Laminar pattern of sensory-evoked dynamic high-frequency oscillatory activity in the macaque auditory cortex.

High-frequency (>60 Hz) neuroelectric signals likely have functional roles distinct from low-frequency (<30 Hz) signals. While high-gamma activity (>60 Hz) does not simply equate to neuronal spiking, they are highly correlated, having similar information encoding. High-gamma activity is typically considered broadband and poorly phase-locked to sensory stimuli and thus is typically analyzed after transformations into absolute amplitude or spectral power. However, those analyses discard signal polarity, compromising the interpretation of neuroelectric events that are essentially dipolar. In the spectrotemporal profiles of field potentials in auditory cortex, we show high-frequency spectral peaks not phase-locked to sound onset, which follow the broadband peak of phase-locked onset responses. Isolating the signal components comprising the high-frequency peaks reveals narrow-band high-frequency oscillatory events, whose instantaneous frequency changes rapidly from >150 to 60 Hz, which may underlie broadband high-frequency spectral peaks in previous reports. The laminar amplitude distributions of the isolated activity had two peak positions, while the laminar phase patterns showed a counterphase relationship between those peaks, indicating the formation of dipoles. Our findings suggest that nonphase-locked HGA arises in part from oscillatory or recurring activity of supragranular-layer neuronal ensembles in auditory cortex.

The impact of CSF-filled cavities on scalp EEG and its implications.

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.

Characterization of Second-Order Mixing Effects in Reconstructed Cross-Spectra of Random Neural Fields.

Functional connectivity in electroencephalography (EEG) and magnetoencephalography (MEG) data is commonly assessed by using measures that are insensitive to instantaneously interacting sources and as such would not give rise to false positive interactions caused by instantaneous mixing of true source signals (first-order mixing). Recent studies, however, have drawn attention to the fact that such measures are still susceptible to instantaneous mixing from lagged sources (i.e. second-order mixing) and that this can lead to a large number of false positive interactions. In this study we relate first- and second-order mixing effects on the cross-spectra of reconstructed source activity to the properties of the resolution operators that are used for the reconstruction. We derive two identities that relate first- and second-order mixing effects to the transformation properties of measurement and source configurations and exploit them to establish several basic properties of signal mixing. First, we provide a characterization of the configurations that are maximally and minimally sensitive to second-order mixing. It turns out that second-order mixing effects are maximal when the measurement locations are far apart and the sources coincide with the measurement locations. Second, we provide a description of second-order mixing effects in the vicinity of the measurement locations in terms of the local geometry of the point-spread functions of the resolution operator. Third, we derive a version of Lagrange's identity for cross-talk functions that establishes the existence of a trade-off between the magnitude of first- and second-order mixing effects. It also shows that, whereas the magnitude of first-order mixing is determined by the inner product of cross-talk functions, the magnitude of second-order mixing is determined by a generalized cross-product of cross-talk functions (the wedge product) which leads to an intuitive geometric understanding of the trade-off. All results are derived within the general framework of random neural fields on cortical manifolds.

How to assess the accuracy of volume conduction models? A validation study with stereotactic EEG data.

Introduction: Volume conduction models 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 conduction models by analyzing the effects of the geometrical and electrical features of the head model, the sensor model, the source model, and the numerical method. 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 perform simulations, and we gradually altered the head models, 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.

First-in-human demonstration of floating EMG sensors and stimulators wirelessly powered and operated by volume conduction.

