Chronic subdural electrocorticography in nonhuman primates by an implantable wireless device for brain-machine interfaces.

Background: Subdural electrocorticography (ECoG) signals have been proposed as a stable, good-quality source for brain-machine interfaces (BMIs), with a higher spatial and temporal resolution than electroencephalography (EEG). However, long-term implantation may lead to chronic inflammatory reactions and connective tissue encapsulation, resulting in a decline in signal recording quality. However, no study has reported the effects of the surrounding tissue on signal recording and device functionality thus far. Methods: In this study, we implanted a wireless recording device with a customized 32-electrode-ECoG array subdurally in two nonhuman primates for 15 months. We evaluated the neural activities recorded from and wirelessly transmitted to the devices and the chronic tissue reactions around the electrodes. In addition, we measured the gain factor of the newly formed ventral fibrous tissue in vivo. Results: Time-frequency analyses of the acute and chronic phases showed similar signal features. The average root mean square voltage and power spectral density showed relatively stable signal quality after chronic implantation. Histological examination revealed thickening of the reactive tissue around the electrode array; however, no evident inflammation in the cortex. From gain factor analysis, we found that tissue proliferation under electrodes reduced the amplitude power of signals. Conclusion: This study suggests that subdural ECoG may provide chronic signal recordings for future clinical applications and neuroscience research. This study also highlights the need to reduce proliferation of reactive tissue ventral to the electrodes to enhance long-term stability.

Intracranial EEG Recordings of High-Frequency Activity From a Wireless Implantable BMI Device in Awake Nonhuman Primates.

OBJECTIVE: Wireless implantable brain machine interfaces (BMIs) are a promising tool to restore communication and motor functions for individuals with severe motor disability. Prior to clinical application, recording performance must be sufficiently confirmed by animal experiments. In this paper, we aimed to evaluate the performance of a novel BMI wireless device for recording brain activity in two nonhuman primates. METHOD: We customized a wireless device for implantable BMIs for clinical application. We used a battery instead of a wireless power charging system. Thirty-two electrodes were subdurally implanted over the left temporoparietal cortex. We evaluated the recording performance of the wireless device by auditory steady-state responses (ASSRs) and ketamine-induced responses. RESULT: The devices successfully recorded broadband oscillatory activities up to the high-frequency band from the temporal cortex in two awake macaque monkeys. Spectral analysis of raw signals demonstrated that the devices detected characteristic results of a 40-Hz ASSR and prominent high-frequency band activity induced by ketamine injection. CONCLUSION: We confirmed the functionality of the wireless device in recording and transmitting electrocorticography (ECoG) signals with both millisecond precision and recording stability. SIGNIFICANCE: These results provide confidence that this wireless device can be a translational tool for other fundamental neuroscientific studies in free-moving models.

Multichannel stimulation module as a tool for animal studies on cortical neural prostheses.

Intracortical microstimulation to the visual cortex is thought to be a feasible technique for inducing localized phosphenes in patients with acquired blindness, and thereby for visual prosthesis. In order to design effective stimuli for the prosthesis, it is important to elucidate relationships between the spatio-temporal patterns of stimuli and the resulting neural responses and phosphenes through pre-clinical animal studies. However, the physiological basis of effective spatial patterns of the stimuli for the prosthesis has been little investigated in the literature, at least partly because that the previously developed multi-channel stimulation systems were designed specifically for the clinical use. In the present, a 64-channel stimulation module was developed as a scalable tool for animal experiments. The operations of the module were verified by not only dry-bench tests but also physiological animal experiments in vivo. The results demonstrated its usefulness for examining the stimulus-response relationships in a quantitative manner, and for inducing the multi-site neural excitations with a multi-electrode array. In addition, this stimulation module could be used to generate spatially patterned stimuli with up to 4,096 channels in a dynamic way, in which the stimulus patterns can be updated at a certain frame rate in accordance with the incoming visual scene. The present study demonstrated that our stimulation module is applicable to the physiological and other future studies in animals on the cortical prostheses.

Electrocorticographic effects of acute ketamine on non-human primate brains.

