Detection and localization of hippocampal activity using beamformers with MEG: a detailed investigation using simulations and empirical data

Cortical and Subcortical Changes in MEG Activity Reflect Parkinson's Progression over a Period of 7 Years

In this study of early functional changes in Parkinson's disease (PD), we aimed to provide a comprehensive assessment of the development of changes in both cortical and subcortical neurophysiological brain activity, including their association with clinical measures of disease severity. Repeated resting-state MEG recordings and clinical assessments were obtained in the context of a unique longitudinal cohort study over a seven-year period using a multiple longitudinal design. We used linear mixed-models to analyze the relationship between neurophysiological (spectral power and functional connectivity) and clinical data. At baseline, early-stage (drug-naïve) PD patients demonstrated spectral slowing compared to healthy controls in both subcortical and cortical brain regions, most outspoken in the latter. Over time, spectral slowing progressed in strong association with clinical measures of disease progression (cognitive and motor). Global functional connectivity was not different between groups at baseline and hardly changed over time. Therefore, investigation of associations with clinical measures of disease progression were not deemed useful. An analysis of individual connections demonstrated differences between groups at baseline (higher frontal theta, lower parieto-occipital alpha2 band functional connectivity) and over time in PD patients (increase in frontal delta and theta band functional connectivity). Our results suggest that spectral measures are promising candidates in the search for non-invasive markers of both early-stage PD and of the ongoing disease process.

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.

Memory retrieval brain-behavior disconnection in mild traumatic brain injury: A magnetoencephalography and diffusion tensor imaging study

Mild traumatic brain (mTBI) injury is often associated with long-term cognitive and behavioral complications, including an increased risk of memory impairment. Current research challenges include a lack of cross-modal convergence regarding the underlying neural-behavioral mechanisms of mTBI, which hinders therapeutics and outcome management for this frequently under-treated and vulnerable population. We used multi-modality imaging methods including magnetoencephalography (MEG) and diffusion tensor imaging (DTI) to investigate brain-behavior impairment in mTBI related to working memory. A total of 41 participants were recruited, including 23 patients with a first-time mTBI imaged within 3 months of injury (all male, age = 29.9, SD = 6.9), and 18 control participants (all male, age = 27.3, SD = 5.3). Whole-brain statistics revealed spatially concomitant functional-structural disruptions in brain-behavior interactions in working memory in the mTBI group compared with the control group. These disruptions are located in the hippocampal-prefrontal region and, additionally, in the amygdala (measured by MEG neural activation and DTI measures of fractional anisotropy in relation to working memory performance; p < .05, two-way ANCOVA, nonparametric permutations, corrected). Impaired brain-behavior connections found in the hippocampal-prefrontal and amygdala circuits indicate brain dysregulation of memory, which may leave mTBI patients vulnerable to increased environmental demands exerting memory resources, leading to related cognitive and emotional psychopathologies. The findings yield clinical implications and highlight a need for early rehabilitation after mTBI, including attention- and sensory-based behavioral exercises.

Simulation Study of Different OPM-MEG Measurement Components

Magnetoencephalography (MEG) is a neuroimaging technique that measures the magnetic fields of the brain outside of the head. In the past, the most suitable magnetometer for MEG was the superconducting quantum interference device (SQUID), but in recent years, a new type has also been used, the optically pumped magnetometer (OPM). OPMs can be configured to measure multiple directions of magnetic field simultaneously. This work explored whether combining multiple directions of the magnetic field lowers the source localization error of brain sources under various conditions of noise. We simulated dipolar-like sources for multiple configurations of both SQUID- and OPM-MEG systems. To test the performance of a given layout, we calculated the average signal-to-noise ratio and the root mean square of the simulated magnetic field; furthermore, we evaluated the performance of the dipole fit. The results showed that the field direction normal to the scalp yields a higher signal-to-noise ratio and that ambient noise has a much lower impact on its localization error; therefore, this is the optimal choice for source localization when only one direction of magnetic field can be measured. For a low number of OPMs, combining multiple field directions greatly improves the source localization results. Lastly, we showed that MEG sensors that can be placed closer to the brain are more suitable for localizing deeper sources.

Sensitive and reproducible MEG resting-state metrics of functional connectivity in Alzheimer's disease

Background

Analysis of functional brain networks in Alzheimer’s disease (AD) has been hampered by a lack of reproducible, yet valid metrics of functional connectivity (FC). This study aimed to assess both the sensitivity and reproducibility of the corrected amplitude envelope correlation (AEC-c) and phase lag index (PLI), two metrics of FC that are insensitive to the effects of volume conduction and field spread, in two separate cohorts of patients with dementia due to AD versus healthy elderly controls.

Methods

Subjects with a clinical diagnosis of AD dementia with biomarker proof, and a control group of subjective cognitive decline (SCD), underwent two 5-min resting-state MEG recordings. Data consisted of a test (AD = 28; SCD = 29) and validation (AD = 29; SCD = 27) cohort. Time-series were estimated for 90 regions of interest (ROIs) in the automated anatomical labelling (AAL) atlas. For each of five canonical frequency bands, the AEC-c and PLI were calculated between all 90 ROIs, and connections were averaged per ROI. General linear models were constructed to compare the global FC differences between the groups, assess the reproducibility, and evaluate the effects of age and relative power. Reproducibility of the regional FC differences was assessed using the Mann-Whitney U tests, with correction for multiple testing using the false discovery rate (FDR).

