An integrative MEG-fMRI study of the primary somatosensory cortex using cross-modal correspondence analysis

The relationship between electrophysiological and hemodynamic measures of neural activity varies across picture naming tasks: A multimodal magnetoencephalography-functional magnetic resonance imaging study

Different neuroimaging methods can yield different views of task-dependent neural engagement. Studies examining the relationship between electromagnetic and hemodynamic measures have revealed correlated patterns across brain regions but the role of the applied stimulation or experimental tasks in these correlation patterns is still poorly understood. Here, we evaluated the across-tasks variability of MEG-fMRI relationship using data recorded during three distinct naming tasks (naming objects and actions from action images, and objects from object images), from the same set of participants. Our results demonstrate that the MEG-fMRI correlation pattern varies according to the performed task, and that this variability shows distinct spectral profiles across brain regions. Notably, analysis of the MEG data alone did not reveal modulations across the examined tasks in the time-frequency windows emerging from the MEG-fMRI correlation analysis. Our results suggest that the electromagnetic-hemodynamic correlation could serve as a more sensitive proxy for task-dependent neural engagement in cognitive tasks than isolated within-modality measures.

Imaging somatosensory cortex responses measured by OPM-MEG: Variational free energy-based spatial smoothing estimation approach

In recent years, optically pumped magnetometer (OPM)-based magnetoencephalography (MEG) has shown potential for analyzing brain activity. It has a flexible sensor configuration and comparable sensitivity to conventional SQUID-MEG. We constructed a 32-channel OPM-MEG system and used it to measure cortical responses to median and ulnar nerve stimulations. Traditional magnetic source imaging methods tend to blur the spatial extent of sources. Accurate estimation of the spatial size of the source is important for studying the organization of brain somatotopy and for pre-surgical functional mapping. We proposed a new method called variational free energy-based spatial smoothing estimation (FESSE) to enhance the accuracy of mapping somatosensory cortex responses. A series of computer simulations based on the OPM-MEG showed better performance than the three types of competing methods under different levels of signal-to-noise ratios, source patch sizes, and co-registration errors. FESSE was then applied to the source imaging of the OPM-MEG experimental data.

Identification of Proprioceptive Thalamocortical Tracts in Children: Comparison of fMRI, MEG, and Manual Seeding of Probabilistic Tractography

Studying white matter connections with tractography is a promising approach to understand the development of different brain processes, such as proprioception. An emerging method is to use functional brain imaging to select the cortical seed points for tractography, which is considered to improve the functional relevance and validity of the studied connections. However, it is unknown whether different functional seeding methods affect the spatial and microstructural properties of the given white matter connection. Here, we compared functional magnetic resonance imaging, magnetoencephalography, and manual seeding of thalamocortical proprioceptive tracts for finger and ankle joints separately. We showed that all three seeding approaches resulted in robust thalamocortical tracts, even though there were significant differences in localization of the respective proprioceptive seed areas in the sensorimotor cortex, and in the microstructural properties of the obtained tracts. Our study shows that the selected functional or manual seeding approach might cause systematic biases to the studied thalamocortical tracts. This result may indicate that the obtained tracts represent different portions and features of the somatosensory system. Our findings highlight the challenges of studying proprioception in the developing brain and illustrate the need for using multimodal imaging to obtain a comprehensive view of the studied brain process.

Evidence of Neurovascular Un-Coupling in Mild Alzheimer's Disease through Multimodal EEG-fNIRS and Multivariate Analysis of Resting-State Data

Alzheimer’s disease (AD) is associated with modifications in cerebral blood perfusion and autoregulation. Hence, neurovascular coupling (NC) alteration could become a biomarker of the disease. NC might be assessed in clinical settings through multimodal electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Multimodal EEG-fNIRS was recorded at rest in an ambulatory setting to assess NC and to evaluate the sensitivity and specificity of the methodology to AD. Global NC was evaluated with a general linear model (GLM) framework by regressing whole-head EEG power envelopes in three frequency bands (theta, alpha and beta) with average fNIRS oxy- and deoxy-hemoglobin concentration changes in the frontal and prefrontal cortices. NC was lower in AD compared to healthy controls (HC) with significant differences in the linkage of theta and alpha bands with oxy- and deoxy-hemoglobin, respectively (p = 0.028 and p = 0.020). Importantly, standalone EEG and fNIRS metrics did not highlight differences between AD and HC. Furthermore, a multivariate data-driven analysis of NC between the three frequency bands and the two hemoglobin species delivered a cross-validated classification performance of AD and HC with an Area Under the Curve, AUC = 0.905 (p = 2.17 × 10⁻⁵). The findings demonstrate that EEG-fNIRS may indeed represent a powerful ecological tool for clinical evaluation of NC and early identification of AD.

Frequency-Dependent Intrinsic Electrophysiological Functional Architecture of the Human Verbal Language Network

Functional magnetic resonance imaging (fMRI) allowed the spatial characterization of the resting-state verbal language network (vLN). While other resting-state networks (RSNs) were matched with their electrophysiological equivalents at rest and could be spectrally defined, such correspondence is lacking for the vLN. This magnetoencephalography (MEG) study aimed at defining the spatio-spectral characteristics of the neuromagnetic intrinsic functional architecture of the vLN. Neuromagnetic activity was recorded at rest in 100 right-handed healthy adults (age range: 18-41 years). Band-limited power envelope correlations were performed within and across frequency bands (θ, α, β, and low γ) from a seed region placed in the left Broca's area, using static orthogonalization as leakage correction. K-means clustering was used to segregate spatio-spectral clusters of resting-state functional connectivity (rsFC). Remarkably, unlike other RSNs, within-frequency long-range rsFC from the left Broca's area was not driven by one main carrying frequency but was characterized by a specific spatio-spectral pattern segregated along the ventral (predominantly θ and α) and dorsal (β and low-γ bands) vLN streams. In contrast, spatial patterns of cross-frequency vLN functional integration were spectrally more widespread and involved multiple frequency bands. Moreover, the static intrinsic functional architecture of the neuromagnetic human vLN involved clearly left-hemisphere-dominant vLN interactions as well as cross-network interactions with the executive control network and postero-medial nodes of the DMN. Overall, this study highlighted the involvement of multiple modes of within and cross-frequency power envelope couplings at the basis of long-range electrophysiological vLN functional integration. As such, it lays the foundation for future works aimed at understanding the pathophysiology of language-related disorders.

