Magnetoencephalography Activity Research Articles

Case Report: Aperiodic Fluctuations of Neural Activity in the Ictal MEG of a Child With Drug-Resistant Fronto-Temporal Epilepsy.

Successful surgical treatment of patients with focal drug-resistant epilepsy remains challenging, especially in cases for which it is difficult to define the area of cortex from which seizures originate, the seizure onset zone (SOZ). Various diagnostic methods are needed to select surgical candidates and determine the extent of resection. Interictal magnetoencephalography (MEG) with source imaging has proven to be useful for presurgical evaluation, but the use of ictal MEG data remains limited. The purpose of the present study was to determine whether pre-ictal variations of spectral properties of neural activity from ictal MEG recordings are predictive of SOZ location.We performed a 4 h overnight MEG recording in an 8-year-old child with drug-resistant focal epilepsy of suspected right fronto-temporal origin and captured one ~45-s seizure. The patient underwent a right temporal resection from the anterior temporal neocortex and amygdala to the mid-posterior temporal neocortex, sparing the hippocampus proper. She remains seizure-free 21 months postoperatively. The histopathological assessment confirmed frank focal cortical dysplasia (FCD) type IIa in the MEG-defined SOZ, which was based on source imaging of averaged ictal spikes at seizure onset. We investigated temporal changes (inter-ictal, pre-ictal, and ictal periods) together with spatial differences (SOZ vs. control regions) in spectral parameters of background brain activity, namely the aperiodic broadband offset and slope, and assessed how they confounded the interpretation of apparent variations of signal power in typical electrophysiological bands. Our data show that the SOZ was associated with a higher aperiodic offset and exponent during the seizure compared to control regions. Both parameters increased in all regions from 2 min before the seizure onwards. Regions anatomically closer to the SOZ also expressed higher values compared to contralateral regions, potentially indicating ictal spread. We also show that narrow-band power changes were caused by these fluctuations in the aperiodic component of ongoing brain activity. Our results indicate that the broadband aperiodic component of ongoing brain activity cannot be reduced to background noise of no physiological interest, and rather may be indicative of the neuropathophysiology of the SOZ. We believe these findings will inspire future studies of ictal MEG cases and confirm their significance.

MEG signatures of long-term effects of agreement and disagreement with the majority

People often change their beliefs by succumbing to an opinion of others. Such changes are often referred to as effects of social influence. While some previous studies have focused on the reinforcement learning mechanisms of social influence or on its internalization, others have reported evidence of changes in sensory processing evoked by social influence of peer groups. In this study, we used magnetoencephalographic (MEG) source imaging to further investigate the long-term effects of agreement and disagreement with the peer group. The study was composed of two sessions. During the first session, participants rated the trustworthiness of faces and subsequently learned group rating of each face. In the first session, a neural marker of an immediate mismatch between individual and group opinions was found in the posterior cingulate cortex, an area involved in conflict-monitoring and reinforcement learning. To identify the neural correlates of the long-lasting effect of the group opinion, we analysed MEG activity while participants rated faces during the second session. We found MEG traces of past disagreement or agreement with the peers at the parietal cortices 230 ms after the face onset. The neural activity of the superior parietal lobule, intraparietal sulcus, and precuneus was significantly stronger when the participant’s rating had previously differed from the ratings of the peers. The early MEG correlates of disagreement with the majority were followed by activity in the orbitofrontal cortex 320 ms after the face onset. Altogether, the results reveal the temporal dynamics of the neural mechanism of long-term effects of disagreement with the peer group: early signatures of modified face processing were followed by later markers of long-term social influence on the valuation process at the ventromedial prefrontal cortex.

Induced brain magnetic activities related to salient birdsong under noisy conditions.

Birdsong sounds are often used to inform visually-challenged people about the presence of basic infrastructures, and therefore need to be salient in noisy urban environments. How salient sounds are processed in the brain could inform us about the optimal birdsong in such environments. However, brain activity related to birdsong salience is not yet known. Oscillatory magnetoencephalographic (MEG) activities and subjective salience induced by six birdsongs under three background noise conditions were measured. Thirteen participants completed the MEG measurements and 11 participants took part in the paired-comparison tests. We estimated the power of induced oscillatory activities, and explored the relationship between subjective salience of birdsongs and the power of induced activities using sparse regression analysis. According to sparse regression analysis, the subjective salience was explained by the power of induced alpha (8-13 Hz) in the frontal region, induced beta (13-30 Hz) in the occipital region, and induced gamma (30-50 Hz) in the parietal region. The power of the frontal alpha and parietal gamma activities significantly varied across both birds and noise conditions. These results indicate that frontal alpha activity is related to the salience of birdsong and that parietal gamma activity is related to differences in salience across noisy environments. These results suggest that salient birdsong under a noisy environment activates the bottom-up attention network.

