A multi-modal neural interface capable of long-term recording and stimulation is essential for advancing brain monitoring and developing targeted therapeutics. Among traditional electrophysiological methods, micro-electrocorticography (μECoG) is appealing for chronic applications because it provides a good compromise between invasiveness and high-resolution neural recording. When combining μECoG with optical technologies, such as calcium imaging and optogenetics, this multi-modal approach enables simultaneous recording of neural activity from individual neurons and the ability to perform cell-specific manipulation. While previous efforts have focused on multi-modal interfaces for small animal models, scaling these technologies to larger primate brains remains challenging. In this paper, we present a multi-modal neural interface, named Smart Dura, a functional version of the commonly used artificial dura with integrated recording and stimulation electrodes for large cortical area coverage of the NHP brain. The Smart Dura is fabricated using a thin-film microfabrication process to monolithically integrate a micron-scale electrode array into a soft, flexible, and transparent substrate with high-density electrodes (up to 256 electrodes) while providing matched mechanical compliance with the native tissue and achieving high optical transparency (exceeding 98%). Our in vivo experiments demonstrate electrophysiological recording capabilities combined with neuromodulation, as well as optical transparency that enables structural and functional imaging. This work paves the way toward a chronic neural interface that can provide large-scale, bidirectional interfacing for multi-modal and closed-loop neuromodulation capabilities to study cortical brain activity in non-human primates, with the potential for translation to humans.

Objective. This paper discusses a novel method for automating the curation of neural spike events detected from neural recordings using spike sorting methods. Spike sorting seeks to identify isolated neural events from extracellular recordings. This is critical for interpretation of electrophysiology recordings in neuroscience studies. Spike sorting analysis is vulnerable to errors because of non-neural events, such as experimental artifacts or electrical interference. To improve the specificity of spike sorting results, a manual postprocessing curation is typically used to examine the detected events and identify neural spikes based on their specific features. However, this manual curation process is subjective, prone to human errors and not scalable, especially for large datasets.Approach. To address these challenges, we introduce AECuration, a novel automatic curation method based on an autoencoder model trained on features of simulated extracellular spike waveforms. Using reconstruction error as a performance metric, our method classifies neural and non-neural events in experimental electrophysiology datasets.Main results. This paper demonstrates that AECuration can classify neural events with 97.46% accuracy on synthetic datasets. Moreover, our method can improve the sensitivity of different spike sorting pipelines on datasets with ground-truth recordings by up to 20%. The ratio of clustered units with low interspike interval violation rates is improved from 55.3% to 85.5% as demonstrated using our in-house experimental dataset.Significance. AEcuration is a time-domain evaluation method that automates the analysis of extracellular recordings based on learned time-domain features. Once trained on a synthetic dataset, this method can be applied to real extracellular datasets without the need for re-training. This highlights the generalizability of AECuration. It can be readily integrated with existing spike sorting pipelines as a preprocessing filtering or a postprocessing curation step to improve the overall accuracy and efficiency.

Multimodal neural interfaces that integrate electrical and optical functionalities are promising tools for neuroscientific and clinical applications that involve recording and manipulating neuronal activity. However, most technologies for multimodal implementation are largely restricted to small animal models and lack the ability to translate to the larger brains of non-human primates (NHPs). Smart Dura, a recently developed large-scale neural interface for NHPs, enables high-density electrophysiological recordings and broad optical accessibility, providing multiscale information with enhanced spatiotemporal resolution. In this paper, the multimodal capabilities of Smart Dura are demonstrated through integration with multiphoton imaging, optical coherence tomography angiography (OCTA), and intrinsic signal optical imaging (ISOI), as well as optical manipulations such as photothrombotic lesioning and optogenetics. Through the transparent Smart Dura, in vivo fluorescence vascular imaging is achieved down to depths of 200 and 550 μm using two-photon and three-photon microscopy, respectively. When combined with simultaneous electrophysiology, Smart Dura also enables assessment of vascular and neural dynamics via OCTA and ISOI, the induction of ischemic stroke, and the application of optogenetic neuromodulation across a wide cortical area of 20 mm in diameter. These capabilities support comprehensive investigations of brain dynamics in NHPs, advancing translational neurotechnology for human applications.

