Subject position affects EEG magnitudes

Mapping the Relationships Between Structural Brain MRI Characteristics and Sleep EEG Patterns: The Multi-Ethnic Study of Atherosclerosis

While brain morphology is well-established as a key factor influencing overall brain function, little is known about how brain structural properties are associated with oscillatory activity, particularly during sleep. In this study, we analyzed whole-night sleep EEG and brain structural MRI data from a subset of 621 individuals in the Multi-Ethnic Study of Atherosclerosis to explore the relationship between brain structure and sleep EEG properties. We found that larger total white matter (WM) volume was associated with higher absolute broad-band power, regardless of sleep stage, likely reflecting WM contribution to enhanced synchronization across cortical regions and reduced activation attenuation via long-range myelinated fibers. Additionally, both WM fractional anisotropy and thalamus volume showed negative association with relative slow power and positive association with delta power during non-rapid eye movement sleep. This was mirrored in the duration of slow oscillations (SOs), both overall and when divided into slow-switching and fast-switching types, with their ratio additionally linked to total WM volume. Furthermore, we observed strong but largely independent effects of age and sex on sleep EEG and structural MRI metrics, suggesting that sleep EEG captures aging processes and sex-specific features that extend beyond the macro-scale brain morphology changes examined here. Overall, these findings deepen our understanding of how structural brain properties influence sleep-related oscillatory activity.

Neuromotor changes in postural control following bed rest

Chronic bed rest (BR) serves as a model for studying the effects of prolonged immobility on physiological and neuromotor functions, particularly postural control. Prolonged BR leads to significant deconditioning of postural balance control, characterized by increased sway path lengths, sway velocity and fall risk, independent of muscle strength. These changes are linked to neural adaptations at spinal and supraspinal levels, including structural and functional brain changes, such as alterations in grey and white matter, increased cerebellar activation, reduced spinal excitability and increased latencies within reflex circuitries. Additionally, BR disrupts sensory integration from proprioceptive, visual and vestibular systems, impairing postural stability. Visual reliance remains stable during BR, though decreased visual acuity and contrast sensitivity are noted. Moreover, BR-induced shifts in cerebrospinal fluid contribute to altered brain activity, impacting sensorimotor function. Vestibular system adaptations, including changes in vestibulospinal reflexes, further exacerbate balance impairments. Understanding these mechanisms is crucial for developing interventions to mitigate the adverse effects of BR on postural control and prevent prolonged recovery times or increased risk of injury. This review highlights the need for further research into the neural underpinnings of BR-induced postural instability, with a focus on sensory integration and neuroplasticity.

An investigation of a passive BCI's performance for different body postures and presentation modalities

Passive brain-computer interfaces (passive BCIs, pBCIs) enable computers to unobtrusively decipher aspects of a user's mental state in real time from recordings of brain activity, e.g. electroencephalography (EEG). When used during human-computer interaction (HCI), this allows a computer to dynamically adapt for enhancing the subjective user experience. For transitioning from controlled laboratory environments to practical applications, understanding BCI performance in real contexts is of utmost importance. Here, Virtual Reality (VR) can play a unique role: both as a fully controllable simulation of a realistic environment and as an independent, increasingly popular real application. Given the potential of VR as a dynamic and controllable environment, and the capability of pBCIs to enable novel modes of interaction, it is tempting to envision a future where pBCI and VR are seamlessly integrated. However, the simultaneous use of these two technologies-both of which are head-mounted-presents new challenges. Due to their immediate proximity, electromagnetic artifacts can arise, contaminating the EEG. Furthermore, the active movements promoted by VR can induce mechanical and muscular artifacts in the EEG. The varying body postures and display preferences of users further complicate the practical application of pBCIs. To address these challenges, the current study investigates the influence of body posture (sitting Versus standing) and display media (computer screen Versus VR) on the performance of a pBCI in assessing cognitive load. Our results show that these conditions indeed led to some changes in the EEG data; nevertheless, the ability of pBCIs to detect cognitive load remained largely unaffected. However, when a classifier trained in one context (body posture or modality) was applied to another (e.g., cross-task application), reductions in classification accuracy were observed. As HCI moves towards increasingly adaptive and more interactive designs, these findings support the expansive potential of pBCIs in VR contexts.

Amplitude of Intracranial Induced Electric Fields Does Not Linearly Decrease with Age: A Computational Study of Anatomical Effects in Adults

Transcranial electrical stimulation, as a means of neural modulation, is increasingly favored by researchers. The distribution and magnitude of the electric field generated within the brain may directly affect the results of neural modulation. Therefore, it is important to clarify the change trend of the cortical electric field and the determinants of the induced electric field in the endodermis at different ages during the adult life cycle. In this study, we used SimNIBS software to perform MR image segmentation and realistic head model reconstruction on 476 individuals (aged 18 to 88 years old) and calculated the cortical electric field of four electrode montages commonly used in cognitive tasks. We divided all participants into groups by age with a span of 10 years for each group and compared the electric field distribution patterns, electric field intensities, and focalities of the cortexes and regions of interest related to cognitive tasks within groups. The degree of influence of global and local anatomical parameters on the electric field was analyzed using a stepwise regression model. The results showed that, in the cortexes and regions of interest, the variability of electric field distribution patterns was highest in adolescents (<20 years old) and elderly individuals (>80 years old). Moreover, throughout the adult lifespan, the electric field induced by transcranial electrical stimulation did not decrease linearly with age but rather presented a U-shaped pattern. In terms of the entire adult life cycle, compared with global anatomical parameters (intracranial brain tissue volume), local anatomical parameters (such as scalp or skull thickness below the electrode) have a greater impact on the amplitude of the intracranial electric field. Our research results indicated that it is necessary to consider the effects caused by different brain tissues when using transcranial electrical stimulation to modulate or treat individuals of different ages.

Take it sitting down: the effect of body posture on cortical potentials during free viewing-A mobile EEG recording study

Brain imaging performed in natural settings is known as mobile brain and body imaging (MoBI). One of the features which distinguishes MoBI and laboratory-based experiments is the body posture. Previous studies pointed to mechanical, autonomic, cortical and cognitive differences between upright stance and sitting or reclining. The purpose of this study was to analyse effects of posture on eye-movement related potentials (EMRP) recorded during free viewing of human faces. A 64-channel wireless EEG was recorded from 14 participants in either standing or reclining postures while they freely viewed pictures of emotional faces displaying fear, anger, sadness, and a neutral emotional state. Eye tracking data was used to insert triggers corresponding to the instant at which the gaze first landed on a face. Spatial filtering of the EEG data was performed using a group independent component analysis (ICA). Grand average EMRPs displayed the post-saccadic lambda component and the face-sensitive N170/vertex positive potential (VPP) complex. The lambda component but not the N170 component was stronger during reclining than upright posture. Emotional expression of faces showed no effects on EMRP components or subjective ratings. Results suggest that posture primarily affects early components of EMRPs recorded using wireless EEG recordings during free viewing of faces. Thus, findings from evoked potential data obtained in seated individuals, e.g., in laboratory experiments, should be interpreted with caution in MoBI experiments with posture affecting primarily the early latency component.

CutFEM-based MEG forward modeling improves source separability and sensitivity to quasi-radial sources: A somatosensory group study

Source analysis of magnetoencephalography (MEG) data requires the computation of the magnetic fields induced by current sources in the brain. This so-called MEG forward problem includes an accurate estimation of the volume conduction effects in the human head. Here, we introduce the Cut finite element method (CutFEM) for the MEG forward problem. CutFEM's meshing process imposes fewer restrictions on tissue anatomy than tetrahedral meshes while being able to mesh curved geometries contrary to hexahedral meshing. To evaluate the new approach, we compare CutFEM with a boundary element method (BEM) that distinguishes three tissue compartments and a 6-compartment hexahedral FEM in an n = 19 group study of somatosensory evoked fields (SEF). The neural generators of the 20 ms post-stimulus SEF components (M20) are reconstructed using both an unregularized and a regularized inversion approach. Changing the forward model resulted in reconstruction differences of about 1 centimeter in location and considerable differences in orientation. The tested 6-compartment FEM approaches significantly increase the goodness of fit to the measured data compared with the 3-compartment BEM. They also demonstrate higher quasi-radial contributions for sources below the gyral crowns. Furthermore, CutFEM improves source separability compared with both other approaches. We conclude that head models with 6 compartments rather than 3 and the new CutFEM approach are valuable additions to MEG source reconstruction, in particular for sources that are predominantly radial.

