Current challenges to the clinical translation of brain machine interface technology

A method for efficient, rapid, and minimally invasive implantation of individual non-functional motes with penetrating subcellular-diameter carbon fiber electrodes into rat cortex

Objective

Distributed arrays of wireless neural interfacing chips with 1-2 channels each, known as "neural dust", could enhance brain machine interfaces (BMIs) by removing the wired connection through the scalp and increasing biocompatibility with their submillimeter size. Although several approaches for neural dust have emerged, a procedure for implanting them in batches that builds upon the safety and performance of currently used electrodes remains to be demonstrated.

Approach

Here, we demonstrate the feasibility of implanting batches of wireless motes that rest on the cortical surface with carbon fiber electrodes of subcellular diameter (6.8-8.4 µm) that penetrate to a target brain depth of 1 mm without insertion aids. To simulate their implantation, we assembled more than 230 mechanically equivalent motes and affixed them to insertion tools with polyethylene glycol (PEG), a quickly dissolvable and biocompatible material. Then, we implanted mote grids of multiple configurations into rat cortex in vivo and evaluated insertion success and their arrangement on the brain surface using photos and videos captured during their implantation.

Main Results

When placing motes onto the insertion device, we found that they aggregated in molten PEG such that the array pitch was only 5% wider than the dimensions of the mote bases themselves (240 x 240 µm). Overall, we found that motes with this arrangement could be inserted into rat cortex with a high success rate, as 171/186 (92%) motes in 4x4 (N=4) and 5x5 (N=5) square grid configurations were successfully inserted using the insertion device alone. After implantation, measurements of how much motes tilted (22±9°, X̄±S) and had been displaced relative to their original positions were smaller than those measured for devices implanted inside the brain in the literature.

Significance

Collectively, these data establish the viability of safely implementing motes with ultrasmall electrodes and epicortically-situated chips for use in future BMIs.

Laser ablation of the pia mater for insertion of high-density microelectrode arrays in a translational sheep model

Objective. 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). However, the pia mater can be difficult to penetrate and causes deformation of underlying cortical tissue during insertion of high-density intracortical arrays. This can lead to neuron damage or failed insertions. The development of a method to ease insertion through the pia mater would represent a significant step toward inserting high density intracortical arrays.Approach. Here we describe a surgical procedure, inspired by laser corneal ablation, that can be used in translational models to thin the pia mater.Main results. We demonstrate that controlled pia removal with laser ablation over a small area of cortex allows for microelectrode arrays to be inserted into the cortex with less force, thus reducing deformation of underlying tissue during placement of the microelectrodes. This procedure 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.Significance. Laser ablation of the pia reduces insertion forces of high-density arrays with minimal to no acute damage to cortical neurons. This approach suggests a promising new path for clinical BCI with high-density microelectrode arrays.

Control for multifunctionality: bioinspired control based on feeding in Aplysia californica

Animals exhibit remarkable feats of behavioral flexibility and multifunctional control that remain challenging for robotic systems. The neural and morphological basis of multifunctionality in animals can provide a source of bioinspiration for robotic controllers. However, many existing approaches to modeling biological neural networks rely on computationally expensive models and tend to focus solely on the nervous system, often neglecting the biomechanics of the periphery. As a consequence, while these models are excellent tools for neuroscience, they fail to predict functional behavior in real time, which is a critical capability for robotic control. To meet the need for real-time multifunctional control, we have developed a hybrid Boolean model framework capable of modeling neural bursting activity and simple biomechanics at speeds faster than real time. Using this approach, we present a multifunctional model of Aplysia californica feeding that qualitatively reproduces three key feeding behaviors (biting, swallowing, and rejection), demonstrates behavioral switching in response to external sensory cues, and incorporates both known neural connectivity and a simple bioinspired mechanical model of the feeding apparatus. We demonstrate that the model can be used for formulating testable hypotheses and discuss the implications of this approach for robotic control and neuroscience.

