OBJECTIVE The long-term goal of this work is to develop a sensorimotor brain-machine interface (BMI) in which intended movements are decoded from the motor cortex and proprioceptive feedback is delivered via intracortical micro stimulation of Brodmann's area 3a. A vital step toward this goal is to demonstrate in rhesus macaques a novel surgical approach for the precise and safe implantation of custom-length microelectrode arrays into area 3a at the bottom of the central sulcus. METHODS Preoperative planning combined high-resolution 7-T MR and CT imaging to generate 3D models of the cortices of 2 subjects. These models were used to fabricate 3D-printed skull replicas and to define a stereotactic trajectory that provided the shortest perpendicular path to the base of the central sulcus, where Brodmann's area 3a resides. Custom variable-length microwire electrode arrays were designed to span this target region. The flexibility of the microwires precluded the standard impact-insertion approach used with stiffer electrodes. Therefore, a custom vacuum-powered microdrive holder that moved with the pulsating brain was developed to maintain electrode orientation and to allow slow, controlled insertion along the planned trajectory. After implantation, the craniotomy was closed, and a skull-mounted recording chamber was secured. Postoperative verification of array placement was performed using CT imaging and neural recordings. RESULTS In both animals, imaging revealed that the base of the central sulcus was positioned anterior to its dorsal opening, making a precentral implant trajectory the shortest and most direct path to the bottom of the central sulcus. The integrated imaging and 3D modeling approach enabled accurate stereotactic placement of custom microelectrode arrays using the novel vacuum-assisted microdrive, as confirmed by postoperative CT imaging. Both surgical procedures were completed without complication, and isolatable neuronal spikes were recorded from multiple channels in each subject. In both animals, neural activity was modulated by passive movements of the arm. CONCLUSIONS Intracortical microelectrode implants for BMI applications have traditionally been limited to short (1.5-mm) electrodes targeting cortical sites exposed on the brain surface. The surgical methodology described here enables safe and accurate implantation of custom-length arrays into deep sulcal targets such as Brodmann's area 3a. By expanding access to previously inaccessible cortical regions, this approach broadens the potential neural information available for future BMI applications.

This study aimed to improve intracortical microelectrode array implantation sites for grasp-related motor decoding by integrating anatomical, functional, and vascular imaging with preoperative 3D modeling. A participant with C5 tetraplegia underwent anatomical MRI, diffusion-weighted imaging, and task-based fMRI to identify grasp-related cortical regions while avoiding vasculature and speech-critical areas. Quicktome software was used to refine target selection by integrating structural connectivity and functional activation data. A 3D-printed skull and cortical model enabled preoperative planning, including craniotomy and electrode positioning simulations. Electrode placement was validated postoperatively using neural data collected from the implanted arrays during attempted movements of the arm and hand. Functional imaging identified distinct grasp-related activation in anterior intraparietal area (AIP), ventral premotor cortex (PMv), and inferior frontal gyrus (IFG). Putative AIP was selected based on its strong connectivity with motor cortex and distinct functional activation. Subregions 6v and 6r of PMv, which exhibited robust grasp-related activity and were surgically accessible, were chosen over the posterior IFG region, which extended into a sulcus making implantation difficult. Postoperatively, the arrays enabled high-fidelity decoding of arm/hand movements, achieving a combined classification accuracy of 96%. This study presents a multi-modal approach for improving intracortical electrode placement by combining MRI-based anatomical mapping, fMRI-guided functional localization, connectivity information, and 3D surgical modeling. These findings demonstrate an effective method for identifying surgically feasible grasp network implant locations in a paralyzed individual. This is an essential step toward brain-machine interfaces that enable individuals with spinal cord injury to control devices using grasp-related brain activity.

