Invasive Neural Recordings Research Articles

Using fMRI to examine nonlinear mixed selectivity tuning to task and category in the human brain

Abstract Recent experimental and theoretical work has shown that nonlinear mixed selectivity, where neurons exhibit interaction effects in their tuning to multiple variables (e.g., stimulus and task) plays a key role in enabling the primate brain to form representations that can adapt to changing task contexts. Thus far all such studies have relied on invasive neural recording techniques. In this study, we demonstrate the feasibility of measuring nonlinear mixed selectivity tuning in the human brain noninvasively using fMRI pattern decoding. To do so, we examined the joint representation of object category and task information across human early, ventral stream, and dorsal stream areas while participants performed either an oddball detection task or a one-back repetition detection task on the same stimuli. These tasks were chosen to equate spatial, object-based, and feature-based attention, in order to test whether task modulations of visual representations still occur when the inputs to visual processing are kept constant between the two tasks, with only the subsequent cognitive operations varying. We found moderate but significant evidence for nonlinear mixed selectivity tuning to object category and task in fMRI response patterns in both human ventral and dorsal areas, suggesting that neurons exhibiting nonlinear mixed selectivity for category and task not only exist in these regions, but cluster at a scale visible to fMRI. Importantly, while such coding in ventral areas corresponds to a rotation or shift in the object representational geometry without changing the representational content (i.e., with the relative similarity among the categories preserved), nonlinear mixed selectivity coding in dorsal areas corresponds to a reshaping of representational geometry, indicative of a change in representational content.

A 'Total Unique Variation Analysis' for Brain-Machine Interfaces.

When designing a fully implantable brain-machine interface (BMI), the primary aim is to detect as much neural information as possible with as few channels as possible. In this paper, we present a total unique variance analysis (TUVA) for evaluating the signal unique to each channel that cannot be predicted by linear combination of signals on other channels. TUVA is a statistical method for determining the total unique variance in multidimensional data, ordering channels from most to least informative, to aid in the design of maximally-efficacious BMIs. We demonstrate how this method can be applied to the design of BMIs by comparing TUVA values computed for simulated lead-field maps for high-channel-count electrocorticography (ECoG) with values computed for recordings in the interictal period in the context of surgery planning for epileptic resection.Clinical Relevance- This paper introduces a new statistical method for comparison of neural interface designs, focused on quantifying recording efficiency by minimizing channel crosstalk, which may help improve the risk-benefit profile of invasive neural recording.

A tassel-type multilayer flexible probe for invasive neural recording

Invasive neural probes are one of the most critical components in the intracortical neural signal recording system. However, they can cause brain damage and tissue response during and after implantation. Thus, neural probes with high flexibility, biocompatibility, and simple implantation methods are required in brain research. Here we present a novel approach to fabricating a multilayer flexible tassel-type neural probe using low-cost maskless laser direct-write lithography, combined with straightforward release and assembly methods to prepare a whole implantation system. The probe has 32 recording electrodes with an area of 8 × 8 µm2, arranged into two rows of different depths and 16 separated shanks, aiming at the neural signal recording in an extensive range. Polyimide and gold are used as the insulating and conductive layers, respectively. With the help of a polyethylene glycol (PEG) coating, the tassel structure was mechanically enhanced for successful implantation, and our morphology characterization showed that the diameter of the coated probe was less than 50 µm. Mechanical property tests also proved that it had the necessary stiffness for brain implantation. Afterwards, electrochemical tests were carried out, which showed that the probe had a rather low impedance after a simple gold electroplating. Finally, in vivo experiments demonstrated our probe can be successfully used in neural recording.

An Ultra-Low-Noise, Low Power and Miniaturized Dual-Channel Wireless Neural Recording Microsystem.

As the basic tools for neuroscience research, invasive neural recording devices can obtain high-resolution neuronal activity signals through electrodes connected to the subject’s brain. Existing wireless neural recording devices are large in size or need external large-scale equipment for wireless power supply, which limits their application. Here, we developed an ultra-low-noise, low power and miniaturized dual-channel wireless neural recording microsystem. With the full-differential front-end structure of the dual operational amplifiers (op-amps), the noise level and power consumption are notably reduced. The hierarchical microassembly technology, which integrates wafer-level packaged op-amps and the miniaturized Bluetooth module, dramatically reduces the size of the wireless neural recording microsystem. The microsystem shows a less than 100 nV/ ultra-low noise level, about 10 mW low power consumption, and 9 × 7 × 5 mm small size. The neural recording ability was then demonstrated in saline and a chronic rat model. Because of its miniaturization, it can be applied to freely behaving small animals, such as rats. Its features of ultra-low noise and high bandwidth are conducive to low-amplitude neural signal recording, which may help advance neuroscientific discovery.