Characterizing hippocampal dynamics with MEG: A systematic review and evidence-based guidelines

The hippocampus, a hub of activity for a variety of important cognitive processes, is a target of increasing interest for researchers and clinicians. Magnetoencephalography (MEG) is an attractive technique for imaging spectro-temporal aspects of function, for example, neural oscillations and network timing, especially in shallow cortical structures. However, the decrease in MEG signal-to-noise ratio as a function of source depth implies that the utility of MEG for investigations of deeper brain structures, including the hippocampus, is less clear. To determine whether MEG can be used to detect and localize activity from the hippocampus, we executed a systematic review of the existing literature and found successful detection of oscillatory neural activity originating in the hippocampus with MEG. Prerequisites are the use of established experimental paradigms, adequate coregistration, forward modeling, analysis methods, optimization of signal-to-noise ratios, and protocol trial designs that maximize contrast for hippocampal activity while minimizing those from other brain regions. While localizing activity to specific sub-structures within the hippocampus has not been achieved, we provide recommendations for improving the reliability of such endeavors.

Prefrontal high gamma during a magnetoencephalographic working memory task

In human electrophysiology research, the high gamma part of the power spectrum (~>60 Hz) is a relatively new area of investigation. Despite a low signal-to-noise ratio, evidence exists that it contains significant information about activity in local cortical networks. Here, using magnetoencephalography (MEG), we found high gamma activity when comparing data from an n-back working memory task to resting data in a large sample of normal volunteers. Initial analysis of power spectra from 0-back, 2-back, and rest trials showed three frequency bands exhibiting task-related differences: alpha, beta, and high gamma. Unlike alpha and beta, the high gamma spectrum was broad, without a peak at a single frequency. In addition, power in high gamma was highest for the 2-back and lowest during rest, while the opposite pattern occurred in the other bands. Beamformer source localization of each of the three frequency bands revealed a distinct set of sources for high gamma. These included several regions of prefrontal cortex that exhibited greater power when both n-back conditions were compared to rest. A subset of these regions had more power when the 2-back was compared to 0-back, which indicates a role in working memory performance. Our results show that high gamma will be important for understanding cortical processing during cognitive and other tasks. Furthermore, data from human intracortical recordings suggest that high gamma is the aggregate of spiking in local cortical networks, which implies that MEG could serve to bridge experimental modalities by noninvasively observing task-related modulation of spiking rates.

The causal role of the somatosensory cortex in prosocial behaviour

Witnessing another person’s suffering elicits vicarious brain activity in areas that are active when we ourselves are in pain. Whether this activity influences prosocial behavior remains the subject of debate. Here participants witnessed a confederate express pain through a reaction of the swatted hand or through a facial expression, and could decide to reduce that pain by donating money. Participants donate more money on trials in which the confederate expressed more pain. Electroencephalography shows that activity of the somatosensory cortex I (SI) hand region explains variance in donation. Transcranial magnetic stimulation (TMS) shows that altering this activity interferes with the pain–donation coupling only when pain is expressed by the hand. High-definition transcranial direct current stimulation (HD-tDCS) shows that altering SI activity also interferes with pain perception. These experiments show that vicarious somatosensory activations contribute to prosocial decision-making and suggest that they do so by helping to transform observed reactions of affected body-parts into accurate perceptions of pain that are necessary for decision-making.

When we experience physical pain, certain areas in our brain that process bodily sensation and emotions switch on. If we see someone else in pain, many of the same regions also get activated. In contrast, convicted criminals with psychopathic traits have less activation in these areas of the brain when witnessing someone’s pain; they also show less empathy and disregard the needs of others. This suggests that a lack of this ‘shared activations’ may lead to problems in empathy. In fact, many scientists believe that shared activations are why we feel empathy for people in pain, and why we are driven to help them. Yet, there is little direct evidence about how the activity in the pain processing parts of the brain actually influences helpful behavior. As a result, some scientists now argue that empathy-related processes may actually contribute very little to helping behavior.

Gallo et al. designed an experiment where participants watched videos of someone having their hand swatted with a belt, and showing different levels of pain as a result. The volunteers could decide to reduce the amount of pain the person received by donating money they could have taken home. The more pain the participants thought the victim was in, the more money they gave up to lessen it. During the study, the activity in the brain region that processes pain in the hand was also measured in the participants. The more active this region was, the more money people donated to help.

Then, Gallo et al. used techniques that interfered with the activity of the brain area involved in perceiving sensations from the hand. This interference changed how accurately participants assessed the victim's pain. It also disrupted the link between donations and the victim's perceived pain: the amount of money people gave no longer matched the level of pain they had witnessed. This suggests that the brain areas that perceive sensations of pain in the self, which evolved primarily to experience our own sensations, also have a social function. They transform the sight of bodily harm into an accurate feeling for how much pain the victim experiences. The findings also show that we need this feeling so we can adapt our help to the needs of others. In the current debate about the role of empathy in helping behaviors, this study demonstrates that empathy-related brain activity indeed promotes helping by allowing us to detect those that need our assistance.

Understanding the relationship between helping behavior and the activity of the brain may further lead to treatments for individuals with antisocial behavior and for children with callous and unemotional traits, a disorder that is associated with a lack of empathy and a general disregard for others.

