Modeling and detecting deep brain activity with MEG & EEG

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.

Magnetoencephalography can reveal deep brain network activities linked to memory processes

Recording from deep neural structures such as hippocampus noninvasively and yet with high temporal resolution remains a major challenge for human neuroscience. Although it has been proposed that deep neuronal activity might be recordable during cognitive tasks using magnetoencephalography (MEG), this remains to be demonstrated as the contribution of deep structures to MEG recordings may be too small to be detected or might be eclipsed by the activity of large‐scale neocortical networks. In the present study, we disentangled mesial activity and large‐scale networks from the MEG signals thanks to blind source separation (BSS). We then validated the MEG BSS components using intracerebral EEG signals recorded simultaneously in patients during their presurgical evaluation of epilepsy. In the MEG signals obtained during a memory task involving the recognition of old and new images, we identified with BSS a putative mesial component, which was present in all patients and all control subjects. The time course of the component selectively correlated with stereo‐electroencephalography signals recorded from hippocampus and rhinal cortex, thus confirming its mesial origin. This finding complements previous studies with epileptic activity and opens new possibilities for using MEG to study deep brain structures in cognition and in brain disorders.

Subcortical Cognition: The Fruit Below the Rind

Cognitive neuroscience has highlighted the cerebral cortex while often overlooking subcortical structures. This cortical proclivity is found in basic and translational research on many aspects of cognition, especially higher cognitive domains such as language, reading, music, and math. We suggest that, for both anatomical and evolutionary reasons, multiple subcortical structures play substantial roles across higher and lower cognition. We present a comprehensive review of existing evidence, which indeed reveals extensive subcortical contributions in multiple cognitive domains. We argue that the findings are overall both real and important. Next, we advance a theoretical framework to capture the nature of (sub)cortical contributions to cognition. Finally, we propose how new subcortical cognitive roles can be identified by leveraging anatomical and evolutionary principles, and we describe specific methods that can be used to reveal subcortical cognition. Altogether, this review aims to advance cognitive neuroscience by highlighting subcortical cognition and facilitating its future investigation. Expected final online publication date for the Annual Review of Neuroscience, Volume 45 is July 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Dynamic brainstem and somatosensory cortical excitability during migraine cycles

Abstract

Background

Migraine has complex pathophysiological characteristics and episodic attacks. To decipher the cyclic neurophysiological features of migraine attacks, in this study, we compared neuronal excitability in the brainstem and primary somatosensory (S1) region between migraine phases for 30 consecutive days in two patients with episodic migraine.

Methods

Both patients underwent EEG recording of event-related potentials with the somatosensory and paired-pulse paradigms for 30 consecutive days. The migraine cycle was divided into the following phases: 24–48 h before headache onset (Pre2), within 24 h before headache onset (Pre1), during the migraine attack (Ictal), within 24 h after headache offset (Post1), and the interval of ˃48 h between the last and next headache phase (Interictal). The normalised current intensity in the brainstem and S1 and gating ratio in the S1 were recorded and examined.

Results

Six migraine cycles (three for each patient) were analysed. In both patients, the somatosensory excitability in the brainstem (peaking at 12–14 ms after stimulation) and S1 (peaking at 18–19 ms after stimulation) peaked in the Pre1 phase. The S1 inhibitory capability was higher in the Ictal phase than in the Pre1 phase.

Conclusion

This study demonstrates that migraine is a cyclic excitatory disorder and that the neural substrates involved include the somatosensory system, starting in the brainstem and spanning subsequently to the S1 before the migraine occurs. Further investigations with larger sample sizes are warranted.

High gamma cortical processing of continuous speech in younger and older listeners