An Immersive Virtual Reality Platform Integrating Human ECOG & sEEG: Implementation & Noise Analysis.

Virtual reality (VR) offers a robust platform for human behavioral neuroscience, granting unprecedented experimental control over every aspect of an immersive and interactive visual environment. VR experiments have already integrated non-invasive neural recording modalities such as EEG and functional MRI to explore the neural correlates of human behavior and cognition. Integration with implanted electrodes would enable significant increase in spatial and temporal resolution of recorded neural signals and the option of direct brain stimulation for neurofeedback. In this paper, we discuss the first such implementation of a VR platform with implanted electrocorticography (ECoG) and stereo-electroencephalography ( sEEG) electrodes in human, in-patient subjects. Noise analyses were performed to evaluate the effect of the VR headset on neural data collected in two VR-naive subjects, one child and one adult, including both ECOG and sEEG electrodes. Results demonstrate an increase in line noise power (57-63Hz) while wearing the VR headset that is mitigated effectively by common average referencing (CAR), and no significant change in the noise floor bandpower (125-240Hz). To our knowledge, this study represents first demonstrations of VR immersion during invasive neural recording with in-patient human subjects. Clinical Relevance- Immersive virtual reality tasks were well-tolerated and the quality of clinical neural signals preserved during VR immersion with two in-patient invasive neural recording subjects.

High-density neural recording system design.

Implantable medical devices capable of monitoring hundreds to thousands of electrodes have received great attention in biomedical applications for understanding of the brain function and to treat brain diseases such as epilepsy, dystonia, and Parkinson's disease. Non-invasive neural recording modalities such as fMRI and EEGs were widely used since the 1960s, but to acquire better information, invasive modalities gained popularity. Since such invasive neural recording system requires high efficiency and low power operation, they have been implemented as integrated circuits. Many techniques have been developed and applied when designing integrated high-density neural recording architecture for better performance, higher efficiency, and lower power consumption. This paper covers general knowledge of neural signals and frequently used neural recording architectures for monitoring neural activity. For neural recording architecture, various neural recording amplifier structures are covered. In addition, several neural processing techniques, which can optimize the neural recording system, are also discussed.

Transient Neurovascular Interface for Minimally Invasive Neural Recording and Stimulation

Adv. Mater. Technol. 2022, 2, 2100176 DOI: 10.1002/admt.202100176 Figure 2i in the original manuscript contained an error in the right y-axis. The error was due to an incorrect conversion while calculating the charge injection capacity. The unit originally reported was mC cm−2 instead of µC cm−2. The findings and conclusions presented in the original article are not affected. An updated version of Figure 2 is given below. Accordingly, a correction was made in the text as follows: “The average (± s.d.) maximum injectable current (always limited by the Emc) was found to be 5.2 ± 4.8 mA (n = 15 electrodes from N = 4 devices) and the respective CIC was 263.6 ± 247.5 µC cm−2 (Figure 2i). Currents used in metallic stent-electrode arrays fall within the range sustainable by the polymeric electrode presented in this article.[6]” Also, the following sentences that were added to justify an unusual CIC higher than the CSC should be removed: “It must be noted though that the CSC is usually an overestimation of the charge transfer potential of the electrodes: in fact when stimulating in vivo, at high frequencies and short pulses, only the superficial layers of the bulk PEDOT:PSS film will be active.[8] Thus, the CIC is expected to be lower than the CSC (typically CIC is 5–20% of the CSC for metals and oxides).[29] In our measurements, PEDOT:PSS electrodes reported a CIC higher than the total CSC with high variability among electrodes. A similar trend has been reported already in literature for PEDOT-coated PtIr electrodes.[38] A factor contributing to the high CIC is the positive open circuit potential reached by the electrodes after a prolonged stimulation at low current pulses to reach stabilization at the electrode-electrolyte interface. This open circuit potential was positive for all electrodes (≈0.25 V for most electrodes with a few exceptions at 0.15 V), leading most electrodes to a positive Emc value for injected currents below 1500 µA.” The authors apologize for this mistake.

