Techniques for Detection and Localization of Weak Hippocampal and Medial Frontal Sources Using Beamformers in MEG

Preliminary Observations of Resting-State Magnetoencephalography in Nonmedicated Children with Obsessive-Compulsive Disorder

Background: Cortico-striato-thalamo-cortical (CSTC) network alterations are hypothesized to contribute to symptoms of obsessive-compulsive disorder (OCD). To date, very few studies have examined whether CSTC network alterations are present in children with OCD, who are medication naive. Medication-naive pediatric imaging samples may be optimal to study neural correlates of illness and identify brain-based markers, given the proximity to illness onset. Methods: Magnetoencephalography (MEG) data were analyzed at rest, in 18 medication-naive children with OCD (M = 12.1 years ±2.0 standard deviation [SD]; 10 M/8 F) and 13 typically developing children (M = 12.3 years ±2.2 SD; 6 M/7 F). Whole-brain MEG-derived resting-state functional connectivity (rs-fc), for alpha- and gamma-band frequencies were compared between OCD and typically developing (control) groups. Results: Increased MEG-derived rs-fc across alpha- and gamma-band frequencies was found in the OCD group compared to the control group. Increased MEG-derived rs-fc at alpha-band frequencies was evident across a number of regions within the CSTC circuitry and beyond, including the cerebellum and limbic regions. Increased MEG-derived rs-fc at gamma-band frequencies was restricted to the frontal and temporal cortices. Conclusions: This MEG study provides preliminary evidence of altered alpha and gamma networks, at rest, in medication-naive children with OCD. These results support prior findings pointing to the relevance of CSTC circuitry in pediatric OCD and further support accumulating evidence of altered connectivity between regions that extend beyond this network, including the cerebellum and limbic regions. Given the substantial portion of children and youth whose OCD symptoms do not respond to conventional treatments, our findings have implications for future treatment innovation research aiming to target and track whether brain patterns associated with having OCD may change with treatment and/or predict treatment response.

Anterior Cingulate Cortex Signals the Need to Control Intrusive Thoughts during Motivated Forgetting

How do people limit awareness of unwanted memories? When such memories intrude, a control process engages the right DLPFC (rDLPFC) to inhibit hippocampal activity and stop retrieval. It remains unknown how the need for control is detected, and whether control operates proactively to prevent unwelcome memories from being retrieved, or responds reactively, to counteract intrusions. We hypothesized that dorsal ACC (dACC) detects the emergence of an unwanted trace in awareness and transmits the need for inhibitory control to rDLPFC. During a memory suppression task, we measured in humans (both sexes) trial-by-trial variations in the theta power and N2 amplitude of dACC, two EEG markers that are thought to reflect the need for control. With simultaneous EEG-fMRI recordings, we tracked interactions among dACC, rDLPFC, and hippocampus during suppression. We found a clear role of dACC in detecting the need for memory control and upregulating prefrontal inhibition. Importantly, we identified distinct early (300-450 ms) and late (500-700 ms) dACC contributions, suggesting both proactive control before recollection and reactive control in response to intrusions. Stronger early activity was associated with reduced hippocampal activity and diminished BOLD signal in dACC and rDLPFC, suggesting that preempting retrieval reduced overall control demands. In the later window, dACC activity was larger, and effective connectivity analyses revealed robust communication from dACC to rDLPFC and from rDLPFC to hippocampus, which are tied to successful forgetting. Together, our findings support a model in which dACC detects the emergence of unwanted content, triggering top-down inhibitory control, and in which rDLPFC countermands intruding thoughts that penetrate awareness.SIGNIFICANCE STATEMENT Preventing unwanted memories from coming to mind is an adaptive ability of humans. This ability relies on inhibitory control processes in the prefrontal cortex to modulate hippocampal retrieval processes. How and when reminders to unwelcome memories come to trigger prefrontal control mechanisms remains unknown. Here we acquired neuroimaging data with both high spatial and temporal resolution as participants suppressed specific memories. We found that the anterior cingulate cortex detects the need for memory control, responding both proactively to early warning signals about unwelcome content and reactively to intrusive thoughts themselves. When unwanted traces emerge in awareness, anterior cingulate communicates with prefrontal cortex and triggers top-down inhibitory control over the hippocampus through specific neural oscillatory networks.

Testing covariance models for MEG source reconstruction of hippocampal activity

Beamforming is one of the most commonly used source reconstruction methods for magneto- and electroencephalography (M/EEG). One underlying assumption, however, is that distant sources are uncorrelated and here we tested whether this is an appropriate model for the human hippocampal data. We revised the Empirical Bayesian Beamfomer (EBB) to accommodate specific a-priori correlated source models. We showed in simulation that we could use model evidence (as approximated by Free Energy) to distinguish between different correlated and uncorrelated source scenarios. Using group MEG data in which the participants performed a hippocampal-dependent task, we explored the possibility that the hippocampus or the cortex or both were correlated in their activity across hemispheres. We found that incorporating a correlated hippocampal source model significantly improved model evidence. Our findings help to explain why, up until now, the majority of MEG-reported hippocampal activity (typically making use of beamformers) has been estimated as unilateral.