High-resolution EEG source localization in personalized segmentation-free head model with multi-dipole fitting

Objective. Electroencephalograms (EEGs) are often used to monitor brain activity. Several source localization methods have been proposed to estimate the location of brain activity corresponding to EEG readings. However, only a few studies evaluated source localization accuracy from measured EEG using personalized head models in a millimeter resolution. In this study, based on a volume conductor analysis of a high-resolution personalized human head model constructed from magnetic resonance images, a finite difference method was used to solve the forward problem and to reconstruct the field distribution.Approach. We used a personalized segmentation-free head model developed using machine learning techniques, in which the abrupt change of electrical conductivity occurred at the tissue interface is suppressed. Using this model, a smooth field distribution was obtained to address the forward problem. Next, multi-dipole fitting was conducted using EEG measurements for each subject (N= 10 male subjects, age: 22.5 ± 0.5), and the source location and electric field distribution were estimated.Main results.For measured somatosensory evoked potential for electrostimulation to the wrist, a multi-dipole model with lead field matrix computed with the volume conductor model was found to be superior than a single dipole model when using personalized segmentation-free models (6/10). The correlation coefficient between measured and estimated scalp potentials was 0.89 for segmentation-free head models and 0.71 for conventional segmented models. The proposed method is straightforward model development and comparable localization difference of the maximum electric field from the target wrist reported using fMR (i.e. 16.4 ± 5.2 mm) in previous study. For comparison, DUNEuro based on sLORETA was (EEG: 17.0 ± 4.0 mm). In addition, somatosensory evoked magnetic fields obtained by Magnetoencephalography was 25.3 ± 8.5 mm using three-layer sphere and sLORETA.Significance. For measured EEG signals, our procedures using personalized head models demonstrated that effective localization of the somatosensory cortex, which is located in a non-shallower cortex region. This method may be potentially applied for imaging brain activity located in other non-shallow regions.

A Combined Magnetoelectric Sensor Array and MRI-Based Human Head Model for Biomagnetic FEM Simulation and Sensor Crosstalk Analysis

Magnetoelectric (ME) magnetic field sensors are novel sensing devices of great interest in the field of biomagnetic measurements. We investigate the influence of magnetic crosstalk and the linearity of the response of ME sensors in different array and excitation configurations. To achieve this aim, we introduce a combined multiscale 3D finite-element method (FEM) model consisting of an array of 15 ME sensors and an MRI-based human head model with three approximated compartments of biological tissues for skin, skull, and white matter. A linearized material model at the small-signal working point is assumed. We apply homogeneous magnetic fields and perform inhomogeneous magnetic field excitation for the ME sensors by placing an electric point dipole source inside the head. Our findings indicate significant magnetic crosstalk between adjacent sensors leading down to a 15.6% lower magnetic response at a close distance of 5 mm and an increasing sensor response with diminishing crosstalk effects at increasing distances up to 5 cm. The outermost sensors in the array exhibit significantly less crosstalk than the sensors located in the center of the array, and the vertically adjacent sensors exhibit a stronger crosstalk effect than the horizontally adjacent ones. Furthermore, we calculate the ratio between the electric and magnetic sensor responses as the sensitivity value and find near-constant sensitivities for each sensor, confirming a linear relationship despite magnetic crosstalk and the potential to simulate excitation sources and sensor responses independently.

Flower electrodes for comfortable dry electroencephalography

Dry electroencephalography (EEG) electrodes provide rapid, gel-free, and easy EEG preparation, but with limited wearing comfort. We propose a novel dry electrode comprising multiple tilted pins in a flower-like arrangement. The novel Flower electrode increases wearing comfort and contact area while maintaining ease of use. In a study with 20 volunteers, we compare the performance of a novel 64-channel dry Flower electrode cap to a commercial dry Multipin electrode cap in sitting and supine positions. The wearing comfort of the Flower cap was rated as significantly improved both in sitting and supine positions. The channel reliability and average impedances of both electrode systems were comparable. Averaged VEP components showed no considerable differences in global field power amplitude and latency, as well as in signal-to-noise ratio and topography. No considerable differences were found in the power spectral density of the resting state EEGs between 1 and 40 Hz. Overall, our findings provide evidence for equivalent channel reliability and signal characteristics of the compared cap systems in the sitting and supine positions. The reliability, signal quality, and significantly improved wearing comfort of the Flower electrode allow new fields of applications for dry EEG in long-term monitoring, sensitive populations, and recording in supine position.

CutFEM forward modeling for EEG source analysis

Introduction

Source analysis of Electroencephalography (EEG) data requires the computation of the scalp potential induced by current sources in the brain. This so-called EEG forward problem is based on an accurate estimation of the volume conduction effects in the human head, represented by a partial differential equation which can be solved using the finite element method (FEM). FEM offers flexibility when modeling anisotropic tissue conductivities but requires a volumetric discretization, a mesh, of the head domain. Structured hexahedral meshes are easy to create in an automatic fashion, while tetrahedral meshes are better suited to model curved geometries. Tetrahedral meshes, thus, offer better accuracy but are more difficult to create.

Methods

We introduce CutFEM for EEG forward simulations to integrate the strengths of hexahedra and tetrahedra. It belongs to the family of unfitted finite element methods, decoupling mesh and geometry representation. Following a description of the method, we will employ CutFEM in both controlled spherical scenarios and the reconstruction of somatosensory-evoked potentials.

Results

CutFEM outperforms competing FEM approaches with regard to numerical accuracy, memory consumption, and computational speed while being able to mesh arbitrarily touching compartments.

Discussion

CutFEM balances numerical accuracy, computational efficiency, and a smooth approximation of complex geometries that has previously not been available in FEM-based EEG forward modeling.

Enhancing precision in human neuroscience

Human neuroscience has always been pushing the boundary of what is measurable. During the last decade, concerns about statistical power and replicability - in science in general, but also specifically in human neuroscience - have fueled an extensive debate. One important insight from this discourse is the need for larger samples, which naturally increases statistical power. An alternative is to increase the precision of measurements, which is the focus of this review. This option is often overlooked, even though statistical power benefits from increasing precision as much as from increasing sample size. Nonetheless, precision has always been at the heart of good scientific practice in human neuroscience, with researchers relying on lab traditions or rules of thumb to ensure sufficient precision for their studies. In this review, we encourage a more systematic approach to precision. We start by introducing measurement precision and its importance for well-powered studies in human neuroscience. Then, determinants for precision in a range of neuroscientific methods (MRI, M/EEG, EDA, Eye-Tracking, and Endocrinology) are elaborated. We end by discussing how a more systematic evaluation of precision and the application of respective insights can lead to an increase in reproducibility in human neuroscience.

Assessing the effects of head modelling errors and measurement noise on EEG source localization accuracy in preterm newborns: A single-subject study

The accuracy of electroencephalogram (EEG) source localization is compromised because of head modelling errors. In this study, we investigated the effect of inaccuracy in the conductivity of head tissues and head model structural deficiencies on the accuracy of EEG source analysis in premature neonates. A series of EEG forward and inverse simulations was performed by introducing structural deficiencies into the reference head models to generate test models, which were then used to investigate head modelling errors caused by cerebrospinal fluid (CSF) exclusion, lack of grey matter (GM)-white matter (WM) distinction, fontanel exclusion and inaccuracy in skull conductivity. The modelling errors were computed between forward and inverse solutions obtained using the reference and test models generated for each deficiency. Our results showed that the exclusion of CSF from the head model had a strong widespread effect on the accuracy of the EEG source localization with position errors lower than 4.17 mm. The GM and WM distinction also caused strong localization errors (up to 3.5 mm). The exclusion of fontanels from the head model also strongly affected the accuracy of the EEG source localization for sources located beneath the fontanels with a maximum localization error of 4.37 mm. Similarly, inaccuracies in the skull conductivity caused errors in EEG forward and inverse modelling in sources beneath cranial bones. Our results indicate that the accuracy of EEG source imaging in premature neonates can be largely improved by using head models, which include not only the brain, skull and scalp but also the CSF, GM, WM and fontanels.

