Electrocorticogram Research Articles

High-density mapping of primate digit representations with a 1152-channel µECoG array

Objective. Advances in brain–machine interfaces (BMIs) are expected to support patients with movement disorders. Electrocorticogram (ECoG) measures electrophysiological activities over a large area using a low-invasive flexible sheet placed on the cortex. ECoG has been considered as a feasible signal source of the clinical BMI device. To capture neural activities more precisely, the feasibility of higher-density arrays has been investigated. However, currently, the number of electrodes is limited to approximately 300 due to wiring difficulties, device size, and system costs. Approach. We developed a high-density recording system with a large coverage (14 × 7 mm2) and using 1152 electrodes by directly integrating dedicated flexible arrays with the neural-recording application-specific integrated circuits and their interposers. Main results. Comparative experiments with a 128-channel array demonstrated that the proposed device could delineate the entire digit representation of a nonhuman primate. Subsampling analysis revealed that higher-amplitude signals can be measured using higher-density arrays. Significance. We expect that the proposed system that simultaneously establishes large-scale sampling, high temporal-precision of electrophysiology, and high spatial resolution comparable to optical imaging will be suitable for next-generation brain-sensing technology.

Changes in beta and high-gamma power in resting-state electrocorticogram induced by repetitive transcranial magnetic stimulation of primary motor cortex in unanesthetized macaque monkeys

Repetitive transcranial magnetic stimulation (rTMS) is now widely used as a means of neuromodulation, but the details of the mechanisms by which rTMS works remain unclarified. As a step forward to unveiling the neural phenomena occurring underneath the TMS coil, we conducted an electrophysiological study using awake and unanesthetized monkeys with subdural electrocorticogram (ECoG) electrodes implanted over the primary motor cortex (MI). We evaluated the effects of low-frequency (1 Hz) and high-frequency (10 Hz) rTMS on the resting-state ECoG signals in the stimulated MI, as well as the motor evoked potentials (MEPs) in the contralateral hand. Following the 1-Hz rTMS application, the ECoG beta band power and the MEP amplitude were significantly decreased. Following the 10-Hz rTMS application, the ECoG high-gamma power and the MEP amplitude significantly increased. Given that beta and high-gamma activities in the ECoG reflect the synchronous firing and the firing frequency of cell assemblies, respectively, in local neural circuits, these results suggest that low-frequency rTMS inhibits neural activity by desynchronizing the firing activity of local circuits, whereas high-frequency rTMS facilitates neural activity by increasing the firing rate of cell assemblies in the local circuits.

Electrophysiological and neurochemical evaluation of the adverse effects of REM sleep deprivation and epileptic seizures on rat's brain

AimThe current study aims to investigate the impact of paradoxical (REM) sleep deprivation and/or epileptic seizures on rat's cortical brain tissues. Main methodsAnimals were divided into four groups; control, epileptic, REM sleep deprived and epileptic subjected to REM sleep deprivation. Electrocorticogram (ECoG) signals were recorded and quantitatively analyzed for each group. Concentrations of amino acid neurotransmitters; proinflammatory cytokines; and oxidative stress parameters; and acetylcholinesterase activity were determined in the cortex of the animals in different groups. Key findingsResults showed significant variations in the spectral distribution of ECoG waves in the epilepsy model, 24- and 48-hours of REM sleep deprivation and their combined effects indicating a state of cortical hyperexcitability. Significant increases in NO and taurine and significant decrement in glutamine, GABA and glycine were determined. In REM sleep deprived rats significant elevation in glutamate, aspartate, glycine and taurine and a significant lowering in GABA were obtained. This was accompanied by significant reduction in AchE and IL-β. In the cortical tissue of epileptic rats deprived from REM sleep significant increases in lipid peroxidation, TNF-α, IL-1β, IL-6 and aspartate and a significant reduction in AchE were observed. SignificanceThe present data indicate that REM sleep deprivation induces an increase in lipid peroxidation and storming in proinflammatory cytokines in the cortex of rat model of epilepsy during SRS. These changes are associated with a decreased seizure threshold as inferred from the increase in alpha and Beta waves and a decrease in Delta waves of ECoG.