Prefrontal Physiomarkers of Anxiety and Depression in Parkinson's Disease.

Objective: Anxiety and depression are prominent non-motor symptoms of Parkinson’s disease (PD), but their pathophysiology remains unclear. We sought to understand their neurophysiological correlates from chronic invasive recordings of the prefrontal cortex (PFC).Methods: We studied four patients undergoing deep brain stimulation (DBS) for their motor signs, who had comorbid mild to moderate anxiety and/or depressive symptoms. In addition to their basal ganglia leads, we placed a permanent prefrontal subdural 4-contact lead. These electrodes were attached to an investigational pulse generator with the capability to sense and store field potential signals, as well as deliver therapeutic neurostimulation. At regular intervals over 3–5 months, participants paired brief invasive neural recordings with self-ratings of symptoms related to depression and anxiety.Results: Mean age was 61 ± 7 years, mean disease duration was 11 ± 8 years and a mean Unified Parkinson’s Disease Rating Scale, with part III (UPDRS-III) off medication score of 37 ± 13. Mean Beck Depression Inventory (BDI) score was 14 ± 5 and Beck Anxiety Index was 16.5 ± 5. Prefrontal cortex spectral power in the beta band correlated with patient self-ratings of symptoms of depression and anxiety, with r-values between 0.31 and 0.48. Mood scores showed negative correlation with beta spectral power in lateral locations, and positive correlation with beta spectral power in a mesial recording location, consistent with the dichotomous organization of reward networks in PFC.Interpretation: These findings suggest a physiological basis for anxiety and depression in PD, which may be useful in the development of neurostimulation paradigms for these non-motor disease features.

Detection of human white matter activation and evaluation of its function in movement decoding using stereo-electroencephalography (SEEG)

Objective. White matter tissue takes up approximately 50% of the human brain volume and it is widely known as a messenger conducting information between areas of the central nervous system. However, the characteristics of white matter neural activity and whether white matter neural recordings can contribute to movement decoding are often ignored and still remain largely unknown. In this work, we make quantitative analyses to investigate these two important questions using invasive neural recordings. Approach. We recorded stereo-electroencephalography (SEEG) data from 32 human subjects during a visually-cued motor task, where SEEG recordings can tap into gray and white matter electrical activity simultaneously. Using the proximal tissue density method, we identified the location (i.e. gray or white matter) of each SEEG contact. Focusing on alpha oscillatory and high gamma activities, we compared the activation patterns between gray matter and white matter. Then, we evaluated the performance of such white matter activation in movement decoding. Main results. The results show that white matter also presents activation under the task, in a similar way with the gray matter but at a significantly lower amplitude. Additionally, this work also demonstrates that combing white matter neural activities together with that of gray matter significantly promotes the movement decoding accuracy than using gray matter signals only. Significance. Taking advantage of SEEG recordings from a large number of subjects, we reveal the response characteristics of white matter neural signals under the task and demonstrate its enhancing function in movement decoding. This study highlights the importance of taking white matter activities into consideration in further scientific research and translational applications.

Transient Neurovascular Interface for Minimally Invasive Neural Recording and Stimulation

AbstractNeural interfaces are used to mitigate the burden of traumatic injuries, neurodegenerative diseases, and mental disorders. However, the transient or permanent placement of an interface in close contact with the neural tissue requires invasive surgery, potentially entailing both short‐ and long‐term complications. To tackle this problem, a transient neurovascular interface for neural recording and stimulation is developed. This endovascular array has been fabricated with facile molding techniques using solely polymeric materials. In vitro experiments have shown promising electrochemical performance for both recording and stimulation, together with a lack of cytotoxicity in cultured cells. The device is compatible with standard endovascular catheters and, once deployed, provide good apposition to a cylindrical structure mimicking a blood vessel. The advantage of this device is twofold. On the one hand, the exploitation of the cerebrovascular system as an access route to the neural tissue avoids invasive surgeries. On the other hand, a transient device may reduce the inflammatory reaction and avoid additional surgeries for removal or replacement. This neurovascular interface combines the benefits of both transient bioelectronics and stent technology in a single device to broaden the range of applications of neural interfaces from neurological diseases and mental disorders to bioelectronics medicine.