BACKGROUND: Recently we reported the design and evaluation of floating semi-implantable devices that receive power from and bidirectionally communicate with an external system using coupling by volume conduction. The approach, of which the semi-implantable devices are proof-of-concept prototypes, may overcome some limitations presented by existing neuroprostheses, especially those related to implant size and deployment, as the implants avoid bulky components and can be developed as threadlike devices. Here, it is reported the first-in-human acute demonstration of these devices for electromyography (EMG) sensing and electrical stimulation. METHODS: A proof-of-concept device, consisting of implantable thin-film electrodes and a nonimplantable miniature electronic circuit connected to them, was deployed in the upper or lower limb of six healthy participants. Two external electrodes were strapped around the limb and were connected to the external system which delivered high frequency current bursts. Within these bursts, 13 commands were modulated to communicate with the implant. RESULTS: Four devices were deployed in the biceps brachii and the gastrocnemius medialis muscles, and the external system was able to power and communicate with them. Limitations regarding insertion and communication speed are reported. Sensing and stimulation parameters were configured from the external system. In one participant, electrical stimulation and EMG acquisition assays were performed, demonstrating the feasibility of the approach to power and communicate with the floating device. CONCLUSIONS: This is the first-in-human demonstration of EMG sensors and electrical stimulators powered and operated by volume conduction. These proof-of-concept devices can be miniaturized using current microelectronic technologies, enabling fully implantable networked neuroprosthetics.

The contribution of the tendon electrode to M-wave characteristics in the biceps brachii, vastus lateralis and tibialis anterior.

In some compound muscle action potentials (M waves) recorded using the belly-tendon configuration, the tendon electrode makes a noticeable contribution to the M wave. However, this finding has only been demonstrated in some hand and foot muscles. Here, we assessed the contribution of the tendon potential to the amplitude of the vastus lateralis, biceps brachii and tibialis anterior M waves, and we also examined the role of this tendon potential in the shoulder-like feature appearing in most M waves. M waves were recorded separately at the belly and tendon locations of the vastus lateralis, biceps brachii and tibialis anterior from 38 participants by placing the reference electrode at a distant (contralateral) site. The amplitude of the M waves and the latency of their peaks and shoulders were measured. In the vastus lateralis, the tendon potential was markedly smaller in amplitude (∼75%) compared to the belly M wave (P = 0.001), whereas for the biceps brachii and tibialis anterior, the tendon and belly potentials had comparable amplitudes. In the vastus lateralis, the tendon potential showed a small positive peak coinciding in latency with the shoulder of the belly-tendon M wave, whilst in the biceps brachii and tibialis anterior, the tendon potential showed a clear negative peak which coincided in latency with the shoulder. The tendon potential makes a significant contribution to the belly-tendon M waves of the biceps brachii and tibialis anterior muscles, but little contribution to the vastus lateralis M waves. The shoulder observed in the belly-tendon M wave of the vastus lateralis is caused by the belly potential, the shoulder in the biceps brachii M wave is generated by the tendon potential, whereas the shoulder in the tibialis anterior M wave is caused by both the tendon and belly potentials. NEW FINDINGS: What is the central question of this study? Does a tendon electrode make a noticeable contribution to the belly-tendon M wave in the vastus lateralis, biceps brachii and tibialis anterior muscles? What is the main finding and its importance? Because the patellar tendon potential is small in amplitude, it hardly influences the amplitude and shape of the belly-tendon M wave of the vastus lateralis. However, for the biceps brachii and tibialis anterior muscles, the potentials at the tendon sites show a large amplitude, and thus have a great impact on the corresponding belly-tendon M waves.

Visual cortical LFP in relation to the hippocampal theta rhythm in track running rats.

Theta oscillations in the primary visual cortex (VC) have been observed during running tasks, but the mechanism behind their generation is not well understood. Some studies have suggested that theta in the VC is locally generated, while others have proposed that it is volume conducted from the hippocampus. The present study aimed to investigate the relationship between hippocampal and VC LFP dynamics. Analysis of power spectral density revealed that LFP in the VC was similar to that in the hippocampus, but with lower overall magnitude. As running velocity increased, both the power and frequency of theta and its harmonics increased in the VC, similarly to what is observed in the hippocampus. Current source density analysis triggered to theta did not identify distinct current sources and sinks in the VC, supporting the idea that theta in the VC is conducted from the adjacent hippocampus. Phase coupling between theta, its harmonics, and gamma is a notable feature in the hippocampus, particularly in the lacunosum moleculare. While some evidence of coupling between theta and its harmonics in the VC was found, bicoherence estimates did not reveal significant phase coupling between theta and gamma. Similar results were seen in the cross-region bicoherence analysis, where theta showed strong coupling with its harmonics with increasing velocity. Thus, theta oscillations observed in the VC during running tasks are likely due to volume conduction from the hippocampus.

