Comparison of DSSP and tSSS algorithms for removing artifacts from vagus nerve stimulators in magnetoencephalography data

Origin coordinate influence on performance of temporally extended signal space separation in magnetoencephalography

OBJECTIVE

Temporally extended signal space separation (tSSS) is a powerful method for artifact suppression in magnetoencephalography (MEG). Because tSSS first separates MEG signals coming from inside and outside a certain sphere, definition of the sphere origin is important. For this study, we explored the influence of origin choice on tSSS performance in spontaneous and evoked activity from epilepsy patients.

METHODS

Interictal epileptiform discharges (IEDs) and somatosensory evoked fields (SEFs) were processed with two tSSSs: one with the default origin of (0, 0, 40 mm) in the head coordinate, and the other with an individual origin estimated using each patient's anatomical magnetic resonance imaging (MRI). Equivalent current dipoles (ECDs) were calculated for the data. The ECD location and quality of estimation were compared across conditions.

RESULTS

MEG data from 21 patients revealed marginal differences in ECD location, but the estimation quality inferred from goodness of fit (GOF) and confidence volume (CV) was better for the tSSS with individual origins. This choice affected IEDs more than it affected SEFs.

CONCLUSIONS

Individual sphere model resulted in better GOF and CV.

SIGNIFICANCE

Application of tSSS using an individual origin would be more desirable when available. This parameter might influence spontaneous activity more strongly.

Binocularly suppressed stimuli induce brain activities related to aesthetic emotions

Introduction

Aesthetic emotions are a class of emotions aroused by evaluating aesthetically appealing objects or events. While evolutionary aesthetics suggests the adaptive roles of these emotions, empirical assessments are lacking. Previous neuroscientific studies have demonstrated that visual stimuli carrying evolutionarily important information induce neural responses even when presented non-consciously. To examine the evolutionary importance of aesthetic emotions, we conducted a neuroscientific study using magnetoencephalography (MEG) to measure induced neural responses to non-consciously presented portrait paintings categorised as biological and non-biological and examined associations between the induced responses and aesthetic ratings.

Methods

MEG and pre-rating data were collected from 23 participants. The pre-rating included visual analogue scales for object saliency, facial saliency, liking, and beauty scores, in addition to 'biologi-ness,' which was used for subcategorising stimuli into biological and non-biological. The stimuli were presented non-consciously using a continuous flash suppression paradigm or consciously using binocular presentation without flashing masks, while dichotomic behavioural responses were obtained (beauty or non-beauty). Time-frequency decomposed MEG data were used for correlation analysis with pre-rating scores for each category.

Results

Behavioural data revealed that saliency scores of non-consciously presented stimuli influenced dichotomic responses (beauty or non-beauty). MEG data showed that non-consciously presented portrait paintings induced spatiotemporally distributed low-frequency brain activities associated with aesthetic ratings, which were distinct between the biological and non-biological categories and conscious and non-conscious conditions.

Conclusion

Aesthetic emotion holds evolutionary significance for humans. Neural pathways are sensitive to visual images that arouse aesthetic emotion in distinct ways for biological and non-biological categories, which are further influenced by consciousness. These differences likely reflect the diversity in mechanisms of aesthetic processing, such as processing fluency, active elaboration, and predictive processing. The aesthetic processing of non-conscious stimuli appears to be characterised by fluency-driven affective processing, while top-down regulatory processes are suppressed. This study provides the first empirical evidence supporting the evolutionary significance of aesthetic processing.

Abnormal gamma phase-amplitude coupling in the parahippocampal cortex is associated with network hyperexcitability in Alzheimer's disease

