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Previous studies have found electroencephalogram (EEG) amplitude and scalp topography differences between neurotypical and neurological/neurosurgical groups, being interpreted at the cognitive level. However, these comparisons are invariably accompanied by anatomical changes. Critical to EEG are the so‐called volume currents, which are affected by the spatial distribution of the different tissues in the head. We investigated the effect of cerebrospinal fluid (CSF)‐filled cavities on simulated EEG scalp data. We simulated EEG scalp potentials for known sources using different volume conduction models: a reference model (i.e., unlesioned brain) and models with realistic CSF‐filled cavities gradually increasing in size. We used this approach for a single source close or far from the CSF‐lesion cavity, and for a scenario with a distributed configuration of sources (i.e., a "cognitive event‐related potential effect"). The magnitude and topography errors between the reference and lesion models were quantified. For the single‐source simulation close to the lesion, the CSF‐filled lesion modulated signal amplitude with more than 17% magnitude error and topography with more than 9% topographical error. Negligible modulation was found for the single source far from the lesion. For the multisource simulations of the cognitive effect, the CSF‐filled lesion modulated signal amplitude with more than 6% magnitude error and topography with more than 16% topography error in a nonmonotonic fashion. In conclusion, the impact of a CSF‐filled cavity cannot be neglected for scalp‐level EEG data. Especially when group‐level comparisons are made, any scalp‐level attenuated, aberrant, or absent effects are difficult to interpret without considering the confounding effect of CSF. Previous studies have found electroencephalogram (EEG) amplitude and scalp topography differences between neurotypical and neurological/neurosurgical groups (whose brain damage leads to the presence of a cerebrospinal fluid‐filled cavity) being interpreted at the cognitive level. Via simulations of scalp‐level EEG patterns, we show that attenuated, aberrant, or absent effects in these comparisons are difficult to interpret without considering the confounding effect of CSF. [ABSTRACT FROM AUTHOR]

We present an extension to the Brain Imaging Data Structure (BIDS) for motion data. Motion data is frequently recorded alongside human brain imaging and electrophysiological data. The goal of Motion-BIDS is to make motion data interoperable across different laboratories and with other data modalities in human brain and behavioral research. To this end, Motion-BIDS standardizes the data format and metadata structure. It describes how to document experimental details, considering the diversity of hardware and software systems for motion data. This promotes findable, accessible, interoperable, and reusable data sharing and Open Science in human motion research. [ABSTRACT FROM AUTHOR]

Introduction: Volume conductionmodels of the human head are used in various neuroscience fields, such as for source reconstruction in EEG and MEG, and for modeling the effects of brain stimulation. Numerous studies have quantified the accuracy and sensitivity of volume conductionmodels by analyzing the effects of the geometrical and electrical features of the head model, the sensor model, the sourcemodel, and the numericalmethod. Most studies are based on simulations as it is hard to obtain sufficiently detailed measurements to compare to models. The recording of stereotactic EEG during electric stimulation mapping provides an opportunity for such empirical validation. Methods: In the study presented here, we used the potential distribution of volume-conducted artifacts that are due to cortical stimulation to evaluate the accuracy of finite element method (FEM) volume conduction models. We adopted a widely used strategy for numerical comparison, i.e., we fixed the geometrical description of the head model and the mathematical method to performsimulations, and we gradually altered the headmodels, by increasing the level of detail of the conductivity profile. We compared the simulated potentials at different levels of refinement with the measured potentials in three epilepsy patients. Results: Our results show that increasing the level of detail of the volume conduction head model only marginally improves the accuracy of the simulated potentials when compared to in-vivo sEEG measurements. The mismatch between measured and simulated potentials is, throughout all patients and models, maximally 40 microvolts (i.e., 10% relative error) in 80% of the stimulation-recording combination pairs and it is modulated by the distance between recording and stimulating electrodes. Discussion: Our study suggests that commonly used strategies used to validate volume conduction models based solely on simulations might give an overly optimistic idea about volume conduction model accuracy. We recommend more empirical validations to be performed to identify those factors in volume conduction models that have the highest impact on the accuracy of simulated potentials. We share the dataset to allow researchers to further investigate the mismatch between measurements and FEM models and to contribute to improving volume conduction models. [ABSTRACT FROM AUTHOR]

Parkinson’s disease (PD) is characterised by a loss of dopamine and dopaminergic cells. The consequences hereof are widespread network disturbances in brain function. It is an ongoing topic of investigation how the disease-related changes in brain function manifest in PD relate to clinical symptoms. We present The Swedish National Facility for Magnetoencephalography Parkinson’s Disease Dataset (NatMEG-PD) as an Open Science contribution to identify the functional neural signatures of Parkinson’s disease and contribute to diagnosis and treatment. The dataset contains whole-head magnetoencephalographic (MEG) recordings from 66 well-characterised PD patients on their regular dose of dopamine replacement therapy and 68 age- and sex-matched healthy controls. NatMEG-PD contains three-minute eyes-closed resting-state MEG, MEG during an active movement task, and MEG during passive movements. The data includes anonymised MRI for source analysis and clinical scores. MEG data is rich in nature and can be used to explore numerous functional features. By sharing these data, we hope other researchers will contribute to advancing our understanding of the relationship between brain activity and disease state or symptoms. [ABSTRACT FROM AUTHOR]

Speaking requires the temporally coordinated planning of core linguistic information, from conceptual meaning to articulation. Recent neurophysiological results suggested that these operations involve a cascade of neural events with subsequent onset times, whilst competing evidence suggests early parallel neural activation. To test these hypotheses, we examined the sources of neuromagnetic activity recorded from 34 participants overtly naming 134 images from 4 object categories (animals, tools, foods and clothes). Within each category, word length and phonological neighbourhood density were co-varied to target phonological/phonetic processes. Multivariate pattern analyses (MVPA) searchlights in source space decoded object categories in occipitotemporal and middle temporal cortex, and phonological/phonetic variables in left inferior frontal (BA 44) and motor cortex early on. The findings suggest early activation of multiple variables due to intercorrelated properties and interactivity of processing, thus raising important questions about the representational properties of target words during the preparatory time enabling overt speaking. [ABSTRACT FROM AUTHOR]