Results

The AEC-c showed significantly and reproducibly lower global FC for the AD group compared to SCD, in the alpha (8–13 Hz) and beta (13–30 Hz) bands, while the PLI revealed reproducibly lower FC for the AD group in the delta (0.5–4 Hz) band and higher FC for the theta (4–8 Hz) band. Regionally, the beta band AEC-c showed reproducibility for almost all ROIs (except for 13 ROIs in the frontal and temporal lobes). For the other bands, the AEC-c and PLI did not show regional reproducibility after FDR correction. The theta band PLI was susceptible to the effect of relative power.

Conclusion

For MEG, the AEC-c is a sensitive and reproducible metric, able to distinguish FC differences between patients with AD dementia and cognitively healthy controls. These two measures likely reflect different aspects of neural activity and show differential sensitivity to changes in neural dynamics.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-00970-4.

A unified view on beamformers for M/EEG source reconstruction

Beamforming is a popular method for functional source reconstruction using magnetoencephalography (MEG) and electroencephalography (EEG) data. Beamformers, which were first proposed for MEG more than two decades ago, have since been applied in hundreds of studies, demonstrating that they are a versatile and robust tool for neuroscience. However, certain characteristics of beamformers remain somewhat elusive and there currently does not exist a unified documentation of the mathematical underpinnings and computational subtleties of beamformers as implemented in the most widely used academic open source software packages for MEG analysis (Brainstorm, FieldTrip, MNE, and SPM). Here, we provide such documentation that aims at providing the mathematical background of beamforming and unifying the terminology. Beamformer implementations are compared across toolboxes and pitfalls of beamforming analyses are discussed. Specifically, we provide details on handling rank deficient covariance matrices, prewhitening, the rank reduction of forward fields, and on the combination of heterogeneous sensor types, such as magnetometers and gradiometers. The overall aim of this paper is to contribute to contemporary efforts towards higher levels of computational transparency in functional neuroimaging.

Stress Impairs Intentional Memory Control through Altered Theta Oscillations in Lateral Parietal Cortex

Accumulating evidence suggests that forgetting is not necessarily a passive process but that we can, to some extent, actively control what we remember and what we forget. Although this intentional control of memory has potentially far-reaching implications, the factors that influence our capacity to intentionally control our memory are largely unknown. Here, we tested whether acute stress may disrupt the intentional control of memory and, if so, through which neural mechanism. We exposed healthy men and women to a stress (n = 27) or control (n = 26) procedure before they aimed repeatedly to retrieve some previously learned cue-target pairs and to actively suppress others. While control participants showed reduced memory for suppressed compared with baseline pairs in a subsequent memory test, this suppression-induced forgetting was completely abolished after stress. Using magnetoencephalography (MEG), we show that the reduced ability to suppress memories after stress is associated with altered theta activity in the inferior temporal cortex when the control process (retrieval or suppression) is triggered and in the lateral parietal cortex when control is exerted, with the latter being directly correlated with the stress hormone cortisol. Moreover, the suppression-induced forgetting was linked to altered connectivity between the hippocampus and right dorsolateral prefrontal cortex (PFC), which in turn was negatively correlated to stress-induced cortisol increases. These findings provide novel insights into conditions under which our capacity to actively control our memory breaks down and may have considerable implications for stress-related psychopathologies, such as posttraumatic stress disorder (PTSD), that are characterized by unwanted memories of distressing events.SIGNIFICANCE STATEMENT It is typically assumed that forgetting is a passive process that can hardly be controlled. There is, however, evidence that we may actively control, to some extent, what we remember and what we forget. This intentional memory control has considerable implications for mental disorders in which patients suffer from unwanted (e.g., traumatic) memories. Here, we demonstrate that the capacity to intentionally control our memory breaks down after stress. Using magnetoencephalography (MEG), we show that this stress-induced memory control deficit is linked to altered activity in the lateral parietal cortex and the connectivity between the hippocampus and right prefrontal cortex (PFC). These findings provide novel insights into conditions under which memory control fails and are highly relevant in the context of stress-related psychopathologies.

Removal of Interictal MEG-Derived Network Hubs Is Associated With Postoperative Seizure Freedom

Objective: To investigate whether MEG network connectivity was associated with epilepsy duration, to identify functional brain network hubs in patients with refractory focal epilepsy, and assess if their surgical removal was associated with post-operative seizure freedom. Methods: We studied 31 patients with drug refractory focal epilepsy who underwent resting state magnetoencephalography (MEG), and structural magnetic resonance imaging (MRI) as part of pre-surgical evaluation. Using the structural MRI, we generated 114 cortical regions of interest, performed surface reconstruction and MEG source localization. Representative source localized signals for each region were correlated with each other to generate a functional brain network. We repeated this procedure across three randomly chosen one-minute epochs. Network hubs were defined as those with the highest intra-hemispheric mean correlations. Post-operative MRI identified regions that were surgically removed. Results: Greater mean MEG network connectivity was associated with a longer duration of epilepsy. Patients who were seizure free after surgery had more hubs surgically removed than patients who were not seizure free (AUC = 0.76, p = 0.01) consistently across three randomly chosen time segments. Conclusion: Our results support a growing literature implicating network hub involvement in focal epilepsy, the removal of which by surgery is associated with greater chance of post-operative seizure freedom.

