Reliable recording and analysis of MEG-based corticokinematic coherence in the presence of strong magnetic artifacts

Cortical networks show characteristic recruitment patterns after somatosensory stimulation by pneumatically evoked repetitive hand movements in newborn infants

Controlled assessment of functional cortical networks is an unmet need in the clinical research of noncooperative subjects, such as infants. We developed an automated, pneumatic stimulation method to actuate naturalistic movements of an infant’s hand, as well as an analysis pipeline for assessing the elicited electroencephalography (EEG) responses and related cortical networks. Twenty newborn infants with perinatal asphyxia were recruited, including 7 with mild-to-moderate hypoxic–ischemic encephalopathy (HIE). Statistically significant corticokinematic coherence (CKC) was observed between repetitive hand movements and EEG in all infants, peaking near the contralateral sensorimotor cortex. CKC was robust to common sources of recording artifacts and to changes in vigilance state. A wide recruitment of cortical networks was observed with directed phase transfer entropy, also including areas ipsilateral to the stimulation. The extent of such recruited cortical networks was quantified using a novel metric, Spreading Index, which showed a decrease in 4 (57%) of the infants with HIE. CKC measurement is noninvasive and easy to perform, even in noncooperative subjects. The stimulation and analysis pipeline can be fully automated, including the statistical evaluation of the cortical responses. Therefore, the CKC paradigm holds great promise as a scientific and clinical tool for controlled assessment of functional cortical networks.

More comprehensive proprioceptive stimulation of the hand amplifies its cortical processing

Corticokinematic coherence (CKC) quantifies the phase coupling between limb kinematics and cortical neurophysiological signals reflecting proprioceptive feedback to the primary sensorimotor (SM1) cortex. We studied whether the CKC strength or cortical source location differs between proprioceptive stimulation (i.e., actuator-evoked movements) of right-hand digits (index, middle, ring, and little). Twenty-one volunteers participated in magnetoencephalography measurements during which three conditions were tested: 1) simultaneous stimulation of all four fingers at the same frequency, 2) stimulation of each finger separately at the same frequency, and 3) simultaneous stimulation of the fingers at finger-specific frequencies. CKC was computed between MEG responses and accelerations of the fingers recorded with three-axis accelerometers. CKC was stronger (P < 0.003) for the simultaneous (0.52 ± 0.02) than separate (0.45 ± 0.02) stimulation at the same frequency. Furthermore, CKC was weaker (P < 0.03) for the simultaneous stimulation at the finger-specific frequencies (0.38 ± 0.02) than for the separate stimulation. CKC source locations of the fingers were concentrated in the hand region of the SM1 cortex and did not follow consistent finger-specific somatotopic order. Our results indicate that proprioceptive afference from the fingers is processed in partly overlapping cortical neuronal circuits, which was demonstrated by the modulation of the finger-specific CKC strengths due to proprioceptive afference arising from simultaneous stimulation of the other fingers of the same hand as well as overlapping cortical source locations. Finally, comprehensive simultaneous proprioceptive stimulation of the hand would optimize functional cortical mapping to pinpoint the hand region, e.g., prior brain surgery.

NEW & NOTEWORTHY Corticokinematic coherence (CKC) can be used to study cortical proprioceptive processing and localize proprioceptive hand representation. Our results indicate that proprioceptive stimulation delivered simultaneously at the same frequency to fingers (D2–D4) maximizes CKC strength allowing robust and fast localization of the human hand region in the sensorimotor cortex using MEG.

Gratifying Gizmos for Research and Clinical MEG

Experimental designs are of utmost importance in neuroimaging. Experimental repertoire needs to be designed with the understanding of physiology, clinical feasibility, and constraints posed by a particular neuroimaging method. Innovations in introducing natural, ecologically-relevant stimuli, with successful collaboration across disciplines, correct timing, and a bit of luck may cultivate novel experiments, new discoveries, and open pathways to new clinical practices. Here I introduce some gizmos that I have initiated in magnetoencephalography (MEG) and applied with my collaborators in my home laboratory and in several other laboratories. These gizmos have been applied to address neuronal correlates of audiotactile interactions, tactile sense, active and passive movements, speech processing, and intermittent photic stimulation (IPS) in humans. This review also includes additional notes on the ideas behind the gizmos, their evolution, and results obtained.