Language production involves a complex set of computations, from conceptualization to articulation, which are thought to engage cascading neural events in the language network. However, recent neuromagnetic evidence suggests simultaneous meaning-to-speech mapping in picture naming tasks, as indexed by early parallel activation of frontotemporal regions to lexical semantic, phonological, and articulatory information. Here we investigate the time course of word production, asking to what extent such "earliness" is a distinctive property of the associated spatiotemporal dynamics. Using MEG, we recorded the neural signals of 34 human subjects (26 males) overtly naming 134 images from four semantic object categories (animals, foods, tools, clothes). Within each category, we covaried word length, as quantified by the number of syllables contained in a word, and phonological neighborhood density to target lexical and post-lexical phonological/phonetic processes. Multivariate pattern analyses searchlights in sensor space distinguished the stimulus-locked spatiotemporal responses to object categories early on, from 150 to 250 ms after picture onset, whereas word length was decoded in left frontotemporal sensors at 250-350 ms, followed by the latency of phonological neighborhood density (350-450 ms). Our results suggest a progression of neural activity from posterior to anterior language regions for the semantic and phonological/phonetic computations preparing overt speech, thus supporting serial cascading models of word production. [ABSTRACT FROM AUTHOR]

Decreases in oscillatory alpha‐ and beta‐band power have been consistently found in spoken‐word production. These have been linked to both motor preparation and conceptual‐lexical retrieval processes. However, the observed power decreases have a broad frequency range that spans two "classic" (sensorimotor) bands: alpha and beta. It remains unclear whether alpha‐ and beta‐band power decreases contribute independently when a spoken word is planned. Using a re‐analysis of existing magnetoencephalography data, we probed whether the effects in alpha and beta bands are spatially distinct. Participants read a sentence that was either constraining or non‐constraining toward the final word, which was presented as a picture. In separate blocks participants had to name the picture or score its predictability via button press. Irregular‐resampling auto‐spectral analysis (IRASA) was used to isolate the oscillatory activity in the alpha and beta bands from the background 1‐over‐f spectrum. The sources of alpha‐ and beta‐band oscillations were localized based on the participants' individualized peak frequencies. For both tasks, alpha‐ and beta‐power decreases overlapped in left posterior temporal and inferior parietal cortex, regions that have previously been associated with conceptual and lexical processes. The spatial distributions of the alpha and beta power effects were spatially similar in these regions to the extent we could assess it. By contrast, for left frontal regions, the spatial distributions differed between alpha and beta effects. Our results suggest that for conceptual‐lexical retrieval, alpha and beta oscillations do not dissociate spatially and, thus, are distinct from the classical sensorimotor alpha and beta oscillations. It remains unclear whether the consistently found alpha‐ and beta‐band power decreases in spoken‐word production support a single operation or contribute independently. Using novel methodology, we probed whether the alpha and beta bands are distinct from an anatomical perspective. We found anatomical overlap in the left posterior temporal and inferior parietal cortex, whereas for the left frontal region, the spatial overlap was limited. Our results suggest that for conceptual‐lexical retrieval, alpha and beta oscillations do not dissociate and, thus, are distinct from the classical sensorimotor alpha and beta. [ABSTRACT FROM AUTHOR]

The Brain Imaging Data Structure (BIDS) is a specification for organizing, sharing, and archiving neuroimaging data and metadata in a reusable way. First developed for magnetic resonance imaging (MRI) datasets, the community-led specification evolved rapidly to include other modalities such as magnetoencephalography, positron emission tomography, and quantitative MRI (qMRI). In this work, we present an extension to BIDS for microscopy imaging data, along with example datasets. Microscopy-BIDS supports common imaging methods, including 2D/3D, ex / in vivo , micro-CT, and optical and electron microscopy. Microscopy-BIDS also includes comprehensible metadata definitions for hardware, image acquisition, and sample properties. This extension will facilitate future harmonization efforts in the context of multi-modal, multi-scale imaging such as the characterization of tissue microstructure with qMRI. [ABSTRACT FROM AUTHOR]

Some articles processed EEG data ( I n i = 9), MEG data ( I n i = 8), joint EEG/MEG data ( I n i = 7), or even EEG/MEG/fMRI data ( I n i = 1). Keywords: EEG; MEG; iEEG; BIDS; pipeline EN EEG MEG iEEG BIDS pipeline 1 4 4 04/18/22 20220413 NES 220413 Free and open-source academic toolboxes have gained increasing prominence in the field of MEG/EEG research to disseminate cutting-edge methods, share best practices between different research groups, and pool resources for developing essential tools for the MEG/EEG community. [Extracted from the article]

It is widely recognized that police performance may be hindered by psychophysiological state changes during acute stress. To address the need for awareness and control of these physiological changes, police academies in many countries have implemented Heart-Rate Variability (HRV) biofeedback training. Despite these trainings now being widely delivered in classroom setups, they typically lack the arousing action context needed for successful transfer to the operational field, where officers must apply learned skills, particularly when stress levels rise. The study presented here aimed to address this gap by training physiological control skills in an arousing decision-making context. We developed a Virtual-Reality (VR) breathing-based biofeedback training in which police officers perform deep and slow diaphragmatic breathing in an engaging game-like action context. This VR game consisted of a selective shoot/don't shoot game designed to assess response inhibition, an impaired capacity in high arousal situations. Biofeedback was provided based on adherence to a slow breathing pace: the slower and deeper the breathing, the less constrained peripheral vision became, facilitating accurate responses to the in-game demands. A total of nine male police trainers completed 10 sessions over a 4-week period as part of a single-case experimental ABAB study-design (i.e., alternating sessions with and without biofeedback). Results showed that eight out of nine participants showed improved breathing control in action, with a positive effect on breathing-induced low frequency HRV, while also improving their in-game behavioral performance. Critically, the breathing-based skill learning transferred to subsequent sessions in which biofeedback was not presented. Importantly, all participants remained highly engaged throughout the training. Altogether, our study showed that our VR environment can be used to train breathing regulation in an arousing and active decision-making context. [ABSTRACT FROM AUTHOR]