Quantitative Assessment of Head Motion toward Functional Magnetic Resonance Imaging during Stepping

Purpose:

Stepping motions have been often used as gait-like patterns in functional magnetic resonance imaging (fMRI) to understand gait control. However, it is still very difficult to stabilize the task-related head motion. Our main purpose is to provide characteristics of the task-related head motion during stepping to develop robust restraints toward fMRI.

Methods:

Multidirectional head and knee position during stepping were acquired using a motion capture system outside MRI room in 13 healthy participants. Six phases in a stepping motion were defined by reference to the left knee angles and the mean of superior-inferior head velocity (V_mean) in each phase was investigated. Furthermore, the correlation between the standard deviation of the knee angle (θ_sd) and the maximum of the head velocity (V_max) was evaluated.

Results:

The standard deviation of each superior-inferior head position and pitch were significantly larger than the other measurements. V_mean showed a characteristic repeating pattern associated with the knee angle. Additionally, there were significant correlations between θ_sd and V_max.

Conclusions:

This is the first report to reveal the characteristics of the task-related head motion during stepping. Our findings are an essential step in the development of robust restraint toward fMRI during stepping task.

Prestimulus oscillatory alpha power and connectivity patterns predispose perceptual integration of an audio and a tactile stimulus

To efficiently perceive and respond to the external environment, our brain has to perceptually integrate or segregate stimuli of different modalities. The temporal relationship between the different sensory modalities is therefore essential for the formation of different multisensory percepts. In this magnetoencephalography study, we created a paradigm where an audio and a tactile stimulus were presented by an ambiguous temporal relationship so that perception of physically identical audiotactile stimuli could vary between integrated (emanating from the same source) and segregated. This bistable paradigm allowed us to compare identical bimodal stimuli that elicited different percepts, providing a possibility to directly infer multisensory interaction effects. Local differences in alpha power over bilateral inferior parietal lobules (IPLs) and superior parietal lobules (SPLs) preceded integrated versus segregated percepts of the two stimuli (audio and tactile). Furthermore, differences in long-range cortical functional connectivity seeded in rIPL (region of maximum difference) revealed differential patterns that predisposed integrated or segregated percepts encompassing secondary areas of all different modalities and prefrontal cortex. We showed that the prestimulus brain states predispose the perception of the audiotactile stimulus both in a global and a local manner. Our findings are in line with a recent consistent body of findings on the importance of prestimulus brain states for perception of an upcoming stimulus. This new perspective on how stimuli originating from different modalities are integrated suggests a non-modality specific network predisposing multisensory perception.

Multivariate analysis of correlation between electrophysiological and hemodynamic responses during cognitive processing

Animal and human studies have frequently shown that in primary sensory and motor regions the BOLD signal correlates positively with high-frequency and negatively with low-frequency neuronal activity. However, recent evidence suggests that this relationship may also vary across cortical areas. Detailed knowledge of the possible spectral diversity between electrophysiological and hemodynamic responses across the human cortex would be essential for neural-level interpretation of fMRI data and for informative multimodal combination of electromagnetic and hemodynamic imaging data, especially in cognitive tasks. We applied multivariate partial least squares correlation analysis to MEG-fMRI data recorded in a reading paradigm to determine the correlation patterns between the data types, at once, across the cortex. Our results revealed heterogeneous patterns of high-frequency correlation between MEG and fMRI responses, with marked dissociation between lower and higher order cortical regions. The low-frequency range showed substantial variance, with negative and positive correlations manifesting at different frequencies across cortical regions. These findings demonstrate the complexity of the neurophysiological counterparts of hemodynamic fluctuations in cognitive processing.

Non-parametric permutation thresholding for adaptive nonlinear beamformer analysis on MEG revealed oscillatory neuronal dynamics in human brain

Adaptive nonlinear beamformer technique for analyzing magnetoencephalography (MEG) data has been proved to be powerful tool for both brain research and clinical applications. A general method of analyzing multiple subject data with a formal statistical treatment for the group data has been developed and applied for various types of MEG data. Our latest application of this method was frontal midline theta rhythm (Fmθ), which indicates focused attention and appears widely distributed over medial prefrontal areas in EEG recordings. To localize cortical generators of the magnetic counterpart of Fmθ precisely and identify cortical sources and underlying neural activity associated with mental calculation processing (i.e., arithmetic subtraction), we applied adaptive nonlinear beamformer and permutation analysis on MEG data. As a result, it was indicated that Fmθ is generated in the dorsal anterior cingulate and adjacent medial prefrontal cortex. Gamma event-related synchronization is as an index of activation in right parietal regions subserving mental subtraction associated with basic numerical processing and number-based spatial attention. Gamma desynchronization appeared in the right lateral prefrontal cortex, likely representing a mechanism to interrupt neural activity that can interfere with the ongoing cognitive task. We suggest that the combination of adaptive nonlinear beamformer and permutation analysis on MEG data is quite powerful tool to reveal the oscillatory neuronal dynamics in human brain.

The virtual brain integrates computational modeling and multimodal neuroimaging

Brain function is thought to emerge from the interactions among neuronal populations. Apart from traditional efforts to reproduce brain dynamics from the micro- to macroscopic scales, complementary approaches develop phenomenological models of lower complexity. Such macroscopic models typically generate only a few selected-ideally functionally relevant-aspects of the brain dynamics. Importantly, they often allow an understanding of the underlying mechanisms beyond computational reproduction. Adding detail to these models will widen their ability to reproduce a broader range of dynamic features of the brain. For instance, such models allow for the exploration of consequences of focal and distributed pathological changes in the system, enabling us to identify and develop approaches to counteract those unfavorable processes. Toward this end, The Virtual Brain (TVB) ( www.thevirtualbrain.org ), a neuroinformatics platform with a brain simulator that incorporates a range of neuronal models and dynamics at its core, has been developed. This integrated framework allows the model-based simulation, analysis, and inference of neurophysiological mechanisms over several brain scales that underlie the generation of macroscopic neuroimaging signals. In this article, we describe how TVB works, and we present the first proof of concept.