Measuring the cortical tracking of speech with optically-pumped magnetometers

During continuous speech listening, brain activity tracks speech rhythmicity at frequencies matching with the repetition rate of phrases (0.2-1.5 Hz), words (2-4 Hz) and syllables (4-8 Hz). Here, we evaluated the applicability of wearable MEG based on optically-pumped magnetometers (OPMs) to measure such cortical tracking of speech (CTS). Measuring CTS with OPMs is a priori challenging given the complications associated with OPM measurements at frequencies below 4 Hz, due to increased intrinsic interference and head movement artifacts. Still, this represents an important development as OPM-MEG provides lifespan compliance and substantially improved spatial resolution compared with classical MEG. In this study, four healthy right-handed adults listened to continuous speech for 9 min. The radial component of the magnetic field was recorded simultaneously with 45-46 OPMs evenly covering the scalp surface and fixed to an additively manufactured helmet which fitted all 4 participants. We estimated CTS with reconstruction accuracy and coherence, and determined the number of dominant principal components (PCs) to remove from the data (as a preprocessing step) for optimal estimation. We also identified the dominant source of CTS using a minimum norm estimate. CTS estimated with reconstruction accuracy and coherence was significant in all 4 participants at phrasal and word rates, and in 3 participants (reconstruction accuracy) or 2 (coherence) at syllabic rate. Overall, close-to-optimal CTS estimation was obtained when the 3 (reconstruction accuracy) or 10 (coherence) first PCs were removed from the data. Importantly, values of reconstruction accuracy (~0.4 for 0.2-1.5-Hz CTS and ~0.1 for 2-8-Hz CTS) were remarkably close to those previously reported in classical MEG studies. Finally, source reconstruction localized the main sources of CTS to bilateral auditory cortices. In conclusion, t his study demonstrates that OPMs can be used for the purpose of CTS assessment. This finding opens new research avenues to unravel the neural network involved in CTS across the lifespan and potential alterations in, e.g., language developmental disorders. Data also suggest that OPMs are generally suitable for recording neural activity at frequencies below 4 Hz provided PCA is used as a preprocessing step; 0.2-1.5-Hz being the lowest frequency range successfully investigated here.

Sensorimotor Mapping With MEG: An Update on the Current State of Clinical Research and Practice With Considerations for Clinical Practice Guidelines

In this article, we present the clinical indications and advances in the use of magnetoencephalography to map the primary sensorimotor (SM1) cortex in neurosurgical patients noninvasively. We emphasize the advantages of magnetoencephalography over sensorimotor mapping using functional magnetic resonance imaging. Recommendations to the referring physicians and the clinical magnetoencephalographers to achieve appropriate sensorimotor cortex mapping using magnetoencephalography are proposed. We finally provide some practical advice for the use of corticomuscular coherence, cortico-kinematic coherence, and mu rhythm suppression in this indication. Magnetoencephalography should now be considered as a method of reference for presurgical functional mapping of the sensorimotor cortex.

Localization accuracy of a common beamformer for the comparison of two conditions

The linearly constrained minimum variance beamformer is frequently used to reconstruct sources underpinning neuromagnetic recordings. When reconstructions must be compared across conditions, it is considered good practice to use a single, "common" beamformer estimated from all the data at once. This is to ensure that differences between conditions are not ascribable to differences in beamformer weights. Here, we investigate the localization accuracy of such a common beamformer. Based on theoretical derivations, we first show that the common beamformer leads to localization errors in source reconstruction. We then turn to simulations in which we attempt to reconstruct a (genuine) source in a first condition, while considering a second condition in which there is an (interfering) source elsewhere in the brain. We estimate maps of mislocalization and assess statistically the difference between "standard" and "common" beamformers. We complement our findings with an application to experimental MEG data. The results show that the common beamformer may yield significant mislocalization. Specifically, the common beamformer may force the genuine source to be reconstructed closer to the interfering source than it really is. As the same applies to the reconstruction of the interfering source, both sources are pulled closer together than they are. This observation was further illustrated in experimental data. Thus, although the common beamformer allows for the comparison of conditions, in some circumstances it introduces localization inaccuracies. We recommend alternative approaches to the general problem of comparing conditions.