High-precision magnetoencephalography for reconstructing amygdalar and hippocampal oscillations during prediction of safety and threat

Learning to associate neutral with aversive events in rodents is thought to depend on hippocampal and amygdala oscillations. In humans, oscillations underlying aversive learning are not well characterised, largely due to the technical difficulty of recording from these two structures. Here, we used high‐precision magnetoencephalography (MEG) during human discriminant delay threat conditioning. We constructed generative anatomical models relating neural activity with recorded magnetic fields at the single‐participant level, including the neocortex with or without the possibility of sources originating in the hippocampal and amygdalar structures. Models including neural activity in amygdala and hippocampus explained MEG data during threat conditioning better than exclusively neocortical models. We found that in both amygdala and hippocampus, theta oscillations during anticipation of an aversive event had lower power compared to safety, both during retrieval and extinction of aversive memories. At the same time, theta synchronisation between hippocampus and amygdala increased over repeated retrieval of aversive predictions, but not during safety. Our results suggest that high‐precision MEG is sensitive to neural activity of the human amygdala and hippocampus during threat conditioning and shed light on the oscillation‐mediated mechanisms underpinning retrieval and extinction of fear memories in humans.

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.

Resting-state MEG measurement of functional activation as a biomarker for cognitive decline in MS

BACKGROUND

Neurophysiological measures of brain function, such as magnetoencephalography (MEG), are widely used in clinical neurology and have strong relations with cognitive impairment and dementia but are still underdeveloped in multiple sclerosis (MS).

OBJECTIVES

To demonstrate the value of clinically applicable MEG-measures in evaluating cognitive impairment in MS.

METHODS

In eyes-closed resting-state, MEG data of 83 MS patients and 34 healthy controls (HCs) peak frequencies and relative power of six canonical frequency bands for 78 cortical and 10 deep gray matter (DGM) areas were calculated. Linear regression models, correcting for age, gender, and education, assessed the relation between cognitive performance and MEG biomarkers.

RESULTS

Increased alpha1 and theta power was strongly associated with impaired cognition in patients, which differed between cognitively impaired (CI) patients and HCs in bilateral parietotemporal cortices. CI patients had a lower peak frequency than HCs. Oscillatory slowing was also widespread in the DGM, most pronounced in the thalamus.

CONCLUSION

There is a clinically relevant slowing of neuronal activity in MS patients in parietotemporal cortical areas and the thalamus, strongly related to cognitive impairment. These measures hold promise for the application of resting-state MEG as a biomarker for cognitive disturbances in MS in a clinical setting.

Low-Frequency Oscillatory Correlates of Auditory Predictive Processing in Cortical-Subcortical Networks: A MEG-Study

Emerging evidence supports the role of neural oscillations as a mechanism for predictive information processing across large-scale networks. However, the oscillatory signatures underlying auditory mismatch detection and information flow between brain regions remain unclear. To address this issue, we examined the contribution of oscillatory activity at theta/alpha-bands (4-8/8-13 Hz) and assessed directed connectivity in magnetoencephalographic data while 17 human participants were presented with sound sequences containing predictable repetitions and order manipulations that elicited prediction-error responses. We characterized the spectro-temporal properties of neural generators using a minimum-norm approach and assessed directed connectivity using Granger Causality analysis. Mismatching sequences elicited increased theta power and phase-locking in auditory, hippocampal and prefrontal cortices, suggesting that theta-band oscillations underlie prediction-error generation in cortical-subcortical networks. Furthermore, enhanced feedforward theta/alpha-band connectivity was observed in auditory-prefrontal networks during mismatching sequences, while increased feedback connectivity in the alpha-band was observed between hippocampus and auditory regions during predictable sounds. Our findings highlight the involvement of hippocampal theta/alpha-band oscillations towards auditory prediction-error generation and suggest a spectral dissociation between inter-areal feedforward vs. feedback signalling, thus providing novel insights into the oscillatory mechanisms underlying auditory predictive processing.

Whole-brain MEG connectivity-based analyses reveals critical hubs in childhood absence epilepsy

Absence seizures are thought to be linked to abnormal interplays between regions of a thalamocortical network. However, the complexity of this widespread network makes characterizing the functional interactions among various brain regions challenging. Using whole-brain functional connectivity and network analysis of magnetoencephalography (MEG) data, we explored pre-treatment brain hubs ("highly connected nodes") of patients aged 6 to 12 years with childhood absence epilepsy. We analyzed ictal MEG data of 74 seizures from 16 patients. We employed a time-domain beamformer technique to estimate MEG sources in broadband (1-40 Hz) where the greatest power changes between ictal and preictal periods were identified. A phase synchrony measure, phase locking value, and a graph theory metric, eigenvector centrality (EVC), were utilized to quantify voxel-level connectivity and network hubs of ictal > preictal periods, respectively. A volumetric atlas containing 116 regions of interests (ROIs) was utilized to summarize the network measures. ROIs with EVC (z-score) > 1.96 were reported as critical hubs. ROIs analysis revealed functional-anatomical hubs in a widespread network containing bilateral precuneus (right/left, z = 2.39, 2.18), left thalamus (z = 2.28), and three anterior cerebellar subunits of lobule "IV-V" (z = 3.9), vermis "IV-V" (z = 3.57), and lobule "III" (z = 2.03). Findings suggest that highly connected brain areas or hubs are present in focal cortical, subcortical, and cerebellar regions during absence seizures. Hubs in thalami, precuneus and cingulate cortex generally support a theory of rapidly engaging and bilaterally distributed networks of cortical and subcortical regions responsible for seizures generation, whereas hubs in anterior cerebellar regions may be linked to terminating motor automatisms frequently seen during typical absence seizures. Whole-brain network connectivity is a powerful analytic tool to reveal focal components of absence seizures in MEG. Our investigations can lead to a better understanding of the pathophysiology of CAE.

