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.

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.

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.

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.

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.

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.

The effect of a Mn(III)tetrakis(4-benzoic acid)porphyrin (MnTBAP) coating on the chronic recording performance of planar silicon intracortical microelectrode arrays.

Intracortical microelectrode arrays (MEAs) are used to record neural activity. However, their implantation initiates a neuroinflammatory cascade, involving the accumulation of reactive oxygen species, leading to interface failure. Here, we coated commercially-available MEAs with Mn(III)tetrakis(4-benzoic acid)porphyrin (MnTBAP), to mitigate oxidative stress. First, we assessed the in vitro cytotoxicity of modified sample substrates. Then, we implanted 36 rats with uncoated, MnTBAP-coated ("Coated"), or (3-Aminopropyl)triethoxysilane (APTES)-coated devices - an intermediate step in the coating process. We assessed electrode performance during the acute (1-5 weeks), sub-chronic (6-11 weeks), and chronic (12-16 weeks) phases after implantation. Three subsets of animals were euthanized at different time points to assess the acute, sub-chronic and chronic immunohistological responses. Results showed that MnTBAP coatings were not cytotoxic in vitro, and their implantation in vivo improved the proportion of electrodes during the sub-chronic and chronic phases; APTES coatings resulted in failure of the neural interface during the chronic phase. In addition, MnTBAP coatings improved the quality of the signal throughout the study and reduced the neuroinflammatory response around the implant as early as two weeks, an effect that remained consistent for months post-implantation. Together, these results suggest that MnTBAP coatings are a potentially useful modification to improve MEA reliability.

How to differentiate induced pluripotent stem cells into sensory neurons for disease modelling: a comparison of two protocols.

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 symptoms. 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 for disease modelling remain key challenges to study human nociception in vitro. Here, we report a detailed characterization of iPSC-derived sensory neurons with an accelerated differentiation protocol ("Anatomic" protocol) compared to the most commonly used small molecule approach ("Chambers" protocol). Methods: Multiple iPSC clones derived from different reprogramming methods, genetics, age, and somatic cell sources were used to generate sensory neurons. Expression profiling of sensory neurons was performed with Immunocytochemistry and in situ hybridization techniques. Manual patch clamp and high throughput cellular screening systems (Fluorescence imaging plate reader, automated patch clamp and multi-well microelectrode arrays recordings) were applied to functionally characterize the generated sensory neurons. 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. High throughput systems confirmed functional expression of Na+ and K+ ion channels. Multi-well microelectrode recordings display spontaneously active neurons with sensitivity to increased temperature indicating expression of heat sensitive ion channels. 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. Conclusions: We validated the efficiency of two differentiation protocols and their potential application for 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.

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 among other regions recorded, 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, and thus decreasing the low:high frequency ratio (LHR). This approach provides an ex vivo method for the evaluation of mechanisms, fuels, and pharmacological agents in a crucial G1D epileptogenic circuit.

Antioxidant Dimethyl Fumarate Temporarily but Not Chronically Improves Intracortical Microelectrode Performance.

Intracortical microelectrode arrays (MEAs) can be used in a range of applications, from basic neuroscience research to providing an intimate interface with the brain as part of a brain-computer interface (BCI) system aimed at restoring function for people living with neurological disorders or injuries. Unfortunately, MEAs tend to fail prematurely, leading to a loss in functionality for many applications. An important contributing factor in MEA failure is oxidative stress resulting from chronically inflammatory-activated microglia and macrophages releasing reactive oxygen species (ROS) around the implant site. Antioxidants offer a means for mitigating oxidative stress and improving tissue health and MEA performance. Here, we investigate using the clinically available antioxidant dimethyl fumarate (DMF) to reduce the neuroinflammatory response and improve MEA performance in a rat MEA model. Daily treatment of DMF for 16 weeks resulted in a significant improvement in the recording capabilities of MEA devices during the sub-chronic (Weeks 5-11) phase (42% active electrode yield vs. 35% for control). However, these sub-chronic improvements were lost in the chronic implantation phase, as a more exacerbated neuroinflammatory response occurs in DMF-treated animals by 16 weeks post-implantation. Yet, neuroinflammation was indiscriminate between treatment and control groups during the sub-chronic phase. Although worse for chronic use, a temporary improvement (<12 weeks) in MEA performance is meaningful. Providing short-term improvement to MEA devices using DMF can allow for improved use for limited-duration studies. Further efforts should be taken to explore the mechanism behind a worsened neuroinflammatory response at the 16-week time point for DMF-treated animals and assess its usefulness for specific applications.