Neural processing along the ascending auditory pathway is often associated with a progressive reduction in characteristic processing rates. For instance, the well-known frequency-following response (FFR) of the auditory midbrain, as measured with electroencephalography (EEG), is dominated by frequencies from ∼100 Hz to several hundred Hz, phase-locking to the acoustic stimulus at those frequencies. In contrast, cortical responses, whether measured by EEG or magnetoencephalography (MEG), are typically characterized by frequencies of a few Hz to a few tens of Hz, time-locking to acoustic envelope features. In this study we investigated a crossover case, cortically generated responses time-locked to continuous speech features at FFR-like rates. Using MEG, we analyzed responses in the high gamma range of 70-200 Hz to continuous speech using neural source-localized reverse correlation and the corresponding temporal response functions (TRFs). Continuous speech stimuli were presented to 40 subjects (17 younger, 23 older adults) with clinically normal hearing and their MEG responses were analyzed in the 70-200 Hz band. Consistent with the relative insensitivity of MEG to many subcortical structures, the spatiotemporal profile of these response components indicated a cortical origin with ∼40 ms peak latency and a right hemisphere bias. TRF analysis was performed using two separate aspects of the speech stimuli: a) the 70-200 Hz carrier of the speech, and b) the 70-200 Hz temporal modulations in the spectral envelope of the speech stimulus. The response was dominantly driven by the envelope modulation, with a much weaker contribution from the carrier. Age-related differences were also analyzed to investigate a reversal previously seen along the ascending auditory pathway, whereby older listeners show weaker midbrain FFR responses than younger listeners, but, paradoxically, have stronger cortical low frequency responses. In contrast to both these earlier results, this study did not find clear age-related differences in high gamma cortical responses to continuous speech. Cortical responses at FFR-like frequencies shared some properties with midbrain responses at the same frequencies and with cortical responses at much lower frequencies.

Subgenual cingulate connectivity and hippocampal activation are related to MST therapeutic and adverse effects

Aberrant connectivity between the dorsolateral prefrontal cortex (DLPFC) and the subgenual cingulate cortex (SGC) has been linked to the pathophysiology of depression. Indirect evidence also links hippocampal activation to the cognitive side effects of seizure treatments. Magnetic seizure therapy (MST) is a novel treatment for patients with treatment resistant depression (TRD). Here we combine transcranial magnetic stimulation with electroencephalography (TMS-EEG) to evaluate the effects of MST on connectivity and activation between the DLPFC, the SGC and hippocampus (Hipp) in patients with TRD. The TMS-EEG was collected from 31 TRD patients prior to and after an MST treatment trial. Through TMS-EEG methodology we evaluated significant current scattering (SCS) as an index of effective connectivity between the SGC and left DLPFC. Significant current density (SCD) was used to assess activity at the level of the Hipp. The SCS between the SGC and DLPFC was reduced after the course of MST (p < 0.036). The DLPFC-SGC effective connectivity reduction correlated with the changes in Hamilton depression score pre-to-post treatment (R = 0.46; p < 0.031). The SCD localized to the Hipp was reduced after the course of MST (p < 0.015), and the SCD change was correlated with montreal cognitive assessment (MOCA) scores pre-post the course of MST (R = -0.59; p < 0.026). Our findings suggest that MST treatment is associated with SGC-DLPFC connectivity reduction and that changes to cognition are associated with Hipp activation reduction. These findings demonstrate two distinct processes which drive efficacy and side effects separately, and might eventually aid in delineating physiological TRD targets in clinical settings.

Magnocellular and parvocellular pathway contributions to facial threat cue processing

Human faces evolved to signal emotions, with their meaning contextualized by eye gaze. For instance, a fearful expression paired with averted gaze clearly signals both presence of threat and its probable location. Conversely, direct gaze paired with facial fear leaves the source of the fear-evoking threat ambiguous. Given that visual perception occurs in parallel streams with different processing emphases, our goal was to test a recently developed hypothesis that clear and ambiguous threat cues would differentially engage the magnocellular (M) and parvocellular (P) pathways, respectively. We employed two-tone face images to characterize the neurodynamics evoked by stimuli that were biased toward M or P pathways. Human observers (N = 57) had to identify the expression of fearful or neutral faces with direct or averted gaze while their magnetoencephalogram was recorded. Phase locking between the amygdaloid complex, orbitofrontal cortex (OFC) and fusiform gyrus increased early (0–300 ms) for M-biased clear threat cues (averted-gaze fear) in the β-band (13–30 Hz) while P-biased ambiguous threat cues (direct-gaze fear) evoked increased θ (4–8 Hz) phase locking in connections with OFC of the right hemisphere. We show that M and P pathways are relatively more sensitive toward clear and ambiguous threat processing, respectively, and characterize the neurodynamics underlying emotional face processing in the M and P pathways.

