitive external stimulations.

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.

Generator localization by current source density (CSD): implications of volume conduction and field closure at intracranial and scalp resolutions

The topographic ambiguity and reference-dependency that has plagued EEG/ERP research throughout its history are largely attributable to volume conduction, which may be concisely described by a vector form of Ohm's Law. This biophysical relationship is common to popular algorithms that infer neuronal generators via inverse solutions. It may be further simplified as Poisson's source equation, which identifies underlying current generators from estimates of the second spatial derivative of the field potential (Laplacian transformation). Intracranial current source density (CSD) studies have dissected the "cortical dipole" into intracortical sources and sinks, corresponding to physiologically-meaningful patterns of neuronal activity at a sublaminar resolution, much of which is locally cancelled (i.e., closed field). By virtue of the macroscopic scale of the scalp-recorded EEG, a surface Laplacian reflects the radial projections of these underlying currents, representing a unique, unambiguous measure of neuronal activity at scalp. Although the surface Laplacian requires minimal assumptions compared to complex, model-sensitive inverses, the resulting waveform topographies faithfully summarize and simplify essential constraints that must be placed on putative generators of a scalp potential topography, even if they arise from deep or partially-closed fields. CSD methods thereby provide a global empirical and biophysical context for generator localization, spanning scales from intracortical to scalp recordings.

Auditory magnetic response to clicks in children and adults: its components, hemispheric lateralization and repetition suppression effect

The auditory magnetic event-related fields (ERF) qualitatively change through the child development, reflecting maturation of auditory cortical areas. Clicks presented with long inter-stimulus interval produce distinct ERF components, and may appear useful to characterize immature EFR morphology in children. The present study is aimed to investigate morphology of the auditory ERFs in school-age children, as well as lateralization and repetition suppression of ERF components evoked by the clicks. School-age children and adults passively listened to pairs of click presented to the right ear, left ear or binaurally, with 8-11 s intervals between the pairs and a 1 s interval within a pair. Adults demonstrated a typical P50m/N100m response. Unlike adults, children had two distinct components preceding the N100m-P50m (at ~65 ms) and P100m (at ~100 ms). The P100m dominated the child ERF, and was most prominent in response to binaural stimulation. The N100m in children was less developed than in adults and partly overlapped in time with the P100m, especially in response to monaural clicks. Strong repetition suppression was observed for P50m both in children and adults, P100m in children and N100m in adults. Both children and adults demonstrated ERF amplitude and/or latency right hemispheric advantage effects that may reflect right hemisphere dominance for preattentive arousal processes. Our results contribute to the knowledge concerning development of auditory processing and its lateralization in children and have implications for investigation of the auditory evoked fields in developmental disorders.

Mapping cortical dynamics using simultaneous MEG/EEG and anatomically-constrained minimum-norm estimates: an auditory attention example

Magneto- and electroencephalography (MEG/EEG) are neuroimaging techniques that provide a high temporal resolution particularly suitable to investigate the cortical networks involved in dynamical perceptual and cognitive tasks, such as attending to different sounds in a cocktail party. Many past studies have employed data recorded at the sensor level only, i.e., the magnetic fields or the electric potentials recorded outside and on the scalp, and have usually focused on activity that is time-locked to the stimulus presentation. This type of event-related field / potential analysis is particularly useful when there are only a small number of distinct dipolar patterns that can be isolated and identified in space and time. Alternatively, by utilizing anatomical information, these distinct field patterns can be localized as current sources on the cortex. However, for a more sustained response that may not be time-locked to a specific stimulus (e.g., in preparation for listening to one of the two simultaneously presented spoken digits based on the cued auditory feature) or may be distributed across multiple spatial locations unknown a priori, the recruitment of a distributed cortical network may not be adequately captured by using a limited number of focal sources. Here, we describe a procedure that employs individual anatomical MRI data to establish a relationship between the sensor information and the dipole activation on the cortex through the use of minimum-norm estimates (MNE). This inverse imaging approach provides us a tool for distributed source analysis. For illustrative purposes, we will describe all procedures using FreeSurfer and MNE software, both freely available. We will summarize the MRI sequences and analysis steps required to produce a forward model that enables us to relate the expected field pattern caused by the dipoles distributed on the cortex onto the M/EEG sensors. Next, we will step through the necessary processes that facilitate us in denoising the sensor data from environmental and physiological contaminants. We will then outline the procedure for combining and mapping MEG/EEG sensor data onto the cortical space, thereby producing a family of time-series of cortical dipole activation on the brain surface (or "brain movies") related to each experimental condition. Finally, we will highlight a few statistical techniques that enable us to make scientific inference across a subject population (i.e., perform group-level analysis) based on a common cortical coordinate space.

