Magnetoencephalography recording and analysis

Comparing the efficacy of awake and sedated MEG to TMS in mapping hand sensorimotor cortex in a clinical cohort

Non-invasive methods such as Transcranial Magnetic Stimulation (TMS) and magnetoencephalography (MEG) aid in the pre-surgical evaluation of patients with epilepsy or brain tumor to identify sensorimotor cortices. MEG requires sedation in children or patients with developmental delay. However, TMS can be applied to awake patients of all ages with any cognitive abilities. In this study, we compared the efficacy of TMS with MEG (in awake and sedated states) in identifying the hand sensorimotor areas in patients with epilepsy or brain tumors. We identified 153 patients who underwent awake- (n = 98) or sedated-MEG (n = 55), along with awake TMS for hand sensorimotor mapping as part of their pre-surgical evaluation. TMS involved stimulating the precentral gyrus and recording electromyography responses, while MEG identified the somatosensory cortex during median nerve stimulation. Awake-MEG had a success rate of 92.35 % and TMS had 99.49 % (p-value = 0.5517). However, in the sedated-MEG cohort, TMS success rate of 95.61 % was significantly higher compared to MEG's 58.77 % (p-value = 0.0001). Factors affecting mapping success were analyzed. Logistic regression across the entire cohort identified patient sedation as the lone significant predictor, contrary to age, lesion, metal, and number of antiseizure medications (ASMs). A subsequent analysis replaced sedation with anesthetic drug dosage, revealing no significant predictors impacting somatosensory mapping success under sedation. This study yields insights into the utility of TMS and MEG in mapping hand sensorimotor cortices and underscores the importance of considering factors that influence eloquent cortex mapping limitations during sedation.

A Hidden Markov Model reveals magnetoencephalography spectral frequency-specific abnormalities of brain state power and phase-coupling in neuropathic pain

Neuronal populations in the brain are engaged in a temporally coordinated manner at rest. Here we show that spontaneous transitions between large-scale resting-state networks are altered in chronic neuropathic pain. We applied an approach based on the Hidden Markov Model to magnetoencephalography data to describe how the brain moves from one activity state to another. This identified 12 fast transient (~80 ms) brain states including the sensorimotor, ascending nociceptive pathway, salience, visual, and default mode networks. Compared to healthy controls, we found that people with neuropathic pain exhibited abnormal alpha power in the right ascending nociceptive pathway state, but higher power and coherence in the sensorimotor network state in the beta band, and shorter time intervals between visits of the sensorimotor network, indicating more active time in this state. Conversely, the neuropathic pain group showed lower coherence and spent less time in the frontal attentional state. Therefore, this study reveals a temporal imbalance and dysregulation of spectral frequency-specific brain microstates in patients with neuropathic pain. These findings can potentially impact the development of a mechanism-based therapeutic approach by identifying brain targets to stimulate using neuromodulation to modify abnormal activity and to restore effective neuronal synchrony between brain states.

Exploring sex differences in alpha brain activity as a potential neuromarker associated with neuropathic pain

ABSTRACT

Alpha oscillatory activity (8-13 Hz) is the dominant rhythm in the awake brain and is known to play an important role in pain states. Previous studies have identified alpha band slowing and increased power in the dynamic pain connectome (DPC) of people with chronic neuropathic pain. However, a link between alpha-band abnormalities and sex differences in brain organization in healthy individuals and those with chronic pain is not known. Here, we used resting-state magnetoencephalography to test the hypothesis that peak alpha frequency (PAF) abnormalities are general features across chronic central and peripheral conditions causing neuropathic pain but exhibit sex-specific differences in networks of the DPC (ascending nociceptive pathway [ANP], default mode network, salience network [SN], and subgenual anterior cingulate cortex). We found that neuropathic pain (N = 25 men and 25 women) was associated with increased PAF power in the DPC compared with 50 age- and sex-matched healthy controls, whereas slower PAF in nodes of the SN (temporoparietal junction) and the ANP (posterior insula) was associated with higher trait pain intensity. In the neuropathic pain group, women exhibited lower PAF power in the subgenual anterior cingulate cortex and faster PAF in the ANP and SN than men. The within-sex analyses indicated that women had neuropathic pain-related increased PAF power in the ANP, SN, and default mode network, whereas men with neuropathic pain had increased PAF power restricted to the ANP. These findings highlight neuropathic pain-related and sex-specific abnormalities in alpha oscillations across the DPC that could underlie aberrant neuronal communication in nociceptive processing and modulation.