Effect of local anesthesia on trigeminal somatosensory-evoked magnetic fields

For objective neurophysiological evaluation of the function of the trigeminal system, magnetoencephalography- based TSEF (trigeminal somatosensory-evoked field) assessment would be valuable in providing spatial and temporal profiles of cortical responses. However, this necessitates knowledge of how TSEF varies with trigeminal nerve dysfunctions. We introduced a conduction block of the trigeminal nerve using local anesthesia (lidocaine) to temporally mimic nerve dysfunctions, and monitored TSEF changes. Following an electrical stimulation of the lower lip, a magnetic response with peak latency of approximately 20 ms was identified in all participants. Dipole for the peak was estimated on the post-central gyrus in the participant's own magnetic resonance image. After normalization to Montreal Neurological Institute (MNI) space and inter-participant data integration, the summary equivalent current dipole localization among participants remained in the post-central gyrus, suggesting validity of the use of MNI space. Partial anesthesia of the lower lip led to a loss of the waveform characteristics of TSEF for electrical stimulation to the trigeminal nerve. We verified that the 20-ms latency cortical response of TSEF components localized at the primary sensory cortex can serve as a robust neurofunctional marker of experimental trigeminal nerve dysfunction.

Concordance of MEG and fMRI patterns in adolescents during verb generation

In this study we focused on direct comparison between the spatial distributions of activation detected by functional magnetic resonance imaging (fMRI) and localization of sources detected by magnetoencephalography (MEG) during identical language tasks. We examined the spatial concordance between MEG and fMRI results in 16 adolescents performing a three-phase verb generation task that involves repeating the auditorily presented concrete noun and generating verbs either overtly or covertly in response to the auditorily presented noun. MEG analysis was completed using a synthetic aperture magnetometry (SAM) technique, while the fMRI data were analyzed using the general linear model approach with random-effects. To quantify the agreement between the two modalities, we implemented voxel-wise concordance correlation coefficient (CCC) and identified the left inferior frontal gyrus and the bilateral motor cortex with high CCC values. At the group level, MEG and fMRI data showed spatial convergence in the left inferior frontal gyrus for covert or overt generation versus overt repetition, and the bilateral motor cortex when overt generation versus covert generation. These findings demonstrate the utility of the CCC as a quantitative measure of spatial convergence between two neuroimaging techniques.

Anxiety, a benefit and detriment to cognition: behavioral and magnetoencephalographic evidence from a mixed-saccade task

Anxiety is typically considered an impediment to cognition. We propose anxiety-related impairments in cognitive-behavioral performance are the consequences of enhanced stimulus-driven attention. Accordingly, reflexive, habitual behaviors that rely on stimulus-driven mechanisms should be facilitated in an anxious state, while novel, flexible behaviors that compete with the former should be impaired. To test these predictions, healthy adults (N=17) performed a mixed-saccade task, which pits habitual actions (pro-saccades) against atypical ones (anti-saccades), under anxiety-inducing threat of shock and safe conditions. Whole-head magnetoencephalography (MEG) captured oscillatory responses in the preparatory interval preceding target onset and saccade execution. Results showed threat-induced anxiety differentially impacted response times based on the type of saccade initiated, slowing anti-saccades but facilitating erroneous pro-saccades on anti-saccade trials. MEG source analyses revealed that successful suppression of reflexive pro-saccades and correct initiation of anti-saccades during threat was marked by increased theta power in right ventrolateral prefrontal cortical and midbrain regions (superior colliculi) implicated in stimulus-driven attention. Theta activity may delay stimulus-driven processes to enable generation of an anti-saccade. Moreover, compared to safety, threat reduced beta desynchronization in inferior parietal cortices during anti-saccade preparation but increased it during pro-saccade preparation. Differential effects in inferior parietal cortices indicate a greater readiness to execute anti-saccades during safety and to execute pro-saccades during threat. These findings suggest that, in an anxiety state, reduced cognitive-behavioral flexibility may stem from enhanced stimulus-driven attention, which may serve the adaptive function of optimizing threat detection.

Connecting mean field models of neural activity to EEG and fMRI data

Progress in functional neuroimaging of the brain increasingly relies on the integration of data from complementary imaging modalities in order to improve spatiotemporal resolution and interpretability. However, the usefulness of merely statistical combinations is limited, since neural signal sources differ between modalities and are related non-trivially. We demonstrate here that a mean field model of brain activity can simultaneously predict EEG and fMRI BOLD with proper signal generation and expression. Simulations are shown using a realistic head model based on structural MRI, which includes both dense short-range background connectivity and long-range specific connectivity between brain regions. The distribution of modeled neural masses is comparable to the spatial resolution of fMRI BOLD, and the temporal resolution of the modeled dynamics, importantly including activity conduction, matches the fastest known EEG phenomena. The creation of a cortical mean field model with anatomically sound geometry, extensive connectivity, and proper signal expression is an important first step towards the model-based integration of multimodal neuroimages.

Negative covariation between task-related responses in alpha/beta-band activity and BOLD in human sensorimotor cortex: an EEG and fMRI study of motor imagery and movements

Similar to the occipital alpha rhythm, electroencephalographic (EEG) signals in the alpha- and beta-frequency bands can be suppressed by movement or motor imagery and have thus been thought to represent the "idling state" of the sensorimotor cortex. A negative correlation between spontaneous alpha EEG and blood-oxygen-level-dependent (BOLD) signals has been reported in combined EEG and fMRI (functional Magnetic Resonance Imaging) experiments when subjects stayed at the resting state or alternated between the resting state and a task. However, the precise nature of the task-induced alpha modulation remains elusive. It was not clear whether alpha/beta rhythm suppressions may co-vary with BOLD when conducting tasks involving varying activations of the cortex. Here, we quantified the task-evoked responses of BOLD and alpha/beta-band power of EEG directly in the cortical source domain, by using source imaging technology, and examined their covariation across task conditions in a mixed block and event-related design. In this study, 13 subjects performed tasks of right-hand, right-foot or left-hand movement and motor imagery when EEG and fMRI data were separately collected. Task-induced increase of BOLD signal and decrease of EEG amplitudes in alpha and beta bands were shown to be co-localized at the somatotopic sensorimotor cortex. At the corresponding regions, the reciprocal changes of the two signals co-varied in the magnitudes across imagination and movement conditions. The spatial correspondence and negative covariation between the two measurements were further shown to exist at somatotopic brain regions associated with different body parts. These results suggest an inverse functional coupling relationship between task-induced changes of BOLD and low-frequency EEG signals.