Vestibular loss disrupts visual reactivity in the alpha EEG rhythm

The alpha rhythm is a dominant electroencephalographic oscillation relevant to sensory-motor and cognitive function. Alpha oscillations are reactive, being for example enhanced by eye closure, and suppressed following eye opening. The determinants of inter-individual variability in reactivity in the alpha rhythm (e.g. changes with amplitude following eye closure) are not fully understood despite the physiological and clinical applicability of this phenomenon, as indicated by the fact that ageing and neurodegeneration reduce reactivity. Strong interactions between visual and vestibular systems raise the theoretical possibility that the vestibular system plays a role in alpha reactivity. To test this hypothesis, we applied electroencephalography in sitting and standing postures in 15 participants with reduced vestibular function (bilateral vestibulopathy, median age = 70 years, interquartile range = 51-77 years) and 15 age-matched controls. We found participants with reduced vestibular function showed less enhancement of alpha electroencephalography power on eye closure in frontoparietal areas, compared to controls. In participants with reduced vestibular function, video head impulse test gain - as a measure of residual vestibulo-ocular reflex function - correlated with reactivity in alpha power across most of the head. Greater reliance on visual input for spatial orientation ('visual dependence', measured with the rod-and-disc test) correlated with less alpha enhancement on eye closure only in participants with reduced vestibular function, and this was partially moderated by video head impulse test gain. Our results demonstrate for the first time that vestibular function influences alpha reactivity. The results are partly explained by the lack of ascending peripheral vestibular input but also by central reorganisation of processing relevant to visuo-vestibular judgements.

Fabrication of a positional brain shift phantom through the utilization of the frozen intermediate hydrogel state

Synthetic models (phantoms) of the brain-skull system are useful tools for the study of surgical events that are otherwise difficult to study directly in humans. To date, very few studies can be found which replicate the full anatomical brain-skull system. Such models are required to study the more global mechanical events that can occur in neurosurgery, such as positional brain shift. Presented in this work is a novel workflow for the fabrication of a biofidelic brain-skull phantom which features a full hydrogel brain with fluid-filled ventricle/fissure spaces, elastomer dural septa and fluid-filled skull. Central to this workflow is the utilization of the frozen intermediate curing state of an established brain tissue surrogate, which allows for a novel moulding and skull installation approach that permits a much fuller recreation of the anatomy. The mechanical realism of the phantom was validated through indentation testing of the phantom's brain and simulation of the supine to prone brain shift event, while the geometric realism was validated through magnetic resonance imaging. The developed phantom captured a novel measurement of the supine to prone brain shift event with a magnitude that accurately reproduces that seen in the literature.

Bioelectromagnetism in Human Brain Research: New Applications, New Questions

Bioelectromagnetism has contributed some of the most commonly used techniques to human neuroscience such as magnetoencephalography (MEG), electroencephalography (EEG), transcranial magnetic stimulation (TMS), and transcranial electric stimulation (TES). The considerable differences in their technical design and practical use give rise to the impression that these are quite different techniques altogether. Here, we review, discuss and illustrate the fundamental principle of Helmholtz reciprocity that provides a common ground for all four techniques. We show that, more than 150 years after its discovery by Helmholtz in 1853, reciprocity is important to appreciate the strengths and limitations of these four classical tools in neuroscience. We build this case by explaining the concept of Helmholtz reciprocity, presenting a methodological account of this principle for all four methods and, finally, by illustrating its application in practical clinical studies.

Effect of Acoustic fMRI-Scanner Noise on the Human Resting State

Our knowledge about the human resting state is predominantly based on either electroencephalographic (EEG) or functional magnetic resonance imaging (fMRI) methods. While EEG recordings can be performed in seated posture in quiet conditions, the fMRI environment presents a substantial contrast with supine and restricted posture in a narrow tube that is filled with acoustic scanner noise (ASN) at a chainsaw-like volume level. However, the influence of these diverging conditions on resting-state brain activation is neither well studied nor broadly discussed. In order to promote data as a source of sharper hypotheses for future studies, we investigated alterations in EEG-frequency-band power (delta, theta, alpha, beta, gamma) and spatial power distribution as well as cortical vigilance measures in different postures and ASN surroundings over the course of time. Participants (N = 18) underwent three consecutive resting-state EEG recordings with a fixed posture and ASN setting sequence; seated, supine, and supine with ASN (supnoise) using an MRI simulator. The results showed that compared to seated, supnoise, the last instance within the posture sequence, was characterized by lower power and altered spatial power distribution in all assessed frequency bands. This might also have been an effect of time alone. In delta, theta, alpha, and beta, the power of supnoise was also reduced compared to supine, as well as the corresponding distribution maps. The vigilance analysis revealed that in supine and supnoise, the highest and lowest vigilance stages were more dominant compared to the seated and earliest posture condition within the sequence. Hence, our results demonstrate that the differences in recording settings and progress of time are related to changes in cortical arousal and vigilance regulation, findings that should be taken into account more profoundly for hypothesis generation as well as analytic strategies in future resting-state studies.

Can individually targeted and optimized multi-channel tDCS outperform standard bipolar tDCS in stimulating the primary somatosensory cortex?

BACKGROUND

Transcranial direct current stimulation (tDCS) has emerged as a non-invasive neuro-modulation technique. Most studies show that anodal tDCS increases cortical excitability, however, with variable outcomes. Previously, we have shown in computer simulations that our multi-channel tDCS (mc-tDCS) approach, the distributed constrained maximum intensity (D-CMI) method can potentially lead to better controlled tDCS results due to the improved directionality of the injected current at the target side for individually optimized D-CMI montages.

OBJECTIVE

In this study, we test the application of the D-CMI approach in an experimental study to stimulate the somatosensory P20/N20 target source in Brodmann area 3b and compare it with standard bipolar tDCS and sham conditions.

METHODS

We applied anodal D-CMI, the standard bipolar and D-CMI based Sham tDCS for 10 min to target the 20 ms post-stimulus somatosensory P20/N20 target brain source in Brodmann area 3b reconstructed using combined magnetoencephalography (MEG) and electroencephalography (EEG) source analysis in realistic head models with calibrated skull conductivity in a group-study with 13 subjects. Finger-stimulated somatosensory evoked fields (SEF) were recorded and the component at 20 ms post-stimulus (M20) was analyzed before and after the application of the three tDCS conditions in order to read out the stimulation effect on Brodmann area 3b.

RESULTS

Analysis of the finger stimulated SEF M20 peak before (baseline) and after tDCS shows a significant increase in source amplitude in Brodmann area 3b for D-CMI (6-16 min after tDCS), while no significant effects are found for standard bipolar (6-16 min after tDCS) and sham (6-16 min after tDCS) stimulation conditions. For the later time courses (16-26 and 27-37 min post-stimulation), we found a significant decrease in M20 peak source amplitude for standard bipolar and sham tDCS, while there was no effect for D-CMI.

CONCLUSION

Our results indicate that targeted and optimized, and thereby highly individualized, mc-tDCS can outperform standard bipolar stimulation and lead to better control over stimulation outcomes with, however, a considerable amount of additional work compared to standard bipolar tDCS.