An individual's blood pressure (BP) reactivity to stress is linked to increased risk of hypertension and cardiovascular disease. However, inter- and intra-individual BP variability makes understanding the coupling between stress, BP reactivity, and long-term outcomes challenging. Previous microneurographic studies of sympathetic signaling to muscle vasculature (i.e. muscle sympathetic nerve activity, MSNA) have established a neural predictor for an individual's BP reactivity during short-lasting stress. Unfortunately, this method is invasive, technically demanding, and time-consuming and thus not optimal for widespread use. Potential central nervous system correlates have not been investigated. We used MagnetoEncephaloGraphy and Magnetic Resonance Imaging to search for neural correlates to sympathetic response profiles within the central autonomic network and sensorimotor (Rolandic) regions in 20 healthy young males. The main correlates include (a) Rolandic beta rebound and an anterior cingulate cortex (ACC) response elicited by sudden stimulation and (b) cortical thickness in the ACC. Our findings highlight the involvement of the ACC in reactions to stress entailing peripheral sympathetic responses to environmental stimuli. The Rolandic response furthermore indicates a surprisingly strong link between somatosensory and autonomic processes. Our results thus demonstrate the potential in using non-invasive neuroimaging-based measures of stress-related MSNA reactions, previously assessed only using invasive microneurography. [ABSTRACT FROM AUTHOR]

Analyses of brain function and anatomy using shared neuroimaging data is an important development, and have acquired the potential to be scaled up with the specification of a new Brain Imaging Data Structure (BIDS) standard. To date, a variety of software tools help researchers in converting their source data to BIDS but often require programming skills or are tailored to specific institutes, data sets, or data formats. In this paper, we introduce BIDScoin, a cross-platform, flexible, and user-friendly converter that provides a graphical user interface (GUI) to help users finding their way in BIDS standard. BIDScoin does not require programming skills to be set up and used and supports plugins to extend their functionality. In this paper, we show its design and demonstrate how it can be applied to a downloadable tutorial data set. BIDScoin is distributed as free and open-source software to foster the community-driven effort to promote and facilitate the use of BIDS standard. [ABSTRACT FROM AUTHOR]

As part of the Dutch national science program "Professional Games for Professional Skills" we developed a stress-exposure biofeedback training in virtual reality (VR) for the Dutch police. We aim to reduce the acute negative impact of stress on performance, as well as long-term consequences for mental health by facilitating physiological stress regulation during a demanding decision task. Conventional biofeedback applications mainly train physiological regulation at rest. This might limit the transfer of the regulation skills to stressful situations. In contrast, we provide the user with the opportunity to practice breathing regulation while they carry out a complex task in VR. This setting poses challenges from a technical – (real-time processing of noisy biosignals) as well as from a user-experience perspective (multi-tasking). We illustrate how we approach these challenges in our training and hope to contribute a useful reference for researchers and developers in academia or industry who are interested in using biosignals to control elements in a dynamic virtual environment. [ABSTRACT FROM AUTHOR]

Activity of sensory and motor cortices is essential for sensorimotor integration. In particular, coherence between these areas may indicate binding of critical functions like perception, motor planning, action, or sleep. Evidence is accumulating that cerebellar output modulates cortical activity and coherence, but how, when, and where it does so is unclear. We studied activity in and coherence between S1 and M1 cortices during whisker stimulation in the absence and presence of optogenetic Purkinje cell stimulation in crus 1 and 2 of awake mice, eliciting strong simple spike rate modulation. Without Purkinje cell stimulation, whisker stimulation triggers fast responses in S1 and M1 involving transient coherence in a broad spectrum. Simultaneous stimulation of Purkinje cells and whiskers affects amplitude and kinetics of sensory responses in S1 and M1 and alters the estimated S1-M1 coherence in theta and gamma bands, allowing bidirectional control dependent on behavioral context. These effects are absent when Purkinje cell activation is delayed by 20 ms. Focal stimulation of Purkinje cells revealed site specificity, with cells in medial crus 2 showing the most prominent and selective impact on estimated coherence, i.e., a strong suppression in the gamma but not the theta band. Granger causality analyses and computational modeling of the involved networks suggest that Purkinje cells control S1-M1 phase consistency predominantly via ventrolateral thalamus and M1. Our results indicate that activity of sensorimotor cortices can be dynamically and functionally modulated by specific cerebellar inputs, highlighting a widespread role of the cerebellum in coordinating sensorimotor behavior. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Learning to associate written letters/characters with speech sounds is crucial for reading acquisition. Most previous studies have focused on audiovisual integration in alphabetic languages. Less is known about logographic languages such as Chinese characters, which map onto mostly syllable-based morphemes in the spoken language. Here we investigated how long-term exposure to native language affects the underlying neural mechanisms of audiovisual integration in a logographic language using magnetoencephalography (MEG). MEG sensor and source data from 12 adult native Chinese speakers and a control group of 13 adult Finnish speakers were analyzed for audiovisual suppression (bimodal responses vs. sum of unimodal responses) and congruency (bimodal incongruent responses vs. bimodal congruent responses) effects. The suppressive integration effect was found in the left angular and supramarginal gyri (205–365 ms), left inferior frontal and left temporal cortices (575–800 ms) in the Chinese group. The Finnish group showed a distinct suppression effect only in the right parietal and occipital cortices at a relatively early time window (285–460 ms). The congruency effect was only observed in the Chinese group in left inferior frontal and superior temporal cortex in a late time window (about 500–800 ms) probably related to modulatory feedback from multi-sensory regions and semantic processing. The audiovisual integration in a logographic language showed a clear resemblance to that in alphabetic languages in the left superior temporal cortex, but with activation specific to the logographic stimuli observed in the left inferior frontal cortex. The current MEG study indicated that learning of logographic languages has a large impact on the audiovisual integration of written characters with some distinct features compared to previous results on alphabetic languages. [ABSTRACT FROM AUTHOR]

