Cochlear implants are neuroprosthetic devices that restore hearing and speech comprehension to profoundly deaf humans and represent an exemplar application of biomedical engineering and research to clinical conditions. However, the utility of these devices in many subjects is limited, largely due to lack of information about how neural circuits respond to implant stimulation. Recently we showed that deafened rats can use cochlear implants to recognize sounds, and that this training refined the responses of single neurons in the primary auditory cortex. Here we asked how local populations of cortical neurons represent acute implant stimuli, using electrode arrays we developed for cortical surface recordings for micro-electrocorticography (µECoG), a form of intracranial electroencephalography (iEEG). We found that there was a coarse, non-random spatial organization with limited evidence for consistent, sharply graded cochleotopy across recording sites, relative to a clearer tonotopic spatial representation in normal-hearing rats. Single-trial iEEG responses to acoustic inputs were more reliable than responses to cochlear implant stimulation, although stimulus identity could be successfully decoded in both cases. However, the spatio-temporal response profiles to acoustic vs cochlear implant stimulation were substantially different. Decoders trained on acoustic responses showed essentially zero information transfer when tested on electrical stimulation responses in the same animals after deafening and cochlear implant stimulation. Thus, while acute cochlear implant stimulation evoked spatially non-random cortical activity with coarse cochleotopic structure, the dynamics of network activity were substantially different from those evoked by acoustic stimulation, with possible implications for perceptual similarity that remain to be tested.

Spreading depolarizations (SDs) are widely recognized as a major contributor to the progression of tissue damage from ischemic stroke even if blood flow can be restored. They are characterized by negative intracortical waveforms of up to -20 mV, propagation velocities of 3 - 6 mm/min, and massive disturbance of membrane ion homeostasis. High-density, micro-electrocorticographic (μECoG) epidural electrodes and custom, DC-coupled, multiplexed amplifiers, were used to continuously characterize and monitor SD and µECoG cortical signal evolution in awake, moving rats over days. This highly innovative approach can define these events over a large brain surface area (~ 3.4 × 3.4 mm), extending across the boundaries of the stroke, and offers sufficient electrode density (60 contacts total per array for a density of 5.7 electrodes / mm 2 ) to measure and determine the origin of SDs in relation to the infarct boundaries. In addition, spontaneous ECoG activity can simultaneously be detected to further define cortical infarct regions. This technology allows us to understand dynamic stroke evolution and provides immediate cortical functional activity over days. Further translational development of this approach may facilitate improved treatment options for acute stroke patients.

Patients suffering from debilitating neurodegenerative diseases often lose the ability to communicate, detrimentally affecting their quality of life. One solution to restore communication is to decode signals directly from the brain to enable neural speech prostheses. However, decoding has been limited by coarse neural recordings which inadequately capture the rich spatio-temporal structure of human brain signals. To resolve this limitation, we performed high-resolution, micro-electrocorticographic (µECoG) neural recordings during intra-operative speech production. We obtained neural signals with 57× higher spatial resolution and 48% higher signal-to-noise ratio compared to macro-ECoG and SEEG. This increased signal quality improved decoding by 35% compared to standard intracranial signals. Accurate decoding was dependent on the high-spatial resolution of the neural interface. Non-linear decoding models designed to utilize enhanced spatio-temporal neural information produced better results than linear techniques. We show that high-density µECoG can enable high-quality speech decoding for future neural speech prostheses.

