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.

Implantable microelectrode arrays (MEAs) enable the recording of electrical activity from cortical neurons for applications that include brain–machine interfaces. However, MEAs show reduced recording capabilities under chronic implantation conditions. This has largely been attributed to the brain’s foreign body response, which is marked by neuroinflammation and gliosis in the immediate vicinity of the MEA implantation site. This has prompted the development of novel MEAs with either coatings or architectures that aim to reduce the tissue response. The present study examines the comparative performance of multi-shank planar, silicon-based devices and low-flexural-rigidity amorphous silicon carbide (a-SiC) MEAs that have a similar architecture but differ with respect to the shank cross-sectional area. Data from a-SiC arrays were previously reported in a prior study from our group. In a manner consistent with the prior work, larger cross-sectional area silicon-based arrays were implanted in the motor cortex of female Sprague-Dawley rats and weekly recordings were made for 16 weeks after implantation. Single unit metrics from the recordings were compared over the implantation period between the device types. Overall, the expression of single units measured from a-SiC devices was significantly higher than for silicon-based MEAs throughout the implantation period. Immunohistochemical analysis demonstrated reduced neuroinflammation and gliosis around the a-SiC MEAs compared to silicon-based devices. Our findings demonstrate that the a-SiC MEAs with a smaller shank cross-sectional area can record single unit activity with more stability and exhibit a reduced inflammatory response compared to the silicon-based device employed in this study.

Background: Recovery from chronic post-stroke aphasia is highly heterogeneous and shaped by lesion characteristics, brain integrity, and systemic health. Traditional group-level models struggle to capture this multidimensional, dynamic variability. Digital twin approaches - patient-specific, continually updating models - may enable individualized prediction and counterfactual evaluation of modifiable risk factors. Therefore, the aim was to develop and validate a proof-of-concept digital twin that predicts individual naming outcomes during language treatment and quantifies the estimated impact of modifiable health factors on naming. This study represents the first application of digital twin modeling to aphasia recovery, and we hypothesize that this could constitute a critical first step toward dynamically adaptive, personalized models for aphasia rehabilitation. Methods: We analyzed longitudinal data from 106 chronic stroke survivors with aphasia enrolled in the POLAR randomized clinical trial. For each participant we combined baseline demographic/health variables (age, sex, education, days post-stroke, hypertension, diabetes, BMI), lesion load in left-hemisphere language ROIs (JHU atlas), ROI-level white-matter microstructure (FA), and resting-state functional connectivity restricted to language regions. A continual-learning linear model (River framework; Adam optimizer) was pretrained on baseline data and updated across timepoints. Model performance was assessed by R² at the final timepoint. Counterfactual simulations systematically altered hypertension, diabetes, and BMI to estimate isolated and combined effects on predicted Philadelphia Naming Test (PNT) scores. Results: The digital twin predicted final PNT scores with R² = 0.5848 (explaining approximately 58% of variance). The largest contributors were prior naming performance, age, lesion load in language regions, and white-matter integrity in temporal regions (notably right MTG and STG pole). Counterfactual results estimated modest but consistent effects of health factors, with them collectively accounting for approximately 25% of the variance in treatment gains. The average change in PNT score with counterfactual changes was 7.92 (SD = 16.11). Therefore, diabetic status explained 2% of the variance in treatment gains, hypertensive status explained 4.75%, and increasing BMI explained 18.5%. Conclusions: This study demonstrate the feasibility and clinical potential of applying a digital twin framework to chronic post-stroke aphasia, with the model successfully predicting more than half the variance in naming performance during language treatment. Through counterfactual simulation, we demonstrated that modifiable health factors exert measurable, bidirectional influences on predicted treatment outcomes, underscoring the role of systemic health in shaping language recovery. Although the individual effects of these factors were modest in magnitude, their cumulative influence on treatment gains illustrates how multiple small biological contributors can add up to shape meaningful differences in language outcomes. More broadly, these findings illustrate the potential value of digital twin models for aphasia treatment, particularly as a tool to integrate diverse biological factors and generate individualized, dynamically updated predictions. Graphical

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. This creates a need for MEAs that can minimize the foreign body response to enable long-term recording. A potential approach to reduce the foreign body response is the use of ultrathin MEAs. Here, we fabricated ultrathin (cross-sectional area: 160 µm ² ) amorphous silicon carbide (a-SiC) MEAs with sixteen electrode channels and implanted them into the motor cortex of seven female Sprague-Dawley rats. A-SiC was chosen as the fabrication base for its high chemical stability, good electrical insulation properties, and amenability to thin film fabrication techniques. Electrochemical analysis and neural recordings were performed weekly for 4 months. MEAs were characterized in vitro pre-implantation 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 immunohistochemistry 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 to 2.9 MΩ at 1 kHz, and 0.11 MΩ to 0.13 MΩ at 30 kHz over 16 weeks. The median charge storage capacity of the implanted electrodes at 50 mV/s were 58.1 mC/cm ² on week 1 and 55.9 mC/cm ² on week 16, and at 50,000 mV/s were 4.27 mC/cm ² on week 1 and 5.93 mC/cm ² 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 only −0.19 per week. We also classified the units as fast and slow spiking based on the trough-to-peak time. Although the overall presence of single units declined, fast and slow spiking units declined at a similar rate. Furthermore, immunohistochemistry showed minimal foreign body response to the a-SiC devices, as highlighted by statistically insignificant differences in activated glial cells between implanted brains slices and contralateral sham slices, as evidenced by GFAP staining. NeuN staining revealed the presence of neural cell bodies close to the implantation site, again statistically not different from a contralateral sham slice. These results support the use of ultrathin a-SiC MEAs for long-term implantation and use in brain-machine interfaces.

Implantable microelectrode arrays (MEAs) enable the recording of electrical activity from cortical neurons for applications that include brain machine interfaces. However, MEAs show reduced recording capabilities under chronic implantation conditions. This has largely been attributed to the brain’s foreign body response, which is marked by neuroinflammation and gliosis in the immediate vicinity of the MEA implantation site. This has prompted the development of novel MEAs with either coatings or architectures that aim to reduce the tissue response. The present study examines the comparative performance of multi-shank planar, silicon-based devices and low flexural rigidity amorphous silicon carbide (a-SiC) MEAs that have a similar architecture but differ with respect to shank cross-sectional area. Data from a-SiC arrays were previously reported in a prior study from our group. In a manner consistent with the prior work, larger cross-sectional area silicon-based arrays were implanted in the motor cortex of female Sprague-Dawley rats and weekly recordings were made for 16 weeks after implantation. Single unit metrics from the recordings were compared over the implantation period between the device types. Overall, the expression of single units measured from a-SiC devices was significantly higher than for silicon-based MEAs throughout the implantation period. Immunohistochemical analysis demonstrated reduced neuroinflammation and gliosis around the a-SiC MEAs compared to silicon-based devices. Our findings demonstrate that the a-SiC MEAs with smaller shank cross-sectional area can record single unit activity with more stability and exhibit a reduced inflammatory response compared to the silicon-based device employed in this study.