The auditory steady state evoked response (ASSR) is a robust and frequently utilized phenomenon in psychophysiological research. It reflects the auditory cortical response to an amplitude-modulated constant carrier frequency signal. The present report provides a concrete example of a group analysis of the EEG data from 29 healthy human participants, recorded during an ASSR paradigm, using the FieldTrip toolbox. First, we demonstrate sensor-level analysis in the time domain, allowing for a description of the event-related potentials (ERPs), as well as their statistical evaluation. Second, frequency analysis is applied to describe the spectral characteristics of the ASSR, followed by group level statistical analysis in the frequency domain. Third, we show how time- and frequency-domain analysis approaches can be combined in order to describe the temporal and spectral development of the ASSR. Finally, we demonstrate source reconstruction techniques to characterize the primary neural generators of the ASSR. Throughout, we pay special attention to explaining the design of the analysis pipeline for single subjects and for the group level analysis. The pipeline presented here can be adjusted to accommodate other experimental paradigms and may serve as a template for similar analyses. [ABSTRACT FROM AUTHOR]

Accurate estimation of the neural activity underlying magnetoencephalography (MEG) signals requires co-registration i.e., determination of the position and orientation of the sensors with respect to the head. In modern MEG systems, an array of hundreds of low-Tc SQUID sensors is used to localize a set of small, magnetic dipole-like (head-position indicator, HPI) coils that are attached to the subject’s head. With accurate prior knowledge of the positions and orientations of the sensors with respect to one another, the HPI coils can be localized with high precision, and thereby the positions of the sensors in relation to the head. With advances in magnetic field sensing technologies, e.g., high-Tc SQUIDs and optically pumped magnetometers (OPM), that require less extreme operating temperatures than low-Tc SQUID sensors, on-scalp MEG is on the horizon. To utilize the full potential of on-scalp MEG, flexible sensor arrays are preferable. Conventional co-registration is impractical for such systems as the relative positions and orientations of the sensors to each other are subject-specific and hence not known a priori. Herein, we present a method for co-registration of on-scalp MEG sensors. We propose to invert the conventional co-registration approach and localize the sensors relative to an array of HPI coils on the subject’s head. We show that given accurate prior knowledge of the positions of the HPI coils with respect to one another, the sensors can be localized with high precision. We simulated our method with realistic parameters and layouts for sensor and coil arrays. Results indicate co-registration is possible with sub-millimeter accuracy, but the performance strongly depends upon a number of factors. Accurate calibration of the coils and precise determination of the positions and orientations of the coils with respect to one another are crucial. Finally, we propose methods to tackle practical challenges to further improve the method. [ABSTRACT FROM AUTHOR]

In Electro- (EEG) and Magnetoencephalography (MEG), one important requirement of source reconstruction is the forward model. The continuous Galerkin finite element method (CG-FEM) has become one of the dominant approaches for solving the forward problem over the last decades. Recently, a discontinuous Galerkin FEM (DG-FEM) EEG forward approach has been proposed as an alternative to CG-FEM (Engwer et al., 2017). It was shown that DG-FEM preserves the property of conservation of charge and that it can, in certain situations such as the so-called skull leakages, be superior to the standard CG-FEM approach. In this paper, we developed, implemented, and evaluated two DG-FEM approaches for the MEG forward problem, namely a conservative and a non-conservative one. The subtraction approach was used as source model. The validation and evaluation work was done in statistical investigations in multi-layer homogeneous sphere models, where an analytic solution exists, and in a six-compartment realistically shaped head volume conductor model. In agreement with the theory, the conservative DG-FEM approach was found to be superior to the non-conservative DG-FEM implementation. This approach also showed convergence with increasing resolution of the hexahedral meshes. While in the EEG case, in presence of skull leakages, DG-FEM outperformed CG-FEM, in MEG, DG-FEM achieved similar numerical errors as the CG-FEM approach, i.e., skull leakages do not play a role for the MEG modality. In particular, for the finest mesh resolution of 1 mm sources with a distance of 1.59 mm from the brain-CSF surface, DG-FEM yielded mean topographical errors (relative difference measure, RDM%) of 1.5% and mean magnitude errors (MAG%) of 0.1% for the magnetic field. However, if the goal is a combined source analysis of EEG and MEG data, then it is highly desirable to employ the same forward model for both EEG and MEG data. Based on these results, we conclude that the newly presented conservative DG-FEM can at least complement and in some scenarios even outperform the established CG-FEM approaches in EEG or combined MEG/EEG source analysis scenarios, which motivates a further evaluation of DG-FEM for applications in bioelectromagnetism. [ABSTRACT FROM AUTHOR]

The development of new magnetic sensor technologies that promise sensitivities approaching that of conventional MEG technology while operating at far lower operating temperatures has catalysed the growing field of on-scalp MEG. The feasibility of on-scalp MEG has been demonstrated via benchmarking of new sensor technologies performing neuromagnetic recordings in close proximity to the head surface against state-of-the-art in-helmet MEG sensor technology. However, earlier work has provided little information about how these two approaches compare, or about the reliability of observed differences. Herein, we present such a comparison, based on recordings of the N20m component of the somatosensory evoked field as elicited by electric median nerve stimulation. As expected from the proximity differences between the on-scalp and in-helmet sensors, the magnitude of the N20m activation as recorded with the on-scalp sensor was higher than that of the in-helmet sensors. The dipole pattern of the on-scalp recordings was also more spatially confined than that of the conventional recordings. Our results furthermore revealed unexpected temporal differences in the peak of the N20m component. An analysis protocol was therefore developed for assessing the reliability of this observed difference. We used this protocol to examine our findings in terms of differences in sensor sensitivity between the two types of MEG recordings. The measurements and subsequent analysis raised attention to the fact that great care has to be taken in measuring the field close to the zero-line crossing of the dipolar field, since it is heavily dependent on the orientation of sensors. Taken together, our findings provide reliable evidence that on-scalp and in-helmet sensors measure neural sources in mostly similar ways. [ABSTRACT FROM AUTHOR]