Adaptive tracking of human ECoG network dynamics

Objective. Extracting and modeling the low-dimensional dynamics of multi-site electrocorticogram (ECoG) network activity is important in studying brain functions and dysfunctions and for developing translational neurotechnologies. Dynamic latent state models can be used to describe the ECoG network dynamics with low-dimensional latent states. But so far, non-stationarity of ECoG network dynamics has largely not been addressed in these latent state models. Such non-stationarity can happen due to a change in brain state or recording instability over time. A critical question is whether adaptive tracking of ECoG network dynamics can lead to further dimensionality reduction and more parsimonious and precise modeling. This question is largely unaddressed. Approach. We investigate this question by employing an adaptive linear state-space model for ECoG network activity constructed from ECoG power feature time-series over tens of hours from 10 human subjects with epilepsy. We study how adaptive modeling affects the prediction and dimensionality reduction for ECoG network dynamics compared with prior non-adaptive models, which do not track non-stationarity. Main results. Across the 10 subjects, adaptive modeling significantly improved the prediction of ECoG network dynamics compared with non-adaptive modeling, especially for lower latent state dimensions. Also, compared with non-adaptive modeling, adaptive modeling allowed for additional dimensionality reduction without degrading prediction performance. Finally, these results suggested that ECoG network dynamics over our recording periods exhibit non-stationarity, which can be tracked with adaptive modeling. Significance. These results have important implications for studying low-dimensional neural representations using ECoG, and for developing future adaptive neurotechnologies for more precise decoding and modulation of brain states in neurological and neuropsychiatric disorders.

Perinatal Fentanyl Exposure Leads to Long-Lasting Impairments in Somatosensory Circuit Function and Behavior.

One consequence of the opioid epidemic are lasting neurodevelopmental sequelae afflicting adolescents exposed to opioids in the womb. A translationally relevant and developmentally accurate preclinical model is needed to understand the behavioral, circuit, network, and molecular abnormalities resulting from this exposure. By employing a novel preclinical model of perinatal fentanyl exposure, our data reveal that fentanyl has several dose-dependent, developmental consequences to somatosensory function and behavior. Newborn male and female mice exhibit signs of withdrawal and sensory-related deficits that extend at least to adolescence. As fentanyl exposure does not affect dams' health or maternal behavior, these effects result from the direct actions of perinatal fentanyl on the pups' developing brain. At adolescence, exposed mice exhibit reduced adaptation to sensory stimuli, and a corresponding impairment in primary somatosensory (S1) function. In vitro electrophysiology demonstrates a long-lasting reduction in S1 synaptic excitation, evidenced by decreases in release probability, NMDA receptor-mediated postsynaptic currents, and frequency of miniature excitatory postsynaptic currents (mEPSCs), as well as increased frequency of miniature inhibitory postsynaptic currents (mIPSCs). In contrast, anterior cingulate cortical neurons exhibit an opposite phenotype, with increased synaptic excitation. Consistent with these changes, electrocorticograms (ECoGs) reveal suppressed ketamine-evoked γ oscillations. Morphologic analysis of S1 pyramidal neurons indicate reduced dendritic complexity, dendritic length, and soma size. Further, exposed mice exhibited abnormal cortical mRNA expression of key receptors involved in synaptic transmission and neuronal growth and development, changes that were consistent with the electrophysiological and morphologic changes. These findings demonstrate the lasting sequelae of perinatal fentanyl exposure on sensory processing and function.SIGNIFICANCE STATEMENT This is the first study to show that exposure to fentanyl in the womb results in behavioral, circuitry, and synaptic effects that last at least to adolescence. We also show, for the first time, that this exposure has different, lasting effects on synapses in different cortical areas.