Localization of deep brain activity with scalp and subdural EEG

To what extent electrocorticography (ECoG) and electroencephalography (scalp EEG) differ in their capability to locate sources of deep brain activity is far from evident. Compared to EEG, the spatial resolution and signal-to-noise ratio of ECoG is superior but its spatial coverage is more restricted, as is arguably the volume of tissue activity effectively measured from. Moreover, scalp EEG studies are providing evidence of locating activity from deep sources such as the hippocampus using high-density setups during quiet wakefulness. To address this question, we recorded a multimodal dataset from 4 patients with refractory epilepsy during quiet wakefulness. This data comprises simultaneous scalp, subdural and depth EEG electrode recordings. The latter was located in the hippocampus or insula and provided us with our "ground truth" for source localization of deep activity. We applied independent component analysis (ICA) for the purpose of separating the independent sources in theta, alpha and beta frequency band activity. In all patients subdural- and scalp EEG components were observed which had a significant zero-lag correlation with one or more contacts of the depth electrodes. Subsequent dipole modeling of the correlating components revealed dipole locations that were significantly closer to the depth electrodes compared to the dipole location of non-correlating components. These findings support the idea that components found in both recording modalities originate from neural activity in close proximity to the depth electrodes. Sources localized with subdural electrodes were ~70% closer to the depth electrode than sources localized with EEG with an absolute improvement of around ~2cm. In our opinion, this is not a considerable improvement in source localization accuracy given that, for clinical purposes, ECoG electrodes were implanted in close proximity to the depth electrodes. Furthermore, the ECoG grid attenuates the scalp EEG, due to the electrically isolating silastic sheets in which the ECoG electrodes are embedded. Our results on dipole modeling show that the deep source localization accuracy of scalp EEG is comparable to that of ECoG. SIGNIFICANCE STATEMENT: Deep and subcortical regions play an important role in brain function. However, as joint recordings at multiple spatial scales to study brain function in humans are still scarce, it is still unresolved to what extent ECoG and EEG differ in their capability to locate sources of deep brain activity. To the best of our knowledge, this is the first study presenting a dataset of simultaneously recorded EEG, ECoG and depth electrodes in the hippocampus or insula, with a focus on non-epileptiform activity (quiet wakefulness). Furthermore, we are the first study to provide experimental findings on the comparison of source localization of deep cortical structures between invasive and non-invasive brain activity measured from the cortical surface.

Abnormal alpha band power in the dynamic pain connectome is a marker of chronic pain with a neuropathic component

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High theta and low gamma activity in the dynamic pain connectome is linked to chronic pain.

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High alpha-band activity is present when neuropathic pain is likely.

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Spectral frequency band strength distinguish neuropathic from non-neuropathic pain.

We previously identified alpha frequency slowing and beta attenuation in the dynamic pain connectome related to pain severity and interference in patients with multiple sclerosis-related neuropathic pain (NP). Here, we determined whether these abnormalities, are markers of aberrant temporal dynamics in non-neuropathic inflammatory pain (non-NP) or when NP is also suspected. We measured resting-state magnetoencephalography (MEG) spectral density in 45 people (17 females, 28 males) with chronic back pain due to ankylosing spondylitis (AS) and 38 age/sex matched healthy controls. We used painDETECT scores to divide the chronic pain group into those with only non-NP (NNP) and those who likely also had a component of NP in addition to their inflammatory pain. We also assessed pain severity, pain interference, and disease activity with the Brief Pain Inventory and Bath AS Disease Activity Index (BASDAI). We examined spectral power in the dynamic pain connectome, including nodes of the ascending nociceptive pathway (ANP), default mode (DMN), and salience networks (SN). Compared to the healthy controls, the AS patients exhibited increased theta power in the DMN and decreased low-gamma power in the DMN and ANP, but did not exhibit beta-band attenuation or peak-alpha slowing. The NNP patients were not different from HCs. Compared to both healthy controls and NNP, NP patients had increased alpha power in the ANP. Increased alpha power within the ANP was associated with reduced BASDAI in the NNP group, and increased pain in the mixed-NP group within the DMN, SN, and ANP. Thus, high theta and low gamma activity may be markers of chronic pain but high alpha-band activity may relate to particular features of neuropathic chronic pain.

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.

Deep brain activities can be detected with magnetoencephalography

The hippocampus and amygdala are key brain structures of the medial temporal lobe, involved in cognitive and emotional processes as well as pathological states such as epilepsy. Despite their importance, it is still unclear whether their  neural activity can be recorded non-invasively. Here, using simultaneous intracerebral and magnetoencephalography (MEG) recordings in patients with focal drug-resistant epilepsy, we demonstrate a direct contribution of amygdala and hippocampal activity to surface MEG recordings. In particular, a method of blind source separation, independent component analysis, enabled activity arising from large neocortical networks to be disentangled from that of deeper structures, whose amplitude at the surface was small but significant. This finding is highly relevant for our understanding of hippocampal and amygdala brain activity as it implies that their activity could potentially be measured non-invasively.

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.