While animal models of Alzheimer's disease (AD) have shown altered gamma oscillations (∼40 Hz) in local neural circuits, the low signal-to-noise ratio of gamma in the resting human brain precludes its quantification via conventional spectral estimates. Phase-amplitude coupling (PAC) indicating the dynamic integration between the gamma amplitude and the phase of low-frequency (4-12 Hz) oscillations is a useful alternative to capture local gamma activity. In addition, PAC is also an index of neuronal excitability as the phase of low-frequency oscillations that modulate gamma amplitude, effectively regulates the excitability of local neuronal firing. In this study, we sought to examine the local neuronal activity and excitability using gamma PAC, within brain regions vulnerable to early AD pathophysiology-entorhinal cortex and parahippocampus, in a clinical population of patients with AD and age-matched controls. Our clinical cohorts consisted of a well-characterized cohort of AD patients (n = 50; age, 60 ± 8 years) with positive AD biomarkers, and age-matched, cognitively unimpaired controls (n = 35; age, 63 ± 5.8 years). We identified the presence or the absence of epileptiform activity in AD patients (AD patients with epileptiform activity, AD-EPI+, n = 20; AD patients without epileptiform activity, AD-EPI-, n = 30) using long-term electroencephalography (LTM-EEG) and 1-hour long magnetoencephalography (MEG) with simultaneous EEG. Using the source reconstructed MEG data, we computed gamma PAC as the coupling between amplitude of the gamma frequency (30-40 Hz) with phase of the theta (4-8 Hz) and alpha (8-12 Hz) frequency oscillations, within entorhinal and parahippocampal cortices. We found that patients with AD have reduced gamma PAC in the left parahippocampal cortex, compared to age-matched controls. Furthermore, AD-EPI+ patients showed greater reductions in gamma PAC than AD-EPI- in bilateral parahippocampal cortices. In contrast, entorhinal cortices did not show gamma PAC abnormalities in patients with AD. Our findings demonstrate the spatial patterns of altered gamma oscillations indicating possible region-specific manifestations of network hyperexcitability within medial temporal lobe regions vulnerable to AD pathophysiology. Greater deficits in AD-EPI+ suggests that reduced gamma PAC is a sensitive index of network hyperexcitability in AD patients. Collectively, the current results emphasize the importance of investigating the role of neural circuit hyperexcitability in early AD pathophysiology and explore its potential as a modifiable contributor to AD pathobiology.

Spatiotemporal signal space separation for regions of interest: Application for extracting neuromagnetic responses evoked by deep brain stimulation

Magnetoencephalography (MEG) recordings are often contaminated by interference that can exceed the amplitude of physiological brain activity by several orders of magnitude. Furthermore, the activity of interference sources may spatially extend (known as source leakage) into the activity of brain signals of interest, resulting in source estimation inaccuracies. This problem is particularly apparent when using MEG to interrogate the effects of brain stimulation on large-scale cortical networks. In this technical report, we develop a novel denoising approach for suppressing the leakage of interference source activity into the activity representing a brain region of interest. This approach leverages spatial and temporal domain projectors for signal arising from prespecified anatomical regions of interest. We apply this denoising approach to reconstruct simulated evoked response topographies to deep brain stimulation (DBS) in a phantom recording. We highlight the advantages of our approach compared to the benchmark-spatiotemporal signal space separation-and show that it can more accurately reveal brain stimulation-evoked response topographies. Finally, we apply our method to MEG recordings from a single patient with Parkinson's disease, to reveal early cortical-evoked responses to DBS of the subthalamic nucleus.

Oscillatory characteristics of resting-state magnetoencephalography reflect pathological and symptomatic conditions of cognitive impairment

Background

Dementia and mild cognitive impairment are characterised by symptoms of cognitive decline, which are typically assessed using neuropsychological assessments (NPAs), such as the Mini-Mental State Examination (MMSE) and Frontal Assessment Battery (FAB). Magnetoencephalography (MEG) is a novel clinical assessment technique that measures brain activities (summarised as oscillatory parameters), which are associated with symptoms of cognitive impairment. However, the relevance of MEG and regional cerebral blood flow (rCBF) data obtained using single-photon emission computed tomography (SPECT) has not been examined using clinical datasets. Therefore, this study aimed to investigate the relationships among MEG oscillatory parameters, clinically validated biomarkers computed from rCBF, and NPAs using outpatient data retrieved from hospital records.

Methods

Clinical data from 64 individuals with mixed pathological backgrounds were retrieved and analysed. MEG oscillatory parameters, including relative power (RP) from delta to high gamma bands, mean frequency, individual alpha frequency, and Shannon's spectral entropy, were computed for each cortical region. For SPECT data, three pathological parameters-'severity', 'extent', and 'ratio'-were computed using an easy z-score imaging system (eZIS). As for NPAs, the MMSE and FAB scores were retrieved.

Results

MEG oscillatory parameters were correlated with eZIS parameters. The eZIS parameters associated with Alzheimer's disease pathology were reflected in theta power augmentation and slower shift of the alpha peak. Moreover, MEG oscillatory parameters were found to reflect NPAs. Global slowing and loss of diversity in neural oscillatory components correlated with MMSE and FAB scores, whereas the associations between eZIS parameters and NPAs were sparse.