Direct MRI mapping of neuronal activity evoked by electrical stimulation of the median nerve at the right wrist

Magnetic source MRI (msMRI) has being developed recently for direct detections of neuronal magnetic fields to map brain activity. However, controversial results have been reported by different research groups. In this study, more evidence was provided to demonstrate that the neuronal current signal could be detected by MRI using a rapid median nerve stimulation paradigm. The experiments were performed on six normal human participants to investigate the temporal specificity of the effect, as well as inter- and intrasubject reproducibility. Significant activation of contralateral primary sensory cortex (S1) was detected 80 ms after stimulation onset (corresponding to the P80 evoked potential peak). The 80-ms latency S1 activation was observed over three independent sessions for one subject and for all six participants. The magnitude of the signal change was 0.2-0.3%. Coinciding with our expectations, no S1 activation was found when MRI data acquisitions were targeted at the N20 and P30 peaks because of mutual cancellation of magnetic fields generated by those peaks. The results demonstrated good reproducibility of S1 activations and indicated that the S1 activations most likely originated from neuronal magnetic field rather than hemodynamic response.

Increased anterior cingulate cortical activity in response to fearful faces: a neurophysiological biomarker that predicts rapid antidepressant response to ketamine

BACKGROUND

Most patients with major depressive disorder (MDD) experience a period of lengthy trial and error when trying to find optimal antidepressant treatment; identifying biomarkers that could predict response to antidepressant treatment would be of enormous benefit. We tested the hypothesis that pretreatment anterior cingulate cortex (ACC) activity could be a putative biomarker of rapid antidepressant response to ketamine, in line with previous findings that investigated the effects of conventional antidepressants. We also investigated patterns of ACC activity to rapid presentation of fearful faces compared with the normal habituation observed in healthy subjects.

METHODS

We elicited ACC activity in drug-free patients with MDD (n = 11) and healthy control subjects (n = 11) by rapidly presenting fearful faces, a paradigm known to activate rostral regions of the ACC. Spatial-filtering analyses were performed on magnetoencephalographic (MEG) recordings, which offer the temporal precision necessary to estimate ACC activity elicited by the rapid presentation of stimuli. Magnetoencephalographic recordings were obtained only once for both patients and control subjects. Patients were subsequently administered a single ketamine infusion followed by assessment of depressive symptoms 4 hours later.

RESULTS

Although healthy subjects had decreased neuromagnetic activity in the rostral ACC across repeated exposures, patients with MDD showed robust increases in pretreatment ACC activity. Notably, this increase was positively correlated with subsequent rapid antidepressant response to ketamine. Exploratory analyses showed that pretreatment amygdala activity was negatively correlated with change in depressive symptoms.

CONCLUSIONS

Pretreatment rostral ACC activation may be a useful biomarker that identifies a subgroup of patients who will respond favorably to ketamine's antidepressant effects.

Decreased cortical somatosensory finger representation in X-linked recessive bulbospinal neuronopathy (Kennedy disease): a magnetoencephalographic study

BACKGROUND

Kennedy disease (KD) clinically presents as progressive lower motor neuron disease with minimal or no sensory impairment. However, electrophysiological studies found abnormal somatosensory-evoked potentials even in absence of clinical deficits. Little is known about possible influences of this sensory neuropathy on the central somatosensory processing.

METHODS

In this study, the cortical topography of index finger representation was studied in 7 patients with genetically proven KD compared to healthy control subjects by means of magnetoencephalography using an established stimulation paradigm. Data analysis was carried out with synthetic aperture magnetometry (SAM). Additionally, the latency and source amplitude of the earliest cortical somatosensory-evoked field (SEF) component were determined based on traditional single dipole source analysis.

RESULTS

In KD patients the latency of the SEF was prolonged (48.6 vs. 37.4 ms, P < .005). There was no significant difference in dipole source amplitude, but stimulus-related SAM activation of the contralateral sensorimotor cortex (pseudo-t-values -.107 vs. -.199, P < .05), including maximum activity (53.5%), was reduced.

CONCLUSIONS

These results implicate that even subclinical sensory neuropathy leads to possible functional reorganization of the sensorimotor cortex in KD patients and reinforces the view that in KD the somatosensory system is extensively involved.

A complementary analytic approach to examining medial temporal lobe sources using magnetoencephalography

Neuropsychological and neuroimaging findings reveal that the hippocampus is important for recognition memory. However, it is unclear when and whether the hippocampus contributes differentially to recognition of previously studied items (old) versus novel items (new), or contributes to a general processing requirement that is necessary for recognition of both types of information. To address this issue, we examined the temporal dynamics and spectral frequency underlying hippocampal activity during recognition of old/new complex scenes using magnetoencephalography (MEG). In order to provide converging evidence to existing literature in support of the potential of MEG to localize the hippocampus, we reconstructed brain source activity using the beamformer method and analyzed three types of processing-related signal changes by applying three different analysis methods: (1) Synthetic aperture magnetometry (SAM) revealed event related and non-event-related spectral power changes; (2) Inter-trial coherence (ITC) revealed time-locked changes in neural synchrony; and (3) Event-related SAM (ER-SAM) revealed averaged event-related responses over time. Hippocampal activity was evident for both old and new information within the theta frequency band and during the first 250 ms following stimulus onset. The early onset of hippocampal responses suggests that general comparison processes related to recognition of new/old information may occur obligatorily.