Objective. Recent brain-machine interface (BMI) studies have challenged traditional views of functional specialization in human motor cortices, suggesting that regions associated with hand movement also support speech. However, the extent of this dual functionality as well as the neural mechanisms underlying it are unclear. This study aims to determine whether mixed speech and grasp representation generalizes across a wide range of cortical regions and if so, to identify the population-level mechanisms supporting such mixed selectivity.Approach. We analyzed intracortical neural activity from seven brain regions (spanning motor, premotor, somatosensory and parietal cortices) while two human participants with tetraplegia completed speech and hand movement tasks. We assessed the population-level encoding of the two tasks using offline neural decoding, functional connectivity and subspace analyses.Main results. Robust grasp decoding was evident across all regions, along with reliable discrete-word decoding during both silent and vocalized speech. Within each region, overlapping neural populations contributed to both tasks, indicating mixed selectivity. However, these populations reconfigured their functional connectivity between tasks, organizing neural activity into non-overlapping speech and grasp subspaces.Significance. Our results indicate that mixed selectivity for speech and grasping generalizes across distributed sensorimotor cortical networks. Additionally, our findings support the development of multi-functional BMIs capable of decoding both speech and grasping from the same implant and highlight ventral premotor area 6r as a novel target.

Objective.Microstimulation delivers electrical pulses directly into the brain, with one of its promises being to restore lost senses to millions of people. Yet a fundamental challenge remains: how do intracortical microstimulation (ICMS) patterns engage neural circuits to achieve the inception of specific experiences, such as vivid sensory percepts of touch and vision? Here, we define 'inception' as the initiation of percepts evoked by microstimulation through the mapping of stimulation to circuit-level activity that results in sensory experiences.Approach.This perspective proposes an integrated research framework that combines Reverse Translation, Forward Translation, and computational neuroscience to bridge insights between clinical observations and high-resolution animal studies.Framework.Our framework envisions the development and evaluation of ICMS strategies within a cross-species system that narrows the range of plausible underlying neural mechanisms and the set of evoked perceptual outcomes. Reverse Translation uses human perceptual reports about phosphenes, tones, and touch to guide investigations in rodents and non-human primates, mapping the cell types and circuits underlying each percept. Forward Translation leverages these biological insights to design refined ICMS protocols for selective circuit engagement. Bidirectional Translation weaves these approaches together through computational neuroscience, ensuring that experimental observations iteratively and continuously refine one another across species and experimental modalities.Significance.This integrated strategy aims to transform microstimulation research into a dynamic dialogue between fundamental science and human experience. Harnessing the Bidirectional Translation Framework can accelerate therapies that enhance quality of life for people with sensory or motor impairments, and contribute more broadly to systems neuroscience by uncovering the mechanisms by which causal manipulation changes activity in neurons and networks.

OBJECTIVE:This study aimed to optimize intracortical microelectrode array implantation sites for grasp-related motor decoding by integrating anatomical, functional, and vascular imaging with preoperative 3D modeling. METHODS:A participant with C5 tetraplegia underwent anatomical magnetic resonance imaging (MRI), diffusion-weighted imaging, and task-based functional MRI (fMRI) to identify grasp-related cortical regions while avoiding vasculature and speech-critical areas. Quicktome software was used to refine target selection by integrating structural connectivity and functional activation data. A 3D-printed skull and cortical model enabled preoperative planning, including craniotomy and electrode positioning simulations. Electrode placement was validated post-operatively using neural data collected from the implanted arrays during attempted movements of the arm and hand. RESULTS:Functional imaging identified distinct grasp-related activation in anterior intraparietal area (AIP), ventral premotor cortex (PMv), and inferior frontal gyrus (IFG). AIP was selected based on its strong connectivity with motor cortex and distinct functional activation. Subregions 6v and 6r of PMv, which exhibited robust grasp-related activity and were surgically accessible, were chosen over the posterior IFG region, which extended into a sulcus making implantation difficult. Post-surgically, the arrays enabled high-fidelity decoding of arm/hand movements, achieving a combined accuracy of 96%. CONCLUSION:This study presents a multi-modal approach for optimizing intracortical electrode placement by combining MRI-based anatomical mapping, fMRI-guided functional localization, connectivity information, and 3D surgical modeling. These findings demonstrate an effective method for identifying surgically feasible grasp network implant locations in a paralyzed individual. This is an essential step for brain-machine interface (BMI) systems that use grasp-related brain activity to command devices, such as neuromuscular stimulation systems for restoring upper limb function in individuals with spinal cord injury (SCI).