Portable neuromodulation induces neuroplasticity to re-activate motor function recovery from brain injury: a high-density MEG case study

BackgroundIn a recent high-profile case study, we used functional magnetic resonance imaging (fMRI) to monitor improvements in motor function related to neuroplasticity following rehabilitation for severe traumatic brain injury (TBI). The findings demonstrated that motor function improvements can occur years beyond current established limits. The current study extends the functional imaging investigation to characterize neuromodulation effects on neuroplasticity to further push the limits.MethodsCanadian Soldier Captain (retired) Trevor Greene (TG) survived a severe open-TBI when attacked with an axe during a 2006 combat tour in Afghanistan. TG has since continued intensive daily rehabilitation to recover motor function, experiencing an extended plateau using conventional physical therapy. To overcome this plateau, we paired translingual neurostimulation (TLNS) with the continuing rehabilitation program.ResultsCombining TLNS with rehabilitation resulted in demonstrable clinical improvements along with corresponding changes in movement evoked electro-encephalography (EEG) activity. High-density magneto-encephalography (MEG) characterized cortical activation changes in corresponding beta frequency range (27 Hz). MEG activation changes corresponded with reduced interhemispheric inhibition in the post-central gyri regions together with increased right superior/middle frontal activation suggesting large scale network level changes.ConclusionsThe findings provide valuable insight into the potential importance of non-invasive neuromodulation to enhance neuroplasticity mechanisms for recovery beyond the perceived limits of rehabilitation.

Individual pain sensitivity is associated with resting-state cortical activities in healthy individuals but not in patients with migraine: a magnetoencephalography study

BackgroundPain sensitivity may determine the risk, severity, prognosis, and efficacy of treatment of clinical pain. Magnetic resonance imaging studies have linked thermal pain sensitivity to changes in brain structure. However, the neural correlates of mechanical pain sensitivity remain to be clarified through investigation of direct neural activities on the resting-state cortical oscillation and synchrony.MethodsWe recorded the resting-state magnetoencephalographic (MEG) activities of 27 healthy individuals and 30 patients with episodic migraine (EM) and analyzed the source-based oscillatory powers and functional connectivity at 2 to 59 Hz in pain-related cortical regions, which are the bilateral anterior cingulate cortex (ACC), medial orbitofrontal (MOF) cortex, lateral orbitofrontal (LOF) cortex, insula cortex, primary somatosensory cortex (SI), primary motor cortex (MI), and posterior cingulate cortex (PCC). The mechanical punctate pain threshold (MPPT) was obtained at the supraorbital area (the first branch of the trigeminal nerve dermatome, V1) and the forearm (the first thoracic nerve dermatome, T1) and further correlated with MEG measures.ResultsThe MPPT is inversely correlated with the resting-state relative powers of gamma oscillation in healthy individuals (all corrected P < 0.05). Specifically, inverse correlation was noted between the MPPT at V1 and gamma powers in the bilateral insula (r = − 0.592 [left] and − 0.529 [right]), PCC (r = − 0.619 and − 0.541) and MI (r = − 0.497 and − 0.549) and between the MPPT at T1 and powers in the left PCC (r = − 0.561) and bilateral MI (r = − 0.509 and − 0.520). Furthermore, resting-state functional connectivity at the delta to beta bands, especially between frontal (MOF, ACC, LOF, and MI), parietal (PCC), and sensorimotor (bilateral SI and MI) regions, showed a positive correlation with the MPPT at V1 and T1 (all corrected P < 0.05). By contrast, in patients with EM, the MPPT was not associated with resting-state cortical activities.ConclusionsPain sensitivity in healthy individuals is associated with the resting-state gamma oscillation and functional connectivity in pain-related cortical regions. Further studies must be conducted in a large population to confirm whether resting-state cortical activities can be an objective measurement of pain sensitivity in individuals without clinical pain.