Optical imaging is the gold standard for visualizing the structure and function of biological tissue. Non-invasive imaging methods can only reach a limited depth while providing a high spatial resolution. On the other hand, implantable imagers that can access deep tissue are prohibitively large and invasive. Here, we present the Microimager, a flexible, miniaturized thin-film endoscope (7 × 400 μm) featuring multiple independent channels for high-resolution light delivery and collection from deep tissue. The Microimager consists of an array of parylene photonic waveguides implemented using a scalable microfabrication process. We experimentally demonstrate spatial discrimination and imaging of 30 µm features on a resolution mask, as well as distinct regions in mouse brain tissue. The Microimager is a useful addition to the optical biomedical imaging toolset and can provide access to deep tissue in a minimally invasive way for a wide range of applications.

Targeted delivery of neurochemicals and biomolecules for neuromodulation of brain activity is a powerful technique that, in addition to electrical recording and stimulation, enables a more thorough investigation of neural circuit dynamics. We have designed a novel, flexible, implantable neural probe capable of controlled, localized chemical stimulation and electrophysiology recording. The neural probe was implemented using planar micromachining processes on Parylene C, a mechanically flexible, biocompatible substrate. The probe shank features two large microelectrodes (chemical sites) for drug loading and sixteen small microelectrodes for electrophysiology recording to monitor neuronal response to drug release. To reduce the impedance while keeping the size of the microelectrodes small, poly(3,4-ethylenedioxythiophene) (PEDOT) was electrochemically coated on recording microelectrodes. In addition, PEDOT doped with mesoporous sulfonated silica nanoparticles (SNPs) was used on chemical sites to achieve controlled, electrically-actuated drug loading and releasing. Different neurotransmitters, including glutamate (Glu) and gamma-aminobutyric acid (GABA), were incorporated into the SNPs and electrically triggered to release repeatedly. An in vitro experiment was conducted to quantify the stimulated release profile by applying a sinusoidal voltage (0.5 V, 2 Hz). The flexible neural probe was implanted in the barrel cortex of the wild-type Sprague Dawley rats. As expected, due to their excitatory and inhibitory effects, Glu and GABA release caused a significant increase and decrease in neural activity, respectively, which was recorded by the recording microelectrodes. This novel flexible neural probe technology, combining on-demand chemical release and high-resolution electrophysiology recording, is an important addition to the neuroscience toolset used to dissect neural circuitry and investigate neural network connectivity.

Optical coherence tomography (OCT) can provide label-free cross-sectional imaging of tissue microstructure over 2-3 mm of depth with micron-scale resolution. While phase-based functional extensions including angiography and polarization-sensitive OCT greatly expand the utility of OCT, the fixed lenses typically used to focus light into a sample couples the lateral resolution with the depth of focus. Ultrasonically-sculpted virtual optical waveguides provides an alternative for the terminal focusing element in an OCT sample arm. Ultrasonic pressure applied to a medium modulates its refractive index and can be used to create a refractive index gradient similar to that in a GRIN lens. We have recently demonstrated that a cylindrical ultrasound transducer can be used in the sample arm of a spectral-domain OCT system.1 We present demonstration that an ultrasound-based virtual lens can provide sufficient phase-stability for flow imaging, and that near-beam waist lateral resolution can be maintained over an extended depth range.

A novel graphene integrated electro-optic nanophotonic sensor capable of encoding sub-mV neural signal into optical domain is demonstrated. Wavelength division multiplexing of such highly sensitive sensors can enable massive parallelization of neural recording.

We present a novel NEMS Optomechanic modulator on a silicon photonics platform capable of resolving sub-millivolt analog signals, making it suitable for the recording and multiplexing of electrophysiological neural signals.