Processed electroencephalography: impact of patient age and surgical position on intraoperative processed electroencephalogram monitoring of burst-suppression

We previously reported that processed EEG underestimated the amount of burst suppression compared to off-line visual analysis. We performed a follow-up study to evaluate the reasons for the discordance. Forty-five patients were monitored intraoperatively with processed EEG. A computer algorithm was used to convert the SedLine® (machine)-generated burst suppression ratio into a raw duration of burst suppression. The reference standard was a precise off-line measurement by two neurologists. We measured other potential variables that may affect machine accuracy such as age, surgery position, and EEG artifacts. Overall, the median duration of bust suppression for all study subjects was 15.4 min (Inter-quartile Range [IQR] = 1.0-20.1) for the machine vs. 16.1 min (IQR = 0.3-19.7) for the neurologists' assessment; the 95% limits of agreement fall within - 4.86 to 5.04 s for individual 30-s epochs. EEG artifacts did not affect the concordance between the two methods. For patients in prone surgical position, the machine estimates had significantly lower overall sensitivity (0.86 vs. 0.97; p = 0.038) and significantly wider limits of agreement ([- 4.24, 3.82] seconds vs. [- 1.36, 1.13] seconds, p = 0.001) than patients in supine position. Machine readings for younger patients (age < 65 years) had higher sensitivity (0.96 vs 0.92; p = 0.021) and specificity (0.99 vs 0.88; p = 0.007) for older patients. The duration of burst suppression estimated by the machine generally had good agreement compared with neurologists' estimation using a more precise off-line measurement. Factors that affected the concordance included patient age and position during surgery, but not EEG artifacts.

Developing control-theoretic objectives for large-scale brain dynamics and cognitive enhancement

The development of technologies for brain stimulation provides a means for scientists and clinicians to directly actuate the brain and nervous system. Brain stimulation has shown intriguing potential in terms of modifying particular symptom clusters in patients and behavioral characteristics of subjects. The stage is thus set for optimization of these techniques and the pursuit of more nuanced stimulation objectives, including the modification of complex cognitive functions such as memory and attention. Control theory and engineering will play a key role in the development of these methods, guiding computational and algorithmic strategies for stimulation. In particular, realizing this goal will require new development of frameworks that allow for controlling not only brain activity, but also latent dynamics that underlie neural computation and information processing. In the current opinion, we review recent progress in brain stimulation and outline challenges and potential research pathways associated with exogenous control of cognitive function.

Data-Driven EEG Theta and Alpha Components Are Associated with Subjective Experience during Resting State

The resting-state paradigm is frequently applied to study spontaneous activity of the brain in normal and clinical conditions. However, the relationship between the ongoing experience of mind wandering and the individual biological signal is still unclear. We aim to estimate associations between subjective experiences measured with the Amsterdam Resting-State Questionnaire and data-driven components of an electroencephalogram extracted by frequency principal component analysis (f-PCA). Five minutes of resting multichannel EEG was recorded in 226 participants and six EEG data-driven components were extracted-three components in the alpha range (peaking at 9, 10.5, and 11.5 Hz) and one each in the delta (peaking at 0.5 Hz), theta (peaking at 5.5 Hz) and beta (peaking at 17 Hz) ranges. Bayesian Pearson's correlation revealed a positive association between the individual loadings of the theta component and ratings for Sleepiness (r = 0.200, BF10 = 7.676), while the individual loadings on one of the alpha components correlated positively with scores for Comfort (r = 0.198, BF10 = 7.115). Our study indicates the relevance of assessments of spontaneous thought occurring during the resting-state for the understanding of the individual intrinsic electrical brain activity.

In vivo Measurements of Electric Fields During Cranial Electrical Stimulation in the Human Brain

Cranial electrical stimulation (CES) has been applied at various current levels in both adults and children with neurological conditions with seemingly promising but somewhat inconsistent results. Stimulation-induced spatial electric fields (EFs) within a specific brain region are likely a significant contributing factor for the biological effects. Although several simulation models have been used to predict EF distributions in the brain, these models actually have not been validated by in vivo CES-induced EF measurements in the live human brain. This study directly measured the CES-induced voltage changes with implanted stereotactic-electroencephalographic (sEEG) electrodes in twenty-one epilepsy participants (16 adults and 5 children) and then compared these measured values with the simulated ones obtained from the personalized models. In addition, we further investigated the influence of stimulation frequency, intensity, electrode montage and age on EFs in parts of participants. We found both measured voltages and EFs obtained in vivo are highly correlated with the predicted ones in our cohort (Voltages: r = 0.93, p &lt; 0.001; EFs: r = 0.73, p &lt; 0.001). In white matter and gray matter, the measured voltages linearly increased when the stimulation intensity increased from 5 to 500 μA but showed no significant changes (averaged coefficient of variation &lt;4.10%) with changing stimulation frequency from 0.5 to 200 Hz. Electrode montage, but not age, significantly affects the distribution of the EFs (n = 5, p &lt; 0.01). Our in vivo measurements demonstrate that the individualized simulation model can reliably predict the CES-induced EFs in both adults and children. It also confirms that the CES-induced EFs highly depend on the electrode montages and individual anatomical features.

Variability of EEG electrode positions and their underlying brain regions: visualizing gel artifacts from a simultaneous EEG-fMRI dataset

INTRODUCTION

We investigated the between-subject variability of EEG (electroencephalography) electrode placement from a simultaneously recorded EEG-fMRI (functional magnetic resonance imaging) dataset.

METHODS

Neuro-navigation software was used to localize electrode positions, made possible by the gel artifacts present in the structural magnetic resonance images. To assess variation in the brain regions directly underneath electrodes we used MNI coordinates, their associated Brodmann areas, and labels from the Harvard-Oxford Cortical Atlas. We outline this relatively simple pipeline with accompanying analysis code.

RESULTS

In a sample of 20 participants, the mean standard deviation of electrode placement was 3.94 mm in x, 5.55 mm in y, and 7.17 mm in z, with the largest variation in parietal and occipital electrodes. In addition, the brain regions covered by electrode pairs were not always consistent; for example, the mean location of electrode PO7 was mapped to BA18 (secondary visual cortex), whereas PO8 was closer to BA19 (visual association cortex). Further, electrode C1 was mapped to BA4 (primary motor cortex), whereas C2 was closer to BA6 (premotor cortex).

CONCLUSIONS

Overall, the results emphasize the variation in electrode positioning that can be found even in a fixed cap. This may be particularly important to consider when using EEG positioning systems to inform non-invasive neurostimulation.

Validating EEG, MEG and Combined MEG and EEG Beamforming for an Estimation of the Epileptogenic Zone in Focal Cortical Dysplasia

MEG and EEG source analysis is frequently used for the presurgical evaluation of pharmacoresistant epilepsy patients. The source localization of the epileptogenic zone depends, among other aspects, on the selected inverse and forward approaches and their respective parameter choices. In this validation study, we compare the standard dipole scanning method with two beamformer approaches for the inverse problem, and we investigate the influence of the covariance estimation method and the strength of regularization on the localization performance for EEG, MEG, and combined EEG and MEG. For forward modelling, we investigate the difference between calibrated six-compartment and standard three-compartment head modelling. In a retrospective study, two patients with focal epilepsy due to focal cortical dysplasia type IIb and seizure freedom following lesionectomy or radiofrequency-guided thermocoagulation (RFTC) used the distance of the localization of interictal epileptic spikes to the resection cavity resp. RFTC lesion as reference for good localization. We found that beamformer localization can be sensitive to the choice of the regularization parameter, which has to be individually optimized. Estimation of the covariance matrix with averaged spike data yielded more robust results across the modalities. MEG was the dominant modality and provided a good localization in one case, while it was EEG for the other. When combining the modalities, the good results of the dominant modality were mostly not spoiled by the weaker modality. For appropriate regularization parameter choices, the beamformer localized better than the standard dipole scan. Compared to the importance of an appropriate regularization, the sensitivity of the localization to the head modelling was smaller, due to similar skull conductivity modelling and the fixed source space without orientation constraint.

Reconstructing subcortical and cortical somatosensory activity via the RAMUS inverse source analysis technique using median nerve SEP data

This study concerns reconstructing brain activity at various depths based on non-invasive EEG (electroencephalography) scalp measurements. We aimed at demonstrating the potential of the RAMUS (randomized multiresolution scanning) technique in localizing weakly distinguishable far-field sources in combination with coinciding cortical activity. As we have shown earlier theoretically and through simulations, RAMUS is a novel mathematical method that by employing the multigrid concept, allows marginalizing noise and depth bias effects and thus enables the recovery of both cortical and subcortical brain activity. To show this capability with experimental data, we examined the 14-30 ms post-stimulus somatosensory evoked potential (SEP) responses of human median nerve stimulation in three healthy adult subjects. We aim at reconstructing the different response components by evaluating a RAMUS-based estimate for the primary current density in the nervous tissue. We present source reconstructions obtained with RAMUS and compare them with the literature knowledge of the SEP components and the outcome of the unit-noise gain beamformer (UGNB) and standardized low-resolution brain electromagnetic tomography (sLORETA). We also analyzed the effect of the iterative alternating sequential technique, the optimization technique of RAMUS, compared to the classical minimum norm estimation (MNE) technique. Matching with our previous numerical studies, the current results suggest that RAMUS could have the potential to enhance the detection of simultaneous deep and cortical components and the distinction between the evoked sulcal and gyral activity.

