Stability and Effect of Parkinsonian State on Deep Brain Stimulation Cortical Evoked Potentials.

OBJECTIVES: To characterize and compare the stability of cortical potentials evoked by deep brain stimulation (DBS) of the subthalamic nucleus (STN) across the naïve, parkinsonian, and pharmacologically treated parkinsonian states. To advance cortical potentials as possible biomarkers for DBS programming. MATERIALS AND METHODS: Serial electrocorticographic (ECoG) recordings were made more than nine months from a single non-human primate instrumented with bilateral ECoG grids spanning anterior parietal to prefrontal cortex. Cortical evoked potentials (CEPs) were generated through time-lock averaging of the ECoG recordings to DBS pulses delivered unilaterally in the STN region using a chronically implanted, six-contact, scaled DBS lead. Recordings were made across the naïve followed by mild and moderate parkinsonian conditions achieved by staged injections of the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) neurotoxin. In addition to characterizing the spatial distribution and stability of the response within each state, changes in the amplitude and latency of CEP components as well as in the frequency content were examined in relation to parkinsonian severity and dopamine replacement. RESULTS: In the naïve state, the STN DBS CEP presented as a multiphase response maximal over M1 cortex, with components attributable to physiological activity distinguishable from stimulus artifact as early as 0.45-0.75 msec poststimulation. When delivered using therapeutically effective parameters in the parkinsonian state, the CEP was highly stable across multiple recording sessions within each behavioral state. Across states, significant differences were present with respect to both the latency and amplitude of individual response components, with greater differences present for longer-latency components (all p < 0.05). Power spectral density analysis revealed a high-beta peak within the evoked response, with significant changes in power between disease states across multiple frequency bands. CONCLUSIONS: Our findings underscore the spatiotemporal specificity and relative stability of the DBS-CEP associated with different disease states and with therapeutic benefit. DBS-CEP may be a viable biomarker for therapeutic programming.

Prediction of mild parkinsonism revealed by neural oscillatory changes and machine learning.

Neural oscillatory changes within and across different frequency bands are thought to underlie motor dysfunction in Parkinson's disease (PD) and may serve as biomarkers for closed-loop deep brain stimulation (DBS) approaches. Here, we used neural oscillatory signals derived from chronically implanted cortical and subcortical electrode arrays as features to train machine learning algorithms to discriminate between naive and mild PD states in a nonhuman primate model. Local field potential (LFP) data were collected over several months from a 12-channel subdural electrocorticography (ECoG) grid and a 6-channel custom array implanted in the subthalamic nucleus (STN). Relative to the naive state, the PD state showed elevated primary motor cortex (M1) and STN power in the beta, high gamma, and high-frequency oscillation (HFO) bands and decreased power in the delta band. Theta power was found to be decreased in STN but not M1. In the PD state there was elevated beta-HFO phase-amplitude coupling (PAC) in the STN. We applied machine learning with support vector machines with radial basis function (SVM-RBF) kernel and k-nearest neighbors (KNN) classifiers trained by features related to power and PAC changes to discriminate between the naive and mild states. Our results show that the most predictive feature of parkinsonism in the STN was high beta (∼86% accuracy), whereas it was HFO in M1 (∼98% accuracy). A feature fusion approach outperformed every individual feature, particularly in the M1, where ∼98% accuracy was achieved with both classifiers. Overall, our data demonstrate the ability to use various frequency band power to classify the clinical state and are also beneficial in developing closed-loop DBS therapeutic approaches.NEW & NOTEWORTHY Neurophysiological biomarkers that correlate with motor symptoms or disease severity are vital to improve our understanding of the pathophysiology in Parkinson's disease (PD) and for the development of more effective treatments, including deep brain stimulation (DBS). This work provides direct insight into the application of these biomarkers in training classifiers to discriminate between brain states, which is a first step toward developing closed-loop DBS systems.

Phase-Centric MOCVD Enabled Synthetic Approaches for Wafer-Scale 2D Tin Selenides.

