27 research outputs found
Implantable Direct Current Neural Modulation: Theory, Feasibility, and Efficacy
Implantable neuroprostheses such as cochlear implants, deep brain stimulators, spinal cord stimulators, and retinal implants use charge-balanced alternating current (AC) pulses to recover delivered charge and thus mitigate toxicity from electrochemical reactions occurring at the metal-tissue interface. At low pulse rates, these short duration pulses have the effect of evoking spikes in neural tissue in a phase-locked fashion. When the therapeutic goal is to suppress neural activity, implants typically work indirectly by delivering excitation to populations of neurons that then inhibit the target neurons, or by delivering very high pulse rates that suffer from a number of undesirable side effects. Direct current (DC) neural modulation is an alternative methodology that can directly modulate extracellular membrane potential. This neuromodulation paradigm can excite or inhibit neurons in a graded fashion while maintaining their stochastic firing patterns. DC can also sensitize or desensitize neurons to input. When applied to a population of neurons, DC can modulate synaptic connectivity. Because DC delivered to metal electrodes inherently violates safe charge injection criteria, its use has not been explored for practical applicability of DC-based neural implants. Recently, several new technologies and strategies have been proposed that address this safety criteria and deliver ionic-based direct current (iDC). This, along with the increased understanding of the mechanisms behind the transcutaneous DC-based modulation of neural targets, has caused a resurgence of interest in the interaction between iDC and neural tissue both in the central and the peripheral nervous system. In this review we assess the feasibility of in-vivo iDC delivery as a form of neural modulation. We present the current understanding of DC/neural interaction. We explore the different design methodologies and technologies that attempt to safely deliver iDC to neural tissue and assess the scope of application for direct current modulation as a form of neuroprosthetic treatment in disease. Finally, we examine the safety implications of long duration iDC delivery. We conclude that DC-based neural implants are a promising new modulation technology that could benefit from further chronic safety assessments and a better understanding of the basic biological and biophysical mechanisms that underpin DC-mediated neural modulation
Stimulation of a Suprachoroidal Retinal Prosthesis Drives Cortical Responses in a Feline Model of Retinal Degeneration
PURPOSE. Retinal prostheses have emerged as a promising technology to restore vision in patients with severe photoreceptor degeneration. To better understand how neural degeneration affects the efficacy of electronic implants, we investigated the function of a suprachoroidal retinal implant in a feline model. METHODS. Unilateral retinal degeneration was induced in four adult felines by intravitreal injection of adenosine triphosphate (ATP). Twelve weeks post injection, animals received suprachoroidal electrode array implants in each eye, and responses to electrical stimulation were obtained using multiunit recordings from the visual cortex. Histologic measurements of neural and glial changes in the retina at the implant site were correlated with cortical thresholds from individual stimulating electrodes. RESULTS. Adenosine triphosphate-injected eyes displayed changes consistent with mid-to-late stage retinal degeneration and remodeling. A significant increase in electrical charge was required to induce a cortical response from stimulation of the degenerated retina compared to that in the fellow control eye. Spatial and temporal characteristics of the electrically evoked cortical responses were no different between eyes. Individual electrode thresholds varied in both the control and the ATP-injected eyes and were correlated with ganglion cell density. In ATP-injected eyes, cortical threshold was also independently correlated with an increase in the extent of retinal gliosis. CONCLUSIONS. These data suggest that even when ganglion cell density remains unaffected, glial changes in the retina following degeneration can influence the efficacy of suprachoroidal electrical stimulation. A better understanding of how glial change impacts retinal prosthesis function may help to further the optimization of retinal implants
Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission
NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (similar to 25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
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Research and Design of a Routing Protocol in Large-Scale Wireless Sensor Networks
无线传感器网络,作为全球未来十大技术之一,集成了传感器技术、嵌入式计算技术、分布式信息处理和自组织网技术,可实时感知、采集、处理、传输网络分布区域内的各种信息数据,在军事国防、生物医疗、环境监测、抢险救灾、防恐反恐、危险区域远程控制等领域具有十分广阔的应用前景。 本文研究分析了无线传感器网络的已有路由协议,并针对大规模的无线传感器网络设计了一种树状路由协议,它根据节点地址信息来形成路由,从而简化了复杂繁冗的路由表查找和维护,节省了不必要的开销,提高了路由效率,实现了快速有效的数据传输。 为支持此路由协议本文提出了一种自适应动态地址分配算——ADAR(AdaptiveDynamicAddre...As one of the ten high technologies in the future, wireless sensor network, which is the integration of micro-sensors, embedded computing, modern network and Ad Hoc technologies, can apperceive, collect, process and transmit various information data within the region. It can be used in military defense, biomedical, environmental monitoring, disaster relief, counter-terrorism, remote control of haz...学位:工学硕士院系专业:信息科学与技术学院通信工程系_通信与信息系统学号:2332007115216
A Hydrogel-Based Microfluidic Nerve Cuff for Neuromodulation of Peripheral Nerves
Implantable neuromodulation devices typically have metal in contact with soft, ion-conducting nerves. These neural interfaces excite neurons using short-duration electrical pulses. While this approach has been extremely successful for multiple clinical applications, it is limited in delivering long-duration pulses or direct current (DC), even for acute term studies. When the charge injection capacity of electrodes is exceeded, irreversible electrochemical processes occur, and toxic byproducts are discharged directly onto the nerve, causing biological damage. Hydrogel coatings on electrodes improve the overall charge injection limit and provide a mechanically pliable interface. To further extend this idea, we developed a silicone-based nerve cuff lead with a hydrogel microfluidic conduit. It serves as a thin, soft and flexible interconnection and provides a greater spatial separation between metal electrodes and the target nerve. In an in vivo rat model, we used this cuff to stimulate and record from sciatic nerves, with performance comparable to that of metal electrodes. Further, we delivered DC through the lead in an acute manner to induce nerve block that is reversible. In contrast to most metallic cuff electrodes, which need microfabrication equipment, we built this cuff using a consumer-grade digital cutter and a simplified molding process. Overall, the device will be beneficial to neuromodulation researchers as a general-purpose nerve cuff electrode for peripheral neuromodulation experiments
HERA-g, a new experiment for glueball, hybrid and odderon studies at DESY. Proposal for a new experimental program using the existing HERA-B detector
textabstractObjectives: To assesses whether automated brain image analysis with quantification of structural brain changes improves diagnostic accuracy in a memory clinic setting. Methods: In 42 memory clinic patients, we evaluated whether automated quantification of brain tissue volumes, hippocampal volume and white matter lesion volume improves diagnostic accuracy for Alzheimer's disease (AD) and frontotemporal dementia (FTD), compared to visual interpretation. Reference data were derived from a dementia-free aging population (n = 4915, aged >45 years), and were expressed as age- and sex-specific percentiles. Experienced radiologists determined the most likely imaging-based diagnosis based on structural brain MRI using three strategies (visual assessment of MRI only, quantitative normative information only, or a combination of both). Diagnostic accuracy of each strategy was calculated with the clinical diagnosis as the reference standard. Results: Providing radiologists with only quantitative data decreased diagnostic accuracy both for AD and FTD compared to conventional visual rating. The combination of quantitative with visual information, however, led to better diagnostic accuracy compared to only visual ratings for AD. This was not the case for FTD. Conclusion: Quantitative assessment of structural brain MRI combined with a reference standard in addition to standard visual assessment may improve diagnostic accuracy in a memory clinic setting