Conclusion

MEG oscillatory parameters correlated with both SPECT (i.e. eZIS) parameters and NPAs, supporting the clinical validity of MEG oscillatory parameters as pathological and symptomatic indicators. The findings indicate that various components of MEG oscillatory characteristics can provide valuable pathological and symptomatic information, making MEG data a rich resource for clinical examinations of patients with cognitive impairments. SPECT (i.e. eZIS) parameters showed no correlations with NPAs. The results contributed to a better understanding of the characteristics of electrophysiological and pathological examinations for patients with cognitive impairments, which will help to facilitate their co-use in clinical application, thereby improving patient care.

Neurophysiological evidence of sensory prediction errors driving speech sensorimotor adaptation

The human sensorimotor system has a remarkable ability to quickly and efficiently learn movements from sensory experience. A prominent example is sensorimotor adaptation, learning that characterizes the sensorimotor system's response to persistent sensory errors by adjusting future movements to compensate for those errors. Despite being essential for maintaining and fine-tuning motor control, mechanisms underlying sensorimotor adaptation remain unclear. A component of sensorimotor adaptation is implicit (i.e., the learner is unaware of the learning process) which has been suggested to result from sensory prediction errors-the discrepancies between predicted sensory consequences of motor commands and actual sensory feedback. However, to date no direct neurophysiological evidence that sensory prediction errors drive adaptation has been demonstrated. Here, we examined prediction errors via magnetoencephalography (MEG) imaging of the auditory cortex during sensorimotor adaptation of speech to altered auditory feedback, an entirely implicit adaptation task. Specifically, we measured how speaking-induced suppression (SIS)--a neural representation of auditory prediction errors--changed over the trials of the adaptation experiment. SIS refers to the suppression of auditory cortical response to speech onset (in particular, the M100 response) to self-produced speech when compared to the response to passive listening to identical playback of that speech. SIS was reduced (reflecting larger prediction errors) during the early learning phase compared to the initial unaltered feedback phase. Furthermore, reduction in SIS positively correlated with behavioral adaptation extents, suggesting that larger prediction errors were associated with more learning. In contrast, such a reduction in SIS was not found in a control experiment in which participants heard unaltered feedback and thus did not adapt. In addition, in some participants who reached a plateau in the late learning phase, SIS increased (reflecting smaller prediction errors), demonstrating that prediction errors were minimal when there was no further adaptation. Together, these findings provide the first neurophysiological evidence for the hypothesis that prediction errors drive human sensorimotor adaptation.

Immediate Effects of Vagal Nerve Stimulation in Drug-Resistant Epilepsy Revealed by Magnetoencephalographic Recordings

Objective: Vagus nerve stimulation (VNS) has been a neuromodulatory option for treating drug-resistant epilepsy (DRE), but its mechanism remains unclear. To obtain insight into the mechanism by which VNS reduces epileptic seizures, the immediate effects of VNS in brain networks of DRE patients were investigated when the patients' vagal nerve stimulators were turned on. Methods: The brain network properties of 14 DRE patients with a vagal nerve stimulator and 14 healthy controls were evaluated using magnetoencephalography recordings for 6 main frequency bands. Results: Compared with healthy controls, DRE patients exhibited significant increases in functional connectivity in the theta, alpha, beta, and gamma bands and significant reductions in the small-world measure in the theta and beta bands. During periods when patients' vagal nerve stimulators were turned on, DRE patients showed significant reductions in functional connectivity in the theta and alpha bands and a significant increase in the small-world measure in the theta band when compared with periods when patients' vagal nerve stimulators were turned off. Conclusions: Our results indicate that the brain networks of DRE patients were pathologically hypersynchronous and instantaneous VNS can decrease the synchronization of brain networks of epileptic patients, which might play a key role in the mechanism by which VNS reduces epileptic seizures. In the theta band, instantaneous VNS can increase the network efficiency of DRE patients, and the increment in network efficiency may be helpful for improving brain cognitive function in epileptic patients. Impact statement For the first time, we investigated the immediate effects of vagus nerve stimulation (VNS) in the brain networks of drug-resistant epilepsy patients using magnetoencephalography. Our results show that instantaneous VNS can decrease the hypersynchronization of epileptic networks and increase the network efficiency of epileptic patients. Our results are helpful in understanding the mechanism of action by which VNS reduces epileptic seizures and improves the cognitive function in epileptic patients and the brain network reorganization caused by long-term VNS.

