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Deception is considered a psychological process by which one individual deliberately attempts to convince another person to accept as true what the liar knows to be false. This paper presents the use of functional near-infrared spectroscopy for deception detection. This technique measures hemodynamic variations in the cortical regions induced by neural activations. The experimental setup involved a mock theft paradigm with ten subjects, where the subjects responded to a set of questions, with each of their answers belonging to one of three categories: Induced Lies, Induced Truths, and Non-Induced responses. The relative changes of the hemodynamic activity in the subject's prefrontal cortex were recorded during the experiment. From this data, the changes in blood volume were derived and represented as false color topograms. Finally, a human evaluator used these topograms as a guide to classify each answer into one of the three categories. His performance was compared with that of a support vector machine (SVM) classifier in terms of accuracy, specificity, and sensitivity. The human evaluator achieved an accuracy of 84.33 % in a tri-class problem and 92 % in a bi-class problem (induced vs. non-induced responses). In comparison, the SVM classifier correctly classified 95.63 % of the answers in a tri-class problem using cross-validation for the selection of the best features. These results suggest a tradeoff between accuracy and computational burden. In other words, it is possible for an interviewer to classify each response by only looking at the topogram of the hemodynamic activity, but at the cost of reduced prediction accuracy.
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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 â¼75â 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.
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Comportamento Animal , Roedores , Ratos , Animais , Algoritmos , Processamento de Imagem Assistida por ComputadorRESUMO
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.
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Aprendizado de Máquina , Humanos , Estimulação Elétrica/métodos , Algoritmos , Animais , Bases de Dados FactuaisRESUMO
Bioelectronic Medicine stands as an emerging field that rapidly evolves and offers distinctive clinical benefits, alongside unique challenges. It consists of the modulation of the nervous system by precise delivery of electrical current for the treatment of clinical conditions, such as post-stroke movement recovery or drug-resistant disorders. The unquestionable clinical impact of Bioelectronic Medicine is underscored by the successful translation to humans in the last decades, and the long list of preclinical studies. Given the emergency of accelerating the progress in new neuromodulation treatments (i.e., drug-resistant hypertension, autoimmune and degenerative diseases), collaboration between multiple fields is imperative. This work intends to foster multidisciplinary work and bring together different fields to provide the fundamental basis underlying Bioelectronic Medicine. In this review we will go from the biophysics of the cell membrane, which we consider the inner core of neuromodulation, to patient care. We will discuss the recently discovered mechanism of neurotransmission switching and how it will impact neuromodulation design, and we will provide an update on neuronal and glial basis in health and disease. The advances in biomedical technology have facilitated the collection of large amounts of data, thereby introducing new challenges in data analysis. We will discuss the current approaches and challenges in high throughput data analysis, encompassing big data, networks, artificial intelligence, and internet of things. Emphasis will be placed on understanding the electrochemical properties of neural interfaces, along with the integration of biocompatible and reliable materials and compliance with biomedical regulations for translational applications. Preclinical validation is foundational to the translational process, and we will discuss the critical aspects of such animal studies. Finally, we will focus on the patient point-of-care and challenges in neuromodulation as the ultimate goal of bioelectronic medicine. This review is a call to scientists from different fields to work together with a common endeavor: accelerate the decoding and modulation of the nervous system in a new era of therapeutic possibilities.
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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.
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Compostos Inorgânicos de Carbono , Eletrodos Implantados , Microeletrodos , Córtex Motor , Ratos Sprague-Dawley , Compostos de Silício , Animais , Compostos de Silício/química , Feminino , Córtex Motor/fisiologia , Córtex Motor/citologia , Compostos Inorgânicos de Carbono/química , Ratos , Neurônios/fisiologiaRESUMO
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.