High density carbon fiber arrays for chronic electrophysiology, fast scan cyclic voltammetry, and correlative anatomy

OBJECTIVE

Multimodal measurements at the neuronal level allow for detailed insight into local circuit function. However, most behavioral studies focus on one or two modalities and are generally limited by the available technology.

APPROACH

Here, we show a combined approach of electrophysiology recordings, chemical sensing, and histological localization of the electrode tips within tissue. The key enabling technology is the underlying use of carbon fiber electrodes, which are small, electrically conductive, and sensitive to dopamine. The carbon fibers were functionalized by coating with Parylene C, a thin insulator with a high dielectric constant, coupled with selective re-exposure of the carbon surface using laser ablation.

MAIN RESULTS

We demonstrate the use of this technology by implanting 16 channel arrays in the rat nucleus accumbens. Chronic electrophysiology and dopamine signals were detected 1 month post implant. Additionally, electrodes were left in the tissue, sliced in place during histology, and showed minimal tissue damage.

SIGNIFICANCE

Our results validate our new technology and methods, which will enable a more comprehensive circuit level understanding of the brain.

Controlling a robotic arm for functional tasks using a wireless head-joystick: A case study of a child with congenital absence of upper and lower limbs

Children with movement impairments needing assistive devices for activities of daily living often require novel methods for controlling these devices. Body-machine interfaces, which rely on body movements, are particularly well-suited for children as they are non-invasive and have high signal-to-noise ratios. Here, we examined the use of a head-joystick to enable a child with congenital absence of all four limbs to control a seven degree-of-freedom robotic arm. Head movements were measured with a wireless inertial measurement unit and used to control a robotic arm to perform two functional tasks-a drinking task and a block stacking task. The child practiced these tasks over multiple sessions; a control participant performed the same tasks with a manual joystick. Our results showed that the child was able to successfully perform both tasks, with movement times decreasing by ~40-50% over 6-8 sessions of training. The child's performance with the head-joystick was also comparable to the control participant using a manual joystick. These results demonstrate the potential of using head movements for the control of high degree-of-freedom tasks in children with limited movement repertoire.

A review for the peripheral nerve interface designer

Informational density and relative accessibility of the peripheral nervous system make it an attractive site for therapeutic intervention. Electrode-based electrophysiological interfaces with peripheral nerves have been under development since the 1960s and, for several applications, have seen widespread clinical implementation. However, many applications require a combination of neural target resolution and stability which has thus far eluded existing peripheral nerve interfaces (PNIs). With the goal of aiding PNI designers in development of devices that meet the demands of next-generation applications, this review seeks to collect and present practical considerations and best practices which emerge from the literature, including both lessons learned during early PNI development and recent ideas. Fundamental and practical principles guiding PNI design are reviewed, followed by an updated and critical account of existing PNI designs and strategies. Finally, a brief survey of in vitro and in vivo PNI characterization methods is presented.

Recent Progress on Non-Conventional Microfabricated Probes for the Chronic Recording of Cortical Neural Activity

Microfabrication technology for cortical interfaces has advanced rapidly over the past few decades for electrophysiological studies and neuroprosthetic devices offering the precise recording and stimulation of neural activity in the cortex. While various cortical microelectrode arrays have been extensively and successfully demonstrated in animal and clinical studies, there remains room for further improvement of the probe structure, materials, and fabrication technology, particularly for high-fidelity recording in chronic implantation. A variety of non-conventional probes featuring unique characteristics in their designs, materials and fabrication methods have been proposed to address the limitations of the conventional standard shank-type ("Utah-" or "Michigan-" type) devices. Such non-conventional probes include multi-sided arrays to avoid shielding and increase recording volumes, mesh- or thread-like arrays for minimized glial scarring and immune response, tube-type or cylindrical probes for three-dimensional (3D) recording and multi-modality, folded arrays for high conformability and 3D recording, self-softening or self-deployable probes for minimized tissue damage and extensions of the recording sites beyond gliosis, nanostructured probes to reduce the immune response, and cone-shaped electrodes for promoting tissue ingrowth and long-term recording stability. Herein, the recent progress with reference to the many different types of non-conventional arrays is reviewed while highlighting the challenges to be addressed and the microfabrication techniques necessary to implement such features.

