Advances in Implantable Microelectrode Array Insertion and Positioning.

OBJECTIVES: Microelectrode arrays offer a means to probe the functional circuitry of the brain and the promise of cortical neuroprosthesis for individuals suffering from paralysis or limb loss. These devices are typically comprised of one or more shanks incorporating microelectrode sites, where the shanks are positioned by inserting the devices along a straight path that is normal to the brain surface. The lack of consistent long-term chronic recording technology has driven interest in novel probe design and approaches that go beyond the standard insertion approach that is limited to a single velocity or axis. This review offers a description of typical approaches and associated limitations and surveys emergent methods for implantation of microelectrode arrays, in particular those new approaches that leverage embedded microactuators and extend the insertion direction beyond a single axis. MATERIALS AND METHODS: This review paper surveys the current technologies that enable probe implantation, repositioning, and the capability to record/stimulate from a tissue volume. A comprehensive literature search was performed using PubMed, Web of Science, and Google Scholar. RESULTS: There has been substantial innovation in the development of microscale and embedded technology that enables probe repositioning to maintain quality recordings in the brain. Innovations in material science have resulted in novel strategies for deployable structures that can record from or stimulate a tissue volume. Moreover, new developments involving magnetically steerable catheters and needles offer an alternative approach to "pull" rather than "push" a probe into the tissue. CONCLUSION: We envision the emergence of a new generation of probes and insertion methodologies for neuromodulation applications that enable reliable chronic performance from devices that can be positioned virtually anywhere in the brain.

Liquid Crystalline Polymers: Opportunities to Shape Neural Interfaces.

OBJECTIVES: Polymers have emerged as constituent materials for the creation of microscale neural interfaces; however, limitations regarding water permeability, delamination, and material degradation impact polymeric device robustness. Liquid crystal polymers (LCPs) have molecular order like a solid but with the fluidity of a liquid, resulting in a unique material, with properties including low water permeability, chemical inertness, and mechanical toughness. The objective of this article is to review the state-of-the-art regarding the use of LCPs in neural interface applications and discuss challenges and opportunities where this class of materials can advance the field of neural interfaces. MATERIALS AND METHODS: This review article focuses on studies that leverage LCP materials to interface with the nervous system in vivo. A comprehensive literature search was performed using PubMed, Web of Science (Clarivate Analytics), and Google Scholar. RESULTS: There have been recent efforts to create neural interfaces that leverage the material advantages of LCPs. The literature offers examples of LCP as a basis for implantable medical devices and neural interfaces in the form of planar electrode arrays for retinal prosthetic, electrocorticography applications, and cuff-like structures for interfacing the peripheral nerve. In addition, there have been efforts to create penetrating intracortical devices capable of microstimulation and resolution of biopotentials. Recent work with a subclass of LCPs, namely liquid crystal elastomers, demonstrates that it is possible to create devices with features that deploy away from a central implantation site to interface with a volume of tissue while offering the possibility of minimizing tissue damage. CONCLUSION: We envision the creation of novel microscale neural interfaces that leverage the physical properties of LCPs and have the capability of deploying within neural tissue for enhanced integration and performance.

Gold nanostructure microelectrode arrays for in vitro recording and stimulation from neuronal networks.

An ideal microelectrode array (MEA) design should include materials and structures which exhibit biocompatibility, low electrode polarization, low impedance/noise, and structural durability. Here, the fabrication of MEAs with indium tin oxide (ITO) electrodes deposited with self-similar gold nanostructures (GNS) is described. We show that fern leaf fractal-like GNS deposited on ITO electrodes are conducive for neural cell attachment and viability while reducing the interfacial impedance more than two orders of magnitude at low frequencies (100-1000 Hz) versus bare ITO. GNS MEAs, with low interfacial impedance, allowed the detection of extracellular action potentials with excellent signal-to-noise ratios (SNR, 20.26 ± 2.14). Additionally, the modified electrodes demonstrated electrochemical and mechanical stability over 29 d in vitro.

The MNK-eIF4E Signaling Axis Contributes to Injury-Induced Nociceptive Plasticity and the Development of Chronic Pain.