Spatio-temporal Reconstruction of Neural Sources Using Indirect Dominant Mode Rejection

Adaptive minimum variance based beamformers (MVB) have been successfully applied to magnetoencephalogram (MEG) and electroencephalogram (EEG) data to localize brain activities. However, the performance of these beamformers falls down in situations where correlated or interference sources exist. To overcome this problem, we propose indirect dominant mode rejection (iDMR) beamformer application in brain source localization. This method by modifying measurement covariance matrix makes MVB applicable in source localization in the presence of correlated and interference sources. Numerical results on both EEG and MEG data demonstrate that presented approach accurately reconstructs time courses of active sources and localizes those sources with high spatial resolution. In addition, the results of real AEF data show the good performance of iDMR in empirical situations. Hence, iDMR can be reliably used for brain source localization especially when there are correlated and interference sources.

Non-invasive Investigation of Human Hippocampal Rhythms Using Magnetoencephalography: A Review

Hippocampal rhythms are believed to support crucial cognitive processes including memory, navigation, and language. Due to the location of the hippocampus deep in the brain, studying hippocampal rhythms using non-invasive magnetoencephalography (MEG) recordings has generally been assumed to be methodologically challenging. However, with the advent of whole-head MEG systems in the 1990s and development of advanced source localization techniques, simulation and empirical studies have provided evidence that human hippocampal signals can be sensed by MEG and reliably reconstructed by source localization algorithms. This paper systematically reviews simulation studies and empirical evidence of the current capacities and limitations of MEG “deep source imaging” of the human hippocampus. Overall, these studies confirm that MEG provides a unique avenue to investigate human hippocampal rhythms in cognition, and can bridge the gap between animal studies and human hippocampal research, as well as elucidate the functional role and the behavioral correlates of human hippocampal oscillations.

Dynamic functional connectivity shapes individual differences in associative learning

Current neuroscientific research has shown that the brain reconfigures its functional interactions at multiple timescales. Here, we sought to link transient changes in functional brain networks to individual differences in behavioral and cognitive performance by using an active learning paradigm. Participants learned associations between pairs of unrelated visual stimuli by using feedback. Interindividual behavioral variability was quantified with a learning rate measure. By using a multivariate statistical framework (partial least squares), we identified patterns of network organization across multiple temporal scales (within a trial, millisecond; across a learning session, minute) and linked these to the rate of change in behavioral performance (fast and slow). Results indicated that posterior network connectivity was present early in the trial for fast, and later in the trial for slow performers. In contrast, connectivity in an associative memory network (frontal, striatal, and medial temporal regions) occurred later in the trial for fast, and earlier for slow performers. Time-dependent changes in the posterior network were correlated with visual/spatial scores obtained from independent neuropsychological assessments, with fast learners performing better on visual/spatial subtests. No relationship was found between functional connectivity dynamics in the memory network and visual/spatial test scores indicative of cognitive skill. By using a comprehensive set of measures (behavioral, cognitive, and neurophysiological), we report that individual variations in learning-related performance change are supported by differences in cognitive ability and time-sensitive connectivity in functional neural networks. Hum Brain Mapp 37:3911-3928, 2016. © 2016 Wiley Periodicals, Inc.

Changes in resting-state directed connectivity in cortico-subcortical networks correlate with cognitive function in Parkinson's disease

OBJECTIVE

The pathophysiological mechanisms underlying Parkinson's disease (PD)-related cognitive decline and conversion to PD dementia are poorly understood. In the healthy human brain, stable patterns of posterior-to-anterior cortical information flow have recently been demonstrated in the higher frequency bands using magnetoencephalography (MEG). In this study we estimated PD-related changes in information flow patterns, as well as the contribution of subcortical regions.

METHODS

Resting-state MEG recordings were acquired in moderately advanced PD patients (n=34; mean Hoehn and Yahr-stage 2.5) and healthy controls (n=12). MEG signals were projected to both cortical and subcortical brain regions, following which we estimated the balance between incoming and outgoing information flow per region.

RESULTS

In PD patients, compared to controls, preferential beta band information outflow was significantly higher for the basal ganglia and frontotemporal cortical regions, and significantly lower for parieto-occipital regions. In addition, in patients, low preferential information outflow from occipital regions correlated with poor global cognitive performance.

CONCLUSION

In the PD brain, a shift in balance towards more anterior-to-posterior beta band information flow takes place and is associated with poorer cognitive performance.

SIGNIFICANCE

Our results indicate that a reversal of the physiological posterior-to-anterior information flow may be an important mechanism in PD-related cognitive decline.