Objective. Acute blockade of glutamate N-methyl-D-aspartate receptors by ketamine induces symptoms and electrophysiological changes similar to schizophrenia. Previous studies have shown that ketamine elicits aberrant gamma oscillations in several cortical areas and impairs coupling strength between the low-frequency phase and fast frequency amplitude, which plays an important role in integrating functional information.Approach. This study utilized a customized wireless electrocorticography (ECoG) recording device to collect subdural signals from the somatosensory and primary auditory cortices in two monkeys. Ketamine was administered at a dose of 3 mg kg-1(intramuscular) or 0.56 mg kg-1(intravenous) to elicit brain oscillation reactions. We analyzed the raw data using methods such as power spectral density, time-frequency spectra, and phase-amplitude coupling (PAC).Main results. Acute ketamine triggered broadband gamma and high gamma oscillation power and decreased lower frequencies. The effect was stronger in the primary auditory cortex than in the somatosensory area. The coupling strength between the low phase of theta and the faster amplitude of gamma/high gamma bands was increased by a lower dose (0.56 mg kg-1iv) and decreased with a higher dose (3 mg kg-1im) ketamine.Significance. Our results showed that lower and higher doses of ketamine elicited differential effects on theta-gamma PAC. These findings support the utility of ECoG models as a translational platform for pharmacodynamic research in future research.

Motor and sensory cortical processing of neural oscillatory activities revealed by human swallowing using intracranial electrodes.

Swallowing is attributed to the orchestration of motor output and sensory input. We hypothesized that swallowing can illustrate differences between motor and sensory neural processing. Eight epileptic participants fitted with intracranial electrodes over the orofacial cortex were asked to swallow a water bolus. Mouth opening and swallowing were treated as motor tasks, whereas water injection was treated as a sensory task. Phase-amplitude coupling between lower-frequency and high γ (HG) bands (75-150 Hz) was investigated. An α (10-16 Hz)-HG coupling appeared before motor-related HG power increases (burst), and a θ (5-9 Hz)-HG coupling appeared during sensory-related HG bursts. The peaks of motor-related coupling were 0.6-0.7 s earlier than that of HG power. The motor-related HG was modulated at the trough of the α oscillation, and the sensory-related HG amplitude was modulated at the peak of the θ oscillation. These contrasting results can help to elucidate the brain's sensory motor functions.

Swallowing-related neural oscillation: an intracranial EEG study.

OBJECTIVE: Swallowing is a unique movement due to the indispensable orchestration of voluntary and involuntary movements. The transition from voluntary to involuntary swallowing is executed within milliseconds. We hypothesized that the underlying neural mechanism of swallowing would be revealed by high-frequency cortical activities. METHODS: Eight epileptic participants fitted with intracranial electrodes over the orofacial cortex were asked to swallow a water bolus and cortical oscillatory changes, including the high γ band (75-150 Hz) and ß band (13-30 Hz), were investigated at the time of mouth opening, water injection, and swallowing. RESULTS: Increases in high γ power associated with mouth opening were observed in the ventrolateral prefrontal cortex (VLPFC) with water injection in the lateral central sulcus and with swallowing in the region along the Sylvian fissure. Mouth opening induced a decrease in ß power, which continued until the completion of swallowing. The high γ burst of activity was focal and specific to swallowing; however, the ß activities were extensive and not specific to swallowing. In the interim between voluntary and involuntary swallowing, swallowing-related high γ power achieved its peak, and subsequently, the power decreased. INTERPRETATION: We demonstrated three distinct activities related to mouth opening, water injection, and swallowing induced at different timings using high γ activities. The peak of high γ power related to swallowing suggests that during voluntary swallowing phases, the cortex is the main driving force for swallowing as opposed to the brain stem.

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.

Minimal Tissue Reaction after Chronic Subdural Electrode Implantation for Fully Implantable Brain-Machine Interfaces.

There is a growing interest in the use of electrocorticographic (ECoG) signals in brain-machine interfaces (BMIs). However, there is still a lack of studies involving the long-term evaluation of the tissue response related to electrode implantation. Here, we investigated biocompatibility, including chronic tissue response to subdural electrodes and a fully implantable wireless BMI device. We implanted a half-sized fully implantable device with subdural electrodes in six beagles for 6 months. Histological analysis of the surrounding tissues, including the dural membrane and cortices, was performed to evaluate the effects of chronic implantation. Our results showed no adverse events, including infectious signs, throughout the 6-month implantation period. Thick connective tissue proliferation was found in the surrounding tissues in the epidural space and subcutaneous space. Quantitative measures of subdural reactive tissues showed minimal encapsulation between the electrodes and the underlying cortex. Immunohistochemical evaluation showed no significant difference in the cell densities of neurons, astrocytes, and microglia between the implanted sites and contralateral sites. In conclusion, we established a beagle model to evaluate cortical implantable devices. We confirmed that a fully implantable wireless device and subdural electrodes could be stably maintained with sufficient biocompatibility in vivo.

Non-invasive quantification of human swallowing using a simple motion tracking system.