Following an initial nucleation stage at the flake level, atomically thin film growth of a van der Waals material is promoted by ultrafast lateral growth and prohibited vertical growth. To produce these highly anisotropic films, synthetic or post-synthetic modifications are required, or even a combination of both, to ensure large-area, pure-phase, and low-temperature deposition. A set of synthetic strategies is hereby presented to selectively produce wafer-scale tin selenides, SnSex (both x = 1 and 2), in the 2D forms. The 2D-SnSe2 films with tuneable thicknesses are directly grown via metal-organic chemical vapor deposition (MOCVD) at 200 °C, and they exhibit outstanding crystallinities and phase homogeneities and consistent film thickness across the entire wafer. This is enabled by excellent control of the volatile metal-organic precursors and decoupled dual-temperature regimes for high-temperature ligand cracking and low-temperature growth. In contrast, SnSe, which intrinsically inhibited from 2D growth, is indirectly prepared by a thermally driven phase transition of an as-grown 2D-SnSe2 film with all the benefits of the MOCVD technique. It is accompanied by the electronic n-type to p-type crossover at the wafer scale. These tailor-made synthetic routes will accelerate the low-thermal-budget production of multiphase 2D materials in a reliable and scalable fashion.

Development and Evaluation of a Real-Time Phase-Triggered Stimulation Algorithm for the CorTec Brain Interchange.

With the development and characterization of biomarkers that may reflect neural network state as well as a patient's clinical deficits, there is growing interest in more complex stimulation designs. While current implantable neuromodulation systems offer pathways to expand the design and application of adaptive stimulation paradigms, technological drawbacks of these systems limit adaptive neuromodulation exploration. In this paper, we discuss the implementation of a phase-triggered stimulation paradigm using a research platform composed of an investigational system known as the CorTec Brain Interchange (CorTec GmbH, Freiburg, Germany), and an open-source software tool known as OMNI-BIC. We then evaluate the stimulation paradigm's performance in both benchtop and in vivo human demonstrations. Our findings indicate that the Brain Interchange and OMNI-BIC platform is capable of reliable administration of phase-triggered stimulation and has the potential to help expand investigation within the adaptive neuromodulation design space.

Open Mind Neuromodulation Interface for the CorTec Brain Interchange (OMNI-BIC): an investigational distributed research platform for next-generation clinical neuromodulation research.

The rise of adaptive stimulation approaches has shown great therapeutic promise in the growing field of neuromodulation. The discovery and growth of these novel adaptive stimulation paradigms has been largely concentrated around several implantable devices with research application programming interfaces (APIs) that allow for custom applications to be created for clinical neuromodulation studies. However, the sunsetting of devices and ongoing development of new platforms is leading to an increased fragmentation in the research environment- resulting in the reinvention of system features and the inability to leverage previous development efforts for future studies. The Open Mind Neuromodulation Interface (OMNI) is a previously proposed solution to address the weaknesses of the DLL-driven API approach of past neuromodulation research by utilizing an alternative gRPC-enabled microservice framework. Here, we introduce OMNI-BIC, an implementation of the OMNI framework to the CorTec Brain Interchange system. This paper describes the design and implementation of the OMNI-BIC software tools and demonstrates the framework's capabilities for implementing customized neuromodulation therapies for clinical investigations. Through the development and deployment of the OMNI-BIC system, we hope to improve future clinical studies with the Brain Interchange system and aid in continuing the growth and momentum of the exciting field of adaptive neuromodulation.

3D-printable, lightweight, and electrically conductive metal inks based on evaporable emulsion templates jammed with natural rheology modifiers.

Conductive metal inks with 3D-printable rheological properties have gained considerable attention, owing to their potential for manufacturing 3D electronics. Typically, such inks are formulated with high volume fractions of metal particles to achieve both rheological and electrical percolation. However, this leads to a high product cost and weight, making this approach potentially undesirable for practical application. In this study, naturally occurring ingredients, i.e., bee pollen microparticles (BPMPs) and citric acids (CAs), are used to produce a jammed hexane-in-aqueous suspension-type emulsion with controllable viscoelasticity as a template for conductive metal particles. Correspondingly, it is possible to develop 3D-printable, lightweight, and conductive inks. The BPMPs and CAs, as rheology modifiers, facilitate the 3D printability of the ink. After drying, the ink forms 3D networks without macroscopic discontinuities. Hexanes co-dispersed with BPMPs and CAs in the aqueous continuous phase improve the ink rheological processability and create internal macropores within the 3D-printed structure upon evaporation under ambient conditions, decreasing the product density. A conductive copper ink based on the emulsion template shows excellent 3D printability and electrical percolation at low metal loadings (<10 vol%); moreover, the printed ink with the optimized formulation has a remarkably low density (<2 g âˆ™ cm-3).

Direct-Writable and Thermally One-Step Curable "Water-Stained" Epoxy Composite Inks.