A MEG Study of Visual Repetition Priming in Schizophrenia: Evidence for Impaired High-Frequency Oscillations and Event-Related Fields in Thalamo-Occipital Cortices

Background: Cognitive dysfunctions represent a core feature of schizophrenia and a predictor for clinical outcomes. One possible mechanism for cognitive impairments could involve an impairment in the experience-dependent modifications of cortical networks. Methods: To address this issue, we employed magnetoencephalography (MEG) during a visual priming paradigm in a sample of chronic patients with schizophrenia (n = 14), and in a group of healthy controls (n = 14). We obtained MEG-recordings during the presentation of visual stimuli that were presented three times either consecutively or with intervening stimuli. MEG-data were analyzed for event-related fields as well as spectral power in the 1-200 Hz range to examine repetition suppression and repetition enhancement. We defined regions of interest in occipital and thalamic regions and obtained virtual-channel data. Results: Behavioral priming did not differ between groups. However, patients with schizophrenia showed prominently reduced oscillatory response to novel stimuli in the gamma-frequency band as well as significantly reduced repetition suppression of gamma-band activity and reduced repetition enhancement of beta-band power in occipital cortex to both consecutive repetitions as well as repetitions with intervening stimuli. Moreover, schizophrenia patients were characterized by a significant deficit in suppression of the C1m component in occipital cortex and thalamus as well as of the late positive component (LPC) in occipital cortex. Conclusions: These data provide novel evidence for impaired repetition suppression in cortical and subcortical circuits in schizophrenia. Although behavioral priming was preserved, patients with schizophrenia showed deficits in repetition suppression as well as repetition enhancement in thalamic and occipital regions, suggesting that experience-dependent modification of neural circuits is impaired in the disorder.

Acute ketamine dysregulates task-related gamma-band oscillations in thalamo-cortical circuits in schizophrenia

Hypofunction of the N-methyl-d-aspartate receptor (NMDAR) has been implicated as a possible mechanism underlying cognitive deficits and aberrant neuronal dynamics in schizophrenia. To test this hypothesis, we first administered a sub-anaesthetic dose of S-ketamine (0.006 mg/kg/min) or saline in a single-blind crossover design in 14 participants while magnetoencephalographic data were recorded during a visual task. In addition, magnetoencephalographic data were obtained in a sample of unmedicated first-episode psychosis patients (n = 10) and in patients with chronic schizophrenia (n = 16) to allow for comparisons of neuronal dynamics in clinical populations versus NMDAR hypofunctioning. Magnetoencephalographic data were analysed at source-level in the 1–90 Hz frequency range in occipital and thalamic regions of interest. In addition, directed functional connectivity analysis was performed using Granger causality and feedback and feedforward activity was investigated using a directed asymmetry index. Psychopathology was assessed with the Positive and Negative Syndrome Scale. Acute ketamine administration in healthy volunteers led to similar effects on cognition and psychopathology as observed in first-episode and chronic schizophrenia patients. However, the effects of ketamine on high-frequency oscillations and their connectivity profile were not consistent with these observations. Ketamine increased amplitude and frequency of gamma-power (63–80 Hz) in occipital regions and upregulated low frequency (5–28 Hz) activity. Moreover, ketamine disrupted feedforward and feedback signalling at high and low frequencies leading to hypo- and hyper-connectivity in thalamo-cortical networks. In contrast, first-episode and chronic schizophrenia patients showed a different pattern of magnetoencephalographic activity, characterized by decreased task-induced high-gamma band oscillations and predominantly increased feedforward/feedback-mediated Granger causality connectivity. Accordingly, the current data have implications for theories of cognitive dysfunctions and circuit impairments in the disorder, suggesting that acute NMDAR hypofunction does not recreate alterations in neural oscillations during visual processing observed in schizophrenia.

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.