Individually optimized multi-channel tDCS for targeting somatosensory cortex

OBJECTIVE

Transcranial direct current stimulation (tDCS) is a non-invasive neuro-modulation technique that delivers current through the scalp by a pair of patch electrodes (2-Patch). This study proposes a new multi-channel tDCS (mc-tDCS) optimization method, the distributed constrained maximum intensity (D-CMI) approach. For targeting the P20/N20 somatosensory source at Brodmann area 3b, an integrated combined magnetoencephalography (MEG) and electroencephalography (EEG) source analysis is used with individualized skull conductivity calibrated realistic head modeling.

METHODS

Simulated electric fields (EF) for our new D-CMI method and the already known maximum intensity (MI), alternating direction method of multipliers (ADMM) and 2-Patch methods were produced and compared for the individualized P20/N20 somatosensory target for 10 subjects.

RESULTS

D-CMI and MI showed highest intensities parallel to the P20/N20 target compared to ADMM and 2-Patch, with ADMM achieving highest focality. D-CMI showed a slight reduction in intensity compared to MI while reducing side effects and skin level sensations by current distribution over multiple stimulation electrodes.

CONCLUSION

Individualized D-CMI montages are preferred for our follow up somatosensory experiment to provide a good balance between high current intensities at the target and reduced side effects and skin sensations.

SIGNIFICANCE

An integrated combined MEG and EEG source analysis with D-CMI montages for mc-tDCS stimulation potentially can improve control, reproducibility and reduce sensitivity differences between sham and real stimulations.

Intracranial Displacement Measurements Within Targeted Anatomical Regions of a Postmortem Human Surrogate Brain Subjected to Impact

The dynamic response of the human brain subjected to impulsive loading conditions is of fundamental importance to the understanding of traumatic brain injuries. Due to the complexity of such measurements, the existing experimental datasets available to researchers are sparse. However, these measurements are used extensively in the validation of complex finite element models used in the design of protective equipment and the development of injury mitigation strategies. The primary objective of this study was to develop a comprehensive methodology to measure displacement in specific anatomical regions of the brain. A state-of-the-art high-speed cineradiography system was used to capture brain motion in post-mortem human surrogate specimens at a rate of 7500 fps. This paper describes the methodology used to capture these data and presents measurements from these tests. Two-dimensional displacement fields are presented and analyzed based on anatomical regions of the brain. These data demonstrated a multi-modal displacement response in several regions of the brain. The full response of the brain consisted of an elastic superposition of a series of bulk rotations of the brain about its centre of gravity. The displacement field could be linked directly to specific anatomical regions. The methods presented mark an improvement in temporal and spatial resolution of data collection, which has implications for our developing understanding of brain trauma.

Classification of Body Position During Muslim Prayer Using the Convolutional Neural Network

Background: Muslim prayer (Namaz) is the most important obligatory religious duty in Islam that is regularly performed five times per day at specific prescribed times by Muslims. Due to the fact that change of body position affects brain activity, Namaz can be considered as a suitable model to assess the effect of quick changes of the body position on brain activity measured by electroencephalography (EEG). Methods: Forty Muslim participants performed a four-cycle Namaz while their brain activity was being recorded using a 14-channel EEG recorder. The brain connectivity (as defined by a mutual correlation between EEG channels in this study) in different frequency bands (delta, theta, alpha, beta, and gamma) was measured in various positions of Namaz including standing, bowing, prostration, and sitting. Results: The results indicated that the delta band demonstrates the most changes in cross-correlation between the recorded channels, and finally, the accuracy of 73.8% was obtained in the data classification.

Full-field MRI measurements of in-vivo positional brain shift reveal the significance of intra-cranial geometry and head orientation for stereotactic surgery

Positional brain shift (PBS), the sagging of the brain under the effect of gravity, is comparable in magnitude to the margin of error for the success of stereotactic interventions ([Formula: see text] 1 mm). This non-uniform shift due to slight differences in head orientation can lead to a significant discrepancy between the planned and the actual location of surgical targets. Accurate in-vivo measurements of this complex deformation are critical for the design and validation of an appropriate compensation to integrate into neuronavigational systems. PBS arising from prone-to-supine change of head orientation was measured with magnetic resonance imaging on 11 young adults. The full-field displacement was extracted on a voxel-basis via digital volume correlation and analysed in a standard reference space. Results showed the need for target-specific correction of surgical targets, as a significant displacement ranging from 0.52 to 0.77 mm was measured at surgically relevant structures. Strain analysis further revealed local variability in compressibility: anterior regions showed expansion (both volume and shape change), whereas posterior regions showed small compression, mostly dominated by shape change. Finally, analysis of correlation demonstrated the potential for further patient- and intervention-specific adjustments, as intra-cranial breadth and head tilt correlated with PBS reaching statistical significance.

Giant pattern VEPs in children

Our aim is to elaborate the clinical significance of giant amplitude pattern reversal visual evoked potentials (VEPs) in children. 'Giant' amplitude VEPs exceed the upper 97.5^th centile, 90% CI for age. We scrutinised 2750 pattern VEPs recorded to international standards between Jan 2015 and 2017 from children aged 16 years and under, attending a specialist children's hospital. Twenty seven children, median age 6yrs, (range 1-16 yrs), were identified with giant VEPs (P100 amplitude range 65-163 μV). Most, 22/27 (81%), had conditions associated with a risk of raised ICP. Sixteen of these twenty two children had craniosynostosis; six multi-sutural and eight single suture disease. Others had Idiopathic Intracranial Hypertension, arachnoid cyst, NF1 with shunted hydrocephalus, chronic infantile neurological cutaneous and articular (CINCA) syndrome, nephrotic cystinosis and obstructive sleep apnoea. Five children presented with a range of conditions, some associated with seizures some symptomatic, but as yet undiagnosed. Frequent structural associations were optical coherence tomography measures of optic disc maximum anterior axial horizontal retinal thickness projection >160 μm and neuro-radiological findings of CSF effacement and copper beaten appearance. Ultrasonography measures of optic nerve sheath diameters varied, but in one child took 2 years to resolve after treatment for raised ICP. Optic disc gradings by fundoscopy were mostly normal, as were visual acuities. Raised ICP was confirmed by gold standard ICP bolt measurements in five of seven children tested. These data suggest that rICP should be considered if a child has sustained giant amplitude VEPs at normal latency.

Removal of physiological artifacts from simultaneous EEG and fMRI recordings

OBJECTIVE

Simultaneous recording of the electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) allows a combination of eletrophysiological and haemodynamic information to be used to form a more complete picture of cerebral dynamics. However, EEG recorded within the MRI scanner is contaminated by both imaging artifacts and physiological artifacts. The majority of the techniques used to pre-process such EEG focus on removal of the imaging and balistocardiogram artifacts, with some success, but don't remove all other physiological artifacts.

METHODS

We propose a new offline EEG artifact removal method based upon a combination of independent component analysis and fMRI-based head movement estimation to aid the removal of physiological artifacts from EEG recorded during EEG-fMRI recordings. Our method makes novel use of head movement trajectories estimated from the fMRI recording in order to assist with identifying physiological artifacts in the EEG and is designed to be used after removal of the fMRI imaging artifact from the EEG.

RESULTS

We evaluate our method on EEG recorded during a joint EEG-fMRI session from healthy adult participants. Our method significantly reduces the influence of all types of physiological artifacts on the EEG. We also compare our method with a state-of-the-art physiological artifact removal method and demonstrate superior performance removing physiological artifacts.