Covariation Between Brain Function (MEG) and Structure (DTI) Differentiates Adolescents with Fetal Alcohol Spectrum Disorder from Typically Developing Controls

The behavioral, cognitive, and sensory difficulties experienced by individuals exposed to alcohol prenatally currently fail to provide early identification for fetal alcohol spectrum disorder (FASD). Attempting to advance this pursuit through a multivariate analysis, we collected magnetoencephalography (MEG) data during auditory, somatosensory, visual paradigms, DTI, and behavior in adolescents ages 12–21 years (FASD: N = 13; HC: N = 20). We assessed the relationship between brain function (MEG) and structure (fractional anisotropy (FA)) utilizing joint independent component analysis (jICA), and examined how this measure relates to behavior. We identified 5 components that reveal group differences in co-variation between MEG and FA. For example, component 5 (t = 3.162, p = 0.003, Hedges’ g = 1.13) contained MEG activity corresponding to all three sensory modalities, most robustly in occipital lobes, and DTI-derived cerebellar FA, underlying the role of the cerebellum in sensory processing. Further, in HCs component 5’s loading factor was positively correlated with verbal ability (r = 0.646, p = 0.002), indicating higher covariation was associated with better verbal performance. Interestingly, this relationship is lacking in FASD (r = 0.009, p = 0.979). Also, component 5 loading factor negatively correlated with impulsivity (r = −0.527, p = 0.002), indicating that stronger function-structure associations were associated with individuals with lower impulsivity. These findings suggest that multimodal integration of MEG and FA provides novel associations between structure and function that may help differentiate adolescents with FASD from HC.

Inefficient visual search strategies in the first-episode schizophrenia spectrum

BackgroundKnowledge is lacking regarding deficits in selective attention and their underlying biological mechanisms during early stages of schizophrenia. The present study examined the N2pc, a neurophysiological index of covert spatial attention, and its cortical sources at first psychotic episode in the schizophrenia spectrum (FESz). MethodsNeurophysiological responses measured simultaneously with magnetoencephalography (MEG) and electroencephalography (EEG) during pop-out and serial search tasks were compared between 32 FESz and 32 matched healthy controls (HC). Mean scalp-recorded N2pc was measured from a cluster of posterior-lateral EEG electrodes. Cortical source-resolved MEG activity contributing to the N2pc signal was derived for the intraparietal sulcus (IPS) and lateral occipital complex (LOC). ResultsGroup differences in EEG N2pc varied by task demand. FESz exhibited reduced N2pc amplitude during pop-out (p < .01), but not serial search (p = .11). Furthermore, group differences in N2pc-related MEG cortical activity varied by task demand and cortical region. Compared to HC, FESz exhibited greater IPS during serial search (p < .01). DiscussionReductions in EEG N2pc amplitude indicate an impairment of visuo-spatial attention evident at an individual's first psychotic episode, specifically during conditions emphasizing bottom-up processing. Examination of its cortical sources with MEG revealed that, compared to HC, FESz engaged parietal structures to a greater extent during the serial search condition. This pattern suggests a less efficient, more resource intensive strategy employed by FESz in response to a minimal demand on attention. The greater reliance on this controlled attentional network may negatively impact real-world functions with much greater complexity and attentional demands.

A multimodal magnetoencephalography 7\u2009T fMRI and 7\u2009T proton MR spectroscopy study in first episode psychosis

We combined magnetoencephalography (MEG), 7 T proton magnetic resonance spectroscopy (MRS), and 7 T fMRI during performance of a task in a group of 23 first episode psychosis (FEP) patients and 26 matched healthy controls (HC). We recorded both the auditory evoked response to 40 Hz tone clicks and the resting state in MEG. Neurometabolite levels were obtained from the anterior cingulate cortex (ACC). The fMRI BOLD response was obtained during the Stroop inhibitory control task. FEP showed a significant increase in resting state low frequency theta activity (p < 0.05; Cohen d = 0.69), but no significant difference in the 40 Hz auditory evoked response compared to HC. An across-groups whole brain analysis of the fMRI BOLD response identified eight regions that were significantly activated during task performance (p < 0.01, FDR-corrected); the mean signal extracted from those regions was significantly different between the groups (p = 0.0006; d = 1.19). In the combined FEP and HC group, there was a significant correlation between the BOLD signal during task performance and MEG resting state low frequency activity (p < 0.05). In FEP, we report significant alteration in resting state low frequency MEG activity, but no alterations in auditory evoked gamma band response, suggesting that the former is a more robust biomarker of early psychosis. There were no correlations between gamma oscillations and GABA levels in either HC or FEP. Finally, in this study, each of the three imaging modalities differentiated FEP from HC; fMRI with good and MEG and MRS with moderate effect size.