Reorganization of cortical oscillatory dynamics underlying disinhibition in frontotemporal dementia

The distribution of pathology in frontotemporal dementia is anatomically selective, to distinct cortical regions and with differential neurodegeneration across the cortical layers. The cytoarchitecture and connectivity of cortical laminae preferentially supports frequency-specific oscillations and hierarchical information transfer between brain regions. We therefore predicted that in frontotemporal dementia, core functional deficits such as disinhibition would be associated with differences in the frequency spectrum and altered cross-frequency coupling between frontal cortical regions. We examined this hypothesis using a 'Go-NoGo' response inhibition paradigm with 18 patients with behavioural variant frontotemporal dementia and 20 healthy aged-matched controls during magnetoencephalography. During Go and NoGo trials, beta desynchronization was severely attenuated in patients. Beta power was associated with increased impulsivity, as measured by the Cambridge Behavioural Inventory, a carer-based questionnaire of changes in everyday behaviour. To quantify the changes in cross-frequency coupling in the frontal lobe, we used dynamic causal modelling to test a family of hierarchical casual models, which included the inferior frontal gyrus, pre-supplementary motor area (preSMA) and primary motor cortex. This analysis revealed evidence for cross-frequency coupling in a fully connected network in both groups. However, in the patient group, we identified a significant loss of reciprocal connectivity of the inferior frontal gyrus, particularly for interactions in the gamma band and for theta to alpha coupling. Importantly, although prefrontal coupling was diminished, gamma connectivity between preSMA and motor cortex was enhanced in patients. We propose that the disruption of behavioural control arises from reduced frequency-specific connectivity of the prefrontal cortex, together with a hyper-synchronous reorganization of connectivity among preSMA and motor regions. These results are supported by preclinical evidence of the selectivity of frontotemporal lobar degeneration on oscillatory dynamics, and provide a clinically relevant yet precise neurophysiological signature of behavioural control as a potential pharmacological target for early phase experimental medicines studies.

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.

Beamspace dual signal space projection (bDSSP): a method for selective detection of deep sources in MEG measurements

OBJECTIVE

Magnetoencephalography (MEG) has a well-recognized weakness at detecting deeper brain activities. This paper proposes a novel algorithm for selective detection of deep sources by suppressing interference signals from superficial sources in MEG measurements.

APPROACH

The proposed algorithm combines the beamspace preprocessing method with the dual signal space projection (DSSP) interference suppression method. A prerequisite of the proposed algorithm is prior knowledge of the location of the deep sources. The proposed algorithm first derives the basis vectors that span a local region just covering the locations of the deep sources. It then estimates the time-domain signal subspace of the superficial sources by using the projector composed of these basis vectors. Signals from the deep sources are extracted by projecting the row space of the data matrix onto the direction orthogonal to the signal subspace of the superficial sources.

MAIN RESULTS

Compared with the previously proposed beamspace signal space separation (SSS) method, the proposed algorithm is capable of suppressing much stronger interference from superficial sources. This capability is demonstrated in our computer simulation as well as experiments using phantom data.

SIGNIFICANCE

The proposed bDSSP algorithm can be a powerful tool in studies of physiological functions of midbrain and deep brain structures.

Neurodynamics and connectivity during facial fear perception: The role of threat exposure and signal congruity

Fearful faces convey threat cues whose meaning is contextualized by eye gaze: While averted gaze is congruent with facial fear (both signal avoidance), direct gaze (an approach signal) is incongruent with it. We have previously shown using fMRI that the amygdala is engaged more strongly by fear with averted gaze during brief exposures. However, the amygdala also responds more to fear with direct gaze during longer exposures. Here we examined previously unexplored brain oscillatory responses to characterize the neurodynamics and connectivity during brief (~250 ms) and longer (~883 ms) exposures of fearful faces with direct or averted eye gaze. We performed two experiments: one replicating the exposure time by gaze direction interaction in fMRI (N = 23), and another where we confirmed greater early phase locking to averted-gaze fear (congruent threat signal) with MEG (N = 60) in a network of face processing regions, regardless of exposure duration. Phase locking to direct-gaze fear (incongruent threat signal) then increased significantly for brief exposures at ~350 ms, and at ~700 ms for longer exposures. Our results characterize the stages of congruent and incongruent facial threat signal processing and show that stimulus exposure strongly affects the onset and duration of these stages.