Injury-induced sensitization of nociceptors contributes to pain states and the development of chronic pain. Inhibiting activity-dependent mRNA translation through mechanistic target of rapamycin and mitogen-activated protein kinase (MAPK) pathways blocks the development of nociceptor sensitization. These pathways convergently signal to the eukaryotic translation initiation factor (eIF) 4F complex to regulate the sensitization of nociceptors, but the details of this process are ill defined. Here we investigated the hypothesis that phosphorylation of the 5' cap-binding protein eIF4E by its specific kinase MAPK interacting kinases (MNKs) 1/2 is a key factor in nociceptor sensitization and the development of chronic pain. Phosphorylation of ser209 on eIF4E regulates the translation of a subset of mRNAs. We show that pronociceptive and inflammatory factors, such as nerve growth factor (NGF), interleukin-6 (IL-6), and carrageenan, produce decreased mechanical and thermal hypersensitivity, decreased affective pain behaviors, and strongly reduced hyperalgesic priming in mice lacking eIF4E phosphorylation (eIF4ES209A ). Tests were done in both sexes, and no sex differences were found. Moreover, in patch-clamp electrophysiology and Ca2+ imaging experiments on dorsal root ganglion neurons, NGF- and IL-6-induced increases in excitability were attenuated in neurons from eIF4ES209A mice. These effects were recapitulated in Mnk1/2-/- mice and with the MNK1/2 inhibitor cercosporamide. We also find that cold hypersensitivity induced by peripheral nerve injury is reduced in eIF4ES209A and Mnk1/2-/- mice and following cercosporamide treatment. Our findings demonstrate that the MNK1/2-eIF4E signaling axis is an important contributing factor to mechanisms of nociceptor plasticity and the development of chronic pain.SIGNIFICANCE STATEMENT Chronic pain is a debilitating disease affecting approximately one in three Americans. Chronic pain is thought to be driven by changes in the excitability of peripheral nociceptive neurons, but the precise mechanisms controlling these changes are not elucidated. Emerging evidence demonstrates that mRNA translation regulation pathways are key factors in changes in nociceptor excitability. Our work demonstrates that a single phosphorylation site on the 5' cap-binding protein eIF4E is a critical mechanism for changes in nociceptor excitability that drive the development of chronic pain. We reveal a new mechanistic target for the development of a chronic pain state and propose that targeting the upstream kinase, MAPK interacting kinase 1/2, could be used as a therapeutic approach for chronic pain.

Chronic recording and electrochemical performance of Utah microelectrode arrays implanted in rat motor cortex.

Multisite implantable electrode arrays serve as a tool to understand cortical network connectivity and plasticity. Furthermore, they enable electrical stimulation to drive plasticity, study motor/sensory mapping, or provide network input for controlling brain-computer interfaces. Neurobehavioral rodent models are prevalent in studies of motor cortex injury and recovery as well as restoration of auditory/visual cues due to their relatively low cost and ease of training. Therefore, it is important to understand the chronic performance of relevant electrode arrays in rodent models. In this report, we evaluate the chronic recording and electrochemical performance of 16-channel Utah electrode arrays, the current state-of-the-art in pre-/clinical cortical recording and stimulation, in rat motor cortex over a period of 6 mo. The single-unit active electrode yield decreased from 52.8 ± 10.0 ( week 1) to 13.4 ± 5.1% ( week 24). Similarly, the total number of single units recorded on all electrodes across all arrays decreased from 106 to 15 over the same time period. Parallel measurements of electrochemical impedance spectra and cathodic charge storage capacity exhibited significant changes in electrochemical characteristics consistent with development of electrolyte leakage pathways over time. Additionally, measurements of maximum cathodal potential excursion indicated that only a relatively small fraction of electrodes (10-35% at 1 and 24 wk postimplantation) were capable of delivering relevant currents (20 µA at 4 nC/ph) without exceeding negative or positive electrochemical potential limits. In total, our findings suggest mainly abiotic failure modes, including mechanical wire breakage as well as degradation of conducting and insulating substrates. NEW & NOTEWORTHY Multisite implantable electrode arrays serve as a tool to record cortical network activity and enable electrical stimulation to drive plasticity or provide network feedback. The use of rodent models in these fields is prevalent. We evaluated chronic recording and electrochemical performance of 16-channel Utah electrode arrays in rat motor cortex over a period of 6 mo. We primarily observed abiotic failure modes suggestive of mechanical wire breakage and/or degradation of insulation.