A Sub-$\mu$ W Reconfigurable Front-End for Invasive Neural Recording That Exploits the Spectral Characteristics of the Wideband Neural Signal

This paper presents a sub-μW ac-coupled reconfigurable front-end for invasive wideband neural signal recording. The proposed topology embeds filtering capabilities enabling the selection of different frequency bands inside the neural signal spectrum. Power consumption is optimized by defining specific noise targets for each sub-band. These targets take into account the spectral characteristics of wideband neural signals: local field potentials (LFP) exhibit 1/f x magnitude scaling while action potentials (AP) show uniform magnitude across frequency. Additionally, noise targets also consider electrode noise and the spectral distribution of noise sources in the circuit. An experimentally verified prototype designed in a standard 180 nm CMOS process draws 815 nW from a 1 V supply. The front-end is able to select among four different frequency bands (modes) up to 5 kHz. The measured input-referred spot-noise at 500 Hz in the LFP mode (1 Hz - 700 Hz) is 55 nV/√Hz while the integrated noise in the AP mode (200 Hz - 5 kHz) is 4.1 μV rms . The proposed front-end achieves sub-μW operation without penalizing other specifications such as input swing, common-mode or power-supply rejection ratios. It reduces the power consumption of neural front-ends with spectral selectivity by 6.1x and, compared with conventional wideband front-ends, it obtains a reduction of 2.5 x.

Neural Circuit and Clinical Insights from Intraoperative Recordings During Deep Brain Stimulation Surgery.

Observations using invasive neural recordings from patient populations undergoing neurosurgical interventions have led to critical breakthroughs in our understanding of human neural circuit function and malfunction. The opportunity to interact with patients during neurophysiological mapping allowed for early insights in functional localization to improve surgical outcomes, but has since expanded into exploring fundamental aspects of human cognition including reward processing, language, the storage and retrieval of memory, decision-making, as well as sensory and motor processing. The increasing use of chronic neuromodulation, via deep brain stimulation, for a spectrum of neurological and psychiatric conditions has in tandem led to increased opportunity for linking theories of cognitive processing and neural circuit function. Our purpose here is to motivate the neuroscience and neurosurgical community to capitalize on the opportunities that this next decade will bring. To this end, we will highlight recent studies that have successfully leveraged invasive recordings during deep brain stimulation surgery to advance our understanding of human cognition with an emphasis on reward processing, improving clinical outcomes, and informing advances in neuromodulatory interventions.

Multimodal approaches to functional connectivity in autism spectrum disorders: An integrative perspective.

Atypical functional connectivity has been implicated in autism spectrum disorders (ASDs). However, the literature to date has been largely inconsistent, with mixed and conflicting reports of hypo- and hyper-connectivity. These discrepancies are partly due to differences between various neuroimaging modalities. Functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and magnetoencephalography (MEG) measure distinct indices of functional connectivity (e.g., blood-oxygenation level-dependent [BOLD] signal vs. electrical activity). Furthermore, each method has unique benefits and disadvantages with respect to spatial and temporal resolution, vulnerability to specific artifacts, and practical implementation. Thus far, functional connectivity research on ASDs has remained almost exclusively unimodal; therefore, interpreting findings across modalities remains a challenge. Multimodal integration of fMRI, EEG, and MEG data is critical in resolving discrepancies in the literature, and working toward a unifying framework for interpreting past and future findings. This review aims to provide a theoretical foundation for future multimodal research on ASDs. First, we will discuss the merits and shortcomings of several popular theories in ASD functional connectivity research, using examples from the literature to date. Next, the neurophysiological relationships between imaging modalities, including their relationship with invasive neural recordings, will be reviewed. Finally, methodological approaches to multimodal data integration will be presented, and their future application to ASDs will be discussed. Analyses relating transient patterns of neural activity ("states") are particularly promising. This strategy provides a comparable measure across modalities, captures complex spatiotemporal patterns, and is a natural extension of recent dynamic fMRI research in ASDs. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 456-473, 2018.

Neurofeedback Control in Parkinsonian Patients Using Electrocorticography Signals Accessed Wirelessly With a Chronic, Fully Implanted Device.