Theoretical considerations and supporting evidence for the primary role of source geometry on field potential amplitude and spatial extent.

Field potential (FP) recording is an accessible means to capture the shifts in the activity of neuron populations. However, the spatial and composite nature of these signals has largely been ignored, at least until it became technically possible to separate activities from co-activated sources in different structures or those that overlap in a volume. The pathway-specificity of mesoscopic sources has provided an anatomical reference that facilitates transcending from theoretical analysis to the exploration of real brain structures. We review computational and experimental findings that indicate how prioritizing the spatial geometry and density of sources, as opposed to the distance to the recording site, better defines the amplitudes and spatial reach of FPs. The role of geometry is enhanced by considering that zones of the active populations that act as sources or sinks of current may arrange differently with respect to each other, and have different geometry and densities. Thus, observations that seem counterintuitive in the scheme of distance-based logic alone can now be explained. For example, geometric factors explain why some structures produce FPs and others do not, why different FP motifs generated in the same structure extend far while others remain local, why factors like the size of an active population or the strong synchronicity of its neurons may fail to affect FPs, or why the rate of FP decay varies in different directions. These considerations are exemplified in large structures like the cortex and hippocampus, in which the role of geometrical elements and regional activation in shaping well-known FP oscillations generally go unnoticed. Discovering the geometry of the sources in play will decrease the risk of population or pathway misassignments based solely on the FP amplitude or temporal pattern.

Volume conduction: Extracellular waveform generation in theory and practice.

The extracellular waveform manifestations of the intracellular action potential are the quintessential diagnostic foundation of electrodiagnostic medicine, and clinical neurophysiology in general. Volume conduction is the extracellular current flow and associated voltage distributions in an ionic conducting media, such as occurs in the human body. Both surface and intramuscular electrodes, in association with contemporary digital electromyographic systems, permit very sensitive detection and visualization of this extracellular spontaneous, voluntary, and evoked nerve/muscle electrical activity. Waveform configuration, with its associated discharge rate/rhythm, permits the identification of normal and abnormal waveforms, thereby assisting in the diagnosis of nerve and muscle pathology. This monograph utilizes a simple model to explain the various waveforms that may be encountered. There are a limited number of waveforms capable of being generated in excitable tissues which conform to well-known volume conductor concepts. Using these principles, such waveforms can be quickly identified in real time during clinical studies.

Comparing Motor-Evoked Potential Characteristics of NEedle versus suRFACE Recording Electrodes during Spinal Cord Monitoring-The NERFACE Study Part I.

Muscle-recorded transcranial electrical stimulation motor-evoked potentials (mTc-MEPs) are used to assess the spinal cord integrity. They are commonly recorded with subcutaneous needle or surface electrodes, but the different characteristics of mTc-MEP signals recorded with the two types of electrodes have not been formally compared yet. In this study, mTc-MEPs were simultaneously recorded from the tibialis anterior (TA) muscles using surface and subcutaneous needle electrodes in 242 consecutive patients. Elicitability, motor thresholds, amplitude, area under the curve (AUC), signal-to-noise ratio (SNR), and the variability between mTc-MEP amplitudes were compared. Whereas amplitude and AUC were significantly higher in subcutaneous needle recordings (p < 0.01), motor thresholds and elicitability were similar for surface and subcutaneous needle recordings. Moreover, the SNRs were >2 in more than 99.5% of the surface and subcutaneous needle recordings, and the variability between consecutive amplitudes was not significantly different between the two recording electrode types (p = 0.34). Surface electrodes appear to be a good alternative to needle electrodes for spinal cord monitoring. They are non-invasive, can record signals at similar threshold intensities, have adequately high SNRs, and record signals with equivalent variability. Whether surface electrodes are non-inferior to subcutaneous needle electrodes in detecting motor warnings is investigated in part II of the NERFACE study.