Mapping Critical Language Sites in Children Performing Verb Generation: Whole-Brain Connectivity and Graph Theoretical Analysis in MEG

A classic left frontal-temporal brain network is known to support language processes. However, the level of participation of constituent regions, and the contribution of extra-canonical areas, is not fully understood; this is particularly true in children, and in individuals who have experienced early neurological insult. In the present work, we propose whole-brain connectivity and graph-theoretical analysis of magnetoencephalography (MEG) source estimates to provide robust maps of the pediatric expressive language network. We examined neuromagnetic data from a group of typically-developing young children (n = 15, ages 4–6 years) and adolescents (n = 14, 16–18 years) completing an auditory verb generation task in MEG. All source analyses were carried out using a linearly-constrained minimum-variance (LCMV) beamformer. Conventional differential analyses revealed significant (p < 0.05, corrected) low-beta (13–23 Hz) event related desynchrony (ERD) focused in the left inferior frontal region (Broca’s area) in both groups, consistent with previous studies. Connectivity analyses were carried out in broadband (3–30 Hz) on time-course estimates obtained at the voxel level. Patterns of connectivity were characterized by phase locking value (PLV), and network hubs identified through eigenvector centrality (EVC). Hub analysis revealed the importance of left perisylvian sites, i.e., Broca’s and Wernicke’s areas, across groups. The hemispheric distribution of frontal and temporal lobe EVC values was asymmetrical in most subjects; left dominant EVC was observed in 20% of young children, and 71% of adolescents. Interestingly, the adolescent group demonstrated increased critical sites in the right cerebellum, left inferior frontal gyrus (IFG) and left putamen. Here, we show that whole brain connectivity and network analysis can be used to map critical language sites in typical development; these methods may be useful for defining the margins of eloquent tissue in neurosurgical candidates.

Using generative models to make probabilistic statements about hippocampal engagement in MEG

Magnetoencephalography (MEG) enables non-invasive real time characterization of brain activity. However, convincing demonstrations of signal contributions from deeper sources such as the hippocampus remain controversial and are made difficult by its depth, structural complexity and proximity to neocortex. Here, we demonstrate a method for quantifying hippocampal engagement probabilistically using simulated hippocampal activity and realistic anatomical and electromagnetic source modelling. We construct two generative models, one which supports neuronal current flow on the cortical surface, and one which supports neuronal current flow on both the cortical and hippocampal surface. Using Bayesian model comparison, we then infer which of the two models provides a more likely explanation of the dataset at hand. We also carry out a set of control experiments to rule out bias, including simulating medial temporal lobe sources to assess the risk of falsely positive results, and adding different types of displacements to the hippocampal portion of the mesh to test for anatomical specificity of the results. In addition, we test the robustness of this inference by adding co-registration error and sensor level noise. We find that the model comparison framework is sensitive to hippocampal activity when co-registration error is <3 mm and the sensor-level signal-to-noise ratio (SNR) is >-20 dB. These levels of co-registration error and SNR can now be achieved empirically using recently developed subject-specific head-casts.

Brain oscillations and connectivity in autism spectrum disorders (ASD): new approaches to methodology, measurement and modelling

Although atypical social behaviour remains a key characterisation of ASD, the presence of sensory and perceptual abnormalities has been given a more central role in recent classification changes. An understanding of the origins of such aberrations could thus prove a fruitful focus for ASD research. Early neurocognitive models of ASD suggested that the study of high frequency activity in the brain as a measure of cortical connectivity might provide the key to understanding the neural correlates of sensory and perceptual deviations in ASD. As our review shows, the findings from subsequent research have been inconsistent, with a lack of agreement about the nature of any high frequency disturbances in ASD brains. Based on the application of new techniques using more sophisticated measures of brain synchronisation, direction of information flow, and invoking the coupling between high and low frequency bands, we propose a framework which could reconcile apparently conflicting findings in this area and would be consistent both with emerging neurocognitive models of autism and with the heterogeneity of the condition.

Episodic sequence memory is supported by a theta-gamma phase code

The meaning we derive from our experiences is not a simple static extraction of the elements but is largely based on the order in which those elements occur. Models propose that sequence encoding is supported by interactions between high- and low-frequency oscillations, such that elements within an experience are represented by neural cell assemblies firing at higher frequencies (gamma) and sequential order is encoded by the specific timing of firing with respect to a lower frequency oscillation (theta). During episodic sequence memory formation in humans, we provide evidence that items in different sequence positions exhibit greater gamma power along distinct phases of a theta oscillation. Furthermore, this segregation is related to successful temporal order memory. Our results provide compelling evidence that memory for order, a core component of an episodic memory, capitalizes on the ubiquitous physiological mechanism of theta-gamma phase-amplitude coupling.

Post-Traumatic Stress Constrains the Dynamic Repertoire of Neural Activity

Post-traumatic stress disorder (PTSD) is an anxiety disorder arising from exposure to a traumatic event. Although primarily defined in terms of behavioral symptoms, the global neurophysiological effects of traumatic stress are increasingly recognized as a critical facet of the human PTSD phenotype. Here we use magnetoencephalographic recordings to investigate two aspects of information processing: inter-regional communication (measured by functional connectivity) and the dynamic range of neural activity (measured in terms of local signal variability). We find that both measures differentiate soldiers diagnosed with PTSD from soldiers without PTSD, from healthy civilians, and from civilians with mild traumatic brain injury, which is commonly comorbid with PTSD. Specifically, soldiers with PTSD display inter-regional hypersynchrony at high frequencies (80-150 Hz), as well as a concomitant decrease in signal variability. The two patterns are spatially correlated and most pronounced in a left temporal subnetwork, including the hippocampus and amygdala. We hypothesize that the observed hypersynchrony may effectively constrain the expression of local dynamics, resulting in less variable activity and a reduced dynamic repertoire. Thus, the re-experiencing phenomena and affective sequelae in combat-related PTSD may result from functional networks becoming "stuck" in configurations reflecting memories, emotions, and thoughts originating from the traumatizing experience.