OBJECTIVE:Effective surgical treatment of drug-resistant epilepsy depends on accurate localization of the epileptogenic zone (EZ). High-frequency oscillations (HFOs) are potential biomarkers of the EZ. Previous research has shown that HFOs often occur within submillimeter areas of brain tissue and that the coarse spatial sampling of clinical intracranial electrode arrays may limit the accurate capture of HFO activity. In this study, we sought to characterize microscale HFO activity captured on thin, flexible microelectrocorticographic (μECoG) arrays, which provide high spatial resolution over large cortical surface areas.METHODS:We used novel liquid crystal polymer thin-film μECoG arrays (.76-1.72-mm intercontact spacing) to capture HFOs in eight intraoperative recordings from seven patients with epilepsy. We identified ripple (80-250 Hz) and fast ripple (250-600 Hz) HFOs using a common energy thresholding detection algorithm along with two stages of artifact rejection. We visualized microscale subregions of HFO activity using spatial maps of HFO rate, signal-to-noise ratio, and mean peak frequency. We quantified the spatial extent of HFO events by measuring covariance between detected HFOs and surrounding activity. We also compared HFO detection rates on microcontacts to simulated macrocontacts by spatially averaging data.RESULTS:We found visually delineable subregions of elevated HFO activity within each μECoG recording. Forty-seven percent of HFOs occurred on single 200-μm-diameter recording contacts, with minimal high-frequency activity on surrounding contacts. Other HFO events occurred across multiple contacts simultaneously, with covarying activity most often limited to a .95-mm radius. Through spatial averaging, we estimated that macrocontacts with 2-3-mm diameter would only capture 44% of the HFOs detected in our μECoG recordings.SIGNIFICANCE:These results demonstrate that thin-film microcontact surface arrays with both highresolution and large coverage accurately capture microscale HFO activity and may improve the utility of HFOs to localize the EZ for treatment of drug-resistant epilepsy.

Techniques to study brain activities have evolved dramatically, yet tremendous challenges remain in acquiring high-throughput electrophysiological recordings minimally invasively. Here, we develop an integrated neuroelectronic array that is filamentary, high-density and flexible. Specifically, with a design of single-transistor multiplexing and current sensing, the total 256 neuroelectrodes achieve only a 2.3 × 0.3 mm2 area, unprecedentedly on a flexible substrate. A single-transistor multiplexing acquisition circuit further reduces noise from the electrodes, decreases the footprint of each pixel, and potentially increases the device’s lifetime. The filamentary neuroelectronic array also integrates with a rollable contact pad design, allowing the device to be injected through a syringe, enabling potential minimally invasive array delivery. Successful acute auditory experiments in rats validate the ability of the array to record neural signals with high tone decoding accuracy. Together, these results establish soft, high-density neuroelectronic arrays as promising devices for neuroscience research and clinical applications.

Simultaneous interrogation of electrical signals from wide areas of the brain is vital for neuroscience research and can aid in understanding the mechanisms of brain function and treatments for neurological disorders. There emerges a demand for development of devices with highly conformal interfaces that can span large cortical regions, have sufficient spatial resolution, and chronic recording capability while keeping a small implantation footprint. In this work, we have designed 61 channel and 48 channel high-density, cortical, micro-electrocorticographic electrode arrays with 400 µm pitch on an ultra-soft but durable substrate. We have also developed a custom multiplexing integrated circuit (IC), methods for packaging the IC in a water-tight liquid crystal polymer casing, and a micro-bonding method for attaching the electronics package to the electrode array. With the integrated multiplexer, the number of external wire connections can be reduced to 16 wires, thereby diminishing the invasive footprint of the device. Both the electrode array and IC were tested in vivo in a rat model to demonstrate the ability to sense finely-localized electrophysiological signals.

One-third of epilepsy patients suffer from medication-resistant seizures. While surgery to remove epileptogenic tissue helps some patients, 30-70% of patients continue to experience seizures following resection. Surgical outcomes may be improved with more accurate localization of epileptogenic tissue. We have previously developed novel thin-film, subdural electrode arrays with hundreds of microelectrodes over a 100-1,000 mm2 area to enable high-resolution mapping of neural activity. Here we used these high-density arrays to study microscale properties of human epileptiform activity. We performed intraoperative micro-electrocorticographic recordings within epileptic cortex (the site of seizure onset and early spread) in nine patients with epilepsy. In two of these patients, we obtained recordings from cortical areas distal to the epileptic cortex. Additionally, we recorded from two non-epileptic patients with movement disorders undergoing deep brain stimulator implantation as non-epileptic tissue controls. A board-certified epileptologist identified microseizures, which resembled electrographic seizures normally observed with clinical macroelectrodes. Epileptic cortex exhibited a significantly higher microseizure rate (2.01 events/min) than non-epileptic cortex (0.01 events/min; permutation test, P=0.0068). Using spatial averaging to simulate recordings from larger electrode contacts, we found that the number of detected microseizures decreased rapidly with increasing contact diameter and decreasing contact density. In cases in which microseizures were spatially distributed across multiple channels, the approximate onset region was identified. Our results suggest that micro-electrocorticographic electrode arrays with a high density of contacts and large coverage are essential for capturing microseizures in epilepsy patients and may be beneficial for localizing epileptogenic tissue to plan surgery or target brain stimulation.