Evoked amygdala responses to negative faces revealed by adaptive MEG beamformers

Adaptive beamformer analyses of magnetoencephalograms (MEG) have shown promise as a method for functional imaging of cortical processes. Although recent evidence is encouraging, it is unclear whether these methods can both localize and reconstruct the time course of activity in subcortical structures such as the amygdala. Fourteen healthy participants (7 women) performed a perceptual matching task of negative emotional faces (angry and fearful) and geometric shapes that was designed for functional magnetic resonance imaging (fMRI) studies to maximize amygdala activation. Neuromagnetic data were collected with a 275-channel whole-head magnetometer, and event-related adaptive beamformer analyses were conducted to estimate broadband evoked responses to faces and shapes across the whole brain in 7 mm steps. Group analyses revealed greater left amygdala activity to faces over shapes, both when face-matching and shape-matching trials were presented in separate blocks and when they were randomly intermixed. This finding was replicated in a second experiment with 7 new participants (3 women). Virtual sensor time series showed clear evoked responses in the left amygdala and left fusiform gyrus in both runs and experiments. We conclude that amygdala activity can be resolved from MEGs with adaptive beamformers with temporal resolution superior to other neuroimaging modalities. This demonstration should encourage the use of MEG for elucidating functional networks mediating fear-related neural phenomena that likely unfold rapidly in time across cortical and subcortical structures.

Human hippocampal and parahippocampal theta during goal-directed spatial navigation predicts performance on a virtual Morris water maze

The hippocampus and parahippocampal cortices exhibit theta oscillations during spatial navigation in animals and humans, and in the former are thought to mediate spatial memory formation. Functional specificity of human hippocampal theta, however, is unclear. Neuromagnetic activity was recorded with a whole-head 275-channel magnetoencephalographic (MEG) system as healthy participants navigated to a hidden platform in a virtual reality Morris water maze. MEG data were analyzed for underlying oscillatory sources in the 4-8 Hz band using a spatial filtering technique (i.e., synthetic aperture magnetometry). Source analyses revealed greater theta activity in the left anterior hippocampus and parahippocampal cortices during goal-directed navigation relative to aimless movements in a sensorimotor control condition. Additional analyses showed that left anterior hippocampal activity was predominantly observed during the first one-half of training, pointing to a role for this region in early learning. Moreover, posterior hippocampal theta was highly correlated with navigation performance, with the former accounting for 76% of the variance of the latter. Our findings suggest human spatial learning is dependent on hippocampal and parahippocampal theta oscillations, extending to humans a significant body of research demonstrating such a pivotal role for hippocampal theta in animal navigation.

Simultaneous recording of EEG and BOLD responses: A historical perspective

Electromagnetic fields as measured with electroencephalogram (EEG) are a direct consequence of neuronal activity and feature the same timescale as the underlying cognitive processes, while hemodynamic signals as measured with functional magnetic resonance imaging (fMRI) are related to the energy consumption of neuronal populations. It is obvious that a combination of both techniques is a very attractive aim in neuroscience, in order to achieve both high temporal and spatial resolution for the non-invasive study of cognitive brain function. During the last decade a number of research groups have taken up this challenge. Here, we review the development of the combined EEG-fMRI approach. We summarize the main data integration approaches developed to achieve such a combination, discuss the current state-of-the-art in this field and outline challenges for the future success of this promising approach.

Complex relationship between BOLD signal and synchronization/desynchronization of human brain MEG oscillations

Functional magnetic resonance imaging (fMRI) depends on the coupling of cerebral blood flow, energy demand, and neural activity. The precise nature of this interaction, however, is poorly understood. A positive correlation between BOLD-response and cortically generated local field potentials, which reflect the weighted average of synchronized dentrosomatic components of pyramidal synaptic signals, has been demonstrated. Likewise, positive BOLD-responses have been reported in conjunction with scalp-recorded synchronized electromagnetic activity by a number of groups. However, it is not yet clear how the opposite electromagnetic pattern, i.e. cortical desynchronization, is related to the BOLD signal. To address this question, we conducted a combined event-related fMRI and 275 sensor whole-head MEG study during identical visual two-choice reaction time task conditions in 10 human subjects. We found complex sequences of MEG-synchronization and desynchronization across a wide frequency range in the visual and motor area in close correspondence with "locales" of positive BOLD-responses. These results indicate that a correspondence of positive BOLD-responses is not exclusively found for cortical synchronization but also for desynchronization, suggesting that the relationship between BOLD signals and electromagnetic activity might be more complex than previously thought.

Event-related beamforming: a robust method for presurgical functional mapping using MEG

OBJECTIVE

We describe the application of a new spatial filtering technique--event-related beamforming (ERB)--for presurgical functional mapping of primary sensory areas using MEG. This method provides an alternative to equivalent current dipole (ECD) modeling that potentially eliminates problems of intracranial magnetic artifacts due to movement of ferromagnetic materials (e.g., orthodontic braces) or eye movements.

METHODS

We compared localization results for ERB and ECD localization of primary somatosensory (M20) and auditory (M100) evoked responses in 12 healthy control subjects and four subjects with metallic dental implants. Data were recorded with a 151-channel CTF MEG system using standard presurgical mapping protocols.

RESULTS

We found a high level of agreement between the two methods in control subjects (overall localization difference was 5.9+/-2.2 mm for M20 and 10.4+/-5.6 mm for M100). Subjects with dental implants showed severely distorted evoked responses that could not be analyzed using ECD, whereas the ERB method localized sources to expected anatomical locations.

CONCLUSIONS

MEG functional mapping may be carried out without removal of orthodontic or other metallic implants using event-related beamformer analysis.