The number of patients with dysphagia is rapidly increasing due to the ageing of the population. Therefore, the importance of objectively assessing swallowing function has received increasing attention. Videofluoroscopy and videoendoscopy are the standard clinical examinations for dysphagia, but these techniques are not suitable for daily use because of their invasiveness. Here, we aimed to develop a novel, non-invasive method for measuring swallowing function using a motion tracking system, the Kinect v2 sensor. Five males and five females with normal swallowing function participated in this study. We defined three mouth-related parameters and two larynx-related parameters and recorded data from 2.5 seconds before to 2.5 seconds after swallowing onset. Changes in mouth-related parameters were observed before swallowing and reached peak values at the time of swallowing. In contrast, larynx-related parameters showed little change before swallowing and reached peak values immediately after swallowing. This simple swallow tracking system (SSTS) successfully quantified the swallowing process from the oral phase to the laryngeal phase. This SSTS is non-invasive, wireless, easy to set up, and simultaneously measures the dynamics of swallowing from the mouth to the larynx. We propose the SSTS for use as a novel and non-invasive swallowing assessment tool in the clinic.

Cortical neural excitations in rats in vivo with using a prototype of a wireless multi-channel microstimulation system.

Understanding neural responses to multi-site electrical stimuli would be of essential importance for developing cortical neural prostheses. In order to provide a tool for such studies in experimental animals, we recently constructed a prototype of a wireless multi-channel microstimulation system, consisting of a stimulator chip, wireless data/power transmitters and receivers, and microcomputers. The proper operations of the system in cortical neural excitations were examined in anesthetized rats in vivo, with utilizing the voltage-sensitive dye imaging technique.

A multichannel current stimulator chip for spatiotemporal pattern stimulation of neural tissues.

We developed a prototype very-large-scale integration chip of a multichannel current stimulator for stimulating neural tissues by utilizing 0.25 µm high-voltage complementary metal-oxide-semiconductor technology. Our designed chip has 20 output channels that are driven by five current buffers arranged in parallel; each buffer controls four output channels in time-sharing mode. The amplitude of a stimulation pulse can be controlled within a range of approximately ±100 µA/phase in each output channel. The stimulus parameters, e.g., amplitude and duration, are controlled separately for each channel by digital codes stored in built-in registers. Combinations of anode and cathode electrodes to pass the current can be changed online. We integrated our stimulator chip with a multielectrode array and studied the neuronal responses to multichannel current stimulations with various temporal patterns in mouse brain slices.

Wide-dynamic-range APS-based silicon retina with brightness constancy.

A silicon retina is an intelligent vision sensor that can execute real-time image preprocessing by using a parallel analog circuit that mimics the structure of the neuronal circuits in the vertebrate retina. For enhancing the sensor's robustness to changes in illumination in a practical environment, we have designed and fabricated a silicon retina on the basis of a computational model of brightness constancy. The chip has a wide-dynamic-range and shows a constant response against changes in the illumination intensity. The photosensor in the present chip approximates logarithmic illumination-to-voltage transfer characteristics as a result of the application of a time-modulated reset voltage technique. Two types of image processing, namely, Laplacian-Gaussian-like spatial filtering and computing the frame difference, are carried out by using resistive networks and sample/hold circuits in the chip. As a result of these processings, the chip exhibits brightness constancy over a wide range of illumination. The chip is fabricated by using the 0.25- µm complementary metal-oxide semiconductor image sensor technology. The number of pixels is 64 × 64, and the power consumption is 32 mW at the frame rate of 30 fps. We show that our chip not only has a wide-dynamic-range but also shows a constant response to the changes in illumination.

An analog silicon retina with multichip configuration.

The neuromorphic silicon retina is a novel analog very large scale integrated circuit that emulates the structure and the function of the retinal neuronal circuit. We fabricated a neuromorphic silicon retina, in which sample/hold circuits were embedded to generate fluctuation-suppressed outputs in the previous study [1]. The applications of this silicon retina, however, are limited because of a low spatial resolution and computational variability. In this paper, we have fabricated a multichip silicon retina in which the functional network circuits are divided into two chips: the photoreceptor network chip (P chip) and the horizontal cell network chip (H chip). The output images of the P chip are transferred to the H chip with analog voltages through the line-parallel transfer bus. The sample/hold circuits embedded in the P and H chips compensate for the pattern noise generated on the circuits, including the analog communication pathway. Using the multichip silicon retina together with an off-chip differential amplifier, spatial filtering of the image with an odd- and an even-symmetric orientation selective receptive fields was carried out in real time. The analog data transfer method in the present multichip silicon retina is useful to design analog neuromorphic multichip systems that mimic the hierarchical structure of neuronal networks in the visual system.