Objective: We present a benchmarking protocol for quantitatively comparing emerging on-scalp magnetoencephalography (MEG) sensor technologies to their counterparts in state-of-the-art MEG systems. Methods: As a means of validation, we compare a high-critical-temperature superconducting quantum interference device (high $T_{{c}}$ SQUID) with the low-$T_{{c}}$ SQUIDs of an Elekta Neuromag TRIUX system in MEG recordings of auditory and somatosensory evoked fields (SEFs) on one human subject. Results: We measure the expected signal gain for the auditory-evoked fields (deeper sources) and notice some unfamiliar features in the on-scalp sensor-based recordings of SEFs (shallower sources). Conclusion: The experimental results serve as a proof of principle for the benchmarking protocol. This approach is straightforward, general to various on-scalp MEG sensors, and convenient to use on human subjects. The unexpected features in the SEFs suggest on-scalp MEG sensors may reveal information about neuromagnetic sources that is otherwise difficult to extract from state-of-the-art MEG recordings. Significance: As the first systematically established on-scalp MEG benchmarking protocol, magnetic sensor developers can employ this method to prove the utility of their technology in MEG recordings. Further exploration of the SEFs with on-scalp MEG sensors may reveal unique information about their sources. [ABSTRACT FROM AUTHOR]

Several electrophysiological studies suggest that Parkinson's disease (PD) patients have a reduced tendency to entrain to regular environmental patterns. Here we investigate whether this reduced entrainment concerns a generalized deficit or is confined to movement-related activity, leaving sensory entrainment intact. Magnetoencephalography was recorded during a rhythmic auditory target detection task in 14 PD patients and 14 control subjects. Participants were instructed to press a button when hearing a target tone amid an isochronous sequence of standard tones. The variable pitch of standard tones indicated the probability of the next tone to be a target. In addition, targets were occasionally omitted to evaluate entrainment uncontaminated by stimulus effects. Response times were not significantly different between groups and both groups benefited equally from the predictive value of standard tones. Analyses of oscillatory beta power over auditory cortices showed equal entrainment to the tones in both groups. By contrast, oscillatory beta power and event-related fields demonstrated a reduced engagement of motor cortical areas in PD patients, expressed in the modulation depth of beta power, in the response to omitted stimuli, and in an absent motor area P300 effect. Together, these results show equally strong entrainment of neural activity over sensory areas in controls and patients, but, in patients, a deficient translation of the adjustment to the task rhythm to motor circuits. We suggest that the reduced activation reflects not merely altered resonance to rhythmic external events, but a compromised recruitment of an endogenous response reflecting internal rhythm generation. NEW & NOTEWORTHY: Previous studies suggest that motor cortical activity in PD patients has a reduced tendency to entrain to regular environmental patterns. This study demonstrates that the deficient entrainment in PD concerns the motor system only, by showing equally strong entrainment of neural activity over sensory areas in controls and patients but, in patients, a deficient translation of this adjustment to the task rhythm to motor circuits. [ABSTRACT FROM AUTHOR]

Neuronal oscillations support cognitive processing. Modern views suggest that neuronal oscillations do not only reflect coordinated activity in spatially distributed networks, but also that there is interaction between the oscillations at different frequencies. For example, invasive recordings in animals and humans have found that the amplitude of fast oscillations (>40 Hz) occur non-uniformly within the phase of slower oscillations, forming the so-called cross-frequency coupling (CFC). However, the CFC patterns might be influenced by features in the signal that do not relate to underlying physiological interactions. For example, CFC estimates may be sensitive to spectral correlations due to non-sinusoidal properties of the alpha band wave morphology. To investigate this issue, we performed CFC analysis using experimental and synthetic data. The former consisted in a double-blind magnetoencephalography pharmacological study in which participants received either placebo, 0.5 or 1.5mg of lorazepam (LZP; GABAergic enhancer) in different experimental sessions. By recording oscillatory brain activity with during rest and working memory (WM), we were able to demonstrate that posterior alpha (8–12 Hz) phase was coupled to beta-low gamma band (20–45 Hz) amplitude envelope during all sessions. Importantly, bicoherence values around the harmonics of the alpha frequency were similar both in magnitude and topographic distribution to the cross-frequency coherence (CFCoh) values observed in the alpha-phase to beta-low gamma coupling. In addition, despite the large CFCoh we found no significant cross-frequency directionality (CFD). Critically, simulations demonstrated that a sizable part of our empirical CFCoh between alpha and beta-low gamma coupling and the lack of CFD could be explained by two-three harmonics aligned in zero phase-lag produced by the physiologically characteristic alpha asymmetry in the amplitude of the peaks relative to the troughs. Furthermore, we showed that periodic signals whose waveform deviate from pure sine waves produce non-zero CFCoh with predictable CFD. Our results reveal the important role of the non-sinusoidal wave morphology on state of the art CFC metrics and we recommend caution with strong physiological interpretations of CFC and suggest basic data quality checks to enhance the mechanistic understanding of CFC. [ABSTRACT FROM AUTHOR]

Ethologically inspired models of movement preparation view the sensorimotor system as sampling information from the environment in a parallel fashion in preparation for multiple potential actions. In support, the configuration of the physical workspace, manipulated by the number or spatial separation of potential targets, has been shown to modulate sensorimotor neural activity. It is unclear, however, whether this modulation is driven by the sensory layout of the workspace or through the associated motor plans. Here, we combine a delayed-movement pre-cuing task with visuomotor adaptation to address this question in human subjects while recording MEG. By dissociating visual and motor coordinates of two targets using visuomotor adaptation, the task was designed to evaluate, in a selective fashion, the effects of visual and movement target separation on movement preparatory activity. The results did not allow the intended comparison due to an unanticipated effect of the direction of visuomotor adaptation on baseline oscillatory power in beta and lowgammabands. Fortuitously, this effect was dependent on whether the adaptation direction decreased or increased the angular separation between alternative movements. That is, there was a sustained reduction of oscillatory power, which was stronger at small compared with large target separation. These results support a direct influence of movement target separation on motor cortex neural activity, mediated by lateral interactions between simultaneously active motor plans. The results further demonstrate a novel effect of visuomotor adaptation on motor cortex oscillatory activity, with properties that support the local nature of learned changes in visuomotor mapping. [ABSTRACT FROM AUTHOR]