EEG Spectral Generators Involved in Motor Imagery: A swLORETA Study

In order to characterize the neural generators of the brain oscillations related to motor imagery (MI), we investigated the cortical, subcortical, and cerebellar localizations of their respective electroencephalogram (EEG) spectral power and phase locking modulations. The MI task consisted in throwing a ball with the dominant upper limb while in a standing posture, within an ecological virtual reality (VR) environment (tennis court). The MI was triggered by the visual cues common to the control condition, during which the participant remained mentally passive. As previously developed, our paradigm considers the confounding problem that the reference condition allows two complementary analyses: one which uses the baseline before the occurrence of the visual cues in the MI and control resting conditions respectively; and the other which compares the analog periods between the MI and the control resting-state conditions. We demonstrate that MI activates specific, complex brain networks for the power and phase modulations of the EEG oscillations. An early (225 ms) delta phase-locking related to MI was generated in the thalamus and cerebellum and was followed (480 ms) by phase-locking in theta and alpha oscillations, generated in specific cortical areas and the cerebellum. Phase-locking preceded the power modulations (mainly alpha-beta ERD), whose cortical generators were situated in the frontal BA45, BA11, BA10, central BA6, lateral BA13, and posterior cortex BA2. Cerebellar-thalamic involvement through phase-locking is discussed as an underlying mechanism for recruiting at later stages the cortical areas involved in a cognitive role during MI.

Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain.

The Effect of Botulinum Toxin on Network Connectivity in Cervical Dystonia: Lessons from Magnetoencephalography

BACKGROUND

Pharmacological management of cervical dystonia (CD) is considered to be symptomatic in effect, rather than targeting the underlying pathophysiology of the disease. Magnetoencephalography (MEG), a direct measure of neuronal activity, while accepted as a modality for pre-surgical mapping in epilepsy, has never been used to explore the effect of pharmacotherapy in movement disorders.

METHODS

Resting state MEG data were collected from patients with CD, pre- and post-botulinum toxin injections. All of these patients exhibited good clinical benefit with botulinum toxin. Resting state MEG data from four age- and gender-matched healthy controls with no neurological disorders were also collected.

RESULTS

Our exploratory study reveals a difference in coherence between controls and patients in the following regions: fronto-striatal, occipito-striatal, parieto-striatal, and striato-temporal networks. In these regions there is an increase after botulinum toxin. Specifically, increased coherence in the left putamen and right superior parietal gyrus was noticeable. Both intrahemispheric and interhemispheric networks were affected.

DISCUSSION

This is the first attempt to directly assess changes in functional connectivity with pharmacotherapy using MEG. Botulinum toxin might affect sensorimotor integration, leading to clinical benefit. The presence of increased interhemispheric coherence and intrahemispheric coherence points to the importance of global and local networks in the pathophysiology of dystonia.

Magnetoencephalography as a Tool in Psychiatric Research: Current Status and Perspective

The application of neuroimaging to provide mechanistic insights into circuit dysfunctions in major psychiatric conditions and the development of biomarkers are core challenges in current psychiatric research. We propose that recent technological and analytic advances in magnetoencephalography (MEG), a technique that allows measurement of neuronal events directly and noninvasively with millisecond resolution, provides novel opportunities to address these fundamental questions. Because of its potential in delineating normal and abnormal brain dynamics, we propose that MEG provides a crucial tool to advance our understanding of pathophysiological mechanisms of major neuropsychiatric conditions, such as schizophrenia, autism spectrum disorders, and the dementias. We summarize the mechanisms underlying the generation of MEG signals and the tools available to reconstruct generators and underlying networks using advanced source-reconstruction techniques. We then surveyed recent studies that have used MEG to examine aberrant rhythmic activity in neuropsychiatric disorders. This was followed by links with preclinical research that has highlighted possible neurobiological mechanisms, such as disturbances in excitation/inhibition parameters, that could account for measured changes in neural oscillations. Finally, we discuss challenges as well as novel methodological developments that could pave the way for widespread application of MEG in translational research with the aim of developing biomarkers for early detection and diagnosis.