Parkinson's disease (PD) is characterized by motor symptoms such as rigidity and bradykinesia that prevent normal movement. Beta band oscillations (13-30 Hz) in neural local field potentials (LFPs) have been associated with these motor symptoms. Here, three PD patients implanted with a therapeutic deep brain neural stimulator that can also record and wirelessly stream neural data played a neurofeedback game where they modulated their beta band power from sensorimotor cortical areas. Patients' beta band power was streamed in real-time to update the position of a cursor that they tried to drive into a cued target. After playing the game for 1-2 hours each, all three patients exhibited above chance-level performance regardless of subcortical stimulation levels. This study, for the first time, demonstrates using an invasive neural recording system for at-home neurofeedback training. Future work will investigate chronic neurofeedback training as a potentially therapeutic tool for patients with neurological disorders.

Handcrafted Electrocorticography Electrodes for a Rodent Behavioral Model

Electrocorticography (ECoG) is a minimally invasive neural recording method that has been extensively used for neuroscience applications. It has proven to have the potential to ease the establishment of proper links for neural interfaces that can offer disabled patients an alternative solution for their lost sensory and motor functions through the use of brain-computer interface (BCI) technology. Although many neural recording methods exist, ECoG provides a combination of stability, high spatial and temporal resolution with chronic and mobile capabilities that could make BCI systems accessible for daily applications. However, many ECoG electrodes require MEMS fabricating techniques which are accompanied by various expenses that are obstacles for research projects. For this reason, this paper presents an animal study using a low cost and simple handcrafted ECoG electrode that is made of commercially accessible materials. The study is performed on a Lewis rat implanted with a handcrafted 32-channel non-penetrative ECoG electrode covering an area of 3 × 3 mm2 on the cortical surface. The ECoG electrodes were placed on the motor and somatosensory cortex to record the signal patterns while the animal was active on a treadmill. Using a Tucker-Davis Technologies acquisition system and the software Synapse to monitor and analyze the electrophysiological signals, the electrodes obtained signals within the amplitude range of 200 µV for local field potentials with reliable spatiotemporal profiles. It was also confirmed that the handcrafted ECoG electrode has the stability and chronic features found in other commercial electrodes.

A Window into brain development: hdEEG methods to track visual development in nonhuman primates.

Electroencephalography (EEG) is widely used to study human brain activity, and is a useful tool for bridging the gap between invasive neural recording assays and behavioral data. High-density EEG (hdEEG) methods currently used for human subjects for use with infant macaque monkeys, a species that exhibits similar visual development to humans over a shorter time course was adapted. Unlike monkeys, human subjects were difficult to study longitudinally and were not appropriate for direct within-species comparison to neuronal data. About 27-channel electrode caps, which allowed collection of hdEEG data from infant monkeys across development were designed. Acuity and contrast sweep VEP responses to grating stimuli was obtained and a new method for objective threshold estimation based on response signal-to-noise ratios at different stimulus levels was established. The developmental trajectories of VEP-measured contrast sensitivity and acuity to previously collected behavioral and neuronal data were compared. The VEP measures showed similar rates of development to behavioral measures, both of which were slower than direct neuronal measures; VEP thresholds were higher than other measures. This is the first usage of non-invasive technology in non-human primates. Other means to assess neural sensitivity in infants were all invasive. Use of hdEEG with infant monkeys opens many possibilities for tracking development of vision and other functions in non-human primates, and can expand our understanding of the relationship between neuronal activity and behavioral capabilities across various sensory and cognitive domains. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 76: 1342-1359, 2016.

FDA Regulation of Invasive Neural Recording Electrodes: A Daunting Task for Medical Innovators

The U.S. Food and Drug Administration (FDA) is charged with assuring the safety and effectiveness of medical devices. Before any medical device can be brought to market, it must comply with all federal regulations regarding FDA processes for clearance or approval. Navigating the FDA regulatory process may seem like a daunting task to the innovator of a novel medical device who has little experience with the FDA regulatory process or device commercialization. This review introduces the basics of the FDA regulatory premarket process, with a focus on issues relating to chronically implanted recording devices in the central or peripheral nervous system. Topics of device classification and regulatory pathways, the use of standards and guidance documents, and optimal time lines for interaction with the FDA are discussed. Additionally, this article summarizes the regulatory research on neural implant safety and reliability conducted by the FDA's Office of Science and Engineering Laboratories (OSEL) in collaboration with Defense Advanced Research Projects Agency (DARPA) Reliable Neural Technology (RE-NET) Program. For a more detailed explanation of the medical device regulatory process, please refer to several excellent reviews of the FDA's regulatory pathways for medical devices [1]-[4].

