Few-shot Algorithms for Consistent Neural Decoding (FALCON) Benchmark.

Intracortical brain-computer interfaces (iBCIs) can restore movement and communication abilities to individuals with paralysis by decoding their intended behavior from neural activity recorded with an implanted device. While this activity yields high-performance decoding over short timescales, neural data are often nonstationary, which can lead to decoder failure if not accounted for. To maintain performance, users must frequently recalibrate decoders, which requires the arduous collection of new neural and behavioral data.

Functional Electrical Stimulation and Brain-Machine Interfaces for Simultaneous Control of Wrist and Finger Flexion.

Brain-machine interface (BMI) controlled functional electrical stimulation (FES) is a promising treatment to restore hand movements to people with cervical spinal cord injury. Recent intracortical BMIs have shown unprecedented successes in decoding user intentions, however the hand movements restored by FES have largely been limited to predetermined grasps. Restoring dexterous hand movements will require continuous control of many biomechanically linked degrees-of-freedom in the hand, such as wrist and finger flexion, that would form the basis of those movements.

Artificial neural network for brain-machine interface consistently produces more naturalistic finger movements than linear methods.

Unlabelled: Brain-machine interfaces (BMI) aim to restore function to persons living with spinal cord injuries by 'decoding' neural signals into behavior. Recently, nonlinear BMI decoders have outperformed previous state-of-the-art linear decoders, but few studies have investigated what specific improvements these nonlinear approaches provide. In this study, we compare how temporally convolved feedforward neural networks (tcFNNs) and linear approaches predict individuated finger movements in open and closed-loop settings.

Intracellular neural control of an active feeding structure in Aplysia using a carbon fiber electrode array.

Background: To study neural control of behavior, intracellular recording and stimulation of many neurons in freely moving animals would be ideal. However, current technologies limit the number of neurons that can be monitored and manipulated. A new technology has become available for intracellular recording and stimulation which we demonstrate in the tractable nervous system of Aplysia.

Fabrication and Validation of Sub-Cellular Carbon Fiber Electrodes.

Multielectrode arrays for interfacing with neurons are of great interest for a wide range of medical applications. However, current electrodes cause damage over time. Ultra small carbon fibers help to address issues but controlling the electrode site geometry is difficult.

Electrical Stimulation of Regenerative Peripheral Nerve Interfaces (RPNIs) Induces Referred Sensations in People With Upper Limb Loss.

Individuals with upper limb loss lack sensation of the missing hand, which can negatively impact their daily function. Several groups have attempted to restore this sensation through electrical stimulation of residual nerves. The purpose of this study was to explore the utility of regenerative peripheral nerve interfaces (RPNIs) in eliciting referred sensation.

Realizing Upper Extremity Bionic Limbs: Leveraging Neuroprosthetic Control Strategies.

Innovations in prosthetic devices and neuroprosthetic control strategies have opened new frontiers for the treatment and rehabilitation of individuals undergoing amputation. Commercial prosthetic devices are now available with sophisticated electrical and mechanical components that can closely replicate the functions of the human musculoskeletal system. However, to truly recognize the potential of such prosthetic devices and develop the next generation of bionic limbs, a highly reliable prosthetic device control strategy is required.

Sex Differences in Dopamine Release in Nucleus Accumbens and Dorsal Striatum Determined by Chronic Fast Scan Cyclic Voltammetry: Effects of social housing and repeated stimulation.

We investigated sex differences in dopamine (DA) release in the nucleus accumbens (NAc) and dorsolateral striatum (DLS) using a chronic 16-channel carbon fiber electrode and fast-scan cyclic voltammetry (FSCV). Electrical stimulation (ES; 60Hz) induced DA release was recorded in the NAc of single or pair-housed male and female rats. When core (NAcC) and shell (NAcS) were recorded simultaneously, there was greater ES DA release in NAcC of pair-housed females compared with single females and males.

Error detection and correction in intracortical brain-machine interfaces controlling two finger groups.

While brain-machine interfaces (BMIs) are promising technologies that could provide direct pathways for controlling the external world and thus regaining motor capabilities, their effectiveness is hampered by decoding errors. Previous research has demonstrated the detection and correction of BMI outcome errors, which occur at the end of trials. Here we focus on continuous detection and correction of BMI execution errors, which occur during real-time movements.

Combining voltage-sensitive dye, carbon fiber array, and extracellular nerve electrodes using a 3-D printed recording chamber and manipulators.

Background: The analyses of neuronal circuits require high-throughput technologies for stimulating and recording many neurons simultaneously with single-neuron precision. Voltage-sensitive dyes (VSDs) have enabled the monitoring of membrane potentials of many (10-100 s) neurons simultaneously. Carbon fiber electrode (CFE) arrays allow for stimulation and recording of many neurons simultaneously, including intracellularly.

Balancing Memorization and Generalization in RNNs for High Performance Brain-Machine Interfaces.

Brain-machine interfaces (BMIs) can restore motor function to people with paralysis but are currently limited by the accuracy of real-time decoding algorithms. Recurrent neural networks (RNNs) using modern training techniques have shown promise in accurately predicting movements from neural signals but have yet to be rigorously evaluated against other decoding algorithms in a closed-loop setting. Here we compared RNNs to other neural network architectures in real-time, continuous decoding of finger movements using intracortical signals from nonhuman primates.