Adult mouse sensory neurons on microelectrode arrays exhibit increased spontaneous and stimulus-evoked activity in the presence of interleukin-6.

Following inflammation or injury, sensory neurons located in the dorsal root ganglia (DRG) may exhibit increased spontaneous and/or stimulus-evoked activity, contributing to chronic pain. Current treatment options for peripherally mediated chronic pain are highly limited, driving the development of cell- or tissue-based phenotypic (function-based) screening assays for peripheral analgesic and mechanistic lead discovery. Extant assays are often limited by throughput, content, use of tumorigenic cell lines, or tissue sources from immature developmental stages (i.e., embryonic or postnatal). Here, we describe a protocol for culturing adult mouse DRG neurons on substrate-integrated multiwell microelectrode arrays (MEAs). This approach enables multiplexed measurements of spontaneous as well as stimulus-evoked extracellular action potentials from large populations of cells. The DRG cultures exhibit stable spontaneous activity from 9 to 21 days in vitro. Activity is readily evoked by known chemical and physical agonists of sensory neuron activity such as capsaicin, bradykinin, PGE2, heat, and electrical field stimulation. Most importantly, we demonstrate that both spontaneous and stimulus-evoked activity may be potentiated by incubation with the inflammatory cytokine interleukin-6 (IL-6). Acute responsiveness to IL-6 is inhibited by treatment with a MAPK-interacting kinase 1/2 inhibitor, cercosporamide. In total, these findings suggest that adult mouse DRG neurons on multiwell MEAs are applicable to ongoing efforts to discover peripheral analgesic and their mechanisms of action. NEW & NOTEWORTHY This work describes methodologies for culturing spontaneously active adult mouse dorsal root ganglia (DRG) sensory neurons on microelectrode arrays. We characterize spontaneous and stimulus-evoked adult DRG activity over durations consistent with pharmacological interventions. Furthermore, persistent hyperexcitability could be induced by incubation with inflammatory cytokine IL-6 and attenuated with cercosporamide, an inhibitor of the IL-6 sensitization pathway. This constitutes a more physiologically relevant, moderate-throughput in vitro model for peripheral analgesic screening as well as mechanistic lead discovery.

A patterned polystyrene-based microelectrode array for in vitro neuronal recordings.

Substrate-integrated microelectrode arrays (MEAs) are non-invasive platforms for recording supra-threshold signals, i.e. action potentials or spikes, from a variety of cultured electrically active cells, and are useful for pharmacological and toxicological studies. However, the MEA substrate, which is often fabricated using semiconductor processing technology, presents some challenges to the user. Specifically, the electrode encapsulation, which may consist of a variety of inorganic and organic materials, requires a specific substrate preparation protocol to optimize cell adhesion to the surface. Often, these protocols differ from and are more complex than traditional protocols for in vitro cell culture in polystyrene petri dishes. Here, we describe the fabrication of an MEA with indium tin oxide microelectrodes and a patterned polystyrene electrode encapsulation. We demonstrate the electrochemical stability of the electrodes and encapsulation, and show viable cell culture and in vitro recordings.

Thinking Small: Progress on Microscale Neurostimulation Technology.

OBJECTIVES: Neural stimulation is well-accepted as an effective therapy for a wide range of neurological disorders. While the scale of clinical devices is relatively large, translational, and pilot clinical applications are underway for microelectrode-based systems. Microelectrodes have the advantage of stimulating a relatively small tissue volume which may improve selectivity of therapeutic stimuli. Current microelectrode technology is associated with chronic tissue response which limits utility of these devices for neural recording and stimulation. One approach for addressing the tissue response problem may be to reduce physical dimensions of the device. "Thinking small" is a trend for the electronics industry, and for implantable neural interfaces, the result may be a device that can evade the foreign body response. MATERIALS AND METHODS: This review paper surveys our current understanding pertaining to the relationship between implant size and tissue response and the state-of-the-art in ultrasmall microelectrodes. A comprehensive literature search was performed using PubMed, Web of Science (Clarivate Analytics), and Google Scholar. RESULTS: The literature review shows recent efforts to create microelectrodes that are extremely thin appear to reduce or even eliminate the chronic tissue response. With high charge capacity coatings, ultramicroelectrodes fabricated from emerging polymers, and amorphous silicon carbide appear promising for neurostimulation applications. CONCLUSION: We envision the emergence of robust and manufacturable ultramicroelectrodes that leverage advanced materials where the small cross-sectional geometry enables compliance within tissue. Nevertheless, future testing under in vivo conditions is particularly important for assessing the stability of thin film devices under chronic stimulation.