CONCLUSIONS

Our proposed method is able to remove significantly more physiological artifact components from the EEG, recorded during a joint EEG-fMRI session, than other state-of-the-art methods.

SIGNIFICANCE

Our proposed method represents a marked improvement over current processing pipelines for removing physiological noise from EEG recorded during a joint EEG-fMRI session.

Validating Patient-Specific Finite Element Models of Direct Electrocortical Stimulation

Direct electrocortical stimulation (DECS) with electrocorticography electrodes is an established therapy for epilepsy and an emerging application for stroke rehabilitation and brain-computer interfaces. However, the electrophysiological mechanisms that result in a therapeutic effect remain unclear. Patient-specific computational models are promising tools to predict the voltages in the brain and better understand the neural and clinical response to DECS, but the accuracy of such models has not been directly validated in humans. A key hurdle to modeling DECS is accurately locating the electrodes on the cortical surface due to brain shift after electrode implantation. Despite the inherent uncertainty introduced by brain shift, the effects of electrode localization parameters have not been investigated. The goal of this study was to validate patient-specific computational models of DECS against in vivo voltage recordings obtained during DECS and quantify the effects of electrode localization parameters on simulated voltages on the cortical surface. We measured intracranial voltages in six epilepsy patients during DECS and investigated the following electrode localization parameters: principal axis, Hermes, and Dykstra electrode projection methods combined with 0, 1, and 2 mm of cerebral spinal fluid (CSF) below the electrodes. Greater CSF depth between the electrode and cortical surface increased model errors and decreased predicted voltage accuracy. The electrode localization parameters that best estimated the recorded voltages across six patients with varying amounts of brain shift were the Hermes projection method and a CSF depth of 0 mm (r = 0.92 and linear regression slope = 1.21). These results are the first to quantify the effects of electrode localization parameters with in vivo intracranial recordings and may serve as the basis for future studies investigating the neuronal and clinical effects of DECS for epilepsy, stroke, and other emerging closed-loop applications.

The effect of body posture on resting-state functional connectivity

INTRODUCTION

An important but under-investigated confound of functional MRI (fMRI) is body posture. Although it is well-established that body position changes cerebral blood flow, the amount of cerebrospinal fluid in the brain, intracranial pressure, and even the firing rate of certain cell types, there is currently no study that directly examines its effect on fMRI measurements. Moreover, fMRI is typically done in a supine position, which often does not correspond to how these processes are performed in everyday settings.

METHODS

In this study, 20 healthy adults underwent resting-state fMRI under three body positions: supine, right lateral decubitus (RLD), and left lateral decubitus (LLD). We first investigated whether there were differences in overall organization of whole-brain connectivity between conditions using graph theory. Second, we examined whether functional connectivity of two most studied default mode network (DMN) seeds to the rest of the brain was altered as a function of body position.

RESULTS

Nonparametric statistical analyses revealed that global network measures differed among conditions, with the supine and LLD showing identical results compared to the RLD. There was decreased connectivity for DMN seeds in the RLD condition compared to the supine and LLD, but there were no significant differences between the latter two conditions.

DISCUSSION

Potential mechanisms underlying these alterations include gravity, changes in physiology, and body anatomy. Our results suggest that, compared to supine and LLD, the RLD position leads to changes in whole-brain and DMN connectivity. Finally, depending on the research question, combining imaging modalities that allow for more naturalistic settings can provide a better understanding of certain phenomena.

DUNEuro-A software toolbox for forward modeling in bioelectromagnetism

Accurate and efficient source analysis in electro- and magnetoencephalography using sophisticated realistic head geometries requires advanced numerical approaches. This paper presents DUNEuro, a free and open-source C++ software toolbox for the numerical computation of forward solutions in bioelectromagnetism. Building upon the DUNE framework, it provides implementations of modern fitted and unfitted finite element methods to efficiently solve the forward problems of electro- and magnetoencephalography. The user can choose between a variety of different source models that are implemented. The software's aim is to provide interfaces that are extendable and easy-to-use. In order to enable a closer integration into existing analysis pipelines, interfaces to Python and MATLAB are provided. The practical use is demonstrated by a source analysis example of somatosensory evoked potentials using a realistic six-compartment head model. Detailed installation instructions and example scripts using spherical and realistic head models are appended.

Effect of Static Posture on Online Performance of P300-Based BCIs for TV Control

To implement a practical brain–computer interface (BCI) for daily use, continuing changes in postures while performing daily tasks must be considered in the design of BCIs. To examine whether the performance of a BCI could depend on postures, we compared the online performance of P300-based BCIs built to select TV channels when subjects took sitting, recline, supine, and right lateral recumbent postures during BCI use. Subjects self-reported the degrees of interference, comfort, and familiarity after BCI control in each posture. We found no significant difference in the BCI performance as well as the amplitude and latency of P300 and N200 among the four postures. However, when we compared BCI accuracy outcomes normalized within individuals between two cases where subjects reported relatively more positively or more negatively about using the BCI in a particular posture, we found higher BCI accuracy in those postures for which individual subjects reported more positively. As a result, although the change of postures did not affect the overall performance of P300-based BCIs, the BCI performance varied depending on the degree of postural comfort felt by individual subjects. Our results suggest considering the postural comfort felt by individual BCI users when using a P300-based BCI at home.

A comprehensive study on electroencephalography and magnetoencephalography sensitivity to cortical and subcortical sources

Signal-to-noise ratio (SNR) maps are a good way to visualize electroencephalography (EEG) and magnetoencephalography (MEG) sensitivity. SNR maps extend the knowledge about the modulation of EEG and MEG signals by source locations and orientations and can therefore help to better understand and interpret measured signals as well as source reconstruction results thereof. Our work has two main objectives. First, we investigated the accuracy and reliability of EEG and MEG finite element method (FEM)-based sensitivity maps for three different head models, namely an isotropic three and four-compartment and an anisotropic six-compartment head model. As a result, we found that ignoring the cerebrospinal fluid leads to an overestimation of EEG SNR values. Second, we examined and compared EEG and MEG SNR mappings for both cortical and subcortical sources and their modulation by source location and orientation. Our results for cortical sources show that EEG sensitivity is higher for radial and deep sources and MEG for tangential ones, which are the majority of sources. As to the subcortical sources, we found that deep sources with sufficient tangential source orientation are recordable by the MEG. Our work, which represents the first comprehensive study where cortical and subcortical sources are considered in highly detailed FEM-based EEG and MEG SNR mappings, sheds a new light on the sensitivity of EEG and MEG and might influence the decision of brain researchers or clinicians in their choice of the best modality for their experiment or diagnostics, respectively.

Head-Down Tilt Position, but Not the Duration of Bed Rest Affects Resting State Electrocortical Activity

Adverse cognitive and behavioral conditions and psychiatric disorders are considered a critical and unmitigated risk during future long-duration space missions (LDSM). Monitoring and mitigating crew health and performance risks during these missions will require tools and technologies that allow to reliably assess cognitive performance and mental well-being. Electroencephalography (EEG) has the potential to meet the technical requirements for the non-invasive and objective monitoring of neurobehavioral conditions during LDSM. Weightlessness is associated with fluid and brain shifts, and these effects could potentially challenge the interpretation of resting state EEG recordings. Head-down tilt bed rest (HDBR) provides a unique spaceflight analog to study these effects on Earth. Here, we present data from two long-duration HDBR experiments, which were used to systematically investigate the time course of resting state electrocortical activity during prolonged HDBR. EEG spectral power significantly reduced within the delta, theta, alpha, and beta frequency bands. Likewise, EEG source localization revealed significantly lower activity in a broad range of centroparietal and occipital areas within the alpha and beta frequency domains. These changes were observed shortly after the onset of HDBR, did not change throughout HDBR, and returned to baseline after the cessation of bed rest. EEG resting state functional connectivity was not affected by HDBR. The results provide evidence for a postural effect on resting state brain activity that persists throughout long-duration HDBR, indicating that immobilization and inactivity per se do not affect resting state electrocortical activity during HDBR. Our findings raise an important issue on the validity of EEG to identify the time course of changes in brain function during prolonged HBDR, and highlight the importance to maintain a consistent body posture during all testing sessions, including data collections at baseline and recovery.