Representation Learning for Motor Imagery Recognition with Deep Neural Network

This study describes a method for classifying electrocorticograms (ECoGs) based on motor imagery (MI) on the brain–computer interface (BCI) system. This method is different from the traditional feature extraction and classification method. In this paper, the proposed method employs the deep learning algorithm for extracting features and the traditional algorithm for classification. Specifically, we mainly use the convolution neural network (CNN) to extract the features from the training data and then classify those features by combing with the gradient boosting (GB) algorithm. The comprehensive study with CNN and GB algorithms will profoundly help us to obtain more feature information from brain activities, enabling us to obtain the classification results from human body actions. The performance of the proposed framework has been evaluated on the dataset I of BCI Competition III. Furthermore, the combination of deep learning and traditional algorithms provides some ideas for future research with the BCI systems.

ВЛИЯНИЕ ПОСЛЕДСТВИЙ ГИПОКСИЧЕСКИХ ВОЗДЕЙСТВИЙ В РАЗНЫЕ ПЕРИОДЫ ЭМБРИОГЕНЕЗА, НА ЭЛЕКТРИЧЕСКУЮ АКТИВНОСТЬ СЛУХОВОЙ КОРЫ В ПЕРВЫЙ МЕСЯЦ ПОСТНАТАЛЬНОГО РАЗВИТИЯ КРОЛИКОВ

The spectral composition of the auditory cortex electrocorticogram (ECoG) was studied in 20- and 30-day-old rabbit pups exposed to hypoxia at different stages of prenatal life. Oxygen deficiency had differential effects on the formation of the auditory cortex ECoG spectrum at the embryonic (E1–8), pre-fetal (E8–18), and fetal (E18–28) stages of prenatal development. These differences were mainly manifested in an increased number of slow waves of electrical activity. Both in 20- and 30-day-old rabbit pups exposed to hypoxia at the embryonic stage, ECoG spectral characteristics insignificantly deviated from the normal level. By contrast, hypoxia experienced at the pre-fetal and fetal stages led to more pronounced, though similar, changes in spectral characteristics. These data suggest that neural structures of the rabbit auditory cortex are more sensitive to oxygen deficiency at the pre-fetal and fetal stages of prenatal development compared to the embryonic stage.

ЭЛЕКТРОФИЗИОЛОГИЧЕСКОЕ ИССЛЕДОВАНИЕ ОСЦИЛЛЯТОРНОЙ АКТИВНОСТИ МОЗГА ОБЕЗЬЯН MACACA MULATTA

It is well known that rhythmic light stimulation can alter the electrical activity of the human and animal brain. Moreover, the brain response to certain flicker frequencies significantly exceeds the responses to neighboring frequencies. This phenomenon is thought to be related with the effect of resonance, as evidenced by the coincidence of one of the maxima in the profile of the response to flashes with the frequency of the alpha rhythm. However, other frequencies that cause an increased response to flashes are not reflected in electroencephalogram (EEG) as dominant oscillations. The goal of this study was to reveal the relationship between local maxima in the profile of the responses to flashes of different frequencies and dominant brain oscillations recorded in electrocorticogram (ECoG) of rhesus monkeys without stimulation. The study was carried out on four male Macaca mulatta individuals. In three animals, peak responses were elicited by flickers at 8 and 16 Hz, while one monkey showed a second peak in the 22−30 Hz range. The first maximum (8−10 Hz) in the profile of the response to rhythmic photostimulation coincided with the dominant rhythm recorded in the occipital and parietal regions at rest. The second maximum at 16 Hz coincided with the dominant ECoG rhythm in one of the primates when it was in the state of emotional arousal, which may account for the resonant origin of the increase in responses in this frequency range. The data obtained indicate that dominant brain rhythms, including latent rhythms revealed only by rhythmic photostimulation, can coincide in frequency in monkeys and humans. Neuronal mechanisms of selective sensitivity of neural networks to different frequencies of photostimulation are discussed.

Neuronal excitability and sensory responsiveness in the thalamo-cortical network in a novel rat model of isoelectric brain state.