Site-dependent shaping of field potential waveforms.

The activity of neuron populations gives rise to field potentials (FPs) that extend beyond the sources. Their mixing in the volume dilutes the original temporal motifs in a site-dependent manner, a fact that has received little attention. And yet, it potentially rids of physiological significance the time-frequency parameters of individual waves (amplitude, phase, duration). This is most likely to happen when a single source or a local origin is erroneously assumed. Recent studies using spatial treatment of these signals and anatomically realistic modeling of neuron aggregates provide convincing evidence for the multisource origin and site-dependent blend of FPs. Thus, FPs generated in primary structures like the neocortex and hippocampus reach far and cross-contaminate each other but also, they add and even impose their temporal traits on distant regions. Furthermore, both structures house neurons that act as spatially distinct (but overlapped) FP sources whose activation is state, region, and time dependent, making the composition of so-called local FPs highly volatile and strongly site dependent. Since the spatial reach cannot be predicted without source geometry, it is important to assess whether waveforms and temporal motifs arise from a single source; otherwise, those from each of the co-active sources should be sought.

HArtMuT-modeling eye and muscle contributors in neuroelectric imaging.

Objective.Magneto- and electroencephalography (M/EEG) measurements record a mix of signals from the brain, eyes, and muscles. These signals can be disentangled for artifact cleaning e.g. using spatial filtering techniques. However, correctly localizing and identifying these components relies on head models that so far only take brain sources into account.Approach.We thus developed the Head Artifact Model using Tripoles (HArtMuT). This volume conduction head model extends to the neck and includes brain sources as well as sources representing eyes and muscles that can be modeled as single dipoles, symmetrical dipoles, and tripoles. We compared a HArtMuT four-layer boundary element model (BEM) with the EEGLAB standard head model on their localization accuracy and residual variance (RV) using a HArtMuT finite element model (FEM) as ground truth. We also evaluated the RV on real-world data of mobile participants, comparing different HArtMuT BEM types with the EEGLAB standard head model.Main results.We found that HArtMuT improves localization for all sources, especially non-brain, and localization error and RV of non-brain sources were in the same range as those of brain sources. The best results were achieved by using cortical dipoles, muscular tripoles, and ocular symmetric dipoles, but dipolar sources alone can already lead to convincing results.Significance.We conclude that HArtMuT is well suited for modeling eye and muscle contributions to the M/EEG signal. It can be used to localize sources and to identify brain, eye, and muscle components. HArtMuT is freely available and can be integrated into standard software.

Teaching Essential EMG Theory to Kinesiologists and Physical Therapists Using Analogies Visual Descriptions, and Qualitative Analysis of Biophysical Concepts.

Electromyography (EMG) is a multidisciplinary field that brings together allied health (kinesiology and physical therapy) and the engineering sciences (biomedical and electrical). Since the physical sciences are used in the measurement of a biological process, the presentation of the theoretical foundations of EMG is most conveniently conducted using math and physics. However, given the multidisciplinary nature of EMG, a course will most likely include students from diverse backgrounds, with varying levels of math and physics. This is a pedagogical paper that outlines an approach for teaching foundational concepts in EMG to kinesiologists and physical therapists that uses a combination of analogies, visual descriptions, and qualitative analysis of biophysical concepts to develop an intuitive understanding for those who are new to surface EMG. The approach focuses on muscle fiber action potentials (MFAPs), motor unit action potentials (MUAPs), and compound muscle action potentials (CMAPs) because changes in these waveforms are much easier to identify and describe in comparison to the surface EMG interference pattern (IP).