In this study, a simple method for preparing direct-writable and thermally one-step curable epoxy composite inks was proposed. Specifically, colloidal inks containing a mixture of ordinary epoxy resin and anhydride-type hardener with the suspended alumina microplates, as exemplary fillers, are "stained" with small amounts of water. This increases the elasticity of the ink via the interparticle capillary attraction and promotes curing of the epoxy matrix in low-temperature ranges, causing the three-dimensional (3D) printed ink to avoid structural disruption during one-step thermal curing without the tedious pre-curing step. The proposed mechanisms for the shape retention of thermally cured water-stained inks were discussed with thorough analyses using shear rheometry, DSC, FTIR, and SEM. Results of the computer-vision numerical analysis of the SEM images reveal that the particles in water-stained inks are oriented more in the vertical direction than those in water-free samples, corroborating the proposed mechanisms. The suggested concept is extremely simple and does not require any additional cost to the one required for the preparation of the common epoxy-filler composites, which is thus expected to be well-exploited in various applications where 3D printing of epoxy-based formulations is necessary.

Consistent Changes in Cortico-Subthalamic Directed Connectivity Are Associated With the Induction of Parkinsonism in a Chronically Recorded Non-human Primate Model.

Parkinson's disease is a neurological disease with cardinal motor signs including bradykinesia and tremor. Although beta-band hypersynchrony in the cortico-basal ganglia network is thought to contribute to disease manifestation, the resulting effects on network connectivity are unclear. We examined local field potentials from a non-human primate across the naïve, mild, and moderate disease states (model was asymmetric, left-hemispheric dominant) and probed power spectral density as well as cortico-cortical and cortico-subthalamic connectivity using both coherence and Granger causality, which measure undirected and directed effective connectivity, respectively. Our network included the left subthalamic nucleus (L-STN), bilateral primary motor cortices (L-M1, R-M1), and bilateral premotor cortices (L-PMC, R-PMC). Results showed two distinct peaks (Peak A at 5-20 Hz, Peak B at 25-45 Hz) across all analyses. Power and coherence analyses showed widespread increases in power and connectivity in both the Peak A and Peak B bands with disease progression. For Granger causality, increases in Peak B connectivity and decreases in Peak A connectivity were associated with the disease. Induction of mild disease was associated with several changes in connectivity: (1) the cortico-subthalamic connectivity in the descending direction (L-PMC to L-STN) decreased in the Peak A range while the reciprocal, ascending connectivity (L-STN to L-PMC) increased in the Peak B range; this may play a role in generating beta-band hypersynchrony in the cortex, (2) both L-M1 to L-PMC and R-M1 to R-PMC causalities increased, which may either be compensatory or a pathologic effect of disease, and (3) a decrease in connectivity occurred from the R-PMC to R-M1. The only significant change seen between mild and moderate disease was increased right cortical connectivity, which may reflect compensation for the left-hemispheric dominant moderate disease state.

Clinical and microbial evaluation of the effects on gingivitis of a mouth rinse containing an Enteromorpha linza extract.

Enteromorpha linza, a green alga, has been recognized as a potential source of natural antimicrobial and antifungal compounds. We previously reported that an E. linza extract strongly inhibited the growth of Prevotella intermedia and Porphyromonas gingivalis. The principal objective of this study was to evaluate the clinical effect of a mouth rinse containing the E. linza extract on gingivitis disease, as measured by the plaque index (PI), gingival index (GI), and bleeding on probing (BOP), and on two bacterial strains (P. intermedia and P. gingivalis), in comparison with Listerine(®) (Listerine-Korea, Seoul, Korea), which was used as a positive control. In total, 55 subjects were recruited into active participation in this clinical study. The PI, GI, BOP, and bacterial strains were then evaluated over a test period of 6 weeks. After 1, 2, 4, and 6 weeks, the same clinical indices were recorded, and the levels of P. intermedia and P. gingivalis were quantified via real-time polymerase chain reaction. At the end of the study, the group using the mouth rinse containing the E. linza extract evidenced significant reductions in the clinical indices (PI, GI, and BOP) and P. gingivalis compared with baseline values. Moreover, E. linza extract containing mouth rinse produced effects similar to those of Listerine. Overall, these results indicate that a mouth rinse containing E. linza extract significantly reduces plaque, improves the condition of gingival tissues, and reduces bleeding. Additionally, E. linza extract mouth rinse significantly inhibits P. gingivalis and P. intermedia. Thus, this clinical study demonstrated that the twice-daily use of an E. linza extract mouth rinse can inhibit and prevent gingivitis.