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.

Tools for Surface Treatment of Silicon Planar Intracortical Microelectrodes.

Intracortical microelectrodes hold great therapeutic potential. But they are challenged with significant performance reduction after modest implantation durations. A substantial contributor to the observed decline is the damage to the neural tissue proximal to the implant and subsequent neuroinflammatory response. Efforts to improve device longevity include chemical modifications or coating applications to the device surface to improve the tissue response. Development of such surface treatments is typically completed using non-functional "dummy" probes that lack the electrical components required for the intended application. Translation to functional devices requires additional consideration given the fragility of intracortical microelectrode arrays. Handling tools greatly facilitate surface treatments to assembled devices, particularly for modifications that require long procedural times. The handling tools described here are used for surface treatments applied via gas-phase deposition and aqueous solution exposure. Characterization of the coating is performed using ellipsometry and x-ray photoelectron spectroscopy. A comparison of electrical impedance spectroscopy recordings before and after the coating procedure on functional devices confirmed device integrity following modification. The described tools can be readily adapted for alternative electrode devices and treatment methods that maintain chemical compatibility.

Characterization of Active Electrode Yield for Intracortical Arrays: Awake versus Anesthesia.

Intracortical microelectrode arrays are used for recording neural signals at single-unit resolution and are promising tools for studying brain function and developing neuroprosthetics. Research is being done to increase the chronic performance and reliability of these probes, which tend to decrease or fail within several months of implantation. Although recording paradigms vary, studies focused on assessing the reliability and performance of these devices often perform recordings under anesthesia. However, anesthetics-such as isoflurane-are known to alter neural activity and electrophysiologic function. Therefore, we compared the neural recording performance under anesthesia (2% isoflurane) followed by awake conditions for probes implanted in the motor cortex of both male and female Sprague-Dawley rats. While the single-unit spike rate was significantly higher by almost 600% under awake compared to anesthetized conditions, we found no difference in the active electrode yield between the two conditions two weeks after surgery. Additionally, the signal-to-noise ratio was greater under anesthesia due to the noise levels being nearly 50% greater in awake recordings, even though there was a 14% increase in the peak-to-peak voltage of distinguished single units when awake. We observe that these findings are similar for chronic time points as well. Our observations indicate that either anesthetized or awake recordings are acceptable for studies assessing the chronic reliability and performance of intracortical microelectrode arrays.

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.

Investigating the Function of Adult DRG Neuron Axons Using an In Vitro Microfluidic Culture System.

A critical role of the peripheral axons of nociceptors of the dorsal root ganglion (DRG) is the conduction of all-or-nothing action potentials from peripheral nerve endings to the central nervous system for the perception of noxious stimuli. Plasticity along multiple sites along the pain axis has now been widely implicated in the maladaptive changes that occur in pathological pain states such as neuropathic and inflammatory pain. Notably, increasing evidence suggests that nociceptive axons actively participate through the local expression of ion channels, receptors, and signal transduction molecules through axonal mRNA translation machinery that is independent of the soma component. In this report, we explore the sensitization of sensory neurons through the treatment of compartmentalized axon-like structures spanning microchannels that have been treated with the cytokine IL-6 and, subsequently, capsaicin. These data demonstrate the utility of isolating DRG axon-like structures using microfluidic systems, laying the groundwork for constructing the complex in vitro models of cellular networks that are involved in pain signaling for targeted pharmacological and genetic perturbations.