The neuronal and network properties that persist during an isoelectric coma remain largely unknown. We developed a new in vivo rat model to assess cell excitability and sensory responsiveness in the thalamo-cortical pathway during an isoflurane-induced isoelectric brain state. The isoelectric electrocorticogram reflected a complete interruption of spontaneous synaptic and firing activities in cortical and thalamic neurons. Cell excitability and sensory responses in the thalamo-cortical network persisted at a reduced level in the isoelectric condition and returned to control values after resumption of background brain activity. These findings could lead to a reassessment of the functional status of the drug-induced isoelectric state: a latent state in which individual neurons and networks retain to some extent the ability of being activated by external inputs. The neuronal and network properties that persist in an isoelectric brain completely deprived of spontaneous electrical activity remain largely unexplored. Here, we developed a new in vivo rat model to examine cell excitability and sensory responsiveness in somatosensory thalamo-cortical networks during the interruption of endogenous brain activity induced by high doses of isoflurane. Electrocorticograms (ECoGs) from the barrel cortex were captured simultaneously with either intracellular recordings of subjacent cortical pyramidal neurons or extracellular records of the related thalamo-cortical neurons. Isoelectric ECoG periods reflected the disappearance of spontaneous synaptic and firing activities in cortical and thalamic neurons. This was associated with a sustained membrane hyperpolarization and a reduced intrinsic excitability in deep-layer cortical neurons, without significant changes in their membrane input resistance. Concomitantly, we found that whisker-evoked potentials in the ECoG and synaptic responses in cortical neurons were attenuated in amplitude and increased in latency. Impaired responsiveness in the barrel cortex paralleled with a lowering of the sensory-induced firing in thalamic cells. The return of endogenous brain electrical activities, after reinstatement of a control isoflurane concentration, led to the recovery of cortical neurons excitability and sensory responsiveness. These findings demonstrate the persistence of a certain level of cell excitability and sensory integration in the isoelectric state and the full recovery of cortico-thalamic functions after restoration of internal cerebral activities.

Excitation of the Pre-frontal and Primary Visual Cortex in Response to Transcorneal Electrical Stimulation in Retinal Degeneration Mice

Retinal degeneration (rd) is one of the leading causes of blindness in the modern world today. Various strategies including electrical stimulation are being researched for the restoration of partial or complete vision. Previous studies have demonstrated that the effectiveness of electrical stimulation in somatosensory, frontal and visual cortices is dependent on stimulation parameters including stimulation frequency and brain states. The aim of the study is to investigate the effect of applying a prolonged electrical stimulation on the eye of rd mice with various stimulation frequencies, in awake and anesthetized brain states. We recorded spontaneous electrocorticogram (ECoG) neural activity in prefrontal cortex and primary visual cortex in a mouse model of retinitis pigmentosa (RP) after prolonged (5-day) transcorneal electrical stimulation (pTES) at various frequencies (2, 10, and 20 Hz). We evaluated the absolute power and coherence of spontaneous ECoG neural activities in contralateral primary visual cortex (contra Vcx) and contralateral pre-frontal cortex (contra PFx). Under the awake state, the absolute power of theta, alpha and beta oscillations in contra Vcx, at 10 Hz stimulation, was higher than in the sham group. Under the anesthetized state, the absolute power of medium-, high-, and ultra-high gamma oscillations in the contra PFx, at 2 Hz stimulation, was higher than in the sham group. We also observed that the ultra-high gamma band coherence in contra Vcx-contra PFx was higher than in the sham group, with both 10 and 20 Hz stimulation frequencies. Our results showed that pTES modulates rd brain oscillations in a frequency and brain state-dependent manner. These findings suggest that non-invasive electrical stimulation of retina changes patterns of neural oscillations in the brain circuitry. This also provides a starting point for investigating the sustained effect of electrical stimulation of the retina to brain activities.

A Swallowing Decoder Based on Deep Transfer Learning: AlexNet Classification of the Intracranial Electrocorticogram.