SIGNIFICANCE STATEMENT

The present study investigates the effects of post-traumatic stress disorder (PTSD) in combat-exposed soldiers. We find that soldiers with PTSD exhibit hypersynchrony in a circuit of temporal lobe areas associated with learning and memory function. This rigid functional architecture is associated with a decrease in signal variability in the same areas, suggesting that the observed hypersynchrony may constrain the expression of local dynamics, resulting in a reduced dynamic range. Our findings suggest that the re-experiencing of traumatic events in PTSD may result from functional networks becoming locked in configurations that reflect memories, emotions, and thoughts associated with the traumatic experience.

Neuromagnetic evidence for hippocampal modulation of auditory processing

The hippocampus is well known to be involved in memory, as well as in perceptual processing. To date, the electrophysiological process by which unilateral hippocampal lesions, such as hippocampal sclerosis (HS), modulate the auditory processing remains unknown. Auditory-evoked magnetic fields (AEFs) are valuable for evaluating auditory functions, because M100, a major component of AEFs, originates from auditory areas. Therefore, AEFs of mesial temporal lobe epilepsy (mTLE, n=17) with unilateral HS were compared with those of healthy (HC, n=17) and disease controls (n=9), thereby determining whether AEFs were indicative of hippocampal influences on the auditory processing. Monaural tone-burst stimuli were presented for each side, followed by analysis of M100 and a previously less characterized exogenous component (M400: 300-500ms). The frequency of acceptable M100 dipoles was significantly decreased in the HS side. Beam-forming-based source localization analysis also showed decreased activity of the auditory area, which corresponded to the inadequately estimated dipoles. M400 was found to be related to the medial temporal structure on the HS side. Volumetric analysis was also performed, focusing on the auditory-related areas (planum temporale, Heschl's gyrus, and superior temporal gyrus), as well as the hippocampus. M100 amplitudes positively correlated with hippocampal and planum temporale volumes in the HC group, whereas they negatively correlated with Heschl's gyrus volume in the mTLE group. Interestingly, significantly enhanced M400 component was observed in the HS side of the mTLE patients. In addition, the M400 component positively correlated with Heschl's gyrus volume and tended to positively correlate with disease duration. M400 was markedly diminished after hippocampal resection. Although volumetric analysis showed decreased hippocampal volume in the HS side, the planum temporale and Heschl's gyrus, the two major sources of M100, were preserved. These results suggested that HS significantly influenced AEFs. Therefore, we concluded that the hippocampus modulates auditory processing differently under normal conditions and in HS.

Responses of monkey prefrontal neurons during the execution of transverse patterning

Recent functional imaging studies have suggested that the prefrontal cortex (PF) is engaged in the performance of transverse patterning (TP), which consists of 3 conflicting discriminations (A+/B-, B+/C-, C+/A-). However, the roles of PF in TP are still unclear. To address this issue, we examined the neuronal responses in 3 regions [the principal sulcus (PS), dorsal convexity (DC), and medial prefrontal cortex (MPF)] of the macaque PF during the performance of an oculomotor version of TP. A delayed matching-to-sample (DMS) task was used as a control task. The TP task-responsive neurons were most abundant in MPF. We analyzed the dependency of each neuronal response on the task type (TP or DMS), target shape (A, B, or C), and target location (left or right). Immediately after the choice cue presentation, many MPF neurons showed task dependency. Interestingly, some of them already exhibited differential activity between the 2 tasks before the choice cue presentation. Immediately before the saccade, the number of target location-dependent neurons increased in MPF and PS. Among them, many MPF neurons were also influenced by the task type, whereas PS neurons tended to show location dependency without task dependency. These results suggest that MPF and PS are involved in the execution of TP: MPF appears to be more important in the target selection based on the TP rule, whereas PS is apparently more related to the response preparation. In addition, some neurons showed a postsaccadic response, which may be related to the feedback mechanism.

The use of magnetoencephalography in the study of psychopharmacology (pharmaco-MEG)

Magnetoencephalography (MEG) is a neuroimaging technique that allows direct measurement of the magnetic fields generated by synchronised ionic neural currents in the brain with moderately good spatial resolution and high temporal resolution. Because chemical neuromodulation can cause changes in neuronal processing on the millisecond time-scale, the combination of MEG with pharmacological interventions (pharmaco-MEG) is a powerful tool for measuring the effects of experimental modulations of neurotransmission in the living human brain. Importantly, pharmaco-MEG can be used in both healthy humans to understand normal brain function and in patients to understand brain pathologies and drug-treatment effects. In this paper, the physiological and technical basis of pharmaco-MEG is introduced and contrasted with other pharmacological neuroimaging techniques. Ongoing developments in MEG analysis techniques such as source-localisation, functional and effective connectivity analyses, which have allowed for more powerful inferences to be made with recent pharmaco-MEG data, are described. Studies which have utilised pharmaco-MEG across a range of neurotransmitter systems (GABA, glutamate, acetylcholine, dopamine and serotonin) are reviewed.

