Publications – 2024

Optical neurotechnologies use light to interface with neurons and can monitor and manipulate neural activity with high spatial-temporal precision over large cortical areas. There has been considerable progress in miniaturizing microscopes for head-mounted configurations, but existing devices are bulky and their application in humans will require a more non-invasive, fully implantable form factor. Here we report an ultrathin, miniaturized subdural complementary metal–oxide–semiconductor (CMOS) optical device for bidirectional optical stimulation and recording. We use a custom CMOS application-specific integrated circuit that is capable of both fluorescence imaging and optogenetic stimulation, creating a probe with a total thickness of less than 200 µm, which is thin enough to lie entirely within the subdural space of the primate brain. We show that the device can be used for imaging and optical stimulation in a mouse model and can be used to decode reach movement speed in a non-human primate.

Optical neurotechnologies use light to interface with neurons and can monitor and manipulate neural activity with high spatial-temporal precision over large cortical areas. There has been considerable progress in miniaturizing microscopes for head-mounted configurations, but existing devices are bulky and their application in humans will require a more non-invasive, fully implantable form factor. Here we report an ultrathin, miniaturized subdural complementary metal–oxide–semiconductor (CMOS) optical device for bidirectional optical stimulation and recording. We use a custom CMOS application-specific integrated circuit that is capable of both fluorescence imaging and optogenetic stimulation, creating a probe with a total thickness of less than 200 µm, which is thin enough to lie entirely within the subdural space of the primate brain. We show that the device can be used for imaging and optical stimulation in a mouse model and can be used to decode reach movement speed in a non-human primate.

Discrete amplitude levels in ordered, time-domain data often represent different underlying latent states of the system that is being interrogated. Analysis and feature extraction from these data sets generally requires considering the order of each individual point; this approach cannot take advantage of contemporary general-purpose graphics processing units (gpGPU) and single-instruction multiple-data (SIMD) instruction set architectures. Two sources of such data from single-molecule biological measurements are nanopores and single- molecule field effect transistor (smFET) nanotube devices; both generate streams of time-ordered current or voltage data, typically sampled near 1 MS/s, with run times of minutes, yielding terabyte-scale datasets. Here, we present three gpGPU-based algorithms to overcome limitations associated with serial event detection in time series data, resulting in a 250× improvement in the rate with which we can detect salient features in nanopore and smFET datasets. The code is freely available.

One of the goals of neuroengineering is to establish high-bandwidth, fully implantable, and minimally invasive wireless neural interfaces that help interrogate neural circuits in freely moving and socially behaving animals. Optical interfaces offer advantages over electrophysiological techniques such as cell-type specificity, low cross-talk bidirectionality, and wide field-of-view (FoV). While most optical interfaces to-date have taken the form of bulky “mini-scopes”, recent advances in optical interfaces have shown promise in achieving high-resolution, volume-efficient brain interfacing over large FoVs with devices accommodated entirely within the subdural space [1, 2]. These devices, however, still require wired connection through the skull, negating advantages of their volumetric efficiency.

Minimally invasive, high-bandwidth brain-computer-interface (BCI) devices can revolutionize human applications. With orders-of-magnitude improvements in volumetric efficiency over other BCI technologies, we developed a 50-μm-thick, mechanically flexible micro-electrocorticography (μECoG) BCI, integrating 256×256 electrodes, signal processing, data telemetry, and wireless powering on a single complementary metal-oxide-semiconductor (CMOS) substrate containing 65,536 recording and 16,384 stimulation channels, from which we can simultaneously record up to 1024 channels at a given time. Fully implanted below the dura, our chip is wirelessly powered, communicating bi-directionally with an external relay station outside the body. We demonstrated chronic, reliable recordings for up to two weeks in pigs and up to two months in behaving non-human primates from somatosensory, motor, and visual cortices, decoding brain signals at high spatiotemporal resolution.

CMOS integration creates the possibility of rendering complex imaging systems into low-cost wearable form factors with the potential to transform medicine through continuous monitoring in a point-of-care setting. The proven safety of ultrasound, its efficacy in soft-tissue imaging, and the integration of electronic systems-on-chip have independently led to the development of active front-end ASICs for handheld ultrasound systems [1]–[4] and passive mechanically flexible 2D transducer arrays tethered to large external electronics [5]. In this work, through innovation in design and packaging, we combine these approaches to produce a mechanically flexible 2D 1024-element 5-MHz wearable ultrasound device (Fig. 1) with a focal depth of up to 3.5 cm that conforms to the surface of the body.

The development of neural probes, capable of on-site amplification and signal conditioning of neuronal signals, has been an increasingly important focus of neurotechnology research in the past few decades (1–3). However, the current state-of-the-art, silicon-based technology is limited by the rigidity of the implants where the hard electrodes do not match the softness and the constant, dynamic movement of the brain, creating damage upon implantation and chronic inflammation (4). Here, we instead develop integrated circuits for this front-end analog signal processing in neural recording applications using soft, flexible semiconductors with dual ionic-electronic conductivity.

Due to their effective ionic-to-electronic signal conversion and mechanical flexibility, organic neural implants hold considerable promise for biocompatible neural interfaces. Current approaches are, however, primarily limited to passive electrodes due to a lack of circuit components to realize complex active circuits at the front-end. Here, we introduce a p-n organic electrochemical diode using complementary p- and n-type conducting polymer films embedded in a 15-μm -diameter vertical stack. Leveraging the efficient motion of encapsulated cations inside this polymer stack and the opposite doping mechanisms of the constituent polymers, we demonstrate high current rectification ratios () and fast switching speeds (230 μs). We integrate p-n organic electrochemical diodes with organic electrochemical transistors in the front-end pixel of a recording array. This configuration facilitates the access of organic electrochemical transistor output currents within a large network operating in the same electrolyte, while minimizing crosstalk from neighboring elements due to minimized reverse-biased leakage. Furthermore, we use these devices to fabricate time-division-multiplexed amplifier arrays. Lastly, we show that, when fabricated in a shank format, this technology enables the multiplexing of amplified local field potentials directly in the active recording pixel (26-μm diameter) in a minimally invasive form factor with shank cross-sectional dimensions of only 50×8 .

Small molecules such as neurotransmitters are critical for biochemical functions in living systems. While conventional ultraviolet–visible spectroscopy and mass spectrometry lack portability and are unsuitable for time-resolved measurements in situ, techniques such as amperometry and traditional field-effect detection require a large ensemble of molecules to reach detectable signal levels. Here we demonstrate the potential of carbon-nanotube-based single-molecule field-effect transistors (smFETs), which can detect the charge on a single molecule, as a new platform for recognizing and assaying small molecules. smFETs are formed by the covalent attachment of a probe molecule, in our case a DNA aptamer, to a carbon nanotube. Conformation changes on binding are manifest as discrete changes in the nanotube electrical conductance. By monitoring the kinetics of conformational changes in a binding aptamer, we show that smFETs can detect and quantify serotonin at the single-molecule level, providing unique insights into the dynamics of the aptamer–ligand system. In particular, we show the involvement of G-quadruplex formation and the disruption of the native hairpin structure in the conformational changes of the serotonin–aptamer complex. The smFET is a label-free approach to analysing molecular interactions at the single-molecule level with high temporal resolution, providing additional insights into complex biological processes.