To realize a brain-machine interface to assist swallowing, neural signal decoding is indispensable. Eight participants with temporal-lobe intracranial electrode implants for epilepsy were asked to swallow during electrocorticogram (ECoG) recording. Raw ECoG signals or certain frequency bands of the ECoG power were converted into images whose vertical axis was electrode number and whose horizontal axis was time in milliseconds, which were used as training data. These data were classified with four labels (Rest, Mouth open, Water injection, and Swallowing). Deep transfer learning was carried out using AlexNet, and power in the high-[Formula: see text] band (75-150[Formula: see text]Hz) was the training set. Accuracy reached 74.01%, sensitivity reached 82.51%, and specificity reached 95.38%. However, using the raw ECoG signals, the accuracy obtained was 76.95%, comparable to that of the high-[Formula: see text] power. We demonstrated that a version of AlexNet pre-trained with visually meaningful images can be used for transfer learning of visually meaningless images made up of ECoG signals. Moreover, we could achieve high decoding accuracy using the raw ECoG signals, allowing us to dispense with the conventional extraction of high-[Formula: see text] power. Thus, the images derived from the raw ECoG signals were equivalent to those derived from the high-[Formula: see text] band for transfer deep learning.

A Translational Study on Acute Traumatic Brain Injury: High Incidence of Epileptiform Activity on Human and Rat Electrocorticograms and Histological Correlates in Rats.

Background: In humans, early pathological activity on invasive electrocorticograms (ECoGs) and its putative association with pathomorphology in the early period of traumatic brain injury (TBI) remains obscure. Methods: We assessed pathological activity on scalp electroencephalograms (EEGs) and ECoGs in patients with acute TBI, early electrophysiological changes after lateral fluid percussion brain injury (FPI), and electrophysiological correlates of hippocampal damage (microgliosis and neuronal loss), a week after TBI in rats. Results: Epileptiform activity on ECoGs was evident in 86% of patients during the acute period of TBI, ECoGs being more sensitive to epileptiform and periodic discharges. A “brush-like” ECoG pattern superimposed over rhythmic delta activity and periodic discharge was described for the first time in acute TBI. In rats, FPI increased high-amplitude spike incidence in the neocortex and, most expressed, in the ipsilateral hippocampus, induced hippocampal microgliosis and neuronal loss, ipsilateral dentate gyrus being most vulnerable, a week after TBI. Epileptiform spike incidence correlated with microglial cell density and neuronal loss in the ipsilateral hippocampus. Conclusion: Epileptiform activity is frequent in the acute period of TBI period and is associated with distant hippocampal damage on a microscopic level. This damage is probably involved in late consequences of TBI. The FPI model is suitable for exploring pathogenetic mechanisms of post-traumatic disorders.

Fetal sheep cerebral electrical activity: A new technique to record EEG

BackgroundSheep models are commonly used to study fetal cortical activity, including response to hypoxia. The standard technique consists of recording electrocorticogram (ECOG) in utero using electrodes placed on the dura mater. New methodWe propose a new method for recording the electroencephalogram (EEG) of fetal sheep, using electrodes placed above the skull bone and fixed to the cranial periosteum. ResultsTwelve animals were instrumented with this new technique. The EEG signal recorded in utero was of sufficient quality for visual and quantitative analysis of the fetal cortical activity. Comparison with existing methodThis new method is less invasive than the standard method commonly used to record cerebral activity in fetal sheep, because it avoids drilling the skull by hand. The EEG signal recorded in utero had visual and quantitative characteristics comparable to ECOG. ConclusionsWe present a new method of EEG recording that appears to be an acceptable alternative to the standard ECOG recording method. Fetal sheep EEG can be used to better understand the physiological mechanisms involved in the cerebral response to hypoxia.

An optically transparent multi-electrode array for combined electrophysiology and optophysiology at the mesoscopic scale