A New Recognition Method for the Auditory Evoked Magnetic Fields

Magnetoencephalography (MEG) is a persuasive tool to study the human brain in physiology and psychology. It can be employed to obtain the inference of change between the external environment and the internal psychology, which requires us to recognize different single trial event-related magnetic fields (ERFs) originated from different functional areas of the brain. Current recognition methods for the single trial data are mainly used for event-related potentials (ERPs) in the electroencephalography (EEG). Although the MEG shares the same signal sources with the EEG, much less interference from the other brain tissues may give the MEG an edge in recognition of the ERFs. In this work, we propose a new recognition method for the single trial auditory evoked magnetic fields (AEFs) through enhancing the signal. We find that the signal strength of the single trial AEFs is concentrated in the primary auditory cortex of the temporal lobe, which can be clearly displayed in the 2D images. These 2D images are then recognized by an artificial neural network (ANN) with 100% accuracy, which realizes the automatic recognition for the single trial AEFs. The method not only may be combined with the source estimation algorithm to improve its accuracy but also paves the way for the implementation of the brain-computer interface (BCI) with the MEG.

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

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

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

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

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

A Comprehensive Review of Magnetoencephalography (MEG) Studies for Brain Functionality in Healthy Aging and Alzheimer's Disease (AD)

Neural oscillations were established with their association with neurophysiological activities and the altered rhythmic patterns are believed to be linked directly to the progression of cognitive decline. Magnetoencephalography (MEG) is a non-invasive technique to record such neuronal activity due to excellent temporal and fair amount of spatial resolution. Single channel, connectivity as well as brain network analysis using MEG data in resting state and task-based experiments were analyzed from existing literature. Single channel analysis studies reported a less complex, more regular and predictable oscillations in Alzheimer's disease (AD) primarily in the left parietal, temporal and occipital regions. Investigations on both functional connectivity (FC) and effective (EC) connectivity analysis demonstrated a loss of connectivity in AD compared to healthy control (HC) subjects found in higher frequency bands. It has been reported from multiplex network of MEG study in AD in the affected regions of hippocampus, posterior default mode network (DMN) and occipital areas, however, conclusions cannot be drawn due to limited availability of clinical literature. Potential utilization of high spatial resolution in MEG likely to provide information related to in-depth brain functioning and underlying factors responsible for changes in neuronal waves in AD. This review is a comprehensive report to investigate diagnostic biomarkers for AD may be identified by from MEG data. It is also important to note that MEG data can also be utilized for the same pursuit in combination with other imaging modalities.

Applications of Resting State Functional MR Imaging to Traumatic Brain Injury

Traumatic brain injury (TBI) is an important public health issue. TBI includes a broad spectrum of injury severities and abnormalities. Functional MR imaging (fMR imaging), both resting state (rs) and task, has been used often in research to study the effects of TBI. Although rs-fMR imaging is not currently applicable in clinical diagnosis of TBI, computer-aided tools are making this a possibility for the future. Specifically, graph theory is being used to study the change in networks after TBI. Machine learning methods allow researchers to build models capable of predicting injury severity and recovery trajectories.

International Veterinary Epilepsy Task Force recommendations for a veterinary epilepsy-specific MRI protocol

Epilepsy is one of the most common chronic neurological diseases in veterinary practice. Magnetic resonance imaging (MRI) is regarded as an important diagnostic test to reach the diagnosis of idiopathic epilepsy. However, given that the diagnosis requires the exclusion of other differentials for seizures, the parameters for MRI examination should allow the detection of subtle lesions which may not be obvious with existing techniques. In addition, there are several differentials for idiopathic epilepsy in humans, for example some focal cortical dysplasias, which may only apparent with special sequences, imaging planes and/or particular techniques used in performing the MRI scan. As a result, there is a need to standardize MRI examination in veterinary patients with techniques that reliably diagnose subtle lesions, identify post-seizure changes, and which will allow for future identification of underlying causes of seizures not yet apparent in the veterinary literature.

There is a need for a standardized veterinary epilepsy-specific MRI protocol which will facilitate more detailed examination of areas susceptible to generating and perpetuating seizures, is cost efficient, simple to perform and can be adapted for both low and high field scanners. Standardisation of imaging will improve clinical communication and uniformity of case definition between research studies. A 6–7 sequence epilepsy-specific MRI protocol for veterinary patients is proposed and further advanced MR and functional imaging is reviewed.