The neural mechanisms of re-experiencing physical fatigue sensation: a magnetoencephalography study

It has been hypothesized that fatigue sensation impairs the ability and efficiency to perform activities and can be a cause of fatigue itself. As such, it is important to clarify the neural mechanisms of fatigue sensation. The re-experiencing of mental fatigue sensation involves brain regions including Brodmann's area (BA) 40, BA 39, and the pulvinar nucleus. In the present study, we examined neural activity caused by re-experiencing a physical fatigue sensation that had been experienced. Fifteen healthy male volunteers participated in fatigue and control experiments in a crossover fashion. In the fatigue experiment, participants performed a handgrip task for 10 min to induce a physical fatigue sensation and then re-experienced the physical fatigue sensation during magnetoencephalography (MEG) session. In the control experiment, they did not perform the handgrip task but re-experienced the sensation without physical fatigue in an MEG session. Neural activity related to re-experiencing physical fatigue sensations of the right hand (right condition), left hand (left condition), and related to listening to the auditory cues (sound condition) was assessed using spatial filtering analyses of the MEG data. Changes in oscillatory band power in some brain regions, including BA 40, were common between the right and left conditions. A part of the neural activity related to the re-experiencing physical fatigue sensation, such as the decrease in alpha (8-13 Hz) band power in the BA 40, was also observed in the sound condition. These findings may help to understand the neural mechanisms related to intentionally and unintentionally re-experiencing physical fatigue sensation.

Eyes Open on Sleep and Wake: In Vivo to In Silico Neural Networks

Functional and effective connectivity of cortical areas are essential for normal brain function under different behavioral states. Appropriate cortical activity during sleep and wakefulness is ensured by the balanced activity of excitatory and inhibitory circuits. Ultimately, fast, millisecond cortical rhythmic oscillations shape cortical function in time and space. On a much longer time scale, brain function also depends on prior sleep-wake history and circadian processes. However, much remains to be established on how the brain operates at the neuronal level in humans during sleep and wakefulness. A key limitation of human neuroscience is the difficulty in isolating neuronal excitation/inhibition drive in vivo. Therefore, computational models are noninvasive approaches of choice to indirectly access hidden neuronal states. In this review, we present a physiologically driven in silico approach, Dynamic Causal Modelling (DCM), as a means to comprehend brain function under different experimental paradigms. Importantly, DCM has allowed for the understanding of how brain dynamics underscore brain plasticity, cognition, and different states of consciousness. In a broader perspective, noninvasive computational approaches, such as DCM, may help to puzzle out the spatial and temporal dynamics of human brain function at different behavioural states.

Development of Three-Dimensional Perception in Human Infants

The play of light on the retina contains multiple sources of information about the three-dimensional (3D) structure of the world. Some of the best information is derived from differencing operations that act on the images that result from the two eyes’ laterally displaced vantage points. Other information is available in systematic retinal patterns of local texture and motion cues. This article describes what is currently known about the development of sensitivity to these binocular and monocular cues for depth in human infants, and it places the results in the context of what is known about the underlying neural mechanisms from work in nonhuman primates and human neuroimaging studies.

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.

The neural mechanisms of re-experiencing mental fatigue sensation: a magnetoencephalography study

There have been several studies which have tried to clarify the neural mechanisms of fatigue sensation; however fatigue sensation has multiple aspects. We hypothesized that past experience related to fatigue sensation is an important factor which contributes to future formation of fatigue sensation through the transfer to memories that are located within specific brain structures. Therefore, we aimed to investigate the neural mechanisms of fatigue sensation related to memory. In the present study, we investigated the neural activity caused by re-experiencing the fatigue sensation that had been experienced during a fatigue-inducing session. Thirteen healthy volunteers participated in fatigue and non-fatigue experiments in a crossover fashion. In the fatigue experiment, they performed a 2-back test session for 40 min to induce fatigue sensation, a rest session for 15 min to recover from fatigue, and a magnetoencephalography (MEG) session in which they were asked to re-experience the state of their body with fatigue that they had experienced in the 2-back test session. In the non-fatigue experiment, the participants performed a free session for 15 min, a rest session for 15 min, and an MEG session in which they were asked to re-experience the state of their body without fatigue that they had experienced in the free session. Spatial filtering analyses of oscillatory brain activity showed that the delta band power in the left Brodmann's area (BA) 39, alpha band power in the right pulvinar nucleus and the left BA 40, and beta band power in the left BA 40 were lower when they re-experienced the fatigue sensation than when they re-experienced the fatigue-free sensation, indicating that these brain regions are related to re-experiencing the fatigue sensation. Our findings may help clarify the neural mechanisms underlying fatigue sensation.