Objective. A number of tissue penetrating opto-electrodes to simultaneously record and optogenetically influence brain activity have been developed. For experiments at the surface of the brain, such as electrocorticogram (ECoG) recordings and surface optogenetics, fewer devices have been described and no device has found widespread adoption for neuroscientific experiments. One issue slowing adoption is the complexity and fragility of existing devices, typically based on transparent electrode materials like graphene and indium-tin oxide (ITO). We focused here on improving existing processes based on metal traces and polyimide (PI), which produce more robust and cost-effective devices, to develop a multi-electrode array for optophysiology. Approach. The most widely used substrate material for surface electrodes, PI, has seen little use for optophysiologicalμECoG/ECoG arrays. This is due to its lack of transparency at optogenetically relevant short wavelengths. Here we use very thin layers of PI in combination with chrome-gold-platinum electrodes to achieve the necessary substrate transparency and high mechanical flexibility in a device that still rejects light artifacts well. Main results. The manufactured surface arrays have a thickness of only 6.5 µm, resulting in 80% transparency for blue light. We demonstrate immunity against opto-electric artifacts, long term stability and biocompatibility as well as suitability for optical voltage imaging. The biocompatible arrays are capable of recording stable ECoGs over months without any measurable degradation and can be used to map the tonotopic organization of the curved rodent auditory cortex. Significance. Our novel probes combine proven materials and processing steps to create optically near-transparent electrode arrays with superior longevity. In contrast to previous opto-electrodes, our probes are simple to manufacture, robust, offer long-term stability, and are a practical engineering solution for optophysiological experiments not requiring transparency of the electrode sites themselves.

Thermal Analysis of a Skull Implant in Brain-Computer Interfaces.

The goal of this study is to estimate the thermal impact of a titanium skull unit (SU) implanted on the exterior aspect of the human skull. We envision this unit to house the front-end of a fully implantable electrocorticogram (ECoG)-based bi-directional (BD) brain-computer interface (BCI). Starting from the bio-heat transfer equation with physiologically and anatomically constrained tissue parameters, we used the finite element method (FEM) implemented in COMSOL to build a computational model of the SU's thermal impact. Based on our simulations, we predicted that the SU could consume up to 75 mW of power without raising the temperature of surrounding tissues above the safe limits (increase in temperature of 1°C). This power budget by far exceeds the power consumption of our front-end prototypes, suggesting that this design can sustain the SU's ability to record ECoG signals and deliver cortical stimulation. These predictions will be used to further refine the existing SU design and inform the design of future SU prototypes.

An ECoG-Based Binary Classification of BCI Using Optimized Extreme Learning Machine

In order to improve the accuracy of brain signal processing and accelerate speed meanwhile, we present an optimal and intelligent method for large dataset classification application in this paper. Optimized Extreme Learning Machine (OELM) is introduced in ElectroCorticoGram (ECoG) feature classification of motor imaginary-based brain-computer interface (BCI) system, with common spatial pattern (CSP) to extract the feature. When comparing it with other conventional classification methods like SVM and ELM, we exploit several metrics to evaluate the performance of all the adopted methods objectively. The accuracy of the proposed BCI system approaches approximately 92.31% when classifying ECoG epochs into left pinky or tongue movement, while the highest accuracy obtained by other methods is no more than 81%, which substantiates that OELM is more efficient than SVM, ELM, etc. Moreover, the simulation results also demonstrate that OELM will significantly improve the performance with p value being far less than 0.001. Hence, the proposed OELM is satisfactory in addressing ECoG signal.

Artifact‐Free 2D Mapping of Neural Activity In Vivo through Transparent Gold Nanonetwork Array

AbstractWith the rapid increase in the use of optogenetics to investigate the nervous system, there is a high demand for a neural interface that enables 2D mapping of electrophysiological neural signals with high precision during simultaneous light stimulation. Here, a gold nanonetwork (Au NN)‐based transparent neural electrocorticogram (ECoG) monitoring system is proposed as implantable neural electronics. The neural interface enables accurate 2D mapping of ECoG neural signals without any photoelectric artifact during light stimulation. By using the Au NN, not only the transmittance of the microelectrodes is increased by 81% but also a low electrochemical impedance of 33.9 kΩ at 1 kHz with improved mechanical stability is achieved. It is demonstrated that the transparent microelectrode array records multichannel in vivo neural activities with no photoelectric artifact and a high signal‐to‐noise ratio. Propagation of neural dynamics of optically driven neural activities is also clearly visualized using the 2D Au NN microelectrode array. This transparent, flexible ECoG microelectrode array is a promising candidate for next‐generation in vitro and in vivo neural interface for 2D mapping of neural dynamics.