Objective.Brain-controlled functional electrical stimulation (FES) of the upper limb has been used to restore arm function to paralyzed individuals in the lab. Able-bodied individuals naturally modulate limb stiffness throughout movements and in anticipation of perturbations. Our goal is to develop, via simulation, a framework for incorporating stiffness modulation into the currently-used 'lookup-table-based' FES control systems while addressing several practical issues: (1) optimizing stimulation across muscles with overlap in function, (2) coordinating stimulation across joints, and (3) minimizing errors due to fatigue. Our calibration process also needs to account for when current spread causes additional muscles to become activated.Approach.We developed an analytical framework for building a lookup-table-based FES controller and simulated the clinical process of calibrating and using the arm. A computational biomechanical model of a human paralyzed arm responding to stimulation was used for simulations with six muscles controlling the shoulder and elbow in the horizontal plane. Both joints had multiple muscles with overlapping functional effects, as well as biarticular muscles to reflect complex interactions between joints. Performance metrics were collectedin silico,and real-time use was demonstrated with a Rhesus macaque using its cortical signals to control the computational arm model in real time.Main results.By explicitly including stiffness as a definable degree of freedom in the lookup table, our analytical approach was able to achieve all our performance criteria. While using more empirical data during controller parameterization produced more accurate lookup tables, interpolation between sparsely sampled points (e.g. 20° angular intervals) still produced good results with median endpoint position errors of less than 1 cm-a range that should be easy to correct for with real-time visual feedback.Significance.Our simplified process for generating an effective FES controller now makes translating upper limb FES systems into mainstream clinical practice closer to reality.

BACKGROUND AND OBJECTIVES:Paralysis after spinal cord injury involves damage to pathways that connect neurons in the brain to peripheral nerves in the limbs. Re-establishing this communication using neural interfaces has the potential to bridge the gap and restore upper extremity function to people with high tetraplegia. We report a novel approach for restoring upper extremity function using selective peripheral nerve stimulation controlled by intracortical microelectrode recordings from sensorimotor networks, along with restoration of tactile sensation of the hand using intracortical microstimulation. METHODS:A 27-year-old right-handed man with AIS-B (motor-complete, sensory-incomplete) C3-C4 tetraplegia was enrolled into the clinical trial. Six 64-channel intracortical microelectrode arrays were implanted into left hemisphere regions involved in upper extremity function, including primary motor and sensory cortices, inferior frontal gyrus, and anterior intraparietal area. Nine 16-channel extraneural peripheral nerve electrodes were implanted to allow targeted stimulation of right median, ulnar (2), radial, axillary, musculocutaneous, suprascapular, lateral pectoral, and long thoracic nerves, to produce selective muscle contractions on demand. Proof-of-concept studies were performed to demonstrate feasibility of using a brain-machine interface to read from and write to the brain for restoring motor and sensory functions of the participant's own arm and hand. RESULTS:Multiunit neural activity that correlated with intended motor action was successfully recorded from intracortical arrays. Microstimulation of electrodes in somatosensory cortex produced repeatable sensory percepts of individual fingers for restoration of touch sensation. Selective electrical activation of peripheral nerves produced antigravity muscle contractions, resulting in functional movements that the participant was able to command under brain control to perform virtual and actual arm and hand movements. The system was well tolerated with no operative complications. CONCLUSION:The combination of implanted cortical electrodes and nerve cuff electrodes has the potential to create bidirectional restoration of motor and sensory functions of the arm and hand after neurological injury.