Recent advances in manufacturing technology and new material processes have enabled novel device designs. As the growing field of robotic tactile sensing calls for advanced tactile sensors, waveguide-based tactile sensors have shown promising mechanisms but system-level integrated solutions are needed to demonstrate their feasibility for sensor applications. In this work, a novel ultra-compact high-resolution tactile sensor based on asymmetric Mach-Zehnder interferometers (MZI) is proposed: PITS (Photonic Integrated Tactile Sensor). It is made from Parylene C waveguides using the Parylene photonic material platform. The sensor is composed of a 4 x 4 array of MZI sensing units and demonstrates multipoint contact sensing as well as shape detection with high sensitivity and low inter-unit crosstalk. The sensing unit is based on multimode interference mechanism explored with supplementary mechanical and optical simulation models. It demonstrates a 0.08 N dynamic range with <0.01 N force resolution, 7.59 signal-to-noise ratio and an average hysteresis of 7.7% over 10 repeated indents. The sensor is fabricated in two layers: a Parylene photonic layer and an align-bonded polydimethylsiloxane (PDMS) micropillar layer on top, which actuates the sensing units. This architecture features a design and fabrication pipeline that allows customizable sensitivity and dynamic range as well as scalable array designs.

Invasive deep-brain stimulation is increasingly being investigated as a treatment for neural disorders. A non-invasive alternative for deep-brain neuromodulation would likely broaden the range of application. However, existing techniques, such as transcranial electrical or magnetic stimulation (TES, TMS), are limited in their depth of stimulation. In this work, we propose DeepFocus, a new minimally invasive approach for stimulation of the deep brain by inserting electrodes in nasal cavities in conjunction with conventional scalp electrodes. As an initial step, an ex vivo model was designed to quantify the current efficiency of the proposed electrode placement in eliciting neural responses. A simplified geometric configuration was employed, where two linear electrode arrays arranged perpendicularly were used to elicit local field potentials (LFP) in mouse brain slices. Through a combination of finite element simulations to model the electric fields, and LFP measurements, we observed that electrode-patterns that use both arrays (modeling transnasal and scalp electrodes) generated higher electric fields and required less current to evoke responses compared to those that use only a single array (modeling scalp-only or transnasal-only). The benefits of two-array stimulation increased as the distance between the electrodes and the brain slice was increased. In addition, we observed that the relative orientation of the electric field compared to the cortical columns affected the neural responses.

Conventional optical lenses are usually used in OCT systems to perform high lateral resolution imaging. However, the Gaussian beam profile typically used in OCT links the depth of focus (DOF) to the lateral resolution. We have experimentally shown that using a cascade system of an ultrasonic virtual tunable optical waveguide (UVTOW) and a short focal-length lens can provide a large DOF without severely compromising the lateral resolution compared to an external lens with the same effective focal length. We demonstrate the tunability of the focal length that this system offers without any need for mechanical perturbation to the imaging setup.

We demonstrate novel trapezoidal and rectangular stratified trench optical waveguide designs that feature low-loss two-dimensional confinement of guided optical modes that can be realized in continuous polymer thin film layers formed in a trench mold. The design is based on geometrical bends in a thin film core to enable two-dimensional confinement of light in the transverse plane, without any variation in the core thickness. Incidentally, the waveguide design would completely obviate the need for etching the waveguide core, avoiding the scattering loss due to the etched sidewall roughness. This new design exhibits an intrinsic leakage loss due to coupling of light out of the trench, which can be minimized by choosing an appropriate waveguide geometry. Finite-difference eigenmode simulation demonstrates a low intrinsic leakage loss of less than 0.15 dB/cm. We discuss the principle of operation of these stratified trench waveguides and present the design and numerical simulations of a specific realization of this waveguide geometry. The design considerations and tradeoffs in propagation loss and confinement compared with traditional ridge waveguides are discussed.