Ictal Source Locations and Cortico-Thalamic Connectivity in Childhood Absence Epilepsy: Associations with Treatment Response

Childhood absence epilepsy (CAE), the most common pediatric epilepsy syndrome, is usually treated with valproic acid (VPA) and lamotrigine (LTG) in China. This study aimed to investigate the ictal source locations and functional connectivity (FC) networks between the cortices and thalamus that are related to treatment response. Magnetoencephalography (MEG) data from 25 patients with CAE were recorded at 300 Hz and analyzed in 1-30 Hz frequency bands. Neuromagnetic sources were volumetrically scanned with accumulated source imaging. The FC networks between the cortices and thalamus were evaluated at the source level through a connectivity analysis. Treatment outcome was assessed after 36-66 months following MEG recording. The children with CAE were divided into LTG responder, LTG non-responder, VPA responder and VPA non-responder groups. The ictal source locations and cortico-thalamic FC networks were compared to the treatment response. The ictal source locations in the post-dorsal medial frontal cortex (post-DMFC, including the medial primary motor cortex and the supplementary sensorimotor area) were observed in all LTG non-responders but in all LTG responders. At 1-7 Hz, patients with fronto-thalamo-parietal/occipital (F-T-P/O) networks were older than those with fronto-thalamic (F-T) networks or other cortico-thalamic networks (p = 0.000). The duration of seizures in patients with F-T-P/O networks at 1-7 Hz was longer than that in patients with F-T networks or other cortico-thalamic networks (p = 0.001). The ictal post-DMFC source localizations suggest that children with CAE might experience initial LTG monotherapy failure. Moreover, the cortico-thalamo-cortical network is associated with age. Finally, the cortico-thalamo-cortical network consists of anterior and posterior cortices and might contribute to the maintenance of discharges.

Magnetoencephalography: Clinical and Research Practices

Magnetoencephalography (MEG) is a neurophysiological technique that detects the magnetic fields associated with brain activity. Synthetic aperture magnetometry (SAM), a MEG magnetic source imaging technique, can be used to construct both detailed maps of global brain activity as well as virtual electrode signals, which provide information that is similar to invasive electrode recordings. This innovative approach has demonstrated utility in both clinical and research settings. For individuals with epilepsy, MEG provides valuable, nonredundant information. MEG accurately localizes the irritative zone associated with interictal spikes, often detecting epileptiform activity other methods cannot, and may give localizing information when other methods fail. These capabilities potentially greatly increase the population eligible for epilepsy surgery and improve planning for those undergoing surgery. MEG methods can be readily adapted to research settings, allowing noninvasive assessment of whole brain neurophysiological activity, with a theoretical spatial range down to submillimeter voxels, and in both humans and nonhuman primates. The combination of clinical and research activities with MEG offers a unique opportunity to advance translational research from bench to bedside and back.

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.

Changes in nonhuman primate brain function following chronic alcohol consumption in previously naïve animals

INTRODUCTION

Chronic alcohol abuse is associated with neurophysiological changes in brain activity; however, these changes are not well localized in humans. Non-human primate models of alcohol abuse enable control over many potential confounding variables associated with human studies. The present study utilized high-resolution magnetoencephalography (MEG) to quantify the effects of chronic EtOH self-administration on resting state (RS) brain function in vervet monkeys.

METHODS

Adolescent male vervet monkeys were trained to self-administer ethanol (n=7) or an isocaloric malto-dextrin solution (n=3). Following training, animals received 12 months of free access to ethanol. Animals then underwent RS magnetoencephalography (MEG) and subsequent power spectral analysis of brain activity at 32 bilateral regions of interest associated with the chronic effects of alcohol use.

RESULTS

demonstrate localized changes in brain activity in chronic heavy drinkers, including reduced power in the anterior cingulate cortex, hippocampus, and amygdala as well as increased power in the right medial orbital and parietal areas.

DISCUSSION

The current study is the first demonstration of whole-head MEG acquisition in vervet monkeys. Changes in brain activity were consistent with human electroencephalographic studies; however, MEG was able to extend these findings by localizing the observed changes in power to specific brain regions. These regions are consistent with those previously found to exhibit volume loss following chronic heavy alcohol use. The ability to use MEG to evaluate changes in brain activity following chronic ethanol exposure provides a potentially powerful tool to better understand both the acute and chronic effects of alcohol on brain function.

Quantify neuromagnetic network changes from pre-ictal to ictal activities in absence seizures

OBJECTIVE

The cortico-thalamo-cortical network plays a key role in childhood absence epilepsy (CAE). However, the exact interaction between the cortex and the thalamus remains incompletely understood. This study aimed to investigate the dynamic changes of frequency-dependent neural networks during the initialization of absence seizures.

METHODS

Magnetoencephalography data from 14 patients with CAE were recorded during and between seizures at a sampling rate of 6000Hz and analyzed in seven frequency bands. Neuromagnetic sources were volumetrically scanned with accumulated source imaging. Effective connectivity networks of the entire brain, including the cortico-thalamo-cortical network, were evaluated at the source level through Granger causality analysis.

RESULTS

The low-frequency (1-80Hz) activities showed significant frontal cortical and parieto-occipito-temporal junction source localization around seizures. The high-frequency (80-250Hz) oscillations showed predominant activities consistently localized in deep brain areas and medial frontal cortex. The increased cortico-thalamic effective connectivity was observed around seizures in both low- and high-frequency ranges. The direction was predominantly from the cortex to the thalamus at the early time, although the cortex that drove connectivity varied among subjects.