NeurostimML: a machine learning model for predicting neurostimulation-induced tissue damage.

Objective. The safe delivery of electrical current to neural tissue depends on many factors, yet previous methods for predicting tissue damage rely on only a few stimulation parameters. Here, we report the development of a machine learning approach that could lead to a more reliable method for predicting electrical stimulation-induced tissue damage by incorporating additional stimulation parameters.Approach. A literature search was conducted to build an initial database of tissue response information after electrical stimulation, categorized as either damaging or non-damaging. Subsequently, we used ordinal encoding and random forest for feature selection, and investigated four machine learning models for classification: Logistic Regression, K-nearest Neighbor, Random Forest, and Multilayer Perceptron. Finally, we compared the results of these models against the accuracy of the Shannon equation.Main Results. We compiled a database with 387 unique stimulation parameter combinations collected from 58 independent studies conducted over a period of 47 years, with 195 (51%) categorized as non-damaging and 190 (49%) categorized as damaging. The features selected for building our model with a Random Forest algorithm were: waveform shape, geometric surface area, pulse width, frequency, pulse amplitude, charge per phase, charge density, current density, duty cycle, daily stimulation duration, daily number of pulses delivered, and daily accumulated charge. The Shannon equation yielded an accuracy of 63.9% using akvalue of 1.79. In contrast, the Random Forest algorithm was able to robustly predict whether a set of stimulation parameters was classified as damaging or non-damaging with an accuracy of 88.3%.Significance. This novel Random Forest model can facilitate more informed decision making in the selection of neuromodulation parameters for both research studies and clinical practice. This study represents the first approach to use machine learning in the prediction of stimulation-induced neural tissue damage, and lays the groundwork for neurostimulation driven by machine learning models.

Real-Time Assessment of Rodent Engagement Using ArUco Markers: A Scalable and Accessible Approach for Scoring Behavior in a Nose-Poking Go/No-Go Task.

In the field of behavioral neuroscience, the classification and scoring of animal behavior play pivotal roles in the quantification and interpretation of complex behaviors displayed by animals. Traditional methods have relied on video examination by investigators, which is labor-intensive and susceptible to bias. To address these challenges, research efforts have focused on computational methods and image-processing algorithms for automated behavioral classification. Two primary approaches have emerged: marker- and markerless-based tracking systems. In this study, we showcase the utility of "Augmented Reality University of Cordoba" (ArUco) markers as a marker-based tracking approach for assessing rat engagement during a nose-poking go/no-go behavioral task. In addition, we introduce a two-state engagement model based on ArUco marker tracking data that can be analyzed with a rectangular kernel convolution to identify critical transition points between states of engagement and distraction. In this study, we hypothesized that ArUco markers could be utilized to accurately estimate animal engagement in a nose-poking go/no-go behavioral task, enabling the computation of optimal task durations for behavioral testing. Here, we present the performance of our ArUco tracking program, demonstrating a classification accuracy of 98% that was validated against the manual curation of video data. Furthermore, our convolution analysis revealed that, on average, our animals became disengaged with the behavioral task at ∼75 min, providing a quantitative basis for limiting experimental session durations. Overall, our approach offers a scalable, efficient, and accessible solution for automated scoring of rodent engagement during behavioral data collection.

In Vitro Pharmacological Modulation of PIEZO1 Channels in Frontal Cortex Neuronal Networks.