The impact of individual electrical fields and anatomical factors on the neurophysiological outcomes of tDCS: A TMS-MEP and MRI study

BACKGROUND

Transcranial direct current stimulation (tDCS), a neuromodulatory non-invasive brain stimulation technique, has shown promising results in basic and clinical studies. The known interindividual variability of the effects, however, limits the efficacy of the technique. Recently we reported neurophysiological effects of tDCS applied over the primary motor cortex at the group level, based on data from twenty-nine participants who received 15min of either sham, 0.5, 1.0, 1.5 or 2.0 mA anodal, or cathodal tDCS. The neurophysiological effects were evaluated via changes in: 1) transcranial magnetic stimulation (TMS)-induced motor evoked potentials (MEP), and 2) cerebral blood flow (CBF) measured by functional magnetic resonance imaging (MRI) via arterial spin labeling (ASL). At the group level, dose-dependent effects of the intervention were obtained, which however displayed interindividual variability.

METHOD

In the present study, we investigated the cause of the observed inter-individual variability. To this end, for each participant, a MRI-based realistic head model was designed to 1) calculate anatomical factors and 2) simulate the tDCS- and TMS-induced electrical fields (EFs). We first investigated at the regional level which individual anatomical factors explained the simulated EFs (magnitude and normal component). Then, we explored which specific anatomical and/or EF factors predicted the neurophysiological outcomes of tDCS.

RESULTS

The results highlight a significant negative correlation between regional electrode-to-cortex distance (rECD) as well as regional CSF (rCSF) thickness, and the individual EF characteristics. In addition, while both rCSF thickness and rECD anticorrelated with tDCS-induced physiological changes, EFs positively correlated with the effects.

CONCLUSION

These results provide novel insights into the dependency of the neuromodulatory effects of tDCS on individual physical factors.

Lying posture affects sleep structures and cortical activities: a simultaneous EEG-fMRI imaging of the sleeping and waking brain

Lying posture influences both neural activity and cognitive performance, and it is essential to sleep hygiene. Whereas, no neuroimaging research has investigated the effect of lying position on brain activity in waking and sleeping conditions. Therefore, we recruited 35 participants to perform a within-participant simultaneous EEG-fMRI recording with lying supine and lateral postures. Our results showed that sleep onset latency (SOL) was affected by both sleep position preference (SPP) and lying poses. SOL in supine was significantly shorter than that in lateral posture. The correlation analysis between SPP and sleep parameters indicated that individuals who prefer supine had less SOL and N2 sleep durations. However, we did not find this significant correlation in lateral-prefer individuals. Besides, different sleep positions mainly caused an alteration of the differences in brain activity patterns. In supine posture, the brain activities in the left precuneus, and anterior cingulate cortex were greater than those in lateral position. However, in the lateral posture, the status was just the opposite. Finally, we also found that the right putamen was sensitive to habitual sleep posture in the awake state. The participants who prefer to lie supine tend to have higher activity in the putamen. Our study may help with the understanding of the contribution of lying posture on brain activity and its relationship with posture preference in sleep.

Brain stimulation in zero gravity: transcranial magnetic stimulation (TMS) motor threshold decreases during zero gravity induced by parabolic flight

We are just beginning to understand how spaceflight may impact brain function. As NASA proceeds with plans to send astronauts to the Moon and commercial space travel interest increases, it is critical to understand how the human brain and peripheral nervous system respond to zero gravity. Here, we developed and refined head-worn transcranial magnetic stimulation (TMS) systems capable of reliably and quickly determining the amount of electromagnetism each individual needs to detect electromyographic (EMG) threshold levels in the thumb (called the resting motor threshold (rMT)). We then collected rMTs in 10 healthy adult participants in the laboratory at baseline, and subsequently at three time points onboard an airplane: (T1) pre-flight at Earth gravity, (T2) during zero gravity periods induced by parabolic flight and (T3) post-flight at Earth gravity. Overall, the subjects required 12.6% less electromagnetism applied to the brain to cause thumb muscle activation during weightlessness compared to Earth gravity, suggesting neurophysiological changes occur during brief periods of zero gravity. We discuss several candidate explanations for this finding, including upward shift of the brain within the skull, acute increases in cortical excitability, changes in intracranial pressure, and diffuse spinal or neuromuscular system effects. All of these possible explanations warrant further study. In summary, we documented neurophysiological changes during brief episodes of zero gravity and thus highlighting the need for further studies of human brain function in altered gravity conditions to optimally prepare for prolonged microgravity exposure during spaceflight.

Impact of Brain Surface Boundary Conditions on Electrophysiology and Implications for Electrocorticography

Volume conduction of electrical potentials in the brain is highly influenced by the material properties and geometry of the tissue and recording devices implanted into the tissue. These effects are very large in EEG due to the volume conduction through the skull and scalp but are often neglected in intracranial electrophysiology. When considering penetrating electrodes deep in the brain, the assumption of an infinite and homogenous medium can be used when the sources are far enough from the brain surface and the electrodes to minimize the boundary effect. When the electrodes are recording from the brain's surface the effect of the boundary cannot be neglected, and the large surface area and commonly used insulating materials in surface electrode arrays may further increase the effect by altering the nature of the boundary in the immediate vicinity of the electrodes. This gives the experimenter some control over the spatial profiles of the potentials by appropriate design of the electrode arrays. We construct a simple three-layer model to describe the effect of material properties and geometry above the brain surface on the electric potentials and conduct empirical experiments to validate this model. A laminar electrode array is used to measure the effect of insulating and relatively conducting layers above the cortical surface by recording evoked potentials alternating between a dried surface and saline covering layer, respectively. Empirically, we find that an insulating boundary amplifies the potentials relative to conductive saline by about a factor of 4, and that the effect is not constrained to potentials that originate near the surface. The model is applied to predict the influence of array design and implantation procedure on the recording amplitude and spatial selectivity of the surface electrode arrays.

Influence of Patient-Specific Head Modeling on EEG Source Imaging

Electromagnetic source imaging (ESI) techniques have become one of the most common alternatives for understanding cognitive processes in the human brain and for guiding possible therapies for neurological diseases. However, ESI accuracy strongly depends on the forward model capabilities to accurately describe the subject's head anatomy from the available structural data. Attempting to improve the ESI performance, we enhance the brain structure model within the individual-defined forward problem formulation, combining the head geometry complexity of the modeled tissue compartments and the prior knowledge of the brain tissue morphology. We validate the proposed methodology using 25 subjects, from which a set of magnetic-resonance imaging scans is acquired, extracting the anatomical priors and an electroencephalography signal set needed for validating the ESI scenarios. Obtained results confirm that incorporating patient-specific head models enhances the performed accuracy and improves the localization of focal and deep sources.

BOLD and EEG signal variability at rest differently relate to aging in the human brain

Variability of neural activity is regarded as a crucial feature of healthy brain function, and several neuroimaging approaches have been employed to assess it noninvasively. Studies on the variability of both evoked brain response and spontaneous brain signals have shown remarkable changes with aging but it is unclear if the different measures of brain signal variability - identified with either hemodynamic or electrophysiological methods - reflect the same underlying physiology. In this study, we aimed to explore age differences of spontaneous brain signal variability with two different imaging modalities (EEG, fMRI) in healthy younger (25 ​± ​3 years, N ​= ​135) and older (67 ​± ​4 years, N ​= ​54) adults. Consistent with the previous studies, we found lower blood oxygenation level dependent (BOLD) variability in the older subjects as well as less signal variability in the amplitude of low-frequency oscillations (1-12 ​Hz), measured in source space. These age-related reductions were mostly observed in the areas that overlap with the default mode network. Moreover, age-related increases of variability in the amplitude of beta-band frequency EEG oscillations (15-25 ​Hz) were seen predominantly in temporal brain regions. There were significant sex differences in EEG signal variability in various brain regions while no significant sex differences were observed in BOLD signal variability. Bivariate and multivariate correlation analyses revealed no significant associations between EEG- and fMRI-based variability measures. In summary, we show that both BOLD and EEG signal variability reflect aging-related processes but are likely to be dominated by different physiological origins, which relate differentially to age and sex.