CONCLUSIONS

The cerebral cortex plays a key role in driving the cortico-thalamic connections at the early portion of the initialization of absence seizures. The oscillatory activities in the thalamus could be triggered by networks from various regions in the cortex.

SIGNIFICANCE

The dynamic changes of neural network provide evidences that absence seizures are probably resulted from cortical initialized cortico-thalamic network.

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.

The impact of MEG source reconstruction method on source-space connectivity estimation: A comparison between minimum-norm solution and beamforming

Despite numerous important contributions, the investigation of brain connectivity with magnetoencephalography (MEG) still faces multiple challenges. One critical aspect of source-level connectivity, largely overlooked in the literature, is the putative effect of the choice of the inverse method on the subsequent cortico-cortical coupling analysis. We set out to investigate the impact of three inverse methods on source coherence detection using simulated MEG data. To this end, thousands of randomly located pairs of sources were created. Several parameters were manipulated, including inter- and intra-source correlation strength, source size and spatial configuration. The simulated pairs of sources were then used to generate sensor-level MEG measurements at varying signal-to-noise ratios (SNR). Next, the source level power and coherence maps were calculated using three methods (a) L2-Minimum-Norm Estimate (MNE), (b) Linearly Constrained Minimum Variance (LCMV) beamforming, and (c) Dynamic Imaging of Coherent Sources (DICS) beamforming. The performances of the methods were evaluated using Receiver Operating Characteristic (ROC) curves. The results indicate that beamformers perform better than MNE for coherence reconstructions if the interacting cortical sources consist of point-like sources. On the other hand, MNE provides better connectivity estimation than beamformers, if the interacting sources are simulated as extended cortical patches, where each patch consists of dipoles with identical time series (high intra-patch coherence). However, the performance of the beamformers for interacting patches improves substantially if each patch of active cortex is simulated with only partly coherent time series (partial intra-patch coherence). These results demonstrate that the choice of the inverse method impacts the results of MEG source-space coherence analysis, and that the optimal choice of the inverse solution depends on the spatial and synchronization profile of the interacting cortical sources. The insights revealed here can guide method selection and help improve data interpretation regarding MEG connectivity estimation.

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.

Towards a Functional Understanding of PGO Waves

Ponto-Geniculo-Occipital (PGO) waves are biphasic field potentials identified in a range of mammalian species that are ubiquitous with sleep, but can also be identified in waking perception and eye movement. Their role in REM sleep and visual perception more broadly may constitute a promising avenue for further research, however what was once an active field of study has recently fallen into stasis. With the reality that invasive recordings performed on animals cannot be replicated in humans; while animals themselves cannot convey experience to the extent required to elucidate how PGO waves factor into awareness and behavior, innovative solutions are required if significant research outcomes are to ever be realized. Advances in non-invasive imaging technologies and sophistication in imaging methods now offer substantial scope to renew the study of the electrophysiological substrates of waking and dreaming perception. Among these, Magnetoencephalogram (MEG) stands out through its capacity to measure deep brain activations with high temporal resolution. With the current trend in sleep and dream research to produce translational findings of psychopathological and medical significance, in addition to the clear links that PGO wave generation sites share, pharmacologically, with receptors involved in expression of mental illness; there is a strong case to support scientific research into PGO waves and develop a functional understanding of their broader role in human perception.

Medial Prefrontal-Medial Temporal Theta Phase Coupling in Dynamic Spatial Imagery

Hippocampal-medial prefrontal interactions are thought to play a crucial role in mental simulation. Notably, the frontal midline/medial pFC (mPFC) theta rhythm in humans has been linked to introspective thought and working memory. In parallel, theta rhythms have been proposed to coordinate processing in the medial temporal cortex, retrosplenial cortex (RSc), and parietal cortex during the movement of viewpoint in imagery, extending their association with physical movement in rodent models. Here, we used noninvasive whole-head MEG to investigate theta oscillatory power and phase-locking during the 18-sec postencoding delay period of a spatial working memory task, in which participants imagined previously learned object sequences either on a blank background (object maintenance), from a first-person viewpoint in a scene (static imagery), or moving along a path past the objects (dynamic imagery). We found increases in 4- to 7-Hz theta power in mPFC when comparing the delay period with a preencoding baseline. We then examined whether the mPFC theta rhythm was phase-coupled with ongoing theta oscillations elsewhere in the brain. The same mPFC region showed significantly higher theta phase coupling with the posterior medial temporal lobe/RSc for dynamic imagery versus either object maintenance or static imagery. mPFC theta phase coupling was not observed with any other brain region. These results implicate oscillatory coupling between mPFC and medial temporal lobe/RSc theta rhythms in the dynamic mental exploration of imagined scenes.

Disconnection from others in autism is more than just a feeling: whole-brain neural synchrony in adults during implicit processing of emotional faces

Background

Socio-emotional difficulties in autism spectrum disorder (ASD) are thought to reflect impaired functional connectivity within the “social brain”. Nonetheless, a whole-brain characterization of the fast responses in functional connectivity during implicit processing of emotional faces in adults with ASD is lacking.

Methods

The present study used magnetoencephalography to investigate early responses in functional connectivity, as measured by interregional phase synchronization, during implicit processing of angry, neutral and happy faces. The sample (n = 44) consisted of 22 young adults with ASD and 22 age- and sex-matched typically developed (TD) controls.