Spatio-temporal mapping cortical neuroplasticity in carpal tunnel syndrome

Neuroimaging data demonstrate that carpal tunnel syndrome, a peripheral neuropathy, is accompanied by maladaptive central neuroplasticity. To further investigate this phenomenon, we collected magnetoencephalography data from 12 patients with carpal tunnel syndrome and 12 healthy control subjects undergoing somatosensory stimulation of the median nerve-innervated Digits 2 and 3, as well as Digit 5, which is innervated by the ulnar nerve. Nerve conduction velocity and psychophysical data were acquired to determine whether standard clinical measures correlated with brain response. In subjects with carpal tunnel syndrome, but not healthy controls, sensory nerve conduction velocity for Digits 2 and 3 was slower than Digit 5. However, somatosensory M20 latencies for Digits 2 and 3 were significantly longer than those of Digit 5. The extent of the M20 delay for median nerve-innervated Digit 2 was positively correlated with decreasing nerve conduction velocity and increasing pain severity. Thus, slower peripheral nerve conduction in carpal tunnel syndrome corresponds to greater delays in the first somatosensory cortical response. Furthermore, spectral analysis demonstrated weaker post-stimulus beta event-related desynchronization and earlier and shorter event-related synchronization in subjects with carpal tunnel syndrome. The extent of the decreased event-related desynchronization for median nerve-innervated digits was positively correlated with paraesthesia severity. We propose that ongoing paraesthesias in median nerve-innervated digits render their corresponding sensorimotor cortical areas 'busy', thus reducing their capacity to process external stimulation. Finally, subjects with carpal tunnel syndrome demonstrated a smaller cortical source separation for Digits 2 and 3 compared with healthy controls. This supports our hypothesis that ongoing paraesthesias promote blurring of median nerve-innervated digit representations through Hebbian plasticity mechanisms. In summary, this study reveals significant correlation between the clinical severity of carpal tunnel syndrome and the latency of the early M20, as well as the strength of long latency beta oscillations. These temporal magnetoencephalography measures are novel markers of neuroplasticity in carpal tunnel syndrome and could be used to study central changes that may occur following clinical intervention.

Facilitating neuronal connectivity analysis of evoked responses by exposing local activity with principal component analysis preprocessing: simulation of evoked MEG

When connectivity analysis is carried out for event related EEG and MEG, the presence of strong spatial correlations from spontaneous activity in background may mask the local neuronal evoked activity and lead to spurious connections. In this paper, we hypothesized PCA decomposition could be used to diminish the background activity and further improve the performance of connectivity analysis in event related experiments. The idea was tested using simulation, where we found that for the 306-channel Elekta Neuromag system, the first 4 PCs represent the dominant background activity, and the source connectivity pattern after preprocessing is consistent with the true connectivity pattern designed in the simulation. Improving signal to noise of the evoked responses by discarding the first few PCs demonstrates increased coherences at major physiological frequency bands when removing the first few PCs. Furthermore, the evoked information was maintained after PCA preprocessing. In conclusion, it is demonstrated that the first few PCs represent background activity, and PCA decomposition can be employed to remove it to expose the evoked activity for the channels under investigation. Therefore, PCA can be applied as a preprocessing approach to improve neuronal connectivity analysis for event related data.

Hearing an illusory vowel in noise: suppression of auditory cortical activity

Human hearing is constructive. For example, when a voice is partially replaced by an extraneous sound (e.g., on the telephone due to a transmission problem), the auditory system may restore the missing portion so that the voice can be perceived as continuous (Miller and Licklider, 1950; for review, see Bregman, 1990; Warren, 1999). The neural mechanisms underlying this continuity illusion have been studied mostly with schematic stimuli (e.g., simple tones) and are still a matter of debate (for review, see Petkov and Sutter, 2011). The goal of the present study was to elucidate how these mechanisms operate under more natural conditions. Using psychophysics and electroencephalography (EEG), we assessed simultaneously the perceived continuity of a human vowel sound through interrupting noise and the concurrent neural activity. We found that vowel continuity illusions were accompanied by a suppression of the 4 Hz EEG power in auditory cortex (AC) that was evoked by the vowel interruption. This suppression was stronger than the suppression accompanying continuity illusions of a simple tone. Finally, continuity perception and 4 Hz power depended on the intactness of the sound that preceded the vowel (i.e., the auditory context). These findings show that a natural sound may be restored during noise due to the suppression of 4 Hz AC activity evoked early during the noise. This mechanism may attenuate sudden pitch changes, adapt the resistance of the auditory system to extraneous sounds across auditory scenes, and provide a useful model for assisted hearing devices.

Auditory cortex responses to clicks and sensory modulation difficulties in children with autism spectrum disorders (ASD)

Auditory sensory modulation difficulties are common in autism spectrum disorders (ASD) and may stem from a faulty arousal system that compromises the ability to regulate an optimal response. To study neurophysiological correlates of the sensory modulation difficulties, we recorded magnetic field responses to clicks in 14 ASD and 15 typically developing (TD) children. We further analyzed the P100m, which is the most prominent component of the auditory magnetic field response in children and may reflect preattentive arousal processes. The P100m was rightward lateralized in the TD, but not in the ASD children, who showed a tendency toward P100m reduction in the right hemisphere (RH). The atypical P100m lateralization in the ASD subjects was associated with greater severity of sensory abnormalities assessed by Short Sensory Profile, as well as with auditory hypersensitivity during the first two years of life. The absence of right-hemispheric predominance of the P100m and a tendency for its right-hemispheric reduction in the ASD children suggests disturbance of the RH ascending reticular brainstem pathways and/or their thalamic and cortical projections, which in turn may contribute to abnormal arousal and attention. The correlation of sensory abnormalities with atypical, more leftward, P100m lateralization suggests that reduced preattentive processing in the right hemisphere and/or its shift to the left hemisphere may contribute to abnormal sensory behavior in ASD.