Feasibility and reproducibility of electroencephalography-based corticokinematic coherence

The most important message in this report is that the corticokinematic coherence (CKC) method is a feasible and reproducible tool to quantify, map, and follow cortical proprioceptive (“the movement sense”) processing using EEG that is more widely available for CKC recordings than previously used magnetoencephalographic designs, in basic research, but especially in clinical environments. We provide useful recommendations for optimal EEG derivations for cost-effective experimental designs, allowing large sample size studies.

Localization of Sensorimotor Cortex Using Navigated Transcranial Magnetic Stimulation and Magnetoencephalography

The mapping of the sensorimotor cortex gives information about the cortical motor and sensory functions. Typical mapping methods are navigated transcranial magnetic stimulation (TMS) and magnetoencephalography (MEG). The differences between these mapping methods are, however, not fully known. TMS center of gravities (CoGs), MEG somatosensory evoked fields (SEFs), corticomuscular coherence (CMC), and corticokinematic coherence (CKC) were mapped in ten healthy adults. TMS mapping was performed for first dorsal interosseous (FDI) and extensor carpi radialis (ECR) muscles. SEFs were induced by tactile stimulation of the index finger. CMC and CKC were determined as the coherence between MEG signals and the electromyography or accelerometer signals, respectively, during voluntary muscle activity. CMC was mapped during the activation of FDI and ECR muscles separately, whereas CKC was measured during the waving of the index finger at a rate of 3–4 Hz. The maximum CMC was found at beta frequency range, whereas maximum CKC was found at the movement frequency. The mean Euclidean distances between different localizations were within 20 mm. The smallest distance was found between TMS FDI and TMS ECR CoGs and longest between CMC FDI and CMC ECR sites. TMS-inferred localizations (CoGs) were less variable across participants than MEG-inferred localizations (CMC, CKC). On average, SEF locations were 8 mm lateral to the TMS CoGs (p < 0.01). No differences between hemispheres were found. Based on the results, TMS appears to be more viable than MEG in locating motor cortical areas.

IFCN-endorsed practical guidelines for clinical magnetoencephalography (MEG)

Magnetoencephalography (MEG) records weak magnetic fields outside the human head and thereby provides millisecond-accurate information about neuronal currents supporting human brain function. MEG and electroencephalography (EEG) are closely related complementary methods and should be interpreted together whenever possible. This manuscript covers the basic physical and physiological principles of MEG and discusses the main aspects of state-of-the-art MEG data analysis. We provide guidelines for best practices of patient preparation, stimulus presentation, MEG data collection and analysis, as well as for MEG interpretation in routine clinical examinations. In 2017, about 200 whole-scalp MEG devices were in operation worldwide, many of them located in clinical environments. Yet, the established clinical indications for MEG examinations remain few, mainly restricted to the diagnostics of epilepsy and to preoperative functional evaluation of neurosurgical patients. We are confident that the extensive ongoing basic MEG research indicates potential for the evaluation of neurological and psychiatric syndromes, developmental disorders, and the integrity of cortical brain networks after stroke. Basic and clinical research is, thus, paving way for new clinical applications to be identified by an increasing number of practitioners of MEG.

Reproducibility of corticokinematic coherence

Corticokinematic coherence (CKC) between limb kinematics and magnetoencephalographic (MEG) signals reflects cortical processing of proprioceptive afference. However, it is unclear whether strength of CKC is reproducible across measurement sessions. We thus examined reproducibility of CKC in a follow-up study. Thirteen healthy right-handed volunteers (7 females, 21.7 ± 4.3 yrs) were measured using MEG in two separate sessions 12.6 ± 1.3 months apart. The participant was seated and relaxed while his/her dominant or non-dominant index finger was continuously moved at 3 Hz (4 min for each hand) using a pneumatic movement actuator. Finger kinematics were recorded with a 3-axis accelerometer. Coherence was computed between finger acceleration and MEG signals. CKC strength was defined as the peak coherence value at 3 Hz form a single sensor among 40 pre-selected Rolandic gradiometers contralateral to the movement. Pneumatic movement actuator provided stable proprioceptive stimuli and significant CKC responses peaking at the contralateral Rolandic sensors. In the group level, CKC strength did not differ between the sessions in dominant (Day-1 0.40 ± 0.19 vs. Day-2 0.41 ± 0.17) or non-dominant (0.35 ± 0.16 vs. 0.36 ± 0.17) hand, nor between the hands. Intraclass-correlation coefficient (ICC) values indicated excellent inter-session reproducibility for CKC strength for both dominant (0.86) and non-dominant (0.97) hand. However, some participants showed pronounced inter-session variability in CKC strength, but only for the dominant hand. CKC is a promising tool to study proprioception in long-term longitudinal studies in the group level to follow, e.g., integrity of cortical proprioceptive processing with motor functions after stroke.