(1) Background: Intracortical microelectrodes (IMEs) are essential to basic brain research and clinical brain–machine interfacing applications. However, the foreign body response to IMEs results in chronic inflammation and an increase in levels of reactive oxygen and nitrogen species (ROS/RNS). The current study builds on our previous work, by testing a new delivery method of a promising antioxidant as a means of extending intracortical microelectrodes performance. While resveratrol has shown efficacy in improving tissue response, chronic delivery has proven difficult because of its low solubility in water and low bioavailability due to extensive first pass metabolism. (2) Methods: Investigation of an intraventricular delivery of resveratrol in rats was performed herein to circumvent bioavailability hurdles of resveratrol delivery to the brain. (3) Results: Intraventricular delivery of resveratrol in rats delivered resveratrol to the electrode interface. However, intraventricular delivery did not have a significant impact on electrophysiological recordings over the six-week study. Histological findings indicated that rats receiving intraventricular delivery of resveratrol had a decrease of oxidative stress, yet other biomarkers of inflammation were found to be not significantly different from control groups. However, investigation of the bioavailability of resveratrol indicated a decrease in resveratrol accumulation in the brain with time coupled with inconsistent drug elution from the cannulas. Further inspection showed that there may be tissue or cellular debris clogging the cannulas, resulting in variable elution, which may have impacted the results of the study. (4) Conclusions: These results indicate that the intraventricular delivery approach described herein needs further optimization, or may not be well suited for this application.

Objective. Intracortical recordings have now been combined with functional electrical stimulation (FES) of arm/hand muscles to demonstrate restoration of upper-limb function after spinal cord injury. However, for each desired limb position decoded from the brain, there are multiple combinations of muscle stimulation levels that can produce that position. The objective of this simulation study is to explore how modulating the amount of coactivation of antagonist muscles during FES can impact reaching performance and energy usage. Stiffening the limb by cocontracting antagonist muscles makes the limb more resistant to perturbation. Minimizing cocontraction saves energy and reduces fatigue. Approach. Prior demonstrations of reaching via FES used a fixed empirically-derived lookup table for each joint that defined the muscle stimulation levels that would position the limb at the desired joint angle decoded from the brain at each timestep. This study expands on that previous work by using simulations to: (a) test the feasibility of controlling arm reaching using a suite of lookup tables with varying levels of cocontraction instead of a single fixed lookup table for each joint, (b) optimize a simple function for automatically switching between these different cocontraction tables using only the desired kinematic information already being decoded from the brain, and (c) compare energy savings and movement performance when using the optimized function to automatically modulate cocontraction during reaching versus using the best fixed level of cocontraction. Main results. Our data suggests energy usage and/or movement performance can be significantly improved by dynamically modulating limb stiffness using our multi-table method and a simple function that determines cocontraction level based on decoded endpoint speed and its derivative. Significance. By demonstrating how modulating cocontraction can reduce energy usage while maintaining or even improving movement performance, this study makes brain-controlled FES a more viable option for restoration of reaching after paralysis.

Obesity remains prevalent in the US. One potential treatment is vagus nerve stimulation (VNS), which activates the sensory afferents innervating the stomach that convey stomach volume and establish satiety. However, current VNS approaches and stimulus optimization could benefit from additional understanding of the underlying neural response to stomach distension. In this study, obesity-prone Sprague Dawley rats consumed a standard, high-carbohydrate, or high-fat diet for several months, leading to diet-induced obesity in the latter two groups. Under anesthesia, the neural activity in the vagus nerve was recorded with a penetrating microelectrode array while the stomach was distended with an implanted balloon. Vagal tone during distension was compared to baseline tone prior to distension. Responses were strongly correlated with stomach distension, but the sensitivity to distension was significantly lower in animals that had been fed the nonstandard diets. The results indicate that both high fat and high carbohydrate diets impair vagus activity.