Addressing the inconsistent electric fields of tDCS by using patient-tailored configurations in chronic stroke: Implications for treatment.

Transcranial direct current stimulation (tDCS) is a promising tool to improve and speed up motor rehabilitation after stroke, but inconsistent clinical effects refrain tDCS from clinical implementation. Therefore, this study aimed to assess the need for individualized tDCS configurations in stroke, considering interindividual variability in brain anatomy and motor function representation. We simulated tDCS in individualized MRI-based finite element head models of 21 chronic stroke subjects and 10 healthy age-matched controls. An anatomy-based stimulation target, i.e. the motor hand knob, was identified with MRI, whereas a motor function-based stimulation target was identified with EEG. For each subject, we simulated conventional anodal tDCS electrode configurations and optimized electrode configurations to maximize stimulation strength within the anatomical and functional target. The normal component of the electric field was extracted and compared between subjects with stroke and healthy, age-matched controls, for both targets, during conventional and optimized tDCS. Electrical field strength was significantly lower, more variable and more frequently in opposite polarity for subjects with stroke compared to healthy age-matched subjects, both for the anatomical and functional target with conventional, i.e. non-individualized, electrode configurations. Optimized, i.e. individualized, electrode configurations increased the electrical field strength in the anatomical and functional target for subjects with stroke but did not reach the same levels as in healthy subjects. Considering individual brain structure and motor function is crucial for applying tDCS in subjects with stroke. Lack of individualized tDCS configurations in subjects with stroke results in lower electric fields in stimulation targets, which may partially explain the inconsistent clinical effects of tDCS in stroke trials.

Wireless networks of injectable microelectronic stimulators based on rectification of volume conducted high frequency currents.

Objective.To develop andin vivodemonstrate threadlike wireless implantable neuromuscular microstimulators that are digitally addressable.Approach.These devices perform, through its two electrodes, electronic rectification of innocuous high frequency current bursts delivered by volume conduction via epidermal textile electrodes. By avoiding the need of large components to obtain electrical energy, this approach allows the development of thin devices that can be intramuscularly implanted by minimally invasive procedures such as injection. For compliance with electrical safety standards, this approach requires a minimum distance, in the order of millimeters or a very few centimeters, between the implant electrodes. Additionally, the devices must cause minimal mechanical damage to tissues, avoid dislocation and be adequate for long-term implantation. Considering these requirements, the implants were conceived as tubular and flexible devices with two electrodes at opposite ends and, at the middle section, a hermetic metallic capsule housing the electronics.Main results.The developed implants have a submillimetric diameter (0.97 mm diameter, 35 mm length) and consist of a microcircuit, which contains a single custom-developed integrated circuit, housed within a titanium capsule (0.7 mm diameter, 6.5 mm length), and two platinum-iridium coils that form two electrodes (3 mm length) located at opposite ends of a silicone body. These neuromuscular stimulators are addressable, allowing to establish a network of microstimulators that can be controlled independently. Their operation was demonstrated in an acute study by injecting a few of them in the hind limb of anesthetized rabbits and inducing controlled and independent contractions.Significance.These results show the feasibility of manufacturing threadlike wireless addressable neuromuscular stimulators by using fabrication techniques and materials well established for chronic electronic implants. Although long-term operation still must be demonstrated, the obtained results pave the way to the clinical development of advanced motor neuroprostheses formed by dense networks of such wireless devices.

Estimating the influence of stroke lesions on MEG source reconstruction.