The local field potential (LFP) is an extracellular electrophysiology signal corresponding to the local activity of neurons and is commonly used in neuroscience to characterize local oscillatory networks of cortical activity. Here, we use the LFP as a measure of the neuronal response evoked by transcranial pulsed stimulation. Traditionally, LFP correlation analysis is used to measure synchronization between brain regions but is unable to capture nonlinear relationships. We propose a mutual information matrix analysis tool to study the nonlinear interactions between the LFPs from different neuron groups and characterize the effect of electrical stimulation on LFPs. The mutual information matrix has many similar properties to the correlation matrix. However, it captures additional nonlinear relationships between the variables. This makes it a complement to the correlation matrix for highly nonlinear neural activity. The mutual information matrix analysis is extended to time-varying signals to capture the nonstationarity of neural activity. As a proof of concept, the analysis is applied to in vivo rodent electrophysiology data, showing that the mutual information matrix is stable during spontaneous activity $(d(M^{0},\ M^{t}) < 2.5)$ and can capture time-varying effects of stimulation, i.e., increased synchronization $(d(M^{0},\ M^{t}\overline{)} > 14.0)$ in the gamma frequency range lasting for about 800 ms after electrical stimulation. This time-varying mutual information analysis has the potential to complement the traditional correlation matrix analysis for neural activity.

We introduce a light steering technology that operates at megahertz frequencies, has no moving parts, and costs less than a hundred dollars. Our technology can benefit many projector and imaging systems that critically rely on high-speed, reliable, low-cost, and wavelength-independent light steering, including laser scanning projectors, LiDAR sensors, and fluorescence microscopes. Our technology uses ultrasound waves to generate a spatiotemporally-varying refractive index field inside a compressible medium, such as water, turning the medium into a dynamic traveling lens. By controlling the electrical input of the ultrasound transducers that generate the waves, we can change the lens, and thus steer light, at the speed of sound (1.5 km/s in water). We build a physical prototype of this technology, use it to realize different scanning techniques at megahertz rates (three orders of magnitude faster than commercial alternatives such as galvo mirror scanners), and demonstrate proof-of-concept projector and LiDAR applications. To encourage further innovation towards this new technology, we derive theory for its fundamental limits and develop a physically-accurate simulator for virtual design. Our technology offers a promising solution for achieving high-speed and low-cost light steering in a variety of applications.

The effect of electrical stimulation on neurons depends on the spatiotemporal properties of the applied electric field as well as on the biophysical properties of the neural tissue, which includes geometric and electrical characteristics of the cells, and the neural circuit dynamics. In this work, we characterize the effect of electric field direction on neural response in cortical layers. This can, for instance, enable more efficient (e.g., with reduced currents) and/or more selective stimulation. We stimulated mice brain slices using a recently developed brain slice platform to study transcranial currents in an ex-vivo model, where electrodes are separated from the brain slice to inject electric fields at a distance. By rotating the electrode array with respect to the slice, we changed the direction of electric field with respect to the cortical column. Our results demonstrate that in somatosensory cortex, the maximum local field potential (LFP) response is attained when the electric field is oriented parallel to the cortical column. For the same field intensity, when the field is oriented perpendicular to the cortical column, the LFP response is absent. This confirms that electric field direction is an important quantity to determine the effect of neuronal stimulation.