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Aminas , Doenças Neuroinflamatórias , Ratos , Animais , Ratos Sprague-Dawley , Microeletrodos , Eletrodos Implantados , Materiais Revestidos Biocompatíveis/químicaRESUMO
Perineal and pelvic floor muscles play an important role in continence by providing mechanical support to pelvic organs. It is also known that the pubococcygeus muscle (PcM) contracts in the storage phase and is inactive during voiding, while the bulbospongiosus muscle (BsM) is active during the voiding phase. Recent evidence suggested an additional role of these muscles in supporting urethral closure in rabbits. However, the individual role of perineal and pelvic muscles as urethral sphincters is not well-defined. Here we evaluated the individual, sequential and synergistic roles of the PcM and BsM in assisting urethral closure and defined the optimal electrical stimulation parameters that can effectively contract these muscles and increase the urethral pressure (P ura ) in young nulliparous animals (n = 11). Unilateral stimulation of either the BsM or PcM at 40 Hz induced modest increases in average P ura (0.23 ± 0.10 and 0.07 ± 0.04 mmHg, respectively). Investigation on the changes in P ura evoked by stimulation frequencies between 5 and 60 Hz show that sequential contralateral PcM-BsM activation at 40 Hz induced a 2-fold average P ura increase (0.23 ± 0.07 mmHg) compared to that evoked by PcM stimulation. Simultaneous activation of PcM and BsM at 40 Hz also showed an increased average P ura (0.26 ± 0.04 mmHg), with a 2-fold increase in average P ura observed during the unilateral sequential PcM-BsM stimulation at 40 Hz (0.69 ± 0.2 mmHg). Finally, stimulation at 40 Hz of the bulbospongiosus nerve (BsN) induced an approximate 4-fold increase in average P ura (0.87 ± 0.44 mmHg; p < 0.04) compared to that elicited by BsM stimulation, confirming that direct nerve stimulation is more effective. Together, this study shows that in the female rabbit, both perineal and pelvic muscles support of the urethral function during continence, and that unilateral stimulation of the BsN at 40-60 Hz is sufficient to achieve maximal secondary sphincter activity. The results also support the potential clinical value of neuromodulation of pelvic and perineal nerves as bioelectronic therapy for stress urinary incontinence.
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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.
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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 â¼95% 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.
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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.
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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.
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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.
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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.
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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.
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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.
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Silício , Ratos , Animais , Microeletrodos , Reprodutibilidade dos Testes , Eletrodos ImplantadosRESUMO
Gyriform mammals display neurophysiological and neural network activity that other species exhibit only in rudimentary or dissimilar form. However, neural recordings from large mammals such as the pig can be anatomically hindered and pharmacologically suppressed by anesthetics. This curtails comparative inferences. To mitigate these limitations, we set out to modify electrocorticography, intracerebral depth and intracortical recording methods to study the anesthetized pig. In the process, we found that common forms of infused anesthesia such as pentobarbital or midazolam can be neurophysiologic suppressants acting in dose-independent fashion relative to anesthetic dose or brain concentration. Further, we corroborated that standard laboratory conditions may impose electrical interference with specific neural signals. We thus aimed to safeguard neural network integrity and recording fidelity by developing surgical, anesthesia and noise reduction methods and by working inside a newly designed Faraday cage, and evaluated this from the point of view of neurophysiological power spectral density and coherence analyses. We also utilized novel silicon carbide electrodes to minimize mechanical disruption of single-neuron activity. These methods allowed for the preservation of native neurophysiological activity for several hours. Pig electrocorticography recordings were essentially indistinguishable from awake human recordings except for the small segment of electrical activity associated with vision in conscious persons. In addition, single-neuron and paired-pulse stimulation recordings were feasible simultaneously with electrocorticography and depth electrode recordings. The spontaneous and stimulus-elicited neuronal activities thus surveyed can be recorded with a degree of precision similar to that achievable in rodent or any other animal studies and prove as informative as unperturbed human electrocorticography.
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Anestésicos , Vigília , Animais , Encéfalo/fisiologia , Humanos , Mamíferos , Midazolam , Neurônios/fisiologia , Pentobarbital , SuínosRESUMO
Pelvic floor muscle stretch injury during pregnancy and birth is associated with the incidence of stress urinary incontinence (SUI), a condition that affects 30-60% of the female population and is characterized by involuntary urine leakage during physical activity, further exacerbated by aging. Aging and multiparous rabbits suffer pelvic nerve and muscle damage, resulting in alterations in pelvic floor muscular contraction and low urethral pressure, resembling SUI. However, the extent of nerve injury is not fully understood. Here, we used electron microscopy analysis of pelvic and perineal nerves in multiparous rabbits to describe the extent of stretch nerve injury based on axon count, axon size, myelin-to-axon ratio, and elliptical ratio. Compared to young nulliparous controls, mid-age multiparous animals showed an increase in the density of unmyelinated axons and in myelin thickness in both nerves, albeit more significant in the bulbospongiosus nerve. This revealed a partial but sustained damage to these nerves, and the presence of some regenerated axons. Additionally, we tested whether electrical stimulation of the bulbospongiosus nerve would induce muscle contraction and urethral closure. Using a miniature wireless stimulator implanted on this perineal nerve in young nulliparous and middle age multiparous female rabbits, we confirmed that these partially damaged nerves can be acutely depolarized, either at low (2-5 Hz) or medium (10-20 Hz) frequencies, to induce a proportional increase in urethral pressure. Evaluation of micturition volume in the mid-age multiparous animals after perineal nerve stimulation, effectively reversed a baseline deficit, increasing it 2-fold (p = 0.02). These results support the notion that selective neuromodulation of pelvic floor muscles might serve as a potential treatment for SUI.