Automated assembly of high-density carbon fiber electrode arrays for single unit electrophysiological recordings.

Carbon fiber (CF) is good for chronic neural recording due to the small diameter (7m), high Young's modulus, and low electrical resistance, but most high-density carbon fiber (HDCF) arrays are manually assembled with labor-intensive procedures and limited by the accuracy and repeatability of the operator handling. A machine to automate the assembly is desired.The HDCF array assembly machine contains: (1) a roller-based CF extruder, (2) a motion system with three linear and one rotary stages, (3) an imaging system with two digital microscope cameras, and (4) a laser cutter.

Restoring continuous finger function with temporarily paralyzed nonhuman primates using brain-machine interfaces.

Brain-machine interfaces (BMIs) have shown promise in extracting upper extremity movement intention from the thoughts of nonhuman primates and people with tetraplegia. Attempts to restore a user's own hand and arm function have employed functional electrical stimulation (FES), but most work has restored discrete grasps. Little is known about how well FES can control continuous finger movements.

Long-term upper-extremity prosthetic control using regenerative peripheral nerve interfaces and implanted EMG electrodes.

Extracting signals directly from the motor system poses challenges in obtaining both high amplitude and sustainable signals for upper-limb neuroprosthetic control. To translate neural interfaces into the clinical space, these interfaces must provide consistent signals and prosthetic performance.Previously, we have demonstrated that the Regenerative Peripheral Nerve Interface (RPNI) is a biologically stable, bioamplifier of efferent motor action potentials.

Post-explant profiling of subcellular-scale carbon fiber intracortical electrodes and surrounding neurons enables modeling of recorded electrophysiology.

Characterizing the relationship between neuron spiking and the signals that electrodes record is vital to defining the neural circuits driving brain function and informing clinical brain-machine interface design. However, high electrode biocompatibility and precisely localizing neurons around the electrodes are critical to defining this relationship.Here, we demonstrate consistent localization of the recording site tips of subcellular-scale (6.

Upper limb prostheses: bridging the sensory gap.

Replacing human hand function with prostheses goes far beyond only recreating muscle movement with feedforward motor control. Natural sensory feedback is pivotal for fine dexterous control and finding both engineering and surgical solutions to replace this complex biological function is imperative to achieve prosthetic hand function that matches the human hand. This review outlines the nature of the problems underlying sensory restitution, the engineering methods that attempt to address this deficit and the surgical techniques that have been developed to integrate advanced neural interfaces with biological systems.

Utah array characterization and histological analysis of a multi-year implant in non-human primate motor and sensory cortices.

The Utah array is widely used in both clinical studies and neuroscience. It has a strong track record of safety. However, it is also known that implanted electrodes promote the formation of scar tissue in the immediate vicinity of the electrodes, which may negatively impact the ability to record neural waveforms.

Real-time brain-machine interface in non-human primates achieves high-velocity prosthetic finger movements using a shallow feedforward neural network decoder.

Despite the rapid progress and interest in brain-machine interfaces that restore motor function, the performance of prosthetic fingers and limbs has yet to mimic native function. The algorithm that converts brain signals to a control signal for the prosthetic device is one of the limitations in achieving rapid and realistic finger movements. To achieve more realistic finger movements, we developed a shallow feed-forward neural network to decode real-time two-degree-of-freedom finger movements in two adult male rhesus macaques.

Use of regenerative peripheral nerve interfaces and intramuscular electrodes to improve prosthetic grasp selection: a case study.

Advanced myoelectric hands enable users to select from multiple functional grasps. Current methods for controlling these hands are unintuitive and require frequent recalibration. This case study assessed the performance of tasks involving grasp selection, object interaction, and dynamic postural changes using intramuscular electrodes with regenerative peripheral nerve interfaces (RPNIs) and residual muscles.

A Light-Tolerant Wireless Neural Recording IC for Motor Prediction With Near-Infrared-Based Power and Data Telemetry.

Miniaturized and wireless near-infrared (NIR) based neural recorders with optical powering and data telemetry have been introduced as a promising approach for safe long-term monitoring with the smallest physical dimension among state-of-the-art standalone recorders. However, a main challenge for the NIR based neural recording ICs is to maintain robust operation in the presence of light-induced parasitic short circuit current from junction diodes. This is especially true when the signal currents are kept small to reduce power consumption.

Characterizing sensory thresholds and intensity sensitivity of Regenerative Peripheral Nerve Interfaces: A Case Study.

Current prosthetic limbs offer little to no sensory feedback. Developments in peripheral nerve interfaces provide opportunities to restore some level of tactile feedback that is referred to the prosthetic limb. One such method is a Regenerative Peripheral Nerve Interface (RPNI), composed of a muscle graft wrapped around a free nerve ending.

Artificial referred sensation in upper and lower limb prosthesis users: a systematic review.

Electrical stimulation can induce sensation in the phantom limb of individuals with amputation. It is difficult to generalize existing findings as there are many approaches to delivering stimulation and to assessing the characteristics and benefits of sensation. Therefore, the goal of this systematic review was to explore the stimulation parameters that effectively elicited referred sensation, the qualities of elicited sensation, and how the utility of referred sensation was assessed.