Progress has been made in the field of neural interfacing using both mouse and rat models, yet standardization of these models' interchangeability has yet to be established. The mouse model allows for transgenic, optogenetic, and advanced imaging modalities which can be used to examine the biological impact and failure mechanisms associated with the neural implant itself. The ability to directly compare electrophysiological data between mouse and rat models is crucial for the development and assessment of neural interfaces. The most obvious difference in the two rodent models is size, which raises concern for the role of device-induced tissue strain. Strain exerted on brain tissue by implanted microelectrode arrays is hypothesized to affect long-term recording performance. Therefore, understanding any potential differences in tissue strain caused by differences in the implant to tissue size ratio is crucial for validating the interchangeability of rat and mouse models. Hence, this study is aimed at investigating the electrophysiological variances and predictive device-induced tissue strain. Rat and mouse electrophysiological recordings were collected from implanted animals for eight weeks. A finite element model was utilized to assess the tissue strain from implanted intracortical microelectrodes, taking into account the differences in the depth within the cortex, implantation depth, and electrode geometry between the two models. The rat model demonstrated a larger percentage of channels recording single unit activity and number of units recorded per channel at acute but not chronic time points, relative to the mouse model Additionally, the finite element models also revealed no predictive differences in tissue strain between the two rodent models. Collectively our results show that these two models are comparable after taking into consideration some recommendations to maintain uniform conditions for future studies where direct comparisons of electrophysiological and tissue strain data between the two animal models will be required.

Long-term reliability of intracortical microelectrodes remains a challenge for increased acceptance and deployment. There are conflicting reports comparing measurements associated with recording quality with postmortem histology, in attempts to better understand failure of intracortical microelectrodes (IMEs). Our group has recently introduced the assessment of motor behavior tasks as another metric to evaluate the effects of IME implantation. We hypothesized that adding the third dimension to our analysis, functional behavior testing, could provide substantial insight on the health of the tissue, success of surgery/implantation, and the long-term performance of the implanted device. Here we present our novel analysis scheme including: (1) the use of numerical formal concept analysis (nFCA) and (2) a regression analysis utilizing modern model/variable selection. The analyses found complimentary relationships between the variables. The histological variables for glial cell activation had associations between each other, as well as the neuronal density around the electrode interface. The neuronal density had associations to the electrophysiological recordings and some of the motor behavior metrics analyzed. The novel analyses presented herein describe a valuable tool that can be utilized to assess and understand relationships between diverse variables being investigated. These models can be applied to a wide range of ongoing investigations utilizing various devices and therapeutics.

Field potentials (e.g. electroencephalograms, electrocorticograms, stereo-electoencephalograms, local field potentials from intracortical microelectrodes) all can provide brain state information for close-loop neuromodulation and neuroprosthetics applications. Large numbers of ‘features’ can be extracted from these field potentials (e.g. individual power bands, cross-frequency coupling) and field potentials can often be linearly combined to create additional signals from which to extract even more useful features for decoding. This abundance of features can be useful for decoding brain state information, such as Parkinsonian symptom state for a closed-loop deep brain stimulation or intended arm movement to control a neuroprosthesis. However, available features are often ignored to avoid degradation of decoder performance due to overfitting.

Introduction: Closed-loop neuromodulation and neuroprosthetic applications rely on accurately decoding one's brain state in real time. This decoding process first requires extracting the relevant 'features' or characteristics of the input signals to use in the decoding process. When using field potentials for decoding (e.g. electroencephalograms, electrocorticograms, stereoelectroencephalograms or local field potentials from intracortical microelectrodes), even a single recorded channel can potentially be expanded into hundreds of individual power features. Furthermore, features involving cross-frequency coupling-such as the phase-amplitude coupling accentuated in Parkinson's disease-can exponentially increase the number of features available for decoding from each individual channel. Finally, if more than one channel is recorded, the number of possible features grows by more than just the number of channels; additional power features can be generated by using different linear combinations of the raw signals. All these possible permutations result in a nearly infinite number of features available from just a handful of electrodes.

Intracortical microelectrodes afford researchers an effective tool to precisely monitor neural spiking activity. Additionally, intracortical microelectrodes have the ability to return function to individuals with paralysis as part of a brain computer interface. Unfortunately, the neural signals recorded by these electrodes degrade over time. Many strategies which target the biological and/or materials mediating failure modes of this decline of function are currently under investigation. The goal of this study is to identify a precise cellular target for future intervention to sustain chronic intracortical microelectrode performance. Previous work from our lab has indicated that the Cluster of Differentiation 14/Toll-like receptor pathway (CD14/TLR) is a viable target to improve chronic laminar, silicon intracortical microelectrode recordings. Here, we use a mouse bone marrow chimera model to selectively knockout CD14, an innate immune receptor, from either brain resident microglia or blood-derived macrophages, in order to understand the most effective targets for future therapeutic options. Using single-unit recordings we demonstrate that inhibiting CD14 from the blood-derived macrophages improves recording quality over the 16 week long study. We conclude that targeting CD14 in blood-derived cells should be part of the strategy to improve the performance of intracortical microelectrodes, and that the daunting task of delivering therapeutics across the blood-brain barrier may not be needed to increase intracortical microelectrode performance.