Objective. Brain functions such as perception, motor control, learning, and memory arise from the coordinated activity of neuronal assemblies distributed across multiple brain regions. While major progress has been made in understanding the function of individual neurons, circuit interactions remain poorly understood. A fundamental obstacle to deciphering circuit interactions is the limited availability of research tools to observe and manipulate the activity of large, distributed neuronal populations in humans. Here we describe the development, validation, and dissemination of flexible, high-resolution, thin-film (TF) electrodes for recording neural activity in animals and humans. Approach. We leveraged standard flexible printed-circuit manufacturing processes to build high-resolution TF electrode arrays. We used biocompatible materials to form the substrate (liquid crystal polymer; LCP), metals (Au, PtIr, and Pd), molding (medical-grade silicone), and 3D-printed housing (nylon). We designed a custom, miniaturized, digitizing headstage to reduce the number of cables required to connect to the acquisition system and reduce the distance between the electrodes and the amplifiers. A custom mechanical system enabled the electrodes and headstages to be pre-assembled prior to sterilization, minimizing the setup time required in the operating room. PtIr electrode coatings lowered impedance and enabled stimulation. High-volume, commercial manufacturing enables cost-effective production of LCP-TF electrodes in large quantities. Main Results. Our LCP-TF arrays achieve 25× higher electrode density, 20× higher channel count, and 11× reduced stiffness than conventional clinical electrodes. We validated our LCP-TF electrodes in multiple human intraoperative recording sessions and have disseminated this technology to >10 research groups. Using these arrays, we have observed high-frequency neural activity with sub-millimeter resolution. Significance. Our LCP-TF electrodes will advance human neuroscience research and improve clinical care by enabling broad access to transformative, high-resolution electrode arrays.

Objective. Large channel count surface-based electrophysiology arrays (e.g. µECoG) are high-throughput neural interfaces with good chronic stability. Electrode spacing remains ad hoc due to redundancy and nonstationarity of field dynamics. Here, we establish a criterion for electrode spacing based on the expected accuracy of predicting unsampled field potential from sampled sites.Approach. We applied spatial covariance modeling and field prediction techniques based on geospatial kriging to quantify sufficient sampling for thousands of 500 ms µECoG snapshots in human, monkey, and rat. We calculated a probably approximately correct (PAC) spacing based on kriging that would be required to predict µECoG fields at≤10% error for most cases (95% of observations).Main results. Kriging theory accurately explained the competing effects of electrode density and noise on predicting field potential. Across five frequency bands from 4-7 to 75-300 Hz, PAC spacing was sub-millimeter for auditory cortex in anesthetized and awake rats, and posterior superior temporal gyrus in anesthetized human. At 75-300 Hz, sub-millimeter PAC spacing was required in all species and cortical areas.Significance. PAC spacing accounted for the effect of signal-to-noise on prediction quality and was sensitive to the full distribution of non-stationary covariance states. Our results show that µECoG arrays should sample at sub-millimeter resolution for applications in diverse cortical areas and for noise resilience.

This paper considers the problem of neural decoding from parallel neural measurements systems such as micro-electrocorticography ($\mu$-ECoG). In systems with large numbers of array elements at very high sampling rates, the dimension of the raw measurement data may be large. Learning neural decoders for this high-dimensional data can be challenging, particularly when the number of training samples is limited. To address this challenge, this work presents a novel neural network decoder with a low-rank structure in the first hidden layer. The low-rank constraints dramatically reduce the number of parameters in the decoder while still enabling a rich class of nonlinear decoder maps. The low-rank decoder is illustrated on $\mu$-ECoG data from the primary auditory cortex (A1) of awake rats. This decoding problem is particularly challenging due to the complexity of neural responses in the auditory cortex and the presence of confounding signals in awake animals. It is shown that the proposed low-rank decoder significantly outperforms models using standard dimensionality reduction techniques such as principal component analysis (PCA).