A New Frontier: The Convergence of Nanotechnology, Brain Machine Interfaces, and Artificial Intelligence

A confluence of technological capabilities is creating an opportunity for machine learning and artificial intelligence (AI) to enable "smart" nanoengineered brain machine interfaces (BMI). This new generation of technologies will be able to communicate with the brain in ways that support contextual learning and adaptation to changing functional requirements. This applies to both invasive technologies aimed at restoring neurological function, as in the case of neural prosthesis, as well as non-invasive technologies enabled by signals such as electroencephalograph (EEG). Advances in computation, hardware, and algorithms that learn and adapt in a contextually dependent way will be able to leverage the capabilities that nanoengineering offers the design and functionality of BMI. We explore the enabling capabilities that these devices may exhibit, why they matter, and the state of the technologies necessary to build them. We also discuss a number of open technical challenges and problems that will need to be solved in order to achieve this.

The current state of the brain-computer interface problem

It was only 40 years ago that the first PC appeared. Over this period, rather short in historical terms, we have witnessed the revolutionary changes in lives of individuals and the entire society. Computer technologies are tightly connected with any field, either directly or indirectly. We can currently claim that computers are manifold superior to a human mind in terms of a number of parameters; however, machines lack the key feature: they are incapable of independent thinking (like a human). However, the key to successful development of humankind is collaboration between the brain and the computer rather than competition. Such collaboration when a computer broadens, supplements, or replaces some brain functions is known as the brain-computer interface. Our review focuses on real-life implementation of this collaboration.

Enhancing brain-machine interface (BMI) control of a hand exoskeleton using electrooculography (EOG)

BACKGROUND

Brain-machine interfaces (BMIs) allow direct translation of electric, magnetic or metabolic brain signals into control commands of external devices such as robots, prostheses or exoskeletons. However, non-stationarity of brain signals and susceptibility to biological or environmental artifacts impede reliable control and safety of BMIs, particularly in daily life environments. Here we introduce and tested a novel hybrid brain-neural computer interaction (BNCI) system fusing electroencephalography (EEG) and electrooculography (EOG) to enhance reliability and safety of continuous hand exoskeleton-driven grasping motions.

FINDINGS

12 healthy volunteers (8 male, mean age 28.1 ± 3.63y) used EEG (condition #1) and hybrid EEG/EOG (condition #2) signals to control a hand exoskeleton. Motor imagery-related brain activity was translated into exoskeleton-driven hand closing motions. Unintended motions could be interrupted by eye movement-related EOG signals. In order to evaluate BNCI control and safety, participants were instructed to follow a visual cue indicating either to move or not to move the hand exoskeleton in a random order. Movements exceeding 25% of a full grasping motion when the device was not supposed to be moved were defined as safety violation. While participants reached comparable control under both conditions, safety was frequently violated under condition #1 (EEG), but not under condition #2 (EEG/EOG).

CONCLUSION

EEG/EOG biosignal fusion can substantially enhance safety of assistive BNCI systems improving their applicability in daily life environments.

Chronic, wireless recordings of large-scale brain activity in freely moving rhesus monkeys

Advances in techniques for recording large-scale brain activity contribute to both the elucidation of neurophysiological principles and the development of brain-machine interfaces (BMIs). Here we describe a neurophysiological paradigm for performing tethered and wireless large-scale recordings based on movable volumetric three-dimensional (3D) multielectrode implants. This approach allowed us to isolate up to 1,800 units per animal and simultaneously record the extracellular activity of close to 500 cortical neurons, distributed across multiple cortical areas, in freely behaving rhesus monkeys. The method is expandable, in principle, to thousands of simultaneously recorded channels. It also allows increased recording longevity (5 consecutive years), and recording of a broad range of behaviors, e.g. social interactions, and BMI paradigms in freely moving primates. We propose that wireless large-scale recordings could have a profound impact on basic primate neurophysiology research, while providing a framework for the development and testing of clinically relevant neuroprostheses.