Here we report that the modulation of alpha activity by covert attention can be used as a control signal in an online brain-computer interface, that it is reliable, and that it is robust. Subjects were instructed to orient covert visual attention to the left or right hemifield. We decoded the direction of attention from the magnetoencephalogram by a template matching classifier and provided the classification outcome to the subject in real-time using a novel graphical user interface. Training data for the templates were obtained from a Posner-cueing task conducted just before the BCI task. Eleven subjects participated in four sessions each. Eight of the subjects achieved classification rates significantly above chance level. Subjects were able to significantly increase their performance from the first to the second session. Individual patterns of posterior alpha power remained stable throughout the four sessions and did not change with increased performance. We conclude that posterior alpha power can successfully be used as a control signal in brain-computer interfaces. We also discuss several ideas for further improving the setup and propose future research based on solid hypotheses about behavioral consequences of modulating neuronal oscillations by brain computer interfacing. [ABSTRACT FROM AUTHOR]

In this study, we explore the possibility to predict the semantic category of words from brain signals in a free word generation task. Participants produced single words from different semantic categories in a modified semantic fluency task. A Bayesian logistic regression classifier was trained to predict the semantic category of words from single-trial MEG data. Significant classification accuracies were achieved using sensor-level MEG time series at the time interval of conceptual preparation. Semantic category prediction was also possible using source-reconstructed time series, based on minimum norm estimates of cortical activity. Brain regions that contributed most to classification on the source level were identified. These were the left inferior frontal gyrus, left middle frontal gyrus, and left posterior middle temporal gyrus. Additionally, the temporal dynamics of brain activity underlying the semantic preparation during word generation was explored. These results provide important insights about central aspects of language production. [ABSTRACT FROM AUTHOR]

How can we understand each other during communicative interactions? An influential suggestion holds that communicators are primed by each other's behaviors, with associative mechanisms automatically coordinating the production of communicative signals and the comprehension of their meanings. An alternative suggestion posits that mutual understanding requires shared conceptualizations of a signal's use, i.e., "conceptual pacts" that are abstracted away from specific experiences. Both accounts predict coherent neural dynamics across communicators, aligned either to the occurrence of a signal or to the dynamics of conceptual pacts. Using coherence spectral-density analysis of cerebral activity simultaneously measured in pairs of communicators, this study shows that establishing mutual understanding of novel signals synchronizes cerebral dynamics across communicators' right temporal lobes. This interpersonal cerebral coherence occurred only within pairs with a shared communicative history, and at temporal scales independent from signals' occurrences. These findings favor the notion that meaning emerges from shared conceptualizations of a signal's use. [ABSTRACT FROM AUTHOR]

Choice behavior is influenced by factors such as reward and number of alternatives but also by physical context, for instance, the relative position of alternative movement targets. At small separation, speeded eye or hand movements are more likely to land between targets (spatial averaging) than at larger separation. Neurocomputational models explain such behavior in terms of cortical activity being preshaped by the movement environment. Here, we manipulate target separation, as a determinant of motor cortical activity in choice behavior, to address neural mechanisms of response selection. Specifically, we investigate whether context-induced changes in the balance of cooperative and competitive interactions between competing groups of neurons are expressed in the power spectrum of sensorimotor rhythms. We recorded magnetoencephalography while participants were precued to two possible movement target locations at different angles of separation (30, 60, or 90°). After a delay, one of the locations was cued as the target for a joystick pointing movement. We found that late delay-period movement-preparatory activity increased more strongly for alternative targets at 30 than at 60 or 90° of separation. This nonlinear pattern was evident in slow event-related fields as well as in beta- and low-gamma-band suppression. A comparable pattern was found within an earlier window for theta-band synchronization. We interpret the late delay effects in terms of increased movement-preparatory activity when there is greater overlap and hence less competition between groups of neurons encoding two response alternatives. Early delayperiod theta-band synchronization may reflect covert response activation relevant to behavioral spatial averaging effects. [ABSTRACT FROM AUTHOR]

When a sensory stimulus repeats, neuronal firing rate and functional MRI blood oxygen level-dependent responses typically decline, yet perception and behavioral performance either stay constant or improve. An additional aspect of neuronal activity is neuronal synchronization, which can enhance the impact of neurons onto their postsynaptic targets independent of neuronal firing rates. We show that stimulus repetition leads to profound changes of neuronal gamma-band (∼40-90 Hz) synchronization. Electrocorticographic recordings in two awake macaque monkeys demonstrated that repeated presentations of a visual grating stimulus resulted in a steady increase of visually induced gamma-band activity in area V1, gamma-band synchronization between areas V1 and V4, and gamma-band activity in area V4. Microelectrode recordings in area V4 of two additional monkeys under the same stimulation conditions allowed a direct comparison of firing rates and gamma-band synchronization strengths for multiunit activity (MUA), as well as for isolated single units, sorted into putative pyramidal cells and putative interneurons. MUA and putative interneurons showed repetition-related decreases in firing rate, yet increases in gamma-band synchronization. Putative pyramidal cells showed no repetition-related firing rate change, but a decrease in gamma-band synchronization for weakly stimulus-driven units and constant gamma-band synchronization for strongly driven units. We propose that the repetition-related changes in gamma-band synchronization maintain the interareal stimulus signaling and sharpen the stimulus representation by gamma-synchronized pyramidal cell spikes. [ABSTRACT FROM AUTHOR]