Spherical harmonic based noise rejection and neuronal sampling with multi-axis OPMs

In this study we explore the interference rejection and spatial sampling properties of multi-axis Optically Pumped Magnetometer (OPM) data. We use both vector spherical harmonics and eigenspectra to quantify how well an array can separate neuronal signal from environmental interference while adequately sampling the entire cortex. We found that triaxial OPMs have superb noise rejection properties allowing for very high orders of interference (L=6) to be accounted for while minimally affecting the neural space (2dB attenuation for a 60-sensor triaxial system). We show that at least 11th order (143 spatial degrees of freedom) irregular solid harmonics or 95 eigenvectors of the lead field are needed to model the neural space for OPM data (regardless of number of axes measured). This can be adequately sampled with 75-100 equidistant triaxial sensors (225-300 channels) or 200 equidistant radial channels. In other words, ordering the same number of channels in triaxial (rather than purely radial) configuration may give significant advantages not only in terms of external noise rejection but also by minimizing cost, weight and cross-talk.

Measuring Brain Response to Transcutaneous Vagus Nerve Stimulation (tVNS) using Simultaneous Magnetoencephalography (MEG)

Objective: Transcutaneous vagus nerve stimulation (tVNS) is form of non-invasive brain stimulation that delivers a sequence of electrical pulses to the auricular branch of the vagus nerve, and is used increasingly in the treatment of a number of health conditions such as epilepsy and depression. Recent research has focused on the efficacy of tVNS to treat different medical conditions, but there is little conclusive evidence concerning the optimal stimulation parameters.There are relatively few studies that have combined tVNS with a neuroimaging modality, and none that have attempted simultaneous magnetoencephalography (MEG) and tVNS due to the presence of large stimulation artifacts produced by the electrical stimulation which are many orders of magnitude larger than underlying brain activity. Approach: The aim of this study is to investigate the utility of MEG to gain insight into the regions of the brain most strongly influenced by tVNS and how variation of the stimulation parameters can affect this response in healthy participants. Main Results: We have successfully demonstrated that MEG can be used to measure brain response to tVNS. We have also shown that varying the stimulation frequency can lead to a difference in brain response, with the brain also responding in different anatomical regions depending on the frequency. Significance: The main contribution of this paper is to demonstrate the feasibility of simultaneous pulsed tVNS and MEG recording, allowing direct investigation of the changes in brain activity that result from different stimulation parameters. This may lead to the development of customised therapeutic approaches for the targeted treatment of different conditions.

The Wisdom and Vision From the ACMEGS Inaugural Decade

Concise history of fascinating magnetoencephalography (MEG) technology and catalog of very selected milestone preclinical and clinical MEG studies are provided as the background. The focus is the societal context defining a journey of MEG to and through clinical practice and formation of the American Clinical MEG Society (ACMEGS). We aspired to provide an objective historic perspective and document contributions of many professionals while focusing on the role of ACMEGS in the growth and maturation of clinical MEG field. The ACMEGS was born (2006) out of inevitability to address two vital issues-fair reimbursement and proper clinical acceptance. A beacon of accountable MEG practice and utilization is now an expanding professional organization with the highest level of competence in practice of clinical MEG and clinical credibility. The ACMEGS facilitated a favorable disposition of insurances toward MEG in the United States by combining the national replication of the grassroots efforts and teaming up with the strategic partners-particularly the American Academy of Neurology (AAN), published two Position Statements (2009 and 2017), the world's only set of MEG Clinical Practice Guidelines (CPGs; 2011) and surveys of clinical MEG practice (2011 and 2020) and use (2020). In addition to the annual ACMEGS Course (2012), we directly engaged MEG practitioners through an Invitational Summit (2019). The Society remains focused on the improvements and expansion of clinical practice, education, clinical training, and constructive engagement of vendors in these issues and pivotal studies toward additional MEG indications. The ACMEGS not only had the critical role in the progress of Clinical MEG in the United States and beyond since 2006 but positioned itself as the field leader in the future.

NUTMEG: Open Source Software for M/EEG Source Reconstruction

Neurodynamic Utility Toolbox for Magnetoencephalo- and Electroencephalography (NUTMEG) is an open-source MATLAB-based toolbox for the analysis and reconstruction of magnetoencephalography/electroencephalography data in source space. NUTMEG includes a variety of options for the user in data import, preprocessing, source reconstruction, and functional connectivity. A group analysis toolbox allows the user to run a variety of inferential statistics on their data in an easy-to-use GUI-driven format. Importantly, NUTMEG features an interactive five-dimensional data visualization platform. A key feature of NUTMEG is the availability of a large menu of interference cancelation and source reconstruction algorithms. Each NUTMEG operation acts as a stand-alone MATLAB function, allowing the package to be easily adaptable and scripted for the more advanced user for interoperability with other software toolboxes. Therefore, NUTMEG enables a wide range of users access to a complete "sensor-to- source-statistics" analysis pipeline.