Results

Reduced phase-synchrony in the beta band around 300 ms emerged during processing of angry faces in the ASD compared to TD group, involving key areas of the social brain. In the same time window, de-synchronization in the beta band in the amygdala was reduced in the ASD group across conditions.

Conclusions

This is the first demonstration of atypical global and local synchrony patterns in the social brain in adults with ASD during implicit processing of emotional faces. The present results replicate and substantially extend previous findings on adolescents, highlighting that atypical brain synchrony during processing of socio-emotional stimuli is a hallmark of clinical sequelae in autism.

Electronic supplementary material

The online version of this article (doi:10.1186/s13229-017-0123-2) contains supplementary material, which is available to authorized users.

Contrasting Effects of Posttraumatic Stress Disorder and Mild Traumatic Brain Injury on the Whole-Brain Resting-State Network: A Magnetoencephalography Study

The aim of this study was to evaluate alterations in whole-brain resting-state networks associated with posttraumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI). Networks were constructed from locations of peak statistical power on an individual basis from magnetoencephalography (MEG) source series data by applying the weighted phase lag index and surrogate data thresholding procedures. Networks representing activity in the alpha bandwidth as well as wideband activity (DC-80 Hz) were created. Statistical comparisons were adjusted for age and education level. Alpha network results demonstrate reductions in network structure associated with PTSD, but no differences associated with mTBI. Wideband network results demonstrate a shift in connectivity from the alpha to theta bandwidth in both PTSD and mTBI. Also, contrasting alterations in network structure are noted, with increased randomness associated with PTSD and increased structure associated with mTBI. These results demonstrate the potential of the analysis of MEG resting-state networks to differentiate two highly comorbid conditions. The importance of the alpha bandwidth to resting-state connectivity is also highlighted, while demonstrating the necessity of considering activity in other bandwidths during network construction.

Detecting Mild Traumatic Brain Injury Using Resting State Magnetoencephalographic Connectivity

Accurate means to detect mild traumatic brain injury (mTBI) using objective and quantitative measures remain elusive. Conventional imaging typically detects no abnormalities despite post-concussive symptoms. In the present study, we recorded resting state magnetoencephalograms (MEG) from adults with mTBI and controls. Atlas-guided reconstruction of resting state activity was performed for 90 cortical and subcortical regions, and calculation of inter-regional oscillatory phase synchrony at various frequencies was performed. We demonstrate that mTBI is associated with reduced network connectivity in the delta and gamma frequency range (>30 Hz), together with increased connectivity in the slower alpha band (8–12 Hz). A similar temporal pattern was associated with correlations between network connectivity and the length of time between the injury and the MEG scan. Using such resting state MEG network synchrony we were able to detect mTBI with 88% accuracy. Classification confidence was also correlated with clinical symptom severity scores. These results provide the first evidence that imaging of MEG network connectivity, in combination with machine learning, has the potential to accurately detect and determine the severity of mTBI.

Detecting concussion is typically not possible using currently clinically used brain imaging, such as MRI and CT scans. Magnetoencephalographic (MEG) imaging is able to directly measure brain activity at fast time scales, and this can be used to map how various areas of the brain interact. We recorded MEG from individuals who had suffered a concussion, as well as control subjects who had not. We found characteristic alterations of inter-regional interactions associated with concussion. Moreover, using a machine learning approach, we were able to detect concussion with 88% accuracy from MEG connectivity, and confidence of classification correlated with symptom severity. This potentially provides new quantitative and objective methods for detecting and assessing the severity of concussion using neuroimaging.

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.

Localising the auditory N1m with event-related beamformers: localisation accuracy following bilateral and unilateral stimulation

The auditory evoked N1m-P2m response complex presents a challenging case for MEG source-modelling, because symmetrical, phase-locked activity occurs in the hemispheres both contralateral and ipsilateral to stimulation. Beamformer methods, in particular, can be susceptible to localisation bias and spurious sources under these conditions. This study explored the accuracy and efficiency of event-related beamformer source models for auditory MEG data under typical experimental conditions: monaural and diotic stimulation; and whole-head beamformer analysis compared to a half-head analysis using only sensors from the hemisphere contralateral to stimulation. Event-related beamformer localisations were also compared with more traditional single-dipole models. At the group level, the event-related beamformer performed equally well as the single-dipole models in terms of accuracy for both the N1m and the P2m, and in terms of efficiency (number of successful source models) for the N1m. The results yielded by the half-head analysis did not differ significantly from those produced by the traditional whole-head analysis. Any localisation bias caused by the presence of correlated sources is minimal in the context of the inter-individual variability in source localisations. In conclusion, event-related beamformers provide a useful alternative to equivalent-current dipole models in localisation of auditory evoked responses.

Slow-theta power decreases during item-place encoding predict spatial accuracy of subsequent context recall

Human hippocampal theta oscillations play a key role in accurate spatial coding. Associative encoding involves similar hippocampal networks but, paradoxically, is also characterized by theta power decreases. Here, we investigated how theta activity relates to associative encoding of place contexts resulting in accurate navigation. Using MEG, we found that slow-theta (2-5Hz) power negatively correlated with subsequent spatial accuracy for virtual contextual locations in posterior hippocampus and other cortical structures involved in spatial cognition. A rare opportunity to simultaneously record MEG and intracranial EEG in an epilepsy patient provided crucial insights: during power decreases, slow-theta in right anterior hippocampus and left inferior frontal gyrus phase-led the left temporal cortex and predicted spatial accuracy. Our findings indicate that decreased slow-theta activity reflects local and long-range neural mechanisms that encode accurate spatial contexts, and strengthens the view that local suppression of low-frequency activity is essential for more efficient processing of detailed information.