The mouse model is an important research tool in neurosciences to examine brain function and diseases with genetic perturbation in different brain regions. However, the limited techniques to map activated brain regions under specific experimental manipulations has been a drawback of the mouse model compared to human functional brain mapping. Here, we present a functional brain mapping method for fast and robust in vivo brain mapping of the mouse brain. The method is based on the acquisition of high density electroencephalography (EEG) with a microarray and EEG source estimation to localize the electrophysiological origins. We adapted the Fieldtrip toolbox for the source estimation, taking advantage of its software openness and flexibility in modeling the EEG volume conduction. Three source estimation techniques were compared: Distribution source modeling with minimum-norm estimation (MNE), scanning with multiple signal classification (MUSIC), and single-dipole fitting. Known sources to evaluate the performance of the localization methods were provided using optogenetic tools. The accuracy was quantified based on the receiver operating characteristic (ROC) analysis. The mean detection accuracy was high, with a false positive rate less than 1.3% and 7% at the sensitivity of 90% plotted with the MNE and MUSIC algorithms, respectively. The mean center-to-center distance was less than 1.2 mm in single dipole fitting algorithm. Mouse microarray EEG source localization using microarray allows a reliable method for functional brain mapping in awake mouse opening an access to cross-species study with human brain. [ABSTRACT FROM AUTHOR]

Human referential communication is often thought as coding-decoding a set of symbols, neglecting that establishing shared meanings requires a computational mechanism powerful enough to mutually negotiate them. Sharing the meaning of a novel symbol might rely on similar conceptual inferences across communicators or on statistical similarities in their sensorimotor behaviors. Using magnetoencephalography, we assess spectral, temporal, and spatial characteristics of neural activity evoked when people generate and understand novel shared symbols during live communicative interactions. Solving those communicative problems induced comparable changes in the spectral profile of neural activity of both communicators and addressees. This shared neuronal up-regulation was spatially localized to the right temporal lobe and the ventromedial prefrontal cortex and emerged already before the occurrence of a specific communicative problem. Communicative innovation relies on neuronal computations that are shared across generating and understanding novel shared symbols, operating over temporal scales independent from transient sensorimotor behavior. [ABSTRACT FROM AUTHOR]

Several studies have demonstrated that prestimulus occipital alpha-band activity substantially influences subjective perception and discrimination of near-threshold or masked visual stimuli. Here, we studied the role of prestimulus power fluctuations in two visual phenomena called double-flash illusion (DFI) and fusion effect (FE), both consisting of suprathreshold stimuli. In both phenomena, human subjects' perception varies on a trial-by-trial basis between perceiving one or two visual stimuli, despite constant stimulation. In the FE, two stimuli correspond to veridical perception. In the DFI, two stimuli correspond to an illusory perception. This provides for a critical test of whether reduced alpha power indeed promotes veridical perception in general. We find that in both, DFI and FE, reduced prestimulus occipital alpha predicts the perception of two stimuli, regardless of whether this is veridical (FE) or illusory (DFI). Our results suggest that reduced alpha-band power does not always predict improved visual processing, but rather enhanced excitability. In addition, for the DFI, enhanced prestimulus occipital gamma-band power predicted the perception of two visual stimuli. These findings provide new insights into the role of prestimulus rhythmic activity for visual processing. [ABSTRACT FROM AUTHOR]

Functional neurosurgery has afforded the opportunity to assess interactions between populations of neurons in the human cerebral cortex and basal ganglia in patients with Parkinson's disease (PD). Interactions occur over a wide range of frequencies, and the functional significance of those >30 Hz is particularly unclear. Do they improve movement, and, if so, in what way? We acquired simultaneously magnetoencephalography and direct recordings from the subthalamic nucleus (STN) in 17 PD patients. We examined the effect of synchronous and sequential finger movements and of the dopamine prodrug levodopa on induced power in the contralateral primary motor cortex (Ml ) and STN and on the coherence between the two structures. We observed discrete peaks in Ml and STN power at 60 -90 Hz and at 300 - 400 Hz. All these power peaks increased with movement and levodopa treatment. Only STN activity at 60 -90 Hz was coherent with activity in Ml. Directionality analysis showed that STN gamma activity at 60 -90 Hz tended to drive gamma activity in Ml. The effects of levodopa on both local and distant synchronization at 60 -90 Hz correlated with the degree of improvement in bradykinesia-rigidity as did local STN activity at 300 - 400 Hz. Despite this, there were no effects of movement type, nor interactions between movement type and levodopa in the STN, nor in the coherence between STN and Ml. We conclude that synchronization at 60-90 Hz in the basal ganglia cortical network is prokinetic but likely through a modulatory effect rather than any involvement in explicit motor processing. [ABSTRACT FROM AUTHOR]

Gamma-band synchronization adjusts the timing of excitatory and inhibitory inputs to a neuron. Neurons in the visual cortex are selective for stimulus orientation because of dynamic interactions between excitatory and inhibitory inputs. We hypothesized that these interactions and hence also orientation selectivity vary during the gamma cycle. We determined for each spike its phase relative to the gamma cycle. As a function of gamma phase, we then determined spike rates and their orientation selectivity. Orientation selectivity was modulated by gamma phase. The firing rate of spiking activity that occurred close to a neuron's mean gamma phase of firing was most orientation selective. This stimulus-selective signal could best be conveyed to postsynaptic neurons if it were not corrupted by noise correlations. Noise correlations between firing rates were modulated by gamma phase such that they were not statistically detectable for the spiking activity occurring close to a neuron's mean gamma phase of firing. Thus, gamma-band synchronization produces spiking activity that carries maximal stimulus selectivity and minimal noise correlation in its firing rate, and at the same time synchronizes this spiking activity for maximal impact on postsynaptic targets. [ABSTRACT FROM AUTHOR]

Independent component analysis (ICA) and blind source separation (BSS) methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG) and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI) in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR) effected by each decomposition, and decomposition 'dipolarity' defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA); best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonlyused decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partiallysynchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison). [ABSTRACT FROM AUTHOR]