Association between tissue hypoxia, perfusion restrictions, and microvascular architecture alterations with lesion-induced impairment of neurovascular coupling

Functional magnetic resonance imaging (fMRI) has been mainly utilized for the preoperative localization of eloquent cortical areas. However, lesion-induced impairment of neurovascular coupling (NVC) in the lesion border zone may lead to false-negative fMRI results. The purpose of this study was to determine physiological factors impacting the NVC. Twenty patients suffering from brain lesions were preoperatively examined using multimodal neuroimaging including fMRI, magnetoencephalography (MEG) during language or sensorimotor tasks (depending on lesion location), and a novel physiologic MRI approach for the combined quantification of oxygen metabolism, perfusion state, and microvascular architecture. Congruence of brain activity patterns between fMRI and MEG were found in 13 patients. In contrast, we observed missing fMRI activity in perilesional cortex that demonstrated MEG activity in seven patients, which was interpreted as lesion-induced impairment of NVC. In these brain regions with impaired NVC, physiologic MRI revealed significant brain tissue hypoxia, as well as significantly decreased macro- and microvascular perfusion and microvascular architecture. We demonstrated that perilesional hypoxia with reduced vascular perfusion and architecture is associated with lesion-induced impairment of NVC. Our physiologic MRI approach is a clinically applicable method for preoperative risk assessment for the presence of false-negative fMRI results and may prevent severe postoperative functional deficits.

Spontaneous MEG activity of the cerebral cortex during eyes closed and open discriminates Alzheimer\u2019s disease from cognitively normal older adults

This study aimed to examine whether magnetoencephalography (MEG) is useful to detect early stage Alzheimer’s disease (AD). We analyzed MEG data from the early stage AD group (n = 20; 6 with mild cognitive impairment due to AD and 14 with AD dementia) and cognitively normal control group (NC, n = 27). MEG was recorded during resting eyes closed (EC) and eyes open (EO), and the following 6 values for each of 5 bands (θ1: 4-6, θ2: 6-8, α1: 8-10, α2: 10-13, β: 13-20 Hz) in the cerebral 68 regions were compared between the groups: (1) absolute power during EC and (2) EO, (3) whole cerebral normalization (WCN) power during EC and (4) EO, (5) difference of the absolute powers between the EC and EO conditions (the EC-EO difference), and (6) WCN value of the EC-EO difference. We found significant differences between the groups in the WCN powers during the EO condition, and the EC-EO differences. Using a Support Vector Machine classifier, a discrimination accuracy of 83% was obtained and an AUC in an ROC analysis was 0.91. This study demonstrates that MEG during resting EC and EO is useful in discriminating between early stage AD and NC.

Corneo-retinal-dipole and eyelid-related eye artifacts can be corrected offline and online in electroencephalographic and magnetoencephalographic signals

Eye movements and blinks contaminate electroencephalographic (EEG) and magnetoencephalographic (MEG) activity. As the eye moves, the corneo-retinal dipole (CRD) and eyelid introduce potential/field changes in the M/EEG activity. These eye artifacts can affect a brain-computer interface and thereby impinge on neurofeedback quality. Here, we introduce the sparse generalized eye artifact subspace subtraction (SGEYESUB) algorithm that can correct these eye artifacts offline and in real time. We provide an open source reference implementation of the algorithm and the paradigm to obtain calibration data. Once the algorithm is fitted to calibration data (approx. 5 ​min), the eye artifact correction reduces to a matrix multiplication. We compared SGEYESUB with 4 state-of-the-art algorithms using M/EEG activity of 69 participants. SGEYESUB achieved the best trade-off between correcting the eye artifacts and preserving brain activity. Residual correlations between the corrected M/EEG channels and the eye artifacts were below 0.1. Error-related and movement-related cortical potentials were attenuated by less than 0.5 ​μV. Our results furthermore demonstrate that CRD and eyelid-related artifacts can be assumed to be stationary for at least 1–1.5 ​h, validating the feasibility of our approach in offline and online eye artifact correction.

Neural Evidence for the Prediction of Animacy Features during Language Comprehension: Evidence from MEG and EEG Representational Similarity Analysis.