Cortical Proprioceptive Processing Is Altered by Aging

Proprioceptive perception is impaired with aging, but little is known about aging-related deterioration of proprioception at the cortical level. Corticokinematic coherence (CKC) between limb kinematic and magnetoencephalographic (MEG) signals reflects cortical processing of proprioceptive afference. We, thus, compared CKC strength to ankle movements between younger and older subjects, and examined whether CKC predicts postural stability. Fifteen younger (range 18–31 years) and eight older (66–73 years) sedentary volunteers were seated in MEG, while their right and left ankle joints were moved separately at 2 Hz (for 4 min each) using a novel MEG-compatible ankle-movement actuator. Coherence was computed between foot acceleration and MEG signals. CKC strength at the movement frequency (F0) and its first harmonic (F1) was quantified. In addition, postural sway was quantified during standing eyes-open and eyes-closed tasks to estimate motor performance. CKC peaked in the gradiometers over the vertex, and was significantly stronger (~76%) at F0 for the older than younger subjects. At F1, only the dominant-leg CKC was significantly stronger (~15%) for the older than younger subjects. In addition, CKC (at F1) was significantly stronger in the non-dominant than dominant leg, but only in the younger subjects. Postural sway was significantly (~64%) higher in the older than younger subjects when standing with eyes closed. Regression models indicated that CKC strength at F1 in the dominant leg and age were the only significant predictors for postural sway. Our results indicated that aging-related cortical-proprioceptive processing is altered by aging. Stronger CKC may reflect poorer cortical proprioceptive processing, and not solely the amount of proprioceptive afference as suggested earlier. In combination with ankle-movement actuator, CKC can be efficiently used to unravel proprioception-related-neuronal mechanisms and the related plastic changes in aging, rehabilitation, motor-skill acquisition, motor disorders etc.

Assessing Brain-Muscle Connectivity in Human Locomotion through Mobile Brain/Body Imaging: Opportunities, Pitfalls, and Future Directions

Assessment of the cortical role during bipedalism has been a methodological challenge. While surface electroencephalography (EEG) is capable of non-invasively measuring cortical activity during human locomotion, it is associated with movement artifacts obscuring cerebral sources of activity. Recently, statistical methods based on blind source separation revealed potential for resolving this issue, by segregating non-cerebral/artifactual from cerebral sources of activity. This step marked a new opportunity for the investigation of the brains' role while moving and was tagged mobile brain/body imaging (MoBI). This methodology involves simultaneous mobile recording of brain activity with several other body behavioral variables (e.g., muscle activity and kinematics), through wireless recording wearable devices/sensors. Notably, several MoBI studies using EEG-EMG approaches recently showed that the brain is functionally connected to the muscles and active throughout the whole gait cycle and, thus, rejecting the long-lasting idea of a solely spinal-driven bipedalism. However, MoBI and brain/muscle connectivity assessments during human locomotion are still in their fledgling state of investigation. Mobile brain/body imaging approaches hint toward promising opportunities; however, there are some remaining pitfalls that need to be resolved before considering their routine clinical use. This article discusses several of these pitfalls and proposes research to address them. Examples relate to the validity, reliability, and reproducibility of this method in ecologically valid scenarios and in different populations. Furthermore, whether brain/muscle connectivity within the MoBI framework represents a potential biomarker in neuromuscular syndromes where gait disturbances are evident (e.g., age-related sarcopenia) remains to be determined.