PIEZO1 is a mechanosensitive ion channel expressed in various organs, including but not limited to the brain, heart, lungs, kidneys, bone, and skin. PIEZO1 has been implicated in astrocyte, microglia, capillary, and oligodendrocyte signaling in the mammalian cortex. Using murine embryonic frontal cortex tissue, we examined the protein expression and functionality of PIEZO1 channels in cultured networks leveraging substrate-integrated microelectrode arrays (MEAs) with additional quantitative results from calcium imaging and whole-cell patch-clamp electrophysiology. MEA data show that the PIEZO1 agonist Yoda1 transiently enhances the mean firing rate (MFR) of single units, while the PIEZO1 antagonist GsMTx4 inhibits both spontaneous activity and Yoda1-induced increase in MFR in cortical networks. Furthermore, calcium imaging experiments revealed that Yoda1 significantly increased the frequency of calcium transients in cortical cells. Additionally, in voltage clamp experiments, Yoda1 exposure shifted the cellular reversal potential towards depolarized potentials consistent with the behavior of PIEZO1 as a non-specific cation-permeable channel. Our work demonstrates that murine frontal cortical neurons express functional PIEZO1 channels and quantifies the electrophysiological effects of channel activation in vitro. By quantifying the electrophysiological effects of PIEZO1 activation in vitro, our study establishes a foundation for future investigations into the role of PIEZO1 in neurological processes and potential therapeutic applications targeting mechanosensitive channels in various physiological contexts.

How to differentiate induced pluripotent stem cells into sensory neurons for disease modelling: a functional assessment.

BACKGROUND: Human induced pluripotent stem cell (iPSC)-derived peripheral sensory neurons present a valuable tool to model human diseases and are a source for applications in drug discovery and regenerative medicine. Clinically, peripheral sensory neuropathies can result in maladies ranging from a complete loss of pain to severe painful neuropathic disorders. Sensory neurons are located in the dorsal root ganglion and are comprised of functionally diverse neuronal types. Low efficiency, reproducibility concerns, variations arising due to genetic factors and time needed to generate functionally mature neuronal populations from iPSCs remain key challenges to study human nociception in vitro. Here, we report a detailed functional characterization of iPSC-derived sensory neurons with an accelerated differentiation protocol ("Anatomic" protocol) compared to the most commonly used small molecule approach ("Chambers" protocol). Anatomic's commercially available RealDRG™ were further characterized for both functional and expression phenotyping of key nociceptor markers. METHODS: Multiple iPSC clones derived from different reprogramming methods, genetics, age, and somatic cell sources were used to generate sensory neurons. Manual patch clamp was used to functionally characterize both control and patient-derived neurons. High throughput techniques were further used to demonstrate that RealDRGs™ derived from the Anatomic protocol are amenable to high throughput technologies for disease modelling. RESULTS: The Anatomic protocol rendered a purer culture without the use of mitomycin C to suppress non-neuronal outgrowth, while Chambers differentiations yielded a mix of cell types. Chambers protocol results in predominantly tonic firing when compared to Anatomic protocol. Patient-derived nociceptors displayed higher frequency firing compared to control subject with both, Chambers and Anatomic differentiation approaches, underlining their potential use for clinical phenotyping as a disease-in-a-dish model. RealDRG™ sensory neurons show heterogeneity of nociceptive markers indicating that the cells may be useful as a humanized model system for translational studies. CONCLUSIONS: We validated the efficiency of two differentiation protocols and their potential application for functional assessment and thus understanding the disease mechanisms from patients suffering from pain disorders. We propose that both differentiation methods can be further exploited for understanding mechanisms and development of novel treatments in pain disorders.

Reactive Amine Functionalized Microelectrode Arrays Provide Short-Term Benefit but Long-Term Detriment to In Vivo Recording Performance.