It has been proposed that people can generate probabilistic predictions at multiple levels of representation during language comprehension. We used magnetoencephalography (MEG) and electroencephalography (EEG), in combination with representational similarity analysis, to seek neural evidence for the prediction of animacy features. In two studies, MEG and EEG activity was measured as human participants (both sexes) read three-sentence scenarios. Verbs in the final sentences constrained for either animate or inanimate semantic features of upcoming nouns, and the broader discourse context constrained for either a specific noun or for multiple nouns belonging to the same animacy category. We quantified the similarity between spatial patterns of brain activity following the verbs until just before the presentation of the nouns. The MEG and EEG datasets revealed converging evidence that the similarity between spatial patterns of neural activity following animate-constraining verbs was greater than following inanimate-constraining verbs. This effect could not be explained by lexical-semantic processing of the verbs themselves. We therefore suggest that it reflected the inherent difference in the semantic similarity structure of the predicted animate and inanimate nouns. Moreover, the effect was present regardless of whether a specific word could be predicted, providing strong evidence for the prediction of coarse-grained semantic features that goes beyond the prediction of individual words.SIGNIFICANCE STATEMENT Language inputs unfold very quickly during real-time communication. By predicting ahead, we can give our brains a "head start," so that language comprehension is faster and more efficient. Although most contexts do not constrain strongly for a specific word, they do allow us to predict some upcoming information. For example, following the context of "they cautioned the…," we can predict that the next word will be animate rather than inanimate (we can caution a person, but not an object). Here, we used EEG and MEG techniques to show that the brain is able to use these contextual constraints to predict the animacy of upcoming words during sentence comprehension, and that these predictions are associated with specific spatial patterns of neural activity.

Accuracy analysis of fMRI and MEG activations determined by intraoperative mapping

By looking at how the accuracy of preoperative brain mapping methods vary according to differences in the distance from the activation clusters used for the analysis, the present study aimed to elucidate how preoperative functional neuroimaging may be used in such a way that maximizes the mapping accuracy. The eloquent function of 19 patients with a brain tumor or cavernoma was mapped prior to resection with both functional MRI (fMRI) and magnetoencephalography (MEG). The mapping results were then validated using direct cortical stimulation mapping performed immediately after craniotomy and prior to resection. The subset of patients with equivalent MEG and fMRI tasks performed for motor (n = 14) and language (n = 12) were evaluated as both individual and combined predictions. Furthermore, the distance resulting in the maximum accuracy, as evaluated by the J statistic, was determined by plotting the sensitivities and specificities against a linearly increasing distance threshold. fMRI showed a maximum mapping accuracy at 5 mm for both motor and language mapping. MEG showed a maximum mapping accuracy at 40 mm for motor and 15 mm for language mapping. At the standard 10-mm distance used in the literature, MEG showed a greater specificity than fMRI for both motor and language mapping but a lower sensitivity for motor mapping. Combining MEG and fMRI showed a maximum accuracy at 15 mm and 5 mm-MEG and fMRI distances, respectively-for motor mapping and at a 10-mm distance for both MEG and fMRI for language mapping. For motor mapping, combining MEG and fMRI at the optimal distances resulted in a greater accuracy than the maximum accuracy of the individual predictions. This study demonstrates that the accuracy of language and motor mapping for both fMRI and MEG is heavily dependent on the distance threshold used in the analysis. Furthermore, combining MEG and fMRI showed the potential for increased motor mapping accuracy compared to when using the modalities separately.Clinical trial registration no.: NCT01535430 (clinicaltrials.gov).

Interictal magnetoencephalography in parietal lobe epilepsy – Comparison of equivalent current dipole and beamformer (SAMepi) analysis

ObjectiveTo evaluate a novel analysis method (SAMepi) in the localization of interictal epileptiform magnetoencephalographic (MEG) activity in parietal lobe epilepsy (PLE) patients in comparison with equivalent current dipole (ECD) analysis. MethodsWe analyzed the preoperative interictal MEG of 17 operated PLE patients utilizing visual analysis and: (1) ECD with a spherical conductor model; (2) ECD with a boundary element method (BEM) conductor model; and (3) SAMepi – a kurtosis beamformer method. Localization results were compared between the three methods, to the location of the resection and to the clinical outcome. ResultsFourteen patients had an epileptiform finding in the visual analysis; SAMepi detected spikes in 11 of them. A unifocal finding in both the ECD and in the SAMepi analysis was associated with a better chance of seizure-freedom (p = 0.02). There was no significant difference in the distances from the unifocal MEG localizations to the nearest border of the resection between the different analysis methods. ConclusionsLocalizations of unifocal interictal spikes detected by SAMepi did not significantly differ from the conventional ECD localizations. SignificanceSAMepi – a novel semiautomatic analysis method – is useful in localizing interictal epileptiform MEG activity in the presurgical evaluation of parietal lobe epilepsy patients.