Electrical interference from various sources is a common issue for experimental extracellular electrophysiology recordings collected using multi-electrode array neural recording systems. This interference deteriorates the signal-to-noise ratio (SNR) of the raw electrophysiology signals and hampers the accuracy of data post-processing using techniques such as spike-sorting. Traditional signal processing methods to digitally remove electrical interference during post-processing include bandpass filtering to limit the signal to the relevant spectral range of the biological data, e.g., the spikes band (300 Hz - 7 kHz), targeted notch filtering to remove power line interference from standard alternating current mains electricity and common reference removal to minimize noise common to all electrodes. These methods require a priori knowledge of the frequency of the interfering signal source to address the unique electromagnetic interference environment of each experimental setup. We discuss an adaptive method for automatically removing narrow-band electrical interference through a spectral peak detection and removal (SPDR) step that can be applied during post-processing of the recorded data, based on the intuition that tall, narrowband signals localized in the signal spectrum correspond to interference, rather than the activity of neurons. A spectral peak prominence (SPP) threshold is used to detect these peaks in the frequency domain, which will then be removed via notch filtering. We applied this method to simulated waveforms and also experimental electrophysiology data collected from cerebral organoids to demonstrate its effectiveness for removing unwanted interference without significantly distorting the neural signals. We discuss that proper selection of the SPP threshold is required to avoid over-filtering, which can result in distortion of the electrophysiology data. We also compare the firing-rate activity in the filtered electrophysiology with fluorescence calcium imaging, a secondary cellular activity marker, to quantify signal distortion and provide bounds on SNR-based optimization of the SPP threshold. The adaptive filtering technique demonstrated in this paper is a powerful method that can automatically detect and remove interband interference in recorded neural signals, potentially enabling data collection in more naturalistic settings where external interference signals are difficult to eliminate.

Chronic interfacing with the brain to record and stimulate neural activity with high spatiotemporal resolution is highly desirable to advance the understanding of neural circuits and design of novel therapeutics. Traditional neural interfaces mainly rely on electrical recording and stimulation, which have inherent limitations such as lack of specificity and a large volume of tissue activation. With the advent of optogenetics, hybrid opto-electrical platforms have emerged as new bidirectional interfaces. In this paper, we introduce our groundwork towards the Smart Dura, a novel device that will ultimately integrate high density recording electrodes and light sources in the form of a chronic implant that can cover large cortical areas in the primate brain (300 mm 2 ) for adaptive recording and stimulation of neural activity in a closed loop. Smart Dura has two main components, the electrical dura for recording and the optical dura for optogenetic stimulation. As the first step to implement this platform, we have implemented the electrical dura as a high density, transparent and flexible $\mu \text{ECoG}$ array, as well as the optical dura, which is a high-density LED array, independently. Both the electrical and optical dura are implemented in flexible polymer substrates that provide mechanical compliance with the brain tissue and can be integrated together in a vertical stack. Here we present the fabrication, bench top characterization and acute in vivo validation of both the electrical and optical dura. This work paves the way towards the ultimate Smart Dura, a functional device that can replace the native dura as a chronic, large-scale bidirectional interface to study cortical brain activity in non-human primates (NHPs), with the potential for translation to humans.

Deciphering the function of neural circuits can help with the understanding of brain function and treating neurological disorders. Progress toward this goal relies on the development of chronically stable neural interfaces capable of recording and modulating neural circuits with high spatial and temporal precision across large areas of the brain. Advanced innovations in designing high-density neural interfaces for small animal models have enabled breakthrough discoveries in neuroscience research. Developing similar neurotechnology for larger animal models such as nonhuman primates (NHPs) is critical to gain significant insights for translation to humans, yet still it remains elusive due to the challenges in design, fabrication, and system-level integration of such devices. This review focuses on implantable surface neural interfaces with electrical and optical functionalities with emphasis on the required technological features to realize scalable multimodal and chronically stable implants to address the unique challenges associated with nonhuman primate studies.

Ultrasonically-sculpted gradient-index optical waveguides enable non-invasive light confinement inside scattering media. The confinement level strongly depends on ultrasound parameters (e.g., amplitude, frequency), and medium optical properties (e.g., extinction coefficient). We develop a physically-accurate simulator, and use it to quantify these dependencies for a radially-symmetric virtual optical waveguide. Our analysis provides insights for optimizing virtual optical waveguides for given applications. We leverage these insights to configure virtual optical waveguides that improve light confinement fourfold compared to previous configurations at five mean free paths. We show that virtual optical waveguides enhance light throughput by 50% compared to an ideal external lens, in a medium with bladder-like optical properties at one transport mean free path. We corroborate these simulation findings with real experiments: we demonstrate, for the first time, that virtual optical waveguides recycle scattered light, and enhance light throughput by 15% compared to an external lens at five transport mean free paths.