Intracortical microelectrode arrays (MEAs) are used for recording neural signals. However, indwelling devices result in chronic neuroinflammation, which leads to decreased recording performance through degradation of the device and surrounding tissue. Coating the MEAs with bioactive molecules is being explored to mitigate neuroinflammation. Such approaches often require an intermediate functionalization step such as (3-aminopropyl)triethoxysilane (APTES), which serves as a linker. However, the standalone effect of this intermediate step has not been previously characterized. Here, we investigated the effect of coating MEAs with APTES by comparing APTES-coated to uncoated controls in vivo and ex vivo. First, we measured water contact angles between silicon uncoated and APTES-coated substrates to verify the hydrophilic characteristics of the APTES coating. Next, we implanted MEAs in the motor cortex (M1) of Sprague-Dawley rats with uncoated or APTES-coated devices. We assessed changes in the electrochemical impedance and neural recording performance over a chronic implantation period of 16 weeks. Additionally, histology and bulk gene expression were analyzed to understand further the reactive tissue changes arising from the coating. Results showed that APTES increased the hydrophilicity of the devices and decreased electrochemical impedance at 1 kHz. APTES coatings proved detrimental to the recording performance, as shown by a constant decay up to 16 weeks postimplantation. Bulk gene analysis showed differential changes in gene expression between groups that were inconclusive with regard to the long-term effect on neuronal tissue. Together, these results suggest that APTES coatings are ultimately detrimental to chronic neural recordings. Furthermore, interpretations of studies using APTES as a functionalization step should consider the potential consequences if the final functionalization step is incomplete.

Planar amorphous silicon carbide microelectrode arrays for chronic recording in rat motor cortex.

Chronic implantation of intracortical microelectrode arrays (MEAs) capable of recording from individual neurons can be used for the development of brain-machine interfaces. However, these devices show reduced recording capabilities under chronic conditions due, at least in part, to the brain's foreign body response (FBR). This creates a need for MEAs that can minimize the FBR to possibly enable long-term recording. A potential approach to reduce the FBR is the use of MEAs with reduced cross-sectional geometries. Here, we fabricated 4-shank amorphous silicon carbide (a-SiC) MEAs and implanted them into the motor cortex of seven female Sprague-Dawley rats. Each a-SiC MEA shank was 8 µm thick by 20 µm wide and had sixteen sputtered iridium oxide film (SIROF) electrodes (4 per shank). A-SiC was chosen as the fabrication base for its high chemical stability, good electrical insulation properties, and amenability to thin film fabrication. Electrochemical analysis and neural recordings were performed weekly for 4 months. MEAs were characterized pre-implantation in buffered saline and in vivo using electrochemical impedance spectroscopy and cyclic voltammetry at 50 mV/s and 50,000 mV/s. Neural recordings were analyzed for single unit activity. At the end of the study, animals were sacrificed for immunohistochemical analysis. We observed statistically significant, but small, increases in 1 and 30 kHz impedance values and 50,000 mV/s charge storage capacity over the 16-week implantation period. Slow sweep 50 mV/s CV and 1 Hz impedance did not significantly change over time. Impedance values increased from 11.6 MΩ to 13.5 MΩ at 1 Hz, 1.2 MΩ-2.9 MΩ at 1 kHz, and 0.11 MΩ-0.13 MΩ at 30 kHz over 16 weeks. The median charge storage capacity of the implanted electrodes at 50 mV/s was 58.1 mC/cm2 on week 1 and 55.9 mC/cm2 on week 16, and at 50,000 mV/s, 4.27 mC/cm2 on week 1 and 5.93 mC/cm2 on week 16. Devices were able to record neural activity from 92% of all active channels at the beginning of the study, At the study endpoint, a-SiC devices were still recording single-unit activity on 51% of electrochemically active electrode channels. In addition, we observed that the signal-to-noise ratio experienced a small decline of -0.19 per week. We also classified observed units as fast and slow repolarizing based on the trough-to-peak time. Although the overall presence of single units declined, fast and slow repolarizing units declined at a similar rate. At recording electrode depth, immunohistochemistry showed minimal tissue response to the a-SiC devices, as indicated by statistically insignificant differences in activated glial cell response between implanted brains slices and contralateral sham slices at 150 µm away from the implant location, as evidenced by GFAP staining. NeuN staining revealed the presence of neuronal cell bodies close to the implantation site, again statistically not different from a contralateral sham slice. These results warrant further investigation of a-SiC MEAs for future long-term implantation neural recording studies.

NeurostimML: A machine learning model for predicting neurostimulation-induced tissue damage.