Slowing of Hippocampal Activity Correlates with Cognitive Decline in Early Onset Alzheimer's Disease. An MEG Study with Virtual Electrodes

Pathology in Alzheimer's disease (AD) starts in the entorhinal cortex and hippocampus. Because of their deep location, activity from these areas is difficult to record with conventional electro- or magnetoencephalography (EEG/MEG). The purpose of this study was to explore hippocampal activity in AD patients and healthy controls using "virtual MEG electrodes". We used resting-state MEG recordings from 27 early onset AD patients [age 60.6 ± 5.4, 12 females, mini-mental state examination (MMSE) range: 19-28] and 26 cognitively healthy age- and gender-matched controls (age 61.8 ± 5.5, 14 females). Activity was reconstructed using beamformer-based virtual electrodes for 78 cortical regions and 6 hippocampal regions. Group differences in peak frequency and relative power in six frequency bands were identified using permutation testing. For the patients, spearman correlations between the MMSE scores and peak frequency or relative power were calculated. Moreover, receiver operator characteristic curves were plotted to estimate the diagnostic accuracy. We found a lower hippocampal peak frequency in AD compared to controls, which, in the patients, correlated positively with MMSE [r(25) = 0.61; p < 0.01] whereas hippocampal relative theta power correlated negatively with MMSE [r(25) = -0.54; p < 0.01]. Cortical peak frequency was also lower in AD in association areas. Furthermore, cortical peak frequency correlated positively with MMSE [r(25) = 0.43; p < 0.05]. In line with this finding, relative theta power was higher in AD across the cortex, and relative alpha and beta power was lower in more circumscribed areas. The average cortical relative theta power was the best discriminator between AD and controls (sensitivity 82%; specificity 81%). Using beamformer-based virtual electrodes, we were able to detect hippocampal activity in AD. In AD, this hippocampal activity is slowed, and correlates better with cognition than the (slowed) activity in cortical areas. On the other hand, the average cortical relative power in the theta band was shown to be the best diagnostic discriminator. We postulate that this novel approach using virtual electrodes can be used in future research to quantify functional interactions between the hippocampi and cortical areas.

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.

Brain responses in humans reveal ideal observer-like sensitivity to complex acoustic patterns

We use behavioral methods, magnetoencephalography, and functional MRI to investigate how human listeners discover temporal patterns and statistical regularities in complex sound sequences. Sensitivity to patterns is fundamental to sensory processing, in particular in the auditory system, because most auditory signals only have meaning as successions over time. Previous evidence suggests that the brain is tuned to the statistics of sensory stimulation. However, the process through which this arises has been elusive. We demonstrate that listeners are remarkably sensitive to the emergence of complex patterns within rapidly evolving sound sequences, performing on par with an ideal observer model. Brain responses reveal online processes of evidence accumulation--dynamic changes in tonic activity precisely correlate with the expected precision or predictability of ongoing auditory input--both in terms of deterministic (first-order) structure and the entropy of random sequences. Source analysis demonstrates an interaction between primary auditory cortex, hippocampus, and inferior frontal gyrus in the process of discovering the regularity within the ongoing sound sequence. The results are consistent with precision based predictive coding accounts of perceptual inference and provide compelling neurophysiological evidence of the brain's capacity to encode high-order temporal structure in sensory signals.

Soldiers With Posttraumatic Stress Disorder See a World Full of Threat: Magnetoencephalography Reveals Enhanced Tuning to Combat-Related Cues

BACKGROUND

Posttraumatic stress disorder (PTSD) is linked to elevated arousal and alterations in cognitive processes. Yet, whether a traumatic experience is linked to neural and behavioral differences in selective attentional tuning to traumatic stimuli is not known. The present study examined selective awareness of threat stimuli and underlying temporal-spatial patterns of brain activation associated with PTSD.

METHODS

Participants were 44 soldiers from the Canadian Armed Forces, 22 with PTSD and 22 without. All completed neuropsychological tests and clinical assessments. Magnetoencephalography data were collected while participants identified two targets in a rapidly presented stream of words. The first target was a number and the second target was either a combat-related or neutral word. The difference in accuracy for combat-related versus neutral words was used as a measure of attentional bias.

RESULTS

All soldiers showed a bias for combat-related words. This bias was enhanced in the PTSD group, and behavioral differences were associated with distinct patterns of brain activity. At early latencies, non-PTSD soldiers showed activation of midline frontal regions associated with fear regulation (90-340 ms after the second target presentation), whereas those with PTSD showed greater visual cortex activation linked to enhanced visual processing of trauma stimuli (200-300 ms).

CONCLUSIONS

These findings suggest that attentional biases in PTSD are linked to deficits in very rapid regulatory activation observed in healthy control subjects. Thus, sufferers with PTSD may literally see a world more populated by traumatic cues, contributing to a positive feedback loop that perpetuates the effects of trauma.