Chronic neural interfacing with cerebral cortex using single-walled carbon nanotube-polymer grids

Objective. The development of electrode arrays able to reliably record brain electrical activity is a critical issue in brain machine interface (BMI) technology. In the present study we undertook a comprehensive physico-chemical, physiological, histological and immunohistochemical characterization of new single-walled carbon nanotubes (SWCNT)-based electrode arrays grafted onto medium-density polyethylene (MD-PE) films. Approach. The long-term electrical stability, flexibility, and biocompatibility of the SWCNT arrays were investigated in vivo in laboratory rats by two-months recording and analysis of subdural electrocorticogram (ECoG). Ex-vivo characterization of a thin flexible and single probe SWCNT/polymer electrode is also provided. Main results. The SWCNT arrays were able to capture high quality and very stable ECoG signals across 8 weeks. The histological and immunohistochemical analyses demonstrated that SWCNT arrays show promising biocompatibility properties and may be used in chronic conditions. The SWCNT-based arrays are flexible and stretchable, providing low electrode-tissue impedance, and, therefore, high compliance with the irregular topography of the cortical surface. Finally, reliable evoked synaptic local field potentials in rat brain slices were recorded using a special SWCNT-polymer-based flexible electrode. Significance. The results demonstrate that the SWCNT arrays grafted in MD-PE are suitable for manufacturing flexible devices for subdural ECoG recording and might represent promising candidates for long-term neural implants for epilepsy monitoring or neuroprosthetic BMI.

Establishing Drug Effects on Electrocorticographic Activity in a Genetic Absence Epilepsy Model: Advances and Pitfalls.

The genetic rat models such as rats of the WAG/Rij strain and GAERS were developed as models for generalized genetic epilepsy and in particular for childhood absence epilepsy. These animal models were described in the eighties of the previous century and both models have, among others, face, construct and predictive validity. Both models were and are currently used as models to predict the action of antiepileptic medication and other experimental treatments, to elucidate neurobiological mechanisms of spike-wave discharges and epileptogenesis. Although the electroencephalagram (EEG)/electrocorticogram (ECoG) is imperative for establishing absence seizures and to quantify the for absence epilepsy typical spike-wave discharges, monitoring the animals behavior is equally necessary. Here an overview is given regarding the design of drug evaluation studies, which animals to use, classical and new EEG variables, the monitoring and quantification of the behavior of the rats, some pitfalls regarding the interpretation of the data, and some developments in EEG technology.

Optimal artifact suppression in simultaneous electrocorticography stimulation and recording for bi-directional brain-computer interface applications

Objective. Electrocorticogram (ECoG)-based brain-computer interfaces (BCIs) are a promising platform for the restoration of motor and sensory functions to those with neurological deficits. Such bi-directional BCI operation necessitates simultaneous ECoG recording and stimulation, which is challenging given the presence of strong stimulation artifacts. This problem is exacerbated if the BCI’s analog front-end operates in an ultra-low power regime, which is a basic requirement for fully implantable medical devices. In this study, we developed a novel method for the suppression of stimulation artifacts before they reach the analog front-end. Approach. Using elementary biophysical considerations, we devised an artifact suppression method that employs a weak auxiliary stimulation delivered between the primary stimulator and the recording grid. The exact location and amplitude of this auxiliary stimulating dipole were then found through a constrained optimization procedure. The performance of our method was tested in both simulations and phantom brain tissue experiments. Main results. The solution found through the optimization procedure matched the optimal canceling dipole in both simulations and experiments. Artifact suppression as large as 28.7 dB and 22.9 dB were achieved in simulations and brain phantom experiments, respectively. Significance. We developed a simple constrained optimization-based method for finding the parameters of an auxiliary stimulating dipole that yields optimal artifact suppression. Our method suppresses stimulation artifacts before they reach the analog front-end and may prevent the front-end amplifiers from saturation. Additionally, it can be used along with other artifact mitigation techniques to further reduce stimulation artifacts.