Objective: The safe delivery of electrical current to neural tissue depends on many factors, yet previous methods for predicting tissue damage rely on only a few stimulation parameters. Here, we report the development of a machine learning approach that could lead to a more reliable method for predicting electrical stimulation-induced tissue damage by incorporating additional stimulation parameters. Approach: A literature search was conducted to build an initial database of tissue response information after electrical stimulation, categorized as either damaging or non-damaging. Subsequently, we used ordinal encoding and random forest for feature selection, and investigated four machine learning models for classification: Logistic Regression, K-nearest Neighbor, Random Forest, and Multilayer Perceptron. Finally, we compared the results of these models against the accuracy of the Shannon equation. Main Results: We compiled a database with 387 unique stimulation parameter combinations collected from 58 independent studies conducted over a period of 47 years, with 195 (51%) categorized as non-damaging and 190 (49%) categorized as damaging. The features selected for building our model with a Random Forest algorithm were: waveform shape, geometric surface area, pulse width, frequency, pulse amplitude, charge per phase, charge density, current density, duty cycle, daily stimulation duration, daily number of pulses delivered, and daily accumulated charge. The Shannon equation yielded an accuracy of 63.9% using a k value of 1.79. In contrast, the Random Forest algorithm was able to robustly predict whether a set of stimulation parameters was classified as damaging or non-damaging with an accuracy of 88.3%. Significance: This novel Random Forest model can facilitate more informed decision making in the selection of neuromodulation parameters for both research studies and clinical practice. This study represents the first approach to use machine learning in the prediction of stimulation-induced neural tissue damage, and lays the groundwork for neurostimulation driven by machine learning models.

Isolation of the murine Glut1 deficient thalamocortical circuit: wavelet characterization and reverse glucose dependence of low and gamma frequency oscillations.

Glucose represents the principal brain energy source. Thus, not unexpectedly, genetic glucose transporter 1 (Glut1) deficiency (G1D) manifests with encephalopathy. G1D seizures, which constitute a prominent disease manifestation, often prove refractory to medications but may respond to therapeutic diets. These seizures are associated with aberrant thalamocortical oscillations as inferred from human electroencephalography and functional imaging. Mouse electrophysiological recordings indicate that inhibitory neuron failure in thalamus and cortex underlies these abnormalities. This provides the motivation to develop a neural circuit testbed to characterize the mechanisms of thalamocortical synchronization and the effects of known or novel interventions. To this end, we used mouse thalamocortical slices on multielectrode arrays and characterized spontaneous low frequency oscillations and less frequent 30-50 Hz or gamma oscillations under near-physiological bath glucose concentration. Using the cortical recordings from layer IV, we quantified oscillation epochs via an automated wavelet-based algorithm. This method proved analytically superior to power spectral density, short-time Fourier transform or amplitude-threshold detection. As expected from human observations, increased bath glucose reduced the lower frequency oscillations while augmenting the gamma oscillations, likely reflecting strengthened inhibitory neuron activity. This approach provides an ex vivo method for the evaluation of mechanisms, fuels, and pharmacological agents in a crucial G1D epileptogenic circuit.

Behavioral paradigm for the evaluation of stimulation-evoked somatosensory perception thresholds in rats.

Intracortical microstimulation (ICMS) of the somatosensory cortex via penetrating microelectrode arrays (MEAs) can evoke cutaneous and proprioceptive sensations for restoration of perception in individuals with spinal cord injuries. However, ICMS current amplitudes needed to evoke these sensory percepts tend to change over time following implantation. Animal models have been used to investigate the mechanisms by which these changes occur and aid in the development of new engineering strategies to mitigate such changes. Non-human primates are commonly the animal of choice for investigating ICMS, but ethical concerns exist regarding their use. Rodents are a preferred animal model due to their availability, affordability, and ease of handling, but there are limited choices of behavioral tasks for investigating ICMS. In this study, we investigated the application of an innovative behavioral go/no-go paradigm capable of estimating ICMS-evoked sensory perception thresholds in freely moving rats. We divided animals into two groups, one receiving ICMS and a control group receiving auditory tones. Then, we trained the animals to nose-poke - a well-established behavioral task for rats - following either a suprathreshold ICMS current-controlled pulse train or frequency-controlled auditory tone. Animals received a sugar pellet reward when nose-poking correctly. When nose-poking incorrectly, animals received a mild air puff. After animals became proficient in this task, as defined by accuracy, precision, and other performance metrics, they continued to the next phase for perception threshold detection, where we varied the ICMS amplitude using a modified staircase method. Finally, we used non-linear regression to estimate perception thresholds. Results indicated that our behavioral protocol could estimate ICMS perception thresholds based on ~95% accuracy of rat nose-poke responses to the conditioned stimulus. This behavioral paradigm provides a robust methodology for evaluating stimulation-evoked somatosensory percepts in rats comparable to the evaluation of auditory percepts. In future studies, this validated methodology can be used to study the performance of novel MEA device technologies on ICMS-evoked perception threshold stability using freely moving rats or to investigate information processing principles in neural circuits related to sensory perception discrimination.

