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Challenges in the Design of Large-Scale, High-Density, Wireless Stimulation and Recording Interface

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Challenges in the Design of Large-Scale, High-Density, Wireless Stimulation and Recording Interface Challenges in the Design of Large-Scale, High-Density, Wireless Stimulation and Recording Interface Po-Min Wang, Stanislav Culaclii, Kyung Jin Seo, Yushan Wang, Hui Fang, Yi-Kai Lo, and Wentai Liu 1 Introduction Neural stimulation and recording have been widely applied to fundamental research to better understand the nervous systems as well as to the clinical therapy of a variety of diseases. Well-known examples include monitoring and manipulating neural activities in the brain to map the brain function [1–3], spinal cord implant to restore the motor function after spinal cord injury [4–6], gastrointestinal (GI) implant to monitor and treat GI motility disorders [7–9], and retinal prostheses to regain eyesight in the blind [10–12]. These applications require continuous techno- logical advancement in designs of stimulation and recording electronics, electrodes, and the interconnections between the electronics and the electrodes. Despite technological advances to date, there are still challenges to overcome in applications requiring large-scale, high-density, wireless stimulation and recording. Concretely, the study of the brain function through monitoring and manipulating neural activities in freely moving and behaving subjects requires decoding the com- plex brain dynamics by mapping brain activity with both large-scale and high spa- tial resolution. This decoding demands a large-scale, high-density electrode array with small electrode size, which imposes significant challenges in electrode array fabrication as well as its interconnect with electronics. In addition, the capability to record high channel number implies the need for wireless electronics with high P.-M. Wang · S. Culaclii · Y. Wang · W. Liu (*) Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA e-mail: [email protected] K. J. Seo · H. Fang Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA Y.-K. Lo Niche Biomedical Inc., Los Angeles, CA, USA © Springer Nature Switzerland AG 2020 1 H. Cao et al. (eds.), Interfacing Bioelectronics and Biomedical Sensing, https://doi.org/10.1007/978-3-030-34467-2_1 2 P.-M. Wang et al. bandwidth. This need trades off with the low power consumption constraint set by the safety regulations of cortical implant. Furthermore, when a large-scale, high resolution neural interface is used to investigate the brain dynamics through simul- taneous electrical stimulation and recording, the recorded signal suffers from severe stimulation artifact. The artifact, which is generated when stimulation is applied, can be several times larger than the recorded neural activities, which results in fail- ure to detect neural response often by saturating the recording front-end. A record- ing scheme needs to integrate specific functions to cancel the stimulation artifact and thus capture the evoked neural response arising right after the stimulation. Furthermore, it is critical to achieve spatially precise stimulation. Performing selec- tive and focalized stimulation to specific neurons would greatly ameliorate the stimulation efficacy by avoiding the undesired spread of electrical charge. Overcoming these challenges is desperately needed to continue driving the technology toward large-scale, high-density wireless stimulation and recording interface. This chapter will review state of the art technologies that address the aforementioned design challenges. Section 2 presents the stimulation artifact can- cellation recording schemas. Section 3 discusses the focalized stimulation. Section 4 describes fabrication of the high-density electrode array. Section 5 focuses on specifics of the high-data-rate wireless link. Section 6 presents a large-scale, high- density, wireless stimulation and recording system that integrates the above components. 2 Cancellation of Artifacts During Simultaneous Neural Stimulation and Recording Next-generation neural interfaces, which investigate neural connectivity in diagnos- tics and research or enable implantable closed-loop therapy for neural diseases, will require the ability to simultaneously stimulate and record from the electrode arrays. But recording during stimulation incurs a challenge in the form of the stimulation artifact. The artifact signal is formed every time the stimulus is injected into the neural tissue; it also propagates to the recording electrode and contaminates the recording. The contamination can slightly distort the data if the artifact amplitude and duration are small compared to the neural signals recorded. The contamination can also completely confound the data of interest if the artifact is larger than the recording amplifier’s