Brain bases of language selection: MEG evidence from Arabic-English bilingual language production

Much of the world's population is bilingual, hence, language selection is a core component of language processing in a significant proportion of individuals. Though language selection has been investigated using artificial cues to language choice such as color, little is known about more ecologically valid cues. We examined with MEG the neurophysiological and behavioral effects of two natural cues: script and cultural context, hypothesizing the former to trigger more automatic language selection. Twenty Arabic-English bilinguals performed a number-naming task with a Match condition, where the cue and target language of response matched, and a Mismatch condition, with opposite instruction. The latter addressed the mechanisms responsible for overriding natural cue-language associations. Early visual responses patterned according to predictions from prior object recognition literature, while at 150–300 ms, the anterior cingulate cortex showed robust sensitivity to cue-type, with enhanced amplitudes to culture trials. In contrast, a mismatch effect for both cue-types was observed at 300–400 ms in the left inferior prefrontal cortex. Our findings provide the first characterization of the spatio-temporal profile of naturally cued language selection and demonstrate that natural but less automatic language-choice, elicited by cultural cues, does not engage the same mechanisms as the clearly unnatural language-choice of our mismatch tasks.

The phase of thalamic alpha activity modulates cortical gamma-band activity: evidence from resting-state MEG recordings

Recent findings have implicated thalamic alpha oscillations in the phasic modulation of cortical activity. However, the precise relationship between thalamic alpha oscillations and neocortical activity remains unclear. Here we show in a large sample of healthy human participants (n = 45) using spatial filtering techniques and measures of phase amplitude coupling that the amplitude of gamma-band activity in posterior medial parietal cortex is modulated by the phase of thalamic alpha oscillations during eyes-closed resting-state recordings. In addition, our findings show that gamma-band activity in visual cortex was not modulated by thalamic alpha oscillations but coupled to the phase of strong cortical alpha activity. To overcome the limitations of electromagnetic source localization we estimated conduction delays using transfer entropy and found nonspurious information transfer from thalamus to cortex. The present findings provide novel evidence for magneto-encephalography-measured phase coupling between cortical gamma-band activity and thalamic alpha oscillations, which highlight the role of phasic inhibition in the coordination of cortical activity.

Region-Specific Slowing of Alpha Oscillations is Associated with Visual-Perceptual Abilities in Children Born Very Preterm

Children born very preterm (≤32 weeks gestational age) without major intellectual or neurological impairments often express selective deficits in visual-perceptual abilities. The alterations in neurophysiological development underlying these problems, however, remain poorly understood. Recent research has indicated that spontaneous alpha oscillations are slowed in children born very preterm, and that atypical alpha-mediated functional network connectivity may underlie selective developmental difficulties in visual-perceptual ability in this group. The present study provides the first source-resolved analysis of slowing of spontaneous alpha oscillations in very preterm children, indicating alterations in a distributed set of brain regions concentrated in areas of posterior parietal and inferior temporal regions associated with visual perception, as well as prefrontal cortical regions and thalamus. We also uniquely demonstrate that slowing of alpha oscillations is associated with selective difficulties in visual-perceptual ability in very preterm children. These results indicate that region-specific slowing of alpha oscillations contribute to selective developmental difficulties prevalent in this population.

Synchronization of medial temporal lobe and prefrontal rhythms in human decision making

Optimal decision making requires that we integrate mnemonic information regarding previous decisions with value signals that entail likely rewards and punishments. The fact that memory and value signals appear to be coded by segregated brain regions, the hippocampus in the case of memory and sectors of prefrontal cortex in the case of value, raises the question as to how they are integrated during human decision making. Using magnetoencephalography to study healthy human participants, we show increased theta oscillations over frontal and temporal sensors during nonspatial decisions based on memories from previous trials. Using source reconstruction we found that the medial temporal lobe (MTL), in a location compatible with the anterior hippocampus, and the anterior cingulate cortex in the medial wall of the frontal lobe are the source of this increased theta power. Moreover, we observed a correlation between theta power in the MTL source and behavioral performance in decision making, supporting a role for MTL theta oscillations in decision-making performance. These MTL theta oscillations were synchronized with several prefrontal sources, including lateral superior frontal gyrus, dorsal anterior cingulate gyrus, and medial frontopolar cortex. There was no relationship between the strength of synchronization and the expected value of choices. Our results indicate a mnemonic guidance of human decision making, beyond anticipation of expected reward, is supported by hippocampal-prefrontal theta synchronization.