Dissociable neural effects of temporal expectations due to passage of time and contextual probability

The human brain is equipped with complex mechanisms to track the changing probability of events in time. While the passage of time itself usually leads to a mounting expectation, context can provide additional information about when events are likely to happen. In this study we dissociate these two sources of temporal expectation in terms of their neural correlates and underlying brain connectivity patterns. We analysed magnetoencephalographic (MEG) data acquired from N = 24 healthy participants listening to auditory stimuli. These stimuli could be presented at different temporal intervals but occurred most often at intermediate intervals, forming a contextual probability distribution. Evoked MEG response amplitude was sensitive to both passage of time (time elapsed since the cue) and contextual probability, albeit at different latencies: the effects of passage of time were observed earlier than the effects of context. The underlying sources of MEG activity were also different across the two types of temporal prediction: the effects of passage of time were localised to early auditory regions and superior temporal gyri, while context was additionally linked to activity in inferior parietal cortices. Finally, these differences were modelled using biophysical (dynamic causal) modelling: passage of time was explained in terms of widespread gain modulation and decreased prediction error signalling at lower levels of the hierarchy, while contextual expectation led to more localised gain modulation and decreased prediction error signalling at higher levels of the hierarchy. These results present a comprehensive account of how independent sources of temporal prediction may be differentially expressed in cortical circuits.

Evidence that alpha blocking is due to increases in system-level oscillatory damping not neuronal population desynchronisation

The attenuation of the alpha rhythm following eyes-opening (alpha blocking) is among the most robust features of the human electroencephalogram with the prevailing view being that it is caused by changes in neuronal population synchrony. To further study the basis for this phenomenon we use theoretically motivated fixed-order Auto-Regressive Moving-Average (ARMA) time series modelling to study the oscillatory dynamics of spontaneous alpha-band electroencephalographic activity in eyes-open and eyes-closed conditions and its modulation by the NMDA antagonist ketamine. We find that the reduction in alpha-band power between eyes-closed and eyes-open states is explicable in terms of an increase in the damping of stochastically perturbed alpha-band relaxation oscillatory activity. These changes in damping are putatively modified by the antagonism of NMDA-mediated glutamatergic neurotransmission but are not directly driven by changes in input to cortex nor by reductions in the phase synchronisation of populations of near identical oscillators. These results not only provide a direct challenge to the dominant view of the role that thalamus and neuronal population de-/synchronisation have in the genesis and modulation of alpha electro-/magnetoencephalographic activity but also suggest potentially important physiological determinants underlying its dynamical control and regulation.

A dual role of prestimulus spontaneous neural activity in visual object recognition

Vision relies on both specific knowledge of visual attributes, such as object categories, and general brain states, such as those reflecting arousal. We hypothesized that these phenomena independently influence recognition of forthcoming stimuli through distinct processes reflected in spontaneous neural activity. Here, we recorded magnetoencephalographic (MEG) activity in participants (N = 24) who viewed images of objects presented at recognition threshold. Using multivariate analysis applied to sensor-level activity patterns recorded before stimulus presentation, we identified two neural processes influencing subsequent subjective recognition: a general process, which disregards stimulus category and correlates with pupil size, and a specific process, which facilitates category-specific recognition. The two processes are doubly-dissociable: the general process correlates with changes in criterion but not in sensitivity, whereas the specific process correlates with changes in sensitivity but not in criterion. Our findings reveal distinct mechanisms of how spontaneous neural activity influences perception and provide a framework to integrate previous findings.