Influence of posture on blink reflex prepulse inhibition induced by somatosensory inputs from upper and lower limbs

BACKGROUND

Prepulse inhibition (PPI) is a neurophysiological phenomenon whereby a weak stimulus modulates the reflex response to a subsequent strong stimulus. Its physiological purpose is to avoid interruption of sensory processing by subsequent disturbing stimuli at the subcortical level, thereby preventing undesired motor reactions. An important hub in the PPI circuit is the pedunculopontine nucleus, which is also involved in the control of posture and sleep/wakefulness.

OBJECTIVE

To study the effect of posture (supine versus standing) on PPI, induced by somatosensory prepulses to either upper or lower limb. PPI was measured as the percentage inhibition of the blink reflex response to electrical supraorbital nerve (SON) stimulation.

METHODS

Sixteen healthy volunteers underwent bilateral blink reflex recordings following SON stimulation either alone (baseline) or preceded by an electrical prepulse to the median nerve (MN) or sural nerve (SN), both in supine and standing. Stimulus intensity was 8 times sensory threshold for SON, and 2 times sensory threshold for MN and SN, respectively. Eight stimuli were applied in each condition.

RESULTS

Baseline blink reflex parameters did not differ significantly between the two postures. Prepulse stimulation to MN and SN caused significant inhibition of R2. In supine but not in standing, R2 was significantly more inhibited by MN than by SN prepulses. In standing, SN stimulation caused significantly more inhibition of R2 than in supine, while the inhibition caused by MN prepulses did not differ significantly between postures.

SIGNIFICANCE

PPI induced by lower limb afferent input may contribute to postural control while standing.

The effect of stimulation type, head modeling, and combined EEG and MEG on the source reconstruction of the somatosensory P20/N20 component

Modeling and experimental parameters influence the Electro- (EEG) and Magnetoencephalography (MEG) source analysis of the somatosensory P20/N20 component. In a sensitivity group study, we compare P20/N20 source analysis due to different stimulation type (Electric-Wrist [EW], Braille-Tactile [BT], or Pneumato-Tactile [PT]), measurement modality (combined EEG/MEG - EMEG, EEG, or MEG) and head model (standard or individually skull-conductivity calibrated including brain anisotropic conductivity). Considerable differences between pairs of stimulation types occurred (EW-BT: 8.7 ± 3.3 mm/27.1° ± 16.4°, BT-PT: 9 ± 5 mm/29.9° ± 17.3°, and EW-PT: 9.8 ± 7.4 mm/15.9° ± 16.5° and 75% strength reduction of BT or PT when compared to EW) regardless of the head model used. EMEG has nearly no localization differences to MEG, but large ones to EEG (16.1 ± 4.9 mm), while source orientation differences are non-negligible to both EEG (14° ± 3.7°) and MEG (12.5° ± 10.9°). Our calibration results show a considerable inter-subject variability (3.1-14 mS/m) for skull conductivity. The comparison due to different head model show localization differences smaller for EMEG (EW: 3.4 ± 2.4 mm, BT: 3.7 ± 3.4 mm, and PT: 5.9 ± 6.8 mm) than for EEG (EW: 8.6 ± 8.3 mm, BT: 11.8 ± 6.2 mm, and PT: 10.5 ± 5.3 mm), while source orientation differences for EMEG (EW: 15.4° ± 6.3°, BT: 25.7° ± 15.2° and PT: 14° ± 11.5°) and EEG (EW: 14.6° ± 9.5°, BT: 16.3° ± 11.1° and PT: 12.9° ± 8.9°) are in the same range. Our results show that stimulation type, modality and head modeling all have a non-negligible influence on the source reconstruction of the P20/N20 component. The complementary information of both modalities in EMEG can be exploited on the basis of detailed and individualized head models.

Effect of Body Positions on EEG signals in Mal de Debarquement Syndrome

Multimodal neuroimaging, such as combined electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), are being increasingly used to investigate the human brain in healthy and diseased conditions. However, certain neuroimaging data are typically acquired in different body positions, e.g., supine fMRI and upright EEG, overlooking the effect of body position on signal characteristics. In the current study we examined EEG signals in three different positions, i.e., supine, standing and sitting, in patients with a balance disorder called mal de debarquement syndrome (MdDS). Individuals with MdDS experience a chronic illusion of self-motion triggered by prolonged exposure to passive motion, such as from sea or air travel. The degree of perception of rocking dizziness is modulated by body position, suggesting a physiological effect related to body positions. In the present study, EEG features were quantified as peak frequency, peak amplitude, and average amplitude of the alpha band due to its strongest signal characteristics compared to other frequencies. The effect of body position was examined in EEG features from data acquired before and after the individuals received treatment with repetitive transcranial magnetic stimulation. Our results indicate a significant effect of body positions on the EEG signals in MdDS.

Mobility may impact attention abilities in healthy term or prematurely born children at 7-years of age: protocol for an intervention controlled trial

BACKGROUND

Seven years of age is a milestone for learning basic knowledge that is strongly related to attention abilities such as Alerting, Orienting, and Inhibition function, allowing for appropriate adaptation to primary school. These attention abilities are also influenced by gestational age at birth in a complex manner, indicating an area of weakness in prematurely born children. Furthermore, recent studies suggest that allowing children to have freedom of movement during learning may improve their attention level and school performance. The purpose of the present study is to determine the influence of mobility on the attentional components that may impact learning abilities in children aged 7-years who were born at term and prematurely.

METHODS

This prospective, randomized, controlled trial will focus on psychometric testing of attentional abilities assessed with the Attention Network Test for Child (Child ANT) and involves a mixed measurement design. Forty-eight children aged 7-years, half of whom were premature at birth and in their expected grade without learning difficulties will be included after parental consent. They will be equipped with a head-mounted display in which the Child ANT will be presented. The association of different flankers and pre-cues will allow the measurement of the development level of Alerting, Orienting, and Inhibition function. The task will be composed of one experimental block of trials randomly performed per posture: seated, standing, or free.

DISCUSSION

This study will assess the contribution of mobility in specific attentional contexts that are usually present during fundamental learning in children. New pedagogical formats of teaching could consider these findings, and new pedagogical tools enabling free spontaneous child mobility might be designed. Moreover, a small percentage of children integrating into the educational system are born prematurely. These children, often considered immature and hyperactive, could benefit from educational innovations that enhance their attention abilities, thereby improving their adaptation to primary school.

TRIAL REGISTRATION

This trial is registered at ClinicalTrials.gov ( NCT03125447 ).

On the Physiological Modulation and Potential Mechanisms Underlying Parieto-Occipital Alpha Oscillations

The parieto-occipital alpha (8–13 Hz) rhythm is by far the strongest spectral fingerprint in the human brain. Almost 90 years later, its physiological origin is still far from clear. In this Research Topic I review human pharmacological studies using electroencephalography (EEG) and magnetoencephalography (MEG) that investigated the physiological mechanisms behind posterior alpha. Based on results from classical and recent experimental studies, I find a wide spectrum of drugs that modulate parieto-occipital alpha power. Alpha frequency is rarely affected, but this might be due to the range of drug dosages employed. Animal and human pharmacological findings suggest that both GABA enhancers and NMDA blockers systematically decrease posterior alpha power. Surprisingly, most of the theoretical frameworks do not seem to embrace these empirical findings and the debate on the functional role of alpha oscillations has been polarized between the inhibition vs. active poles hypotheses. Here, I speculate that the functional role of alpha might depend on physiological excitation as much as on physiological inhibition. This is supported by animal and human pharmacological work showing that GABAergic, glutamatergic, cholinergic, and serotonergic receptors in the thalamus and the cortex play a key role in the regulation of alpha power and frequency. This myriad of physiological modulations fit with the view that the alpha rhythm is a complex rhythm with multiple sources supported by both thalamo-cortical and cortico-cortical loops. Finally, I briefly discuss how future research combining experimental measurements derived from theoretical predictions based of biophysically realistic computational models will be crucial to the reconciliation of these disparate findings.