Neural mechanisms of inhibitory control continue to mature in adolescence

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Brain mechanisms involved in inhibitory control were examined in adults and teens.

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No differences were seen on reaction time and accuracy for the Go/No-go tasks.

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Adults showed the expected activation in right inferior frontal gyrus.

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Teens showed a delayed and left dominant activation of inferior frontal gyri.

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Teens also recruited temporal and parietal regions to support inhibitory processing.

Inhibition is a fundamental executive function necessary for self-management of behaviour. The ability to withhold prepotent responses shows protracted development, extending through childhood and into adulthood. Using magnetoencephalography (MEG) with co-registered MRI, the spatiotemporal neural processes involved in inhibitory control were examined in 15 adolescents and 15 adults during a Go/No-go task. Two tasks were run that contained inverse ratios of Go to No-go trials for the experimental (2:1) and control conditions (1:2). Using vector beamforming, images of neural activation between No-go and Go trials were compared for both age-groups and revealed recruitment of the right inferior frontal gyrus in adults (BA 45; 200–250 ms), but delayed recruitment of the left inferior frontal gyri in adolescents (BA 45; 250–300 ms). Left anticipatory-related activity near the hand motor region (BA 6) was present in both adolescents and adults, but for a longer duration in adults. Adolescents additionally recruited the right middle and superior temporal gyri (BA21, BA22), while adults engaged the right temporal gyrus (BA41) but for a much briefer duration. These findings of delayed recruitment of canonical inhibitory control areas with supplementary and prolonged involvement of temporal areas in adolescents compared to adults indicate an immature inhibitory network even in adolescence.

Reduced beta band connectivity during number estimation in autism

Recent evidence suggests that disruption of integrative processes in sensation and perception may play a critical role in cognitive and behavioural atypicalities characteristic of ASD. In line with this, ASD is associated with altered structural and functional brain connectivity and atypical patterns of inter-regional communication which have been proposed to contribute to cognitive difficulties prevalent in this group. The present MEG study used atlas-guided source space analysis of inter-regional phase synchronization in ASD participants, as well as matched typically developing controls, during a dot number estimation task. This task included stimuli with globally integrated forms (animal shapes) as well as randomly-shaped stimuli which lacked a coherent global pattern. Early task-dependent increases in inter-regional phase synchrony in theta, alpha and beta frequency bands were observed. Reduced long-range beta-band phase synchronization was found in participants with ASD at 70-145 ms during presentation of globally coherent dot patterns. This early reduction in task-dependent inter-regional connectivity encompassed numerous areas including occipital, parietal, temporal, and frontal lobe regions. These results provide the first evidence for inter-regional phase synchronization during numerosity estimation, as well as its alteration in ASD, and suggest that problems with communication among brain areas may contribute to difficulties with integrative processes relevant to extraction of meaningful 'Gestalt' features in this population.

Atypical resting synchrony in autism spectrum disorder

Autism spectrum disorder (ASD) is increasingly understood to be associated with aberrant functional brain connectivity. Few studies, however, have described such atypical neural synchrony among specific brain regions. Here, we used magnetoencephalography (MEG) to characterize alterations in functional connectivity in adolescents with ASD through source space analysis of phase synchrony. Resting-state MEG data were collected from 16 adolescents with ASD and 15 age- and sex-matched typically developing (TD) adolescents. Atlas-guided reconstruction of neural activity at various cortical and subcortical regions was performed and inter-regional phase synchrony was calculated in physiologically relevant frequency bands. Using a multilevel approach, we characterized atypical resting-state synchrony within specific anatomically defined networks as well as altered network topologies at both regional and whole-network scales. Adolescents with ASD demonstrated frequency-dependent alterations in inter-regional functional connectivity. Hyperconnectivity was observed among the frontal, temporal, and subcortical regions in beta and gamma frequency ranges. In contrast, parietal and occipital regions were hypoconnected to widespread brain regions in theta and alpha bands in ASD. Furthermore, we isolated a hyperconnected network in the gamma band in adolescents with ASD which encompassed orbitofrontal, subcortical, and temporal regions implicated in social cognition. Results from graph analyses confirmed that frequency-dependent alterations of network topologies exist at both global and local levels. We present the first source-space investigation of oscillatory phase synchrony in resting-state MEG in ASD. This work provides evidence of atypical connectivity at physiologically relevant time scales and indicates that alterations of functional connectivity in adolescents with ASD are frequency dependent and region dependent.

Neuromagnetic vistas into typical and atypical development of frontal lobe functions

The frontal lobes are involved in many higher-order cognitive functions such as social cognition executive functions and language and speech. These functions are complex and follow a prolonged developmental course from childhood through to early adulthood. Magnetoencephalography (MEG) is ideal for the study of development of these functions, due to its combination of temporal and spatial resolution which allows the determination of age-related changes in both neural timing and location. There are several challenges for MEG developmental studies: to design tasks appropriate to capture the neurodevelopmental trajectory of these cognitive functions, and to develop appropriate analysis strategies to capture various aspects of neuromagnetic frontal lobe activity. Here, we review our MEG research on social and executive functions, and speech in typically developing children and in two clinical groups – children with autism spectrum disorder and children born very preterm. The studies include facial emotional processing, inhibition, visual short-term memory, speech production, and resting-state networks. We present data from event-related analyses as well as on oscillations and connectivity analyses and review their contributions to understanding frontal lobe cognitive development. We also discuss the challenges of testing young children in the MEG and the development of age-appropriate technologies and paradigms.