SIGNIFICANCE

Spatial filtering methods can overcome some of the limitations associated with MEG expanding its applicability, particularly in pediatric clinical environments.

fMRI-vs-MEG evaluation of post-stroke interhemispheric asymmetries in primary sensorimotor hand areas

Growing evidence emphasizes a positive role of brain ipsilesional (IL) reorganization in stroke patients with partial recovery. Ten patients affected by a monohemispheric stroke in the middle cerebral artery territory underwent functional magnetic resonance (fMRI) and magnetoencephalography (MEG) evaluation of the primary sensory (S1) activation via the same paradigm (median nerve galvanic stimulation). Four patients did not present S1 fMRI activation [Rossini, P.M., Altamura, C., Ferretti, A., Vernieri, F., Zappasodi, F., Caulo, M., Pizzella, V., Del Gratta, C., Romani, G.L., Tecchio, F., 2004. Does cerebrovascular disease affect the coupling between neuronal activity and local haemodynamics? Brain 127, 99-110], although inclusion criteria required bilateral identifiable MEG responses. Mean Euclidean distance between fMRI and MEG S1 activation Talairach coordinates was 10.1+/-2.9 mm, with a 3D intra-class correlation (ICC) coefficient of 0.986. Interhemispheric asymmetries, evaluated by an MEG procedure independent of Talairach transformation, were outside or at the boundaries of reference ranges in 6 patients. In 3 of them, the IL activation presented medial or lateral shift with respect to the omega-shaped post-rolandic area while in the other 3, IL areas were outside the peri-rolandic region. In conclusion, despite dissociated intensity, the MEG and fMRI activations displayed good spatial consistency in stroke patients, thus confirming excessive interhemispheric asymmetries as a suitable indicator of unusual recruitments in the ipsilesional hemisphere, within or outside the peri-rolandic region.

Rhythmic brain activities related to singing in humans

To investigate the motor control related to sound production, we studied cortical rhythmic changes during continuous vocalization such as singing. Magnetoencephalographic (MEG) responses were recorded while subjects spoke in the usual way (speaking), sang (singing), hummed (humming) and imagined (imagining) a popular song. The power of alpha (8-15 Hz), beta (15-30 Hz) and low-gamma (30-60 Hz) frequency bands was changed during and after vocalization (singing, speaking and humming). In the alpha band, the oscillatory changes for singing were most pronounced in the right premotor, bilateral sensorimotor, right secondary somatosensory and bilateral superior parietal areas. The beta oscillation for the singing was also confirmed in the premotor, primary and secondary sensorimotor and superior parietal areas in the left and right hemispheres where were partly activated even for imagined a song (imaging). These regions have been traditionally described as vocalization-related sites. The cortical rhythmic changes were distinct in the singing condition compared with the other vocalizing conditions (speaking and humming) and thus we considered that more concentrated control of the vocal tract, diaphragm and abdominal muscles is responsible. Furthermore, characteristic oscillation in the high-gamma (60-200 Hz) frequency band was found in Broca's area only in the imaging condition and might occur singing rehearsal and storage process in Broca's area.

Correspondence between EEG-fMRI and EEG dipole localisation of interictal discharges in focal epilepsy

EEG-fMRI and EEG dipole source localisation are two non-invasive imaging methods that can be applied to the study of the haemodynamic and electrical consequences of epileptic discharges. Using them in combination has the potential to allow imaging with the spatial resolution of fMRI and the temporal resolution of EEG. However, although considerable data are available concerning their concordance in studies involving event-related potentials (ERPs), less is known about how well they agree in epilepsy. To this end, 17 patients were selected from a database of 57 who had undergone an EEG-fMRI scanning session followed by a separate EEG session outside of the scanner. Spatiotemporal dipole modelling was compared with the peak and closest EEG-fMRI activations and deactivations. On average, the dipoles were 58.5 mm from the voxel with the highest positive t value and 32.5 mm from the nearest activated voxel. For deactivations, the corresponding values were 60.8 and 34.0 mm. These values are considerably higher than is generally observed with ERPs, probably as a result of the relatively widespread field, which can lead to artificially deep dipoles, and the occurrence of EEG-fMRI responses remote from the presumed focus of the epileptic activity. The results suggest that EEG and MEG inverse solutions for equivalent current dipole approaches should not be strongly constrained by EEG-fMRI results in epilepsy, and that the use of distributed source modelling will be a more appropriate way of combining EEG-fMRI results with source localisation techniques.

Spatiotemporal mapping of cortical activity accompanying voluntary movements using an event-related beamforming approach

We describe a novel spatial filtering approach to the localization of cortical activity accompanying voluntary movements. The synthetic aperture magnetometry (SAM) minimum-variance beamformer algorithm was used to compute spatial filters three-dimensionally over the entire brain from single trial neuromagnetic recordings of subjects performing self-paced index finger movements. Images of instantaneous source power ("event-related SAM") computed at selected latencies revealed activation of multiple cortical motor areas prior to and following left and right index finger movements in individual subjects, even in the presence of low-frequency noise (e.g., eye movements). A slow premovement motor field (MF) reaching maximal amplitude approximately 50 ms prior to movement onset was localized to the hand area of contralateral precentral gyrus, followed by activity in the contralateral postcentral gyrus at 40 ms, corresponding to the first movement-evoked field (MEFI). A novel finding was a second activation of the precentral gyrus at a latency of approximately 150 ms, corresponding to the second movement-evoked field (MEFII). Group averaging of spatially normalized images indicated additional premovement activity in the ipsilateral precentral gyrus and the left inferior parietal cortex for both left and right finger movements. Weaker activations were also observed in bilateral premotor areas and the supplementary motor area. These results show that event-related beamforming provides a robust method for studying complex patterns of time-locked cortical activity accompanying voluntary movements, and offers a new approach for the localization of multiple cortical sources derived from neuromagnetic recordings in single subject and group data.