Source reconstruction of magnetoencephalography (MEG) has been used to assess brain reorganization after brain damage, such as stroke. Lesions result in parts of the brain having an electrical conductivity that differs from the normal values. The effect this has on the forward solutions (i.e., the propagation of electric currents and magnetic fields generated by cortical activity) is well predictable. However, their influence on source localization results is not well characterized and understood. This is specifically a concern for patient studies with asymmetric (i.e., within one hemisphere) lesions focusing on asymmetric and lateralized brain activity, such as language. In particular, it is good practice to consider the level of geometrical detail that is necessary to compute and interpret reliable source reconstruction results. To understand the effect of lesions on source estimates and propose recommendations to researchers working with clinical data, in this study we consider the trade off between improved accuracy and the additional effort to compute more realistic head models, with the aim to answer the question whether the additional effort is worth it. We simulated and analyzed the effects of a stroke lesion (i.e., an asymmetrically distributed CSF-filled cavity) in the head model with three different sizes and locations when performing MEG source reconstruction using a finite element method (FEM). We compared the effect of the lesion with a homogeneous head model that neglects the lesion. We computed displacement and attenuation/amplification maps to quantify the localization errors and signal magnitude modulation. We conclude that brain lesions leading to asymmetrically distributed CSF-filled cavities should be modeled when performing MEG source reconstruction, especially when investigating deep sources or post-stroke hemispheric lateralization of functions. The strongest effects are not only visible in perilesional areas, but can extend up to 20 mm from the lesion. Bigger lesions lead to stronger effects impacting larger areas, independently from the lesion location. Lastly, we conclude that more priority should be given to usability and accessibility of the required computational tools, to allow researchers with less technical expertise to use the improved methods that are available but currently not widely adopted yet.

The influence of the reference electrode location on the M-wave characteristics in the quadriceps.

INTRODUCTION: In the compound muscle action potential (M wave) recorded using the belly-tendon configuration, the contribution of the tendon electrode is assumed to be negligible compared to the belly electrode. We tested this assumption by placing the reference electrode at a distant (contralateral) site, which allowed separate recording of the belly and tendon contributions. METHODS: M waves were recorded at multiple selected sites over the right quadriceps heads and lower leg using two different locations for the reference electrode: the ipsilateral (right) and contralateral (left) patellar tendon. The general parameters of the M wave (amplitude, area, duration, latency, and frequency) were measured. RESULTS: (1) The tendon potential had a small amplitude (<30%) compared to the belly potential; (2) Changing the reference electrode from the ipsilateral to the contralateral patella produced moderate changes in the M wave recorded over the innervation zone, these changes affecting significantly the amplitude of the M-wave second phase (p = 0.006); (3) Using the contralateral reference system allowed recording of short-latency components occurring immediately after the stimulus artefact, which had the same latency and amplitude (p = 0.18 and 0.25, respectively) at all recording sites over the leg. CONCLUSIONS: The potential recorded at the "tendon" site after femoral nerve stimulation is small (compared to the belly potential), but not negligible, and makes a significant contribution to the second phase of belly-tendon M wave. Adopting a distant (contralateral) reference allowed recording of far-field components that may aid in the understanding of the electrical formation of the M wave.

Floating EMG sensors and stimulators wirelessly powered and operated by volume conduction for networked neuroprosthetics.

BACKGROUND: Implantable neuroprostheses consisting of a central electronic unit wired to electrodes benefit thousands of patients worldwide. However, they present limitations that restrict their use. Those limitations, which are more adverse in motor neuroprostheses, mostly arise from their bulkiness and the need to perform complex surgical implantation procedures. Alternatively, it has been proposed the development of distributed networks of intramuscular wireless microsensors and microstimulators that communicate with external systems for analyzing neuromuscular activity and performing stimulation or controlling external devices. This paradigm requires the development of miniaturized implants that can be wirelessly powered and operated by an external system. To accomplish this, we propose a wireless power transfer (WPT) and communications approach based on volume conduction of innocuous high frequency (HF) current bursts. The currents are applied through external textile electrodes and are collected by the wireless devices through two electrodes for powering and bidirectional digital communications. As these devices do not require bulky components for obtaining power, they may have a flexible threadlike conformation, facilitating deep implantation by injection. METHODS: We report the design and evaluation of advanced prototypes based on the above approach. The system consists of an external unit, floating semi-implantable devices for sensing and stimulation, and a bidirectional communications protocol. The devices are intended for their future use in acute human trials to demonstrate the distributed paradigm. The technology is assayed in vitro using an agar phantom, and in vivo in hindlimbs of anesthetized rabbits. RESULTS: The semi-implantable devices were able to power and bidirectionally communicate with the external unit. Using 13 commands modulated in innocuous 3 MHz HF current bursts, the external unit configured the sensing and stimulation parameters, and controlled their execution. Raw EMG was successfully acquired by the wireless devices at 1 ksps. CONCLUSIONS: The demonstrated approach overcomes key limitations of existing neuroprostheses, paving the way to the development of distributed flexible threadlike sensors and stimulators. To the best of our knowledge, these devices are the first based on WPT by volume conduction that can work as EMG sensors and as electrical stimulators in a network of wireless devices.