Medial prefrontal theta phase coupling during spatial memory retrieval

Memory retrieval is believed to involve a disparate network of areas, including medial prefrontal and medial temporal cortices, but the mechanisms underlying their coordination remain elusive. One suggestion is that oscillatory coherence mediates inter-regional communication, implicating theta phase and theta-gamma phase-amplitude coupling in mnemonic function across species. To examine this hypothesis, we used non-invasive whole-head magnetoencephalography (MEG) as participants retrieved the location of objects encountered within a virtual environment. We demonstrate that, when participants are cued with the image of an object whose location they must subsequently navigate to, there is a significant increase in 4–8 Hz theta power in medial prefrontal cortex (mPFC), and the phase of this oscillation is coupled both with ongoing theta phase in the medial temporal lobe (MTL) and perceptually induced 65–85 Hz gamma amplitude in medial parietal cortex. These results suggest that theta phase coupling between mPFC and MTL and theta-gamma phase-amplitude coupling between mPFC and neocortical regions may play a role in human spatial memory retrieval. © 2014 The Authors. Hippocampus Published by Wiley Periodicals, Inc.

Is inhibitory control a 'no-go' in adolescents with autism spectrum disorder?

Background

Autism spectrum disorder (ASD) refers to a range of neurodevelopmental conditions characterized by social communication deficits, repetitive behaviours, and restrictive interests. Impaired inhibition has been suggested to exacerbate the core symptoms of ASD. This is particularly critical during adolescence when social skills are maturing to adult levels. Using magnetoencephalography (MEG), we identified the location and timing pattern of neural activity associated with inhibition in adolescents with autism, compared to typically developing adolescents.

Methods

The MEG data from 15 adolescents with ASD and 15 age-matched controls (13 to 17 years) were collected during a go/no-go task with inverse ratios of go/no-go trials in two conditions: an inhibition condition (1:2) and a baseline condition (2:1). No-go trials from the two conditions were analyzed using beamformer source localizations from 200 ms to 400 ms post-stimulus onset. Significant activations were determined using permutation testing.

Results

Adolescents with ASD recruited first the right middle frontal gyrus (200 to 250 ms) followed by the left postcentral gyrus (250 to 300 ms) and finally the left middle frontal and right medial frontal gyri (300 to 400 ms). Typically developing adolescents recruited first the left middle frontal gyrus (200 to 250 ms), followed by the left superior and inferior frontal gyri (250 to 300 ms), then the right middle temporal gyrus (300 to 350 ms), and finally the superior and precentral gyri and right inferior lobule (300 to 400 ms).

Conclusions

Adolescents with ASD showed recruitment limited largely to the frontal cortex unlike typically developing adolescents who recruited parietal and temporal regions as well. These findings support the presence of an atypical, restricted inhibitory network in adolescents with ASD compared to controls.

Hippocampal lateralization and memory in children and adults

The neural organization of cognitive processes, particularly hemispheric lateralization, changes throughout childhood and adolescence. Differences in the neural basis of relational memory between children and adults are not well characterized. In this study we used magnetoencephalography to observe the lateralization differences of hippocampal activation in children and adults during performance of a relational memory task, transverse patterning (TP). The TP task was paired with an elemental control task, which does not depend upon the hippocampus. We contrasted two hypotheses; the compensation hypothesis would suggest that more bilateral activation in children would lead to better TP performance, whereas the maturation hypothesis would predict that a more adult-like right-lateralized pattern of hippocampal activation would lead to better performance. Mean-centered partial least squares analysis was used to determine unique patterns of brain activation specific to each task per group, while diminishing activation that is consistent across tasks. Our findings support the maturation hypothesis that a more adult-like pattern of increased right hippocampal lateralization in children leads to superior performance on the TP task. We also found dynamic changes of lateralization throughout the time course for all three groups, suggesting that caution is needed when interpreting conclusions about brain lateralization.

Theta oscillations orchestrate medial temporal lobe and neocortex in remembering autobiographical memories

Remembering autobiographical events can be associated with detailed visual imagery. The medial temporal lobe (MTL), precuneus and prefrontal cortex are held to jointly enable such vivid retrieval, but how these regions are orchestrated remains unclear. An influential prediction from animal physiology is that neural oscillations in theta frequency may be important. In this experiment, participants prospectively collected audio recordings describing personal autobiographical episodes or semantic knowledge over 2 to 7 months. These were replayed as memory retrieval cues while recording brain activity with magnetoencephalography (MEG). We identified a peak of theta power within a left MTL region of interest during both autobiographical and General Semantic retrieval. This MTL region was selectively phase-synchronized with theta oscillations in precuneus and medial prefrontal cortex, and this synchrony was higher during autobiographical as compared to General Semantic knowledge retrieval. Higher synchrony also predicted more detailed visual imagery during retrieval. Thus, theta phase-synchrony orchestrates in humans the MTL with a distributed neocortical memory network when vividly remembering autobiographical experiences.