Objective. Neuroinflammatory mechanisms are hypothesized to contribute to intracortical microelectrode failures. The cluster of differentiation 14 (CD14) molecule is an innate immunity receptor involved in the recognition of pathogens and tissue damage to promote inflammation. The goal of the study was to investigate the effect of CD14 inhibition on intracortical microelectrode recording performance and tissue integration. Approach. Mice implanted with intracortical microelectrodes in the motor cortex underwent electrophysiological characterization for 16 weeks, followed by endpoint histology. Three conditions were examined: (1) wildtype control mice, (2) knockout mice lacking CD14, and (3) wildtype control mice administered a small molecule inhibitor to CD14 called IAXO-101. Main results. The CD14 knockout mice exhibited acute but not chronic improvements in intracortical microelectrode performance without significant differences in endpoint histology. Mice receiving IAXO-101 exhibited significant improvements in recording performance over the entire 16 week duration without significant differences in endpoint histology. Significance. Full removal of CD14 is beneficial at acute time ranges, but limited CD14 signaling is beneficial at chronic time ranges. Innate immunity receptor inhibition strategies have the potential to improve long-term intracortical microelectrode performance.

Objective. Neuroinflammatory mechanisms are hypothesized to contribute to intracortical microelectrode failures. The cluster of differentiation 14 (CD14) molecule is an innate immunity receptor involved in the recognition of pathogens and tissue damage to promote inflammation. The goal of the study was to investigate the effect of CD14 inhibition on intracortical microelectrode recording performance and tissue integration. Approach. Mice implanted with intracortical microelectrodes in the motor cortex underwent electrophysiological characterization for 16 weeks, followed by endpoint histology. Three conditions were examined: (1) wildtype control mice, (2) knockout mice lacking CD14, and (3) wildtype control mice administered a small molecule inhibitor to CD14 called IAXO101. Main results. The CD14 knockout mice exhibited acute but not chronic improvements in intracortical microelectrode performance without significant differences in endpoint histology. Journal of Neural Engineering Inhibition of the cluster of differentiation 14 innate immunity pathway with IAXO101 improves chronic microelectrode performance

Background: Custom-fitted skull replacement pieces are often used after a head injury or surgery to replace damaged bone. Chronic brain recordings are beneficial after injury/surgery for monitoring brain health and seizure development. Embedding electrodes directly in these artificial skull replacement pieces would be a novel, low-risk way to perform chronic brain monitoring in these patients. Similarly, embedding electrodes directly in healthy skull would be a viable minimally-invasive option for many other neuroscience and neurotechnology applications requiring chronic brain recordings.New method: We demonstrate a preclinical testbed that can be used for refining electrode designs embedded in artificial skull replacement pieces or for embedding directly into the skull itself. Options are explored to increase the surface area of the contacts without increasing recording contact diameter to maximize recording resolution.Results: Embedding electrodes in real or artificial skull allows one to lower electrode impedance without increasing the recording contact diameter by making use of conductive channels that extend into the skull. The higher density of small contacts embedded in the artificial skull in this testbed enables one to optimize electrode spacing for use in real bone.Comparison with existing methods: For brain monitoring applications, skull-embedded electrodes fill a gap between electroencephalograms recorded on the scalp surface and the more invasive epidural or subdural electrode sheets.Conclusions: Embedding electrodes into the skull or in skull replacement pieces may provide a safe, convenient, minimally-invasive alternative for chronic brain monitoring. The manufacturing methods described here will facilitate further testing of skull-embedded electrodes in animal models. Published by Elsevier B.V.