Local groups of neurons engaged in a cognitive task often exhibit rhythmically synchronized activity in the gamma band, a phenomenon that likely enhances their impact on downstream areas. The efficacy of neuronal interactions may be enhanced further by interareal synchronization of these local rhythms, establishing mutually well timed fluctuations in neuronal excitability. This notion suggests that long-range synchronization is enhanced selectively for connections that are behaviorally relevant. We tested this prediction in the human motor system, assessing activity from bilateral motor cortices with magnetoencephalography and corresponding spinal activity through electromyography of bilateral hand muscles. A bimanual isometric wrist extension task engaged the two motor cortices simultaneously into interactions and coherence with their respective corresponding contralateral hand muscles. One of the hands was cued before each trial as the response hand and had to be extended further to report an unpredictable visual go cue. We found that, during the isometric hold phase, corticomuscular coherence was enhanced, spatially selective for the corticospinal connection that was effectuating the subsequent motor response. This effect was spectrally selective in the low gamma-frequency band (40-47 Hz) and was observed in the absence of changes in motor output or changes in local cortical gamma-band synchronization. These findings indicate that, in the anatomical connections between the cortex and the spinal cord, gamma-band synchronization is a mechanism that may facilitate behaviorally relevant interactions between these distant neuronal groups. [ABSTRACT FROM AUTHOR]

Both phenotype and treatment response vary in patients with Parkinson's disease. Anatomical and functional imaging studies suggest that individual symptoms may represent malfunction of different segregated networks running in parallel through the basal ganglia. In this study, we use a newly described, electrophysiological method to describe cortico-subthalamic networks in humans. We performed combined magnetoencephalographic and subthalamic local field potential recordings in thirteen patients with Parkinson's disease at rest. Two spatially and spectrally separated networks were identified. A temporoparietal-brainstem network was coherent with the subthalamic nucleus in the alpha (7-13 Hz) band, whilst a predominantly frontal network was coherent in the beta (15-35 Hz) band. Dopaminergic medication modulated the resting beta network, by increasing beta coherence between the subthalamic region and prefrontal cortex. Subthalamic activity was predominantly led by activity in the cortex in both frequency bands. The cortical topography and frequencies involved in the alpha and beta networks suggest that these networks may be involved in attentional and executive, particularly motor planning, processes, respectively. [ABSTRACT FROM AUTHOR]

Both phenotype and treatment response vary in patients with Parkinson’s disease. Anatomical and functional imaging studies suggest that individual symptoms may represent malfunction of different segregated networks running in parallel through the basal ganglia. In this study, we use a newly described, electrophysiological method to describe cortico-subthalamic networks in humans. We performed combined magnetoencephalographic and subthalamic local field potential recordings in thirteen patients with Parkinson’s disease at rest. Two spatially and spectrally separated networks were identified. A temporoparietal-brainstem network was coherent with the subthalamic nucleus in the alpha (7–13 Hz) band, whilst a predominantly frontal network was coherent in the beta (15–35 Hz) band. Dopaminergic medication modulated the resting beta network, by increasing beta coherence between the subthalamic region and prefrontal cortex. Subthalamic activity was predominantly led by activity in the cortex in both frequency bands. The cortical topography and frequencies involved in the alpha and beta networks suggest that these networks may be involved in attentional and executive, particularly motor planning, processes, respectively. [ABSTRACT FROM AUTHOR]

SPMis a free and open source software written in MATLAB (The MathWorks, Inc.). In addition to standard M/EEG preprocessing, we presently offer three main analysis tools: (i) statistical analysis of scalp-maps, time-frequency images, and volumetric 3D source reconstruction images based on the general linear model, with correction for multiple comparisons using random field theory; (ii) Bayesian M/EEG source reconstruction, including support for group studies, simultaneous EEG and MEG, and fMRI priors; (iii) dynamic causal modelling (DCM), an approach combining neural modelling with data analysis for which there are several variants dealing with evoked responses, steady state responses (power spectra and cross-spectra), induced responses, and phase coupling. SPM8 is integrated with the FieldTrip toolbox , making it possible for users to combine a variety of standard analysis methods with new schemes implemented in SPM and build custom analysis tools using powerful graphical user interface (GUI) and batching tools. [ABSTRACT FROM AUTHOR]

This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages. [ABSTRACT FROM AUTHOR]

Multivariate pattern analysis is a technique that allows the decoding of conceptual information such as the semantic category of a perceived object from neuroimaging data. Impressive single-trial classification results have been reported in studies that used fMRI. Here, we investigate the possibility to identify conceptual representations from event-related EEG based on the presentation of an object in different modalities: its spoken name, its visual representation and its written name. We used Bayesian logistic regression with a multivariate Laplace prior for classification. Marked differences in classification performance were observed for the tested modalities. Highest accuracies (89% correctly classified trials) were attained when classifying object drawings. In auditory and orthographical modalities, results were lower though still significant for some subjects. The employed classification method allowed for a precise temporal localization of the features that contributed to the performance of the classifier for three modalities. These findings could help to further understand the mechanisms underlying conceptual representations. The study also provides a first step towards the use of concept decoding in the context of real-time brain-computer interface applications. [ABSTRACT FROM AUTHOR]

Locations of surface electromyography (sEMG) electrodes in the face are usually chosen on a macro-anatomical basis. In this study we describe optimal placement of bipolar electrodes based on a novel method and present results for lower facial muscles. We performed high-density sEMG recordings in 13 healthy participants. Raw sEMG signals were decomposed into motor unit action potentials (MUAPs). We positioned virtual electrode pairs in the interpolated monopolar MUAPs at different positions along muscle fiber direction and calculated the bipolar potentials. Electrode sites were determined where maximal bipolar amplitude was achieved and were validated. Objective guidelines for sEMG electrode placement improve the signal-to-noise ratio and may contribute to reduce cross talk, which is particularly important in the face. The method may be regarded as an important basis for improving the validity and reproducibility of sEMG in complex muscle areas. [ABSTRACT FROM AUTHOR]