Desynchronization of fronto-temporal networks during working memory processing in autism

BACKGROUND

Mounting evidence suggests that autism is a network disorder, characterized by atypical brain connectivity, especially in the context of high level cognitive processes such as working memory (WM). Accordingly, atypical WM processes have been related to the social and cognitive deficits observed in children with autism spectrum disorder (ASD).

METHODS

We used magnetoencephalography (MEG) to investigate connectivity differences during a high memory load (2-back) WM task between 17 children with ASD and 20 age-, sex-, and IQ-matched controls.

RESULTS

We identified reduced inter-regional alpha-band (9-15 Hz) phase synchronization in children with ASD during the WM task. Reduced WM-related brain synchronization encompassed fronto-temporal networks (ps < 0.04 corrected) previously associated with challenging high-level conditions (i.e. the left insula and the anterior cingulate cortex (ACC)) and memory encoding and/or recognition (i.e. the right middle temporal gyrus and the right fusiform gyrus). Additionally, we found that reduced connectivity processes related to the right fusiform were correlated with the severity of symptoms in children with ASD, suggesting that such atypicalities could be directly related to the behavioural deficits observed.

DISCUSSION

This study provides new evidence of atypical long-range synchronization in children with ASD in fronto-temporal areas that crucially contribute to challenging WM tasks, but also emotion regulation and social cognition processes. Thus, these results support the network disorder hypothesis of ASD and argue for a specific pathophysiological contribution of brain processes related to working memory and executive functions on the symptomatology of autism.

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.

Thalamocortical interactions underlying visual fear conditioning in humans

Despite a strong focus on the role of the amygdala in fear conditioning, recent works point to a more distributed network supporting fear conditioning. We aimed to elucidate interactions between subcortical and cortical regions in fear conditioning in humans. To do this, we used two fearful faces as conditioned stimuli (CS) and an electrical stimulation at the left hand, paired with one of the CS, as unconditioned stimulus (US). The luminance of the CS was rhythmically modulated leading to "entrainment" of brain oscillations at a predefined modulation frequency. Steady-state responses (SSR) were recorded by MEG. In addition to occipital regions, spectral analysis of SSR revealed increased power during fear conditioning particularly for thalamus and cerebellum contralateral to the upcoming US. Using thalamus and amygdala as seed-regions, directed functional connectivity was calculated to capture the modulation of interactions that underlie fear conditioning. Importantly, this analysis showed that the thalamus drives the fusiform area during fear conditioning, while amygdala captures the more general effect of fearful faces perception. This study confirms ideas from the animal literature, and demonstrates for the first time the central role of the thalamus in fear conditioning in humans.

Atypical spatiotemporal signatures of working memory brain processes in autism

Working memory (WM) impairments may contribute to the profound behavioural manifestations in children with autism spectrum disorder (ASD). However, previous behavioural results are discrepant as are the few functional magnetic resonance imaging (fMRI) results collected in adults and adolescents with ASD. Here we investigate the precise temporal dynamics of WM-related brain activity using magnetoencephalography (MEG) in 20 children with ASD and matched controls during an n-back WM task across different load levels (1-back vs 2-back). Although behavioural results were similar between ASD and typically developing (TD) children, the between-group comparison performed on functional brain activity showed atypical WM-related brain processes in children with ASD compared with TD children. These atypical responses were observed in the ASD group from 200 to 600 ms post stimulus in both the low- (1-back) and high- (2-back) memory load conditions. During the 1-back condition, children with ASD showed reduced WM-related activations in the right hippocampus and the cingulate gyrus compared with TD children who showed more activation in the left dorso-lateral prefrontal cortex and the insulae. In the 2-back condition, children with ASD showed less activity in the left insula and midcingulate gyrus and more activity in the left precuneus than TD children. In addition, reduced activity in the anterior cingulate cortex was correlated with symptom severity in children with ASD. Thus, this MEG study identified the precise timing and sources of atypical WM-related activity in frontal, temporal and parietal regions in children with ASD. The potential impacts of such atypicalities on social deficits of autism are discussed.

Ventromedial prefrontal cortex drives hippocampal theta oscillations induced by mismatch computations

Detecting environmental change is fundamental for adaptive behavior in an uncertain world. Previous work indicates the hippocampus supports the generation of novelty signals via implementation of a match–mismatch detector that signals when an incoming sensory input violates expectations based on past experience. While existing work has emphasized the particular contribution of the hippocampus, here we ask which other brain structures also contribute to match–mismatch detection. Furthermore, we leverage the fine-grained temporal resolution of magnetoencephalography (MEG) to investigate whether mismatch computations are spectrally confined to the theta range, based on the prominence of this range of oscillations in models of hippocampal function. By recording MEG activity while human subjects perform a task that incorporates conditions of match–mismatch novelty we show that mismatch signals are confined to the theta band and are expressed in both the hippocampus and ventromedial prefrontal cortex (vmPFC). Effective connectivity analyses (dynamic causal modeling) show that the hippocampus and vmPFC work as a functional circuit during mismatch detection. Surprisingly, our results suggest that the vmPFC drives the hippocampus during the generation and processing of mismatch signals. Our findings provide new evidence that the hippocampal–vmPFC circuit is engaged during novelty processing, which has implications for emerging theories regarding the role of vmPFC in memory.

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Mismatch detection engages human hippocampus and ventromedial prefrontal cortex.

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Novelty signals are spectrally confined to the theta band.

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Ventromedial prefrontal cortex drives hippocampal theta induced by mismatches.