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

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

Advances in the diagnosis of anorexia nervosa and bulimia nervosa using brain imaging

INTRODUCTION: Anorexia and bulimia nervosa are severe psychiatric disorders and the availability of brain imaging techniques hold promise that those techniques will be useful in clinical practice. AREAS COVERED: In this review I describe currently available brain imaging techniques and focus on the brain imaging methods functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). Those techniques have helped describe alterations in brain circuitry in AN and BN that related to anxiety and reward processing. Novel computational models help further define brain function in relation to particular neurotransmitters. EXPERT OPINION: Brain imaging techniques are exciting methods to learn about brain function and progress has been made to identify in healthy populations brain circuits that code behaviors. These techniques have been used in AN and BN over the past decade and have improved our understanding of brain function in those disorders. Still, human brain imaging is not at a point yet where it could be used diagnostically. However, with the refinement of imaging hardware as well as improved models that describe brain function we will get closer to our aims to not only better understand the neurobiology of those disorders, but predict illness development, treatment response and long term prognosis.

Dynamic causal modeling of subcortical connectivity of language

Subcortical-cortical interactions in the language network were investigated using dynamic causal modeling of magnetoencephalographic data recorded during auditory comprehension. Participants heard sentences that either were correct or contained violations. Sentences containing violations had syntactic or prosodic violations or both. We show that a hidden source, modeling magnetically silent deep nuclei, is required to explain the data best. This is in line with recent brain imaging studies and intracranial recordings suggesting an involvement of subcortical structures in language processing. Here, the processing of syntactic and prosodic violations elicited a global increase in the amplitude of evoked responses, both at the cortical and subcortical levels. As estimated by Bayesian model averaging, this was accompanied by various changes in cortical-cortical and subcortical-cortical connectivity. The most consistent findings in relation to violations were a decrease of reentrant inputs to Heschl's gyrus (HG) and of transcallosal lateral connections. These results suggest that in conditions where one hemisphere detects a violation, possibly via fast thalamocortical (HG) loops, the intercallosal connectivity is reduced to allow independent processing of syntax (left hemisphere) and of prosody (right hemisphere). This study is the first demonstration in cognitive neuroscience that subcortical-cortical loops can be empirically investigated using noninvasive electrophysiological recordings.

Practical constraints on estimation of source extent with MEG beamformers

We aimed to determine practical constraints on the estimation of the spatial extent of neuronal activation using MEG beamformers. Correct estimation of spatial extent is a pre-requisite for accurate models of electrical activity, allows one to estimate current density, and enables non-invasive monitoring of functional recovery following stroke. The output of an MEG beamformer is maximum when the correct source model is used, so that the spatial extent of a source can in principal be determined through evaluation of different source models with the beamformer. Here, we simulated 275-channel MEG data using sources of varying spatial extents that followed the cortical geometry. These data were subsequently used to estimate the spatial extent of generic disc elements without knowledge of the underlying surface, and we compared these results to estimates based on cortical surface geometry (with and without error in surface location). We found that disc-shaped source models are too simplistic, particularly for areas with high curvature. For areas with low curvature spatial extent was underestimated, although on average there was a linear relationship between the true and estimated extent. In contrast, cortical surface models gave accurate predictions of spatial extent. However, adding small errors (>2 mm) to the estimated location of the cortical surface abolished this relationship between true and estimated extent, implying that accurate co-registration is needed with such models. Our results show that models exploiting surface information are necessary in order to model spatial extent and in turn current density, but in order to render such models applicable in practical situations, the accuracy of the cortical surface model itself needs to improve.

Magnetoencephalographic imaging of deep corticostriatal network activity during a rewards paradigm

The human rewards network is a complex system spanning both cortical and subcortical regions. While much is known about the functions of the various components of the network, research on the behavior of the network as a whole has been stymied due to an inability to detect signals at a high enough temporal resolution from both superficial and deep network components simultaneously. In this paper, we describe the application of magnetoencephalographic imaging (MEG) combined with advanced signal processing techniques to this problem. Using data collected while subjects performed a rewards-related gambling paradigm demonstrated to activate the rewards network, we were able to identify neural signals which correspond to deep network activity. We also show that this signal was not observable prior to filtration. These results suggest that MEG imaging may be a viable tool for the detection of deep neural activity.