Binaural Electric-Acoustic Interactions Recorded from the Inferior Colliculus of Guinea Pigs: The Effect of Masking Observed in the Central Nucleus of the Inferior Colliculus

ObjectivesTo investigate the electric-acoustic interactions within the inferior colliculus of guinea pigs and to observe how central masking appears in invasive neural recordings of the inferior colliculus (IC).MethodsA platinum-iridium wire was inserted to scala tympani through cochleostomy with a depth no greater than 1 mm for intracochlear stimulation of electric pulse train. A 5 mm 100 µm, single-shank, thin-film, penetrating recording probe was inserted perpendicularly to the surface of the IC in the coronal plane at an angle of 30-40° off the parasagittal plane with a depth of 2.0-2.5 mm. The peripheral and central masking effects were compared using electric pulse trains to the left ear and acoustic noise to the left ear (ipsilateral) and to the right ear (contralateral). Binaural acoustic stimuli were presented with different time delays and compared with combined electric and acoustic stimuli. The averaged evoked potentials and total spike numbers were measured using thin-film electrodes inserted into the central nucleus of the IC.ResultsIpsilateral noise had more obvious effects on the electric response than did contralateral noise. Contralateral noise decreased slightly the response amplitude to the electric pulse train stimuli. Immediately after the onset of acoustic noise, the response pattern changed transiently with shorter response intervals. The effects of contralateral noise were evident at the beginning of the continuous noise. The total spike number decreased when the binaural stimuli reached the IC most simultaneously.ConclusionThese results suggest that central masking is quite different from peripheral masking and occurs within the binaural auditory system, and this study showed that the effect of masking could be observed in the IC recording. These effects are more evident and consistent with the psychophysical data from spike number analyses than with the previously reported gross potential data.

Decoding Action Intentions from Preparatory Brain Activity in Human Parieto-Frontal Networks

How and where in the human brain high-level sensorimotor processes such as intentions and decisions are coded remain important yet essentially unanswered questions. This is in part because, to date, decoding intended actions from brain signals has been primarily constrained to invasive neural recordings in nonhuman primates. Here we demonstrate using functional MRI (fMRI) pattern recognition techniques that we can also decode movement intentions from human brain signals, specifically object-directed grasp and reach movements, moments before their initiation. Subjects performed an event-related delayed movement task toward a single centrally located object (consisting of a small cube attached atop a larger cube). For each trial, after visual presentation of the object, one of three hand movements was instructed: grasp the top cube, grasp the bottom cube, or reach to touch the side of the object (without preshaping the hand). We found that, despite an absence of fMRI signal amplitude differences between the planned movements, the spatial activity patterns in multiple parietal and premotor brain areas accurately predicted upcoming grasp and reach movements. Furthermore, the patterns of activity in a subset of these areas additionally predicted which of the two cubes were to be grasped. These findings offer new insights into the detailed movement information contained in human preparatory brain activity and advance our present understanding of sensorimotor planning processes through a unique description of parieto-frontal regions according to the specific types of hand movements they can predict.

Decoding and Cortical Source Localization for Intended Movement Direction With MEG

Magnetoencephalography (MEG) enables a noninvasive interface with the brain that is potentially capable of providing movement-related information similar to that obtained using more invasive neural recording techniques. Previous studies have shown that movement direction can be decoded from multichannel MEG signals recorded in humans performing wrist movements. We studied whether this information can be extracted without overt movement of the subject, because the targeted users of brain-controlled interface (BCI) technology are those with severe motor disabilities. The objectives of this study were twofold: 1) to decode intended movement direction from MEG signals recorded during the planning period before movement onset and during imagined movement and 2) to localize cortical sources modulated by intended movement direction. Ten able-bodied subjects performed both overt and imagined wrist movement while their cortical activities were recorded using a whole head MEG system. The intended movement direction was decoded using linear discriminant analysis and a Bayesian classifier. Minimum current estimation (MCE) in combination with a bootstrapping procedure enabled source-space statistical analysis, which showed that the contralateral motor cortical area was significantly modulated by intended movement direction, and this modulation was the strongest ∼100 ms before the onset of overt movement. These results suggest that it is possible to study cortical representation of specific movement information using MEG, and such studies may aid in presurgical localization of optimal sites for implanting electrodes for BCI systems.