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Envelhecimento/fisiologia , Tecido Nervoso/fisiopatologia , Paridade/fisiologia , Diafragma da Pelve/inervação , Diafragma da Pelve/fisiopatologia , Incontinência Urinária por Estresse/fisiopatologia , Incontinência Urinária por Estresse/terapia , Animais , Axônios/fisiologia , Estimulação Elétrica , Feminino , Regeneração Nervosa/fisiologia , Tecido Nervoso/ultraestrutura , Diafragma da Pelve/lesões , Gravidez , Pressão , Coelhos , Urodinâmica/fisiologiaRESUMO
OBJECTIVE: Recent developments in peripheral nerve electrodes allow the efficient and selective neuromodulation of somatic and autonomic nerves, which has proven beneficial in specific bioelectronic medical applications. However, current most clinical devices are wired and powered by implantable batteries which suffer from several limitations. We recently developed a sub-millimeter inductively powered neural stimulator (electroparticle; EP), and in this study, we report the integration of the EP onto commercial cuff electrodes (EP-C) allowing the wireless activation of peripheral nerves. APPROACH: The current output of this device was defined at different magnetic field strenghts, and with respect to external antenna distance and activation angles. In acute in vivo testing, stimulation of the rat sciatic nerve (ScN) with the EP-C was able to evoke motor responses quantified by 3D tracking of the hind limb movement. Motor recruitment curves were obtained in response to variations in magnetic field strength (0-92.91 A m-1), stimulation frequencies (2-7 Hz), and pulse widths (50-200 µs). MAIN RESULTS: The results show constant output voltage throughout 50 400 stimulating cycles on a benchtop setting, and successful ScN motor activation with a 4 cm distance between external antenna and receiver. We achieved optimal motor recruitment indicated by maximizing range of hindlimb movement (6.01 ± 2.92 mm) with a magnetic field of 40.02 ± 2.85 A m-1 and 150 µs pulse width. Stimulating pulse width or frequency did not significantly influence motor recruitment. SIGNIFICANCE: We confirmed that continuous stimulation for 14 min using monophasic pulses did not deleteriously affect the evoked motor responses when compared to wired charge-balanced biphasic electrical stimulation. We observed, however, a 36%-44% decrease in the evoked limb movement in both groups over time due to muscle fatigue. This study shows that the EP-C device can be used effectively for peripheral nerve neuromodulation.
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Terapia por Estimulação Elétrica/métodos , Potencial Evocado Motor/fisiologia , Neuroestimuladores Implantáveis , Nervo Isquiático/fisiologia , Tecnologia sem Fio , Animais , Terapia por Estimulação Elétrica/instrumentação , Eletrodos Implantados , Campos Eletromagnéticos , Microeletrodos , Nervos Periféricos/fisiologia , Ratos , Tecnologia sem Fio/instrumentaçãoRESUMO
Silicone nerve cuff electrodes are commonly implanted on relatively large and accessible somatic nerves as peripheral neural interfaces. While these cuff electrodes are soft (1-50 MPa), their self-closing mechanism requires of thick walls (200-600 µm), which in turn contribute to fibrotic tissue growth around and inside the device, compromising the neural interface. We report the use of thiol-ene/acrylate shape memory polymer (SMP) for the fabrication of thin film multi-electrode softening cuffs (MSC). We fabricated multi-size MSC with eight titanium nitride (TiN) electrodes ranging from 1.35 to 13.95 × 10-4 cm2 (1-3 kΩ) and eight smaller gold (Au) electrodes (3.3 × 10-5 cm2; 750 kΩ), that soften at physiological conditions to a modulus of 550 MPa. While the SMP material is not as soft as silicone, the flexural forces of the SMP cuff are about 70-700 times lower in the MSC devices due to the 30 µm thick film compared to the 600 µm thick walls of the silicone cuffs. We demonstrated the efficacy of the MSC to record neural signals from rat sciatic and pelvic nerves (1000 µm and 200 µm diameter, respectively), and the selective fascicular stimulation by current steering. When implanted side-by-side and histologically compared 30 days thereafter, the MSC devices showed significantly less inflammation, indicated by a 70-80% reduction in ED1 positive macrophages, and 54-56% less fibrotic vimentin immunoreactivity. Together, the data supports the use of MSC as compliant and adaptable technology for the interfacing of somatic and autonomic peripheral nerves.