Behavioral Paradigm for the Evaluation of Stimulation-Evoked Somatosensory Perception Thresholds in Rats.

Intracortical microstimulation (ICMS) of the somatosensory cortex via penetrating microelectrode arrays (MEAs) can evoke cutaneous and proprioceptive sensations for restoration of perception in individuals with spinal cord injuries. However, ICMS current amplitudes needed to evoke these sensory percepts tend to change over time following implantation. Animal models have been used to investigate the mechanisms by which these changes occur and aid in the development of new engineering strategies to mitigate such changes. Non-human primates are commonly the animal of choice for investigating ICMS, but ethical concerns exist regarding their use. Rodents are a preferred animal model due to their availability, affordability, and ease of handling, but there are limited choices of behavioral tasks for investigating ICMS. In this study, we investigated the application of an innovative behavioral go/no-go paradigm capable of estimating ICMS-evoked sensory perception thresholds in freely moving rats. We divided animals into two groups, one receiving ICMS and a control group receiving auditory tones. Then, we trained the animals to nose-poke - a well-established behavioral task for rats - following either a suprathreshold ICMS current-controlled pulse train or frequency-controlled auditory tone. Animals received a sugar pellet reward when nose-poking correctly. When nose-poking incorrectly, animals received a mild air puff. After animals became proficient in this task, as defined by accuracy, precision, and other performance metrics, they continued to the next phase for perception threshold detection, where we varied the ICMS amplitude using a modified staircase method. Finally, we used non-linear regression to estimate perception thresholds. Results indicated that our behavioral protocol could estimate ICMS perception thresholds based on ∼95% accuracy of rat nose-poke responses to the conditioned stimulus. This behavioral paradigm provides a robust methodology for evaluating stimulation-evoked somatosensory percepts in rats comparable to the evaluation of auditory percepts. In future studies, this validated methodology can be used to study the performance of novel MEA device technologies on ICMS-evoked perception threshold stability using freely moving rats or to investigate information processing principles in neural circuits related to sensory perception discrimination.

Chronic Stability of Local Field Potentials Using Amorphous Silicon Carbide Microelectrode Arrays Implanted in the Rat Motor Cortex.

Implantable microelectrode arrays (MEAs) enable the recording of electrical activity of cortical neurons, allowing the development of brain-machine interfaces. However, MEAs show reduced recording capabilities under chronic conditions, prompting the development of novel MEAs that can improve long-term performance. Conventional planar, silicon-based devices and ultra-thin amorphous silicon carbide (a-SiC) MEAs were implanted in the motor cortex of female Sprague-Dawley rats, and weekly anesthetized recordings were made for 16 weeks after implantation. The spectral density and bandpower between 1 and 500 Hz of recordings were compared over the implantation period for both device types. Initially, the bandpower of the a-SiC devices and standard MEAs was comparable. However, the standard MEAs showed a consistent decline in both bandpower and power spectral density throughout the 16 weeks post-implantation, whereas the a-SiC MEAs showed substantially more stable performance. These differences in bandpower and spectral density between standard and a-SiC MEAs were statistically significant from week 6 post-implantation until the end of the study at 16 weeks. These results support the use of ultra-thin a-SiC MEAs to develop chronic, reliable brain-machine interfaces.