Magnetoencephalographic (MEG) brain activity during a mental flexibility task suggests some shared neurobiology in children with neurodevelopmental disorders

BackgroundChildren with neurodevelopmental disorders (NDDs) exhibit a shared phenotype that involves executive dysfunctions including impairments in mental flexibility (MF). It is of interest to understand if this phenotype stems from some shared neurobiology.MethodsTo investigate this possibility, we used magnetoencephalography (MEG) neuroimaging to compare brain activity in children (n = 88; 8–15 years) with autism spectrum disorders (ASD), attention deficit hyperactivity disorder (ADHD) and obsessive-compulsive disorder (OCD), as they completed a set-shifting/mental flexibility task.ResultsNeuroimaging results revealed a similar parietal activation profile across the NDD, groups suggesting a link to their shared phenotype. Differences in frontal activity differentiated the three clinical groups. Brain-behaviour analyses showed a link with repetitive behaviours suggesting shared dysfunction in the associative loop of the corticostriatal system.ConclusionOur study supports the notion that NDDs may exist along a complex phenotypic/biological continuum. All NDD groups showed a sustained parietal activity profile suggesting that they share a strong reliance on the posterior parietal cortices to complete the mental flexibility task; future studies could elucidate whether this is due to delayed brain development or compensatory functioning. The differences in frontal activity may play a role in differentiating the NDDs. The OCD group showed sustained prefrontal activity that may be reflective of hyperfrontality. The ASD group showed reduced frontal activation suggestive of frontal dysfunction and the ADHD group showed an extensive hypoactivity that included frontal and parietal regions. Brain-behaviour analyses showed a significant correlation with repetitive behaviours which may reflect dysfunction in the associative loop of the corticostriatal system, linked to inflexible behaviours.

Detecting Pre-Stimulus Source-Level Effects on Object Perception with Magnetoencephalography.

Pre-stimulus oscillatory brain activity influences upcoming perception. The characteristics of this pre-stimulus activity can predict whether a near-threshold stimulus will be perceived or not perceived, but can they also predict which one of two competing stimuli with different perceptual contents is perceived? Ambiguous visual stimuli, which can be seen in one of two possible ways at a time, are ideally suited to investigate this question. Magnetoencephalography (MEG) is a neurophysiological measurement technique that records magnetic signals emitted as a result of brain activity. The millisecond temporal resolution of MEG allows for a characterization of oscillatory brain states from as little as 1 second of recorded data. Presenting an empty screen around 1 second prior to the ambiguous stimulus onset therefore provides a time window in which one can investigate whether pre-stimulus oscillatory activity biases the content of upcoming perception, as indicated by participants'reports. The spatial resolution of MEG is not excellent, but sufficient to localise sources of brain activity at the centimetre scale. Source reconstruction of MEG activity then allows for testing hypotheses about the oscillatory activity of specific regions of interest, as well as the time- and frequency-resolved connectivity between regions of interest. The described protocol enables a better understanding of the influence of spontaneous, ongoing brain activity on visual perception.

Non-negative Matrix Factorization Reveals Resting-State Cortical Alpha Network Abnormalities in the First-Episode Schizophrenia Spectrum

BackgroundLittle is known about neural oscillatory dynamics in first-episode psychosis. Pathophysiology of functional connectivity can be measured through network activity of alpha oscillations, reflecting long-range communication between distal brain regions. MethodsResting magnetoencephalographic activity was collected from 31 individuals with first-episode schizophrenia spectrum psychosis and 22 healthy control individuals. Activity was projected to the realistic cortical surface, based on structural magnetic resonance imaging. The first principal component of activity in 40 Brodmann areas per hemisphere was Hilbert transformed within the alpha range. Non-negative matrix factorization was applied to single-trial alpha phase-locking values from all subjects to determine alpha networks. Within networks, energy and entropy were compared. ResultsFour cortical alpha networks were pathological in individuals with first-episode schizophrenia spectrum psychosis. The networks involved the bilateral anterior and posterior cingulate; left auditory, medial temporal, and cingulate cortex; right inferior frontal gyrus and widespread areas; and right posterior parietal cortex and widespread areas. Energy and entropy were associated with the Positive and Negative Syndrome Scale total and thought disorder factors for the first three networks. In addition, the left posterior temporal network was associated with positive and negative factors, and the right inferior frontal network was associated with the positive factor. ConclusionsMachine learning network analysis of resting alpha-band neural activity identified several aberrant networks in individuals with first-episode schizophrenia spectrum psychosis, including the left temporal, right inferior frontal, right posterior parietal, and bilateral cingulate cortices. Abnormal long-range alpha communication is evident at the first presentation for psychosis and may provide clues about mechanisms of dysconnectivity in psychosis and novel targets for noninvasive brain stimulation.