Estimating brain effective connectivity from EEG signals of patients with autism disorder and healthy individuals by reducing volume conduction effect.

Studying brain connectivity has shed light on understanding brain functions. Electroencephalogram signals recorded from the scalp surface comprise inter-dependent multi-channel signals each of which is a linear combination of simultaneously active brain sources as well as adjacent non-brain sources whose activity is widely volume conducted to the scalp through overlapping patterns. Evaluation of brain connectivity based on multivariate autoregressive (MVAR) model identification from neurological time series can be a proper tool for brain signal analysis. However, the MVAR model only considers the lagged influences between time series while ignoring the instantaneous effects (zero-lagged interactions) among simultaneously recorded neurological signals. Hence predicting instant interactions may result in fake connectivity, which may lead to misinterpreting in results. In this study, we aim to find instantaneous effects from coefficients of the MVAR model acquired using an ADALINE neural network and investigate the efficiency of the proposed algorithm by applying it to a simulated signal. We show that our coefficients are estimated accurately from channels of the simulated signal. Moreover, we apply the proposed method on a dataset of a group of 18 healthy children and 10 children with autism by comparing their effective connectivity estimated by direct directed transfer function method using new and old coefficients. Finally, to show the efficiency of the algorithm we exploit the support vector machine method for classifying the dataset. We show that there is a significant improvement in the results obtained from the proposed method.

Is sensor space analysis good enough? Spatial patterns as a tool for assessing spatial mixing of EEG/MEG rhythms.

Analyzing non-invasive recordings of electroencephalography (EEG) and magnetoencephalography (MEG) directly in sensor space, using the signal from individual sensors, is a convenient and standard way of working with this type of data. However, volume conduction introduces considerable challenges for sensor space analysis. While the general idea of signal mixing due to volume conduction in EEG/MEG is recognized, the implications have not yet been clearly exemplified. Here, we illustrate how different types of activity overlap on the level of individual sensors. We show spatial mixing in the context of alpha rhythms, which are known to have generators in different areas of the brain. Using simulations with a realistic 3D head model and lead field and data analysis of a large resting-state EEG dataset, we show that electrode signals can be differentially affected by spatial mixing by computing a sensor complexity measure. While prominent occipital alpha rhythms result in less heterogeneous spatial mixing on posterior electrodes, central electrodes show a diversity of rhythms present. This makes the individual contributions, such as the sensorimotor mu-rhythm and temporal alpha rhythms, hard to disentangle from the dominant occipital alpha. Additionally, we show how strong occipital rhythms can contribute the majority of activity to frontal channels, potentially compromising analyses that are solely conducted in sensor space. We also outline specific consequences of signal mixing for frequently used assessment of power, power ratios and connectivity profiles in basic research and for neurofeedback application. With this work, we hope to illustrate the effects of volume conduction in a concrete way, such that the provided practical illustrations may be of use to EEG researchers to in order to evaluate whether sensor space is an appropriate choice for their topic of investigation.