Long-lasting, high-resolution neural interfaces that are ultrathin and flexible are essential for precise brain mapping and high-performance neuroprosthetic systems. Scaling to sample thousands of sites across large brain regions requires integrating powered electronics to multiplex many electrodes to a few external wires. However, existing multiplexed electrode arrays rely on encapsulation strategies that have limited implant lifetimes. Here, we developed a flexible, multiplexed electrode array, called "Neural Matrix," that provides stable in vivo neural recordings in rodents and nonhuman primates. Neural Matrix lasts over a year and samples a centimeter-scale brain region using over a thousand channels. The long-lasting encapsulation (projected to last at least 6 years), scalable device design, and iterative in vivo optimization described here are essential components to overcoming current hurdles facing next-generation neural technologies.

Chronic studies of flexible μECoG electrodes and the electrode-brain interface have been limited by the inability to assess tissue response over time. The electrophysiological system presented here combines epidural microelectrocorticographic (μECoG) recording capabilities with the ability to visualize tissue response over time through light microscopy and optical coherence tomography (OCT). With the ability to interchange both the electrode and the electronics, and a flushing port for injection of flushing saline and/or drugs, this 3D printed system has future applications in chronic electrophysiology, optogenetics, and advanced imaging methods.

Objective. The clinical use of microsignals recorded over broad cortical regions is largely limited by the chronic reliability of the implanted interfaces. Approach. We evaluated the chronic reliability of novel 61-channel micro-electrocorticographic (µECoG) arrays in rats chronically implanted for over one year and using accelerated aging. Devices were encapsulated with polyimide (PI) or liquid crystal polymer (LCP), and fabricated using commercial manufacturing processes. In vitro failure modes and predicted lifetimes were determined from accelerated soak testing. Successful designs were implanted epidurally over the rodent auditory cortex. Trends in baseline signal level, evoked responses and decoding performance were reported for over one year of implantation. Main results. Devices fabricated with LCP consistently had longer in vitro lifetimes than PI encapsulation. Our accelerated aging results predicted device integrity beyond 3.4 years. Five implanted arrays showed stable performance over the entire implantation period (247–435 d). Our regression analysis showed that impedance predicted signal quality and information content only in the first 31 d of recordings and had little predictive value in the chronic phase (>31 d). In the chronic phase, site impedances slightly decreased yet decoding performance became statistically uncorrelated with impedance. We also employed an improved statistical model of spatial variation to measure sensitivity to locally varying fields, which is typically concealed in standard signal power calculations. Significance. These findings show that µECoG arrays can reliably perform in chronic applications in vivo for over one year, which facilitates the development of a high-density, clinically viable interface.

Micro-electrocorticography (µECoG) is a minimally invasive neural interface that allows for recording from the surface of the brain with high spatial and temporal resolution [1], [2]. However, discerning multi-unit and local field potential (LFP) activity with potentially highly-correlated signals across a dense µECoG array can be challenging. Here we describe a novel µECoG design to compare the effect of referencing recordings to a local reference electrode and common average referencing (CAR). The filtering effect and the significant increase in signal to noise ratio of the evoked response (ESNR) can be seen after re-referencing for both types of referencing. In a preliminary analysis, re-referencing the µECoG signals can increase recording performance at high contact densities in the auditory cortex. This also provides promising evidence for a versatile in-house fabricated µECoG electrode.

Objective. High channel count electrode arrays allow for the monitoring of large-scale neural activity at high spatial resolution. Implantable arrays featuring many recording sites require compact, high bandwidth front-end electronics. In the present study, we investigated the use of a small, light weight, and low cost digital current-sensing integrated circuit for acquiring cortical surface signals from a 61-channel micro-electrocorticographic (μECoG) array. Approach. We recorded both acute and chronic μECoG signal from rat auditory cortex using our novel digital current-sensing headstage. For direct comparison, separate recordings were made in the same anesthetized preparations using an analog voltage headstage. A model of electrode impedance explained the transformation between current- and voltage-sensed signals, and was used to reconstruct cortical potential. We evaluated the digital headstage using several metrics of the baseline and response signals. Main results. The digital current headstage recorded neural signal with similar spatiotemporal statistics and auditory frequency tuning compared to the voltage signal. The signal-to-noise ratio of auditory evoked responses (AERs) was significantly stronger in the current signal. Stimulus decoding based on true and reconstructed voltage signals were not significantly different. Recordings from an implanted system showed AERs that were detectable and decodable for 52 d. The reconstruction filter mitigated the thermal current noise of the electrode impedance and enhanced overall SNR. Significance. We developed and validated a novel approach to headstage acquisition that used current-input circuits to independently digitize 61 channels of μECoG measurements of the cortical field. These low-cost circuits, intended to measure photo-currents in digital imaging, not only provided a signal representing the local cortical field with virtually the same sensitivity and specificity as a traditional voltage headstage but also resulted in a small, light headstage that can easily be scaled to record from hundreds of channels.