input compliance limits or if the artifact’s duration exceeds the timing and length of the neural response. The latter case is more likely in an ultrahigh- density neural interface where the stimulation electrode will be close to the recording electrodes due to shorter electrode-to-electrode pitch. The design of ultrahigh-density bidirectional neural interfaces thus must accommodate large stimulation artifacts while avoiding recording signal loss. Many methods are developed in commercial FDA-approved and research-grade devices to reduce or eliminate the negative effects of stimulation artifacts in neural Challenges in the Design of Large-Scale, High-Density, Wireless Stimulation… 3 recording. Most designs solve the artifact problem either in the circuit domain or in the digital post-processing domain. The latter removes the artifact distortion in neural recordings where the artifact is small and does not saturate the amplifier. The focus of the former, instead, is to preserve amplifier linearity at the recording electrode during large artifact events. 2.1 Stimulation Artifact Cancellation by Circuit Design Most common circuit design approaches employ amplifier blanking and signal filtering (Fig. 1a, b). The advantage of such designs is their simplicity, which allows a simple upgrade from a basic neural amplifier with insignificant additional area needed on the integrated circuit. A popular example of analog filtering for artifact cancellation is Medtronic’s Activa RC + S device [13]. The device is designed to Fig. 1 Methods for stimulation artifact cancellation: (a) high-frequency stimulation tones are well separated in frequency domain from neural signals, allowing stimulation artifact removal by ana- log and digital filters. (b) Blanking switch disconnects signal input to the recording amplifier to avoid signal saturation during stimulus artifact. (c) Subtraction of averaged artifact template is effective when stimulus artifact is of similar amplitude to neural signals, and they do not overlap in time. (d) A complete artifact-free system design combines circuit techniques to reduce artifact and prevent amplifier saturation and uses digital signal processing to remove residual artifacts and reveal an intact neural signal, effectively removing very large artifacts that may overlap with short-­ latency neural responses 4 P.-M. Wang et al. suppress stimulus artifacts specifically in high-frequency stimulation protocols, where low-frequency LFP signals are recorded. A high-order analog filter is used to separate the artifact from neural signals in the frequency domain (Fig. 1a). The filter by itself is not sufficient to suppress a very large artifact, so device users are recom- mended to constrain the electrode placements such that a bipolar stimulation is applied symmetrically at the opposite sides of the recording electrode. This allows the positive and negative stimulation artifacts to cancel in the middle at the record- ing site. The device is widely used for DBS in treatment of movement disorders with a low-channel-count depth electrode, but it is not suitable for high-density electrode arrays where a large number of recording sites are likely positioned non- symmetrically to the site of stimulation. Alternatively, amplifier blanking circuits can be used to reduce the effects of artifacts on the recording. It is often implemented as a switch that momentarily disconnects the amplifier from the recording electrode during the period of the stim- ulation and optionally resets the amplifiers output to a zero value as it is reconnected back shortly after the stimulation event passes (Fig. 1b). A commercially available neural amplifier design (Nano/Micro 2 + Stim by Ripple Neuro) employs blanking and recovers to normal recording at 1 ms post-stimulation. It avoids amplifier satu- ration and lengthy post-saturation recovery, but inherently does not record any sig- nal during blanking. It can thus miss short latency neural responses that can occur as early as 100 μs after the onset of the stimulation event [14] and end before the amplifier comes back online. In addition, blanking would omit neural responses during high frequency stimulation trains, such as during DBS [13], where the high repetition rate of the pulse train would force the amplifier to blank recording for the entire train. Other novel pure-circuit solutions use feedback with chopper amplifier tech- niques to increase the input dynamic range of the recording front-end and accom- modate an artifact with higher amplitude [15, 16]. However, they are insufficient in preventing saturation and signal loss with larger artifacts that can occur during recording near the stimulation site – a scenario likely to occur in high-density neural interface arrays with closely spaced electrodes. 2.2 Stimulation Artifact Cancellation by Digital Signal Processing
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