Biology subjects

Angle, M. R.

Publications and source records attributed to Angle, M. R..

5 recordsLinked to original sources

bioRxiv2025

SONIC: A Benchmarking Paradigm for Brain-Computer Interfaces

Brain-computer interfaces (BCIs) can restore function for individuals with neuro-logical disorders and have the potential to transform the way people interact with digital systems. However, the development of advanced BCI applications, such as fluent speech synthesis, is dependent on the underlying information transfer capacity of the physical neural interface employed. A significant barrier to progress has been the lack of standardized, application-agnostic methods for benchmarking BCI system performance prior to clinical trials. Here, we introduce SONIC, a novel preclinical benchmarking paradigm designed to evaluate the information transfer rate (ITR) of a BCI system. This paradigm treats the brain and BCI as a noisy communication channel, where information is sent into the brain via precisely controlled sensory stimuli and read out by the neural interface. We implemented this paradigm in an ovine model by presenting rapid sequences of pure tones while recording neural activity from the primary auditory cortex with the Paradromics Connexus(C) BCI, a fully implanted system utilizing high-density intracortical micro-electrode arrays with wireless power and data transmission. A convolutional neural network was used to decode tones based on neural features. Our results demonstrate an achieved ITR of over 200 bits per second (bps), which is the highest reported BCI ITR to date. For reference, this rate exceeds the linguistic information content of human speech. This ITR is achieved with a total neural interface, filtering, and data aggregation delay of 56 milliseconds. Further analysis demonstrated that ITR remains high (> 100 bps) for the lowest total delay tested (11 ms), supporting the needs of latency-sensitive applications (e.g., direct speech synthesis). This work establishes a new benchmark for BCI performance and demonstrates that the Connexus BCI possesses the bandwidth necessary to support highly advanced applications. This benchmark provides a robust framework for preclinical BCI evaluation, enabling principled system design optimization to accelerate the translation of next-generation neurotechnology.

bioengineering↗

bioRxiv2020

Laser Ablation of the Pia Mater for Insertion of High-Density Microelectrode Arrays in a Translational Sheep Model

The safe insertion of high density intracortical electrode arrays has been a long-standing practical challenge for neural interface engineering and applications such as brain-computer interfaces (BCIs). Here we describe a surgical procedure, inspired by laser corneal ablation, that can be used in large mammals to thin the pia mater, the innermost meningeal layer encapsulating the brain. This procedure allows for microelectrode arrays to be inserted into the cortex with less force, thus reducing deformation of underlying tissue during placement of the microelectrodes. We demonstrate that controlled pia removal over a small area of cortex allows for insertion of high-density electrode arrays and subsequent acute recordings of spiking neuron activity in sheep cortex. We also show histological and electrophysiological evidence that laser removal of the pia does not acutely affect neuronal viability in the region. This approach suggests a promising new path for clinical BCI with high-density microelectrode arrays.

neuroscience↗

bioRxiv2020

The Argo: A 65,536 channel recording system for high density neural recording in vivo

Here we demonstrate the Argo System, a massively parallel neural recording system based on platinum-iridium microwire electrode arrays bonded to a CMOS voltage amplifier array. The Argo system is the highest channel count in vivo neural recording system built to date, supporting simultaneous recording from 65,536 channels, sampled at over 32 kHz and 12-bit resolution. This system is designed for cortical recordings, compatible with both penetrating and surface microelectrodes. We have validated this system by recording spiking activity from 791 neurons in rats and cortical surface Local Field Potential (LFP) activity from over 30,000 channels in sheep. While currently adapted for head-fixed recording, the microwire-CMOS architecture is well suited for clinical translation. Thus, this demonstration helps pave the way for a future high data rate intracortical implant.

neuroscience↗

bioRxiv2019

Massively Parallel Microwire Arrays Integrated with CMOS chips for Neural Recording

Multi-channel electrical recordings of neural activity in the brain is an increasingly powerful method revealing new aspects of neural communication, computation, and prosthetics. However, while planar silicon-based CMOS devices in conventional electronics scale rapidly, neural interface devices have not kept pace. Here, we present a new strategy to interface silicon-based chips with three-dimensional microwire arrays, providing the link between rapidly-developing electronics and high density neural interfaces. The system consists of a bundle of microwires mated to large-scale microelectrode arrays, such as camera chips. This system has excellent recording performance, demonstrated via single unit and local-field potential recordings in isolated retina and in the motor cortex or striatum of awake moving mice. The modular design enables a variety of microwire types and sizes to be integrated with different types of pixel arrays, connecting the rapid progress of commercial multiplexing, digitisation and data acquisition hardware together with a three-dimensional neural interface.

neuroscience↗

bioRxiv2019

CHIME: CMOS-hosted in-vivo microelectrodes for massively scalable neuronal recordings

Mammalian brains consist of 10s of millions to 100s of billions of neurons operating at millisecond time scales, of which current recording techniques only capture a tiny fraction. Recording techniques capable of sampling neural activity at such temporal resolution have been difficult to scale: The most intensively studied mammalian neuronal networks, such as the neocortex, show layered architecture, where the optimal recording technology samples densely over large areas. However, the need for application-specific designs as well as the mismatch between the threedimensional architecture of the brain and largely two-dimensional microfabrication techniques profoundly limits both neurophysiological research and neural prosthetics.\n\nHere, we propose a novel strategy for scalable neuronal recording by combining bundles of glass-ensheathed microwires with large-scale amplifier arrays derived from commercial CMOS of in-vitro MEA systems or high-speed infrared cameras. High signal-to-noise ratio (<20 V RMS noise floor, SNR up to 25) is achieved due to the high conductivity of core metals in glass-ensheathed microwires allowing for ultrathin metal cores (down to <1 m) and negligible stray capacitance. Multi-step electrochemical modification of the tip enables ultra-low access impedance with minimal geometric area and largely independent of core diameter. We show that microwire size can be reduced to virtually eliminate damage to the blood-brain-barrier upon insertion and demonstrate that microwire arrays can stably record single unit activity.\n\nCombining microwire bundles and CMOS arrays allows for a highly scalable neuronal recording approach, linking the progress of electrical neuronal recording to the rapid scaling of silicon microfabrication. The modular design of the system allows for custom arrangement of recording sites. Our approach of employing bundles of minimally invasive, highly insulated and functionalized microwires to lift a 2-dimensional CMOS architecture into the 3rd dimension can be translated to other CMOS arrays such as electrical stimulation devices.

neuroscience↗