Altered resting state brain dynamics in temporal lobe epilepsy can be observed in spectral power, functional connectivity and graph theory metrics

Despite a wealth of EEG epilepsy data that accumulated for over half a century, our ability to understand brain dynamics associated with epilepsy remains limited. Using EEG data from 15 controls and 9 left temporal lobe epilepsy (LTLE) patients, in this study we characterize how the dynamics of the healthy brain differ from the "dynamically balanced" state of the brain of epilepsy patients treated with anti-epileptic drugs in the context of resting state. We show that such differences can be observed in band power, synchronization and network measures, as well as deviations from the small world network (SWN) architecture of the healthy brain. The θ (4-7 Hz) and high α (10-13 Hz) bands showed the biggest deviations from healthy controls across various measures. In particular, patients demonstrated significantly higher power and synchronization than controls in the θ band, but lower synchronization and power in the high α band. Furthermore, differences between controls and patients in graph theory metrics revealed deviations from a SWN architecture. In the θ band epilepsy patients showed deviations toward an orderly network, while in the high α band they deviated toward a random network. These findings show that, despite the focal nature of LTLE, the epileptic brain differs in its global network characteristics from the healthy brain. To our knowledge, this is the only study to encompass power, connectivity and graph theory metrics to investigate the reorganization of resting state functional networks in LTLE patients.

Assessment of subcortical source localization using deep brain activity imaging model with minimum norm operators: a MEG study

Subcortical structures are involved in many healthy and pathological brain processes. It is crucial for many studies to use magnetoencephalography (MEG) to assess the ability to detect subcortical generators. This study aims to assess the source localization accuracy and to compare the characteristics of three inverse operators in the specific case of subcortical generators. MEG has a low sensitivity to subcortical sources mainly because of their distance from sensors and their complex cyto-architecture. However, we show that using a realistic anatomical and electrophysiological model of deep brain activity (DBA), the sources make measurable contributions to MEG sensors signals. Furthermore, we study the point-spread and cross-talk functions of the wMNE, sLORETA and dSPM inverse operators to characterize distortions in cortical and subcortical regions and to study how noise-normalization methods can improve or bias accuracy. We then run Monte Carlo simulations with neocortical and subcortical activations. In the case of single hippocampus patch activations, the results indicate that MEG can indeed localize the generators in the head and the body of the hippocampus with good accuracy. We then tackle the question of simultaneous cortical and subcortical activations. wMNE can detect hippocampal activations that are embedded in cortical activations that have less than double their amplitude, but it does not completely correct the bias to more superficial sources. dSPM and sLORETA can still detect hippocampal activity above this threshold, but such detection might include the creation of ghost deeper sources. Finally, using the DBA model, we showed that the detection of weak thalamic modulations of ongoing brain activity is possible.

MEG measures of covert orienting and gaze processing in children

We investigated developmental differences in the cortical attention processing network using magnetoencephalography (MEG) and a spatial cueing task in 7-8 and 12-13 year old children. The cueing paradigm consisted of a centrally presented face with left or right averted eye-gaze in the gaze cue condition, and a central face with straight gaze presented with a cue stimulus to the left or right of the face in the peripheral cue condition. Cue congruency was 50 %. MEG was recorded during the two conditions and event-related beamforming was used to determine the timing and location of the brain activity related to target detection with the two types of cueing. The MEG data showed no age differences in the eye-gaze condition, but a developmental difference characterised by slower and more diffuse activations for peripheral cues in the younger versus the older age group. In the 7-8 year olds activation peaked around 300 ms, and was localised to left inferior frontal gyrus as well as posterior areas related to visuo-spatial processing. The 12-13 year olds showed a temporoparietal pattern of activation characteristic of spatial reorientation which resembled that seen for adult participants using the same paradigm (Nagata et al. 2012). The activation peaked around 200 ms and was localised to the left superior frontal gyrus, middle frontal gyrus but bilaterally near the temporoparietal junction. The data indicate maturational changes in brain activity for peripheral cueing.

Spatio-temporal localisation of attentional orienting to gaze and peripheral cues

Another person's eye gaze often triggers our attention such that we follow their direction of gaze. We investigated how the neural mechanisms for processing eye-gaze and spatial attention interact using magnetoencephalography (MEG) in young adults. In a cueing paradigm, a face was presented centrally with left or right averted eye-gaze serving as the directional cue in the eye-gaze condition. In the peripheral cue condition, the face with a straight gaze was presented with a cue stimulus appearing on the left or right of the face. Cue validity was 50%. MEG was recorded during the two conditions and event-related beamforming was used to determine the timing and location of the brain activity related to the two types of cueing. The MEG data indicated that generally the network of activation in response to our two cue types was similar. In contrast, MEG responses to the targets demonstrated one main peak at 286-306 ms for the eye-gaze cue condition while two peaks were found at 238-258 ms and 286-306 ms for the peripheral cue condition. Activation was also consistently larger for the invalid than valid trials. Source images for the invalid minus valid contrasts for the 238-258 ms window showed significant activation only in the peripheral cueing condition, in the left temporoparietal junction and left inferior frontal gyrus. In the 286-306 ms window, both conditions showed left medial frontal activations. Thus, peripheral cues showed more rapid neural processing than the eye-gaze cues, with the second component being common to both, reflecting in part common processing. We suggest that attentional processing was maximal in the left hemisphere, as the right hemisphere was likely engaged in processing the face information.