Neuromagnetic Changes of Brain Rhythm Evoked by Intravenous Olfactory Stimulation in Humans

To identify the changes in the respective frequency band and brain areas related to olfactory perception, we measured magnetoencephalographic (MEG) signals before and after instilling intravenously thiamine propyl disulfide (TPD) and thiamine tetrahydrofurfuryl disulfide monohydrochloride (TTFD), which evoked a strong and weak sensation of odor, respectively. For the frequency analysis of MEG, a beamformer program, synthetic aperture magnetometry (SAM), was employed and event-related desynchronization (ERD) or synchronization (ERS) was statistically determined. Both strong and weak odors induced ERD in (1) beta band (13-30 Hz) in the right precentral gyrus, and the superior and middle frontal gyri in both hemispheres, (2) low gamma band (30-60 Hz) in the left superior frontal gyrus and superior parietal lobule, and the middle frontal gyrus in both hemispheres, and (3) high gamma band 2 (100-200 Hz) in the right inferior frontal gyrus. TPD induced ERD in the left temporal, parietal and occipital lobes, while TTFD induced ERD in the right temporal, parietal and occipital lobes. The results indicate that physiological functions in several regions in the frontal lobe may change and the strength of the odor may play a different role in each hemisphere during olfactory perception in humans.

Temporal information processing in ADHD: Findings to date and new methods

The ability to perceive and represent time is a fundamental but complex cognitive skill that allows us to perceive and organize sequences of events and actions, and to anticipate or predict when future events will occur. It is a multidimensional construct, and a variety of methods have been used to understand timing performance in ADHD samples, which makes it difficult to integrate findings across studies. While further replication is needed, growing evidence links ADHD to problems in several aspects of temporal information processing, including duration discrimination, duration reproduction, and finger tapping. Neuroimaging studies of ADHD have also implicated cerebellar, basal ganglia, and prefrontal regions of the brain, which are believed to subserve temporal information processing. This line of research implicates more basic cognitive mechanisms than previously linked with ADHD and challenges researchers to develop and utilize innovative, multidisciplinary, scientific methods to dissect the various components of temporal information processing. Recent advances in neuroimaging, such as magnetoencephalography in collaboration with structural magnetic resonance imaging, can discriminate temporal processing at the level of a millisecond. This approach can lay the groundwork to provide a more precise understanding of neural network activity during different aspects and stages of temporal information processing in ADHD.

Bayesian analysis of the neuromagnetic inverse problem with l(p)-norm priors

Magnetoencephalography (MEG) allows millisecond-scale non-invasive measurement of magnetic fields generated by neural currents in the brain. However, localization of the underlying current sources is ambiguous due to the so-called inverse problem. The most widely used source localization methods (i.e., minimum-norm and minimum-current estimates (MNE and MCE) and equivalent current dipole (ECD) fitting) require ad hoc determination of the cortical current distribution (l(2)-, l(1)-norm priors and point-sized dipolar, respectively). In this article, we perform a Bayesian analysis of the MEG inverse problem with l(p)-norm priors for the current sources. This way, we circumvent the arbitrary choice between l(1)- and l(2)-norm prior, which is instead rendered automatically based on the data. By obtaining numerical samples from the joint posterior probability distribution of the source current parameters and model hyperparameters (such as the l(p)-norm order p) using Markov chain Monte Carlo (MCMC) methods, we calculated the spatial inverse estimates as expectation values of the source current parameters integrated over the hyperparameters. Real MEG data and simulated (known) source currents with realistic MRI-based cortical geometry and 306-channel MEG sensor array were used. While the proposed model is sensitive to source space discretization size and computationally rather heavy, it is mathematically straightforward, thus allowing incorporation of, for instance, a priori functional magnetic resonance imaging (fMRI) information.

Improving permutation test power for group analysis of spatially filtered MEG data

Non-parametric statistical methods, such as permutation, are flexible tools to analyze data when the population distribution is not known. With minimal assumptions and better statistical power compared to the parametric tests, permutation tests have recently been applied to the spatially filtered magnetoencephalography (MEG) data for group analysis. To perform permutation tests on neuroimaging data, an empirical maximal null distribution has to be found, which is free from any activated voxels, to determine the threshold to classify the voxels as active at a given probability level. An iterative procedure is used to determine the distribution by computing the null distribution, which is recomputed when a possible activated voxel is found within the current distributions. Besides the high computational costs associated with this approach, there is no guarantee that all activated voxels are excluded when constructing the maximal null distribution, which may reduce the statistical power. In this study, we propose a novel way to construct the maximal null distribution from the data of the resting period. The approach is tested on the MEG data from a somatosensory experiment, and demonstrated that the approach could improve the power of the permutation test while reducing the computational cost at the same time.

Percept-related activity in the human somatosensory system: functional magnetic resonance imaging studies

In this paper, we review blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies addressing the neural correlates of touch, thermosensation, pain and the mechanisms of their cognitive modulation in healthy human subjects. There is evidence that fMRI signal changes can be elicited in the parietal cortex by stimulation of single mechanoceptive afferent fibers at suprathreshold intensities for conscious perception. Positive linear relationships between the amplitude or the spatial extents of BOLD fMRI signal changes, stimulus intensity and the perceived touch or pain intensity have been described in different brain areas. Some recent fMRI studies addressed the role of cortical areas in somatosensory perception by comparing the time course of cortical activity evoked by different kinds of stimuli with the temporal features of touch, heat or pain perception. Moreover, parametric single-trial functional MRI designs have been adopted in order to disentangle subprocesses within the nociceptive system. Available evidence suggest that studies that combine fMRI with psychophysical methods may provide a valuable approach for understanding complex perceptual mechanisms and top-down modulation of the somatosensory system by cognitive factors specifically related to selective attention and to anticipation. The brain networks underlying somatosensory perception are complex and highly distributed. A deeper understanding of perceptual-related brain mechanisms therefore requires new approaches suited to investigate the spatial and temporal dynamics of activation in different brain regions and their functional interaction.