Nature Biomedical Engineering 1, 0038 (2017); published 1 March 2017; corrected 9 March 2017. In the version of this Article originally published, the single-voltage trace in Fig. 3b did not display correctly. This has now been amended.

Bioresorbable silicon electronics technology offers unprecedented opportunities to deploy advanced implantable monitoring systems that eliminate risks, cost and discomfort associated with surgical extraction. Applications include postoperative monitoring and transient physiologic recording after percutaneous or minimally invasive placement of vascular, cardiac, orthopaedic, neural or other devices. We present an embodiment of these materials in both passive and actively addressed arrays of bioresorbable silicon electrodes with multiplexing capabilities, which record in vivo electrophysiological signals from the cortical surface and the subgaleal space. The devices detect normal physiologic and epileptiform activity, both in acute and chronic recordings. Comparative studies show sensor performance comparable to standard clinical systems and reduced tissue reactivity relative to conventional clinical electrocorticography (ECoG) electrodes. This technology offers general applicability in neural interfaces, with additional potential utility in treatment of disorders where transient monitoring and modulation of physiologic function, implant integrity and tissue recovery or regeneration are required.

OBJECTIVE:Micro-electrocorticography (μECoG) offers a minimally invasive neural interface with high spatial resolution over large areas of cortex. However, electrode arrays with many contacts that are individually wired to external recording systems are cumbersome and make recordings in freely behaving rodents challenging. We report a novel high-density 60-electrode system for μECoG recording in freely moving rats.APPROACH:Multiplexed headstages overcome the problem of wiring complexity by combining signals from many electrodes to a smaller number of connections. We have developed a low-cost, multiplexed recording system with 60 contacts at 406 μm spacing. We characterized the quality of the electrode signals using multiple metrics that tracked spatial variation, evoked-response detectability, and decoding value. Performance of the system was validated both in anesthetized animals and freely moving awake animals.MAIN RESULTS:We recorded μECoG signals over the primary auditory cortex, measuring responses to acoustic stimuli across all channels. Single-trial responses had high signal-to-noise ratios (SNR) (up to 25 dB under anesthesia), and were used to rapidly measure network topography within ∼10 s by constructing all single-channel receptive fields in parallel. We characterized evoked potential amplitudes and spatial correlations across the array in the anesthetized and awake animals. Recording quality in awake animals was stable for at least 30 days. Finally, we used these responses to accurately decode auditory stimuli on single trials.SIGNIFICANCE:This study introduces (1) a μECoG recording system based on practical hardware design and (2) a rigorous analytical method for characterizing the signal characteristics of μECoG electrode arrays. This methodology can be applied to evaluate the fidelity and lifetime of any μECoG electrode array. Our μECoG-based recording system is accessible and will be useful for studies of perception and decision-making in rodents, particularly over the entire time course of behavioral training and learning.

Micro-electrocorticographic (μECοG) electrode arrays provide a minimally invasive, high-resolution neural interface with broad cortical coverage. Previously, we fabricated μECoG arrays at a lower cost than commercially available devices using low-cost industrial processes [1], [2]. Here, we report the in vitro electrical performance of five μECoG designs undergoing an accelerated aging protocol. The impedance and yield of the μECoG arrays were tracked over time. The equivalent lifetime at 37°C depended on the manufacturer and material stack-up, and ranged between 30 and greater than 760 days (ongoing). The main failure modes of these devices were delamination at the site of the electrode contact and broken traces due to metal dissolution. Based on these in vitro results, we offer several recommendations for μECoG designs suitable for chronic implantation.