ELECTROPHYSIOLOGY OF BASAL GANGLIA (BG) CIRCUITRY AND DYSTONIA AS A MODEL OF MOTOR CONTROL DYSFUNCTION

The basal ganglia (BG) is a complex set of heavily interconnected nuclei located in the central part of the brain that receives inputs from the several areas of the cortex and projects via the thalamus back to the prefrontal and motor cortical areas. Despite playing a significant part in multiple brain functions, the physiology of the BG and associated disorders like dystonia remain poorly understood. Dystonia is a devastating condition characterized by ineffective, twisting movements, prolonged co-contractions and contorted postures. Evidences suggest that it occurs due to abnormal discharge patterning in BG-thalamocortocal (BGTC) circuitry. The central purpose of this study was to understand the electrophysiology of BGTC circuitry and its role in motor control and dystonia. Toward this goal, an advanced multi-target multi-unit recording and analysis system was utilized, which allows simultaneous collection and analysis of multiple neuronal units from multiple brain nuclei. Over the cause of this work, neuronal data from the globus pallidus (GP), subthalamic nucleus (STN), entopenduncular nucleus (EP), pallidal receiving thalamus (VL) and motor cortex (MC) was collected from normal, lesioned and dystonic rats under awake, head restrained conditions. The results have shown that the neuronal population in BG nuclei (GP, STN and EP) were characterized by a dichotomy of firing patterns in normal rats which remains preserved in dystonic rats. Unlike normals, neurons in dystonic rat exhibit reduced mean firing rate, increased irregularity and burstiness at resting state. The chaotic changes that occurs in BG leads to inadequate hyperpolarization levels within the VL thalamic neurons resulting in a shift from the normal bursting mode to an abnormal tonic firing pattern. During movement, the dystonic EP generates abnormally synchronized and elongated burst duration which further corrupts the VL motor signals. It was finally concluded that the loss of specificity and temporal misalignment between motor neurons leads to corrupted signaling to the muscles resulting in dystonic behavior. Furthermore, this study reveals the importance of EP output in controlling firing modes occurring in the VL thalamus

3D FUNCTIONAL MODELING OF DBS EFFICACY AND DEVELOPMENT OF ANALYTICAL TOOLS TO EXPLORE FUNCTIONAL STN

Introduction: Exploring the brain for optimal locations for deep brain stimulation (DBS) therapy is a challenging task, which can be facilitated by analysis of DBS efficacy in a large number of patients with Parkinson’s disease (PD). The Unified Parkinson\u27s Disease Rating Scale (UPDRS) scores indicate the DBS efficacy of the corresponding stimulation location in a particular patient. The spatial distribution of these clinical scores can be used to construct a functional model which closely models the expected efficacy of stimulation in the region. Designs and Methods: In this study, different interpolation techniques were investigated that can appropriately model the DBS efficacy for Parkinson’s disease patients. These techniques are linear triangulation based interpolation, ‘roving window’ interpolation and ‘Monopolar inverse weighted distance’ (MIDW) interpolation. The MIDW interpolation technique is developed on the basis of electric field geometry of the monopolar DBS stimulation electrodes, based on the DBS model of monopolar cathodic stimulation of brain tissues. Each of these models was evaluated for their predictability, interpolation accuracy, as well as other benefits and limitations. The bootstrapping based optimization method was proposed to minimize the observational and patient variability in the collected database. A simulation study was performed to validate that the statistically optimized interpolated models were capable to produce reliable efficacy contour plots and reduced false effect due to outliers. Some additional visualization and analysis tools including a graphic user interface (GUI) were also developed for better understanding of the scenario. Results: The interpolation performance of the MIDW interpolation, the linear triangulation method and Roving window method was evaluated as interpolation error as 0.0903, 0.1219 and0.3006 respectively. Degree of prediction for the above methods was found to be 0.0822, 0.2986 and 0.0367 respectively. The simulation study demonstrate that the mean improvement in outlier handling and increased reliability after bootstrapping based optimization (performed on Linear triangulation interpolation method) is 6.192% and 12.8775% respectively. The different interpolation techniques used to model monopolar and bipolar stimulation data is found to be useful to study the corresponding efficacy distribution. A user friendly GUI (PDRP_GUI) and other utility tools are developed. Conclusion: Our investigation demonstrated that the MIDW and linear triangulation methods provided better degree of prediction, whereas the MIDW interpolation with appropriate configuration provided better interpolation accuracy. The simulation study suggests that the bootstrapping-based optimization can be used as an efficient tool to reduce outlier effects and increase interpolated reliability of the functional model of DBS efficacy. Additionally, the differential interpolation techniques used for monopolar and bipolar stimulation modeling facilitate study of overall DBS efficacy using the entire dataset

Nucleus Basalis of Meynert Stimulation for Dementia: Theoretical and Technical Considerations

Deep brain stimulation (DBS) of nucleus basalis of Meynert (NBM) is currently being evaluated as a potential therapy to improve memory and overall cognitive function in dementia. Although, the animal literature has demonstrated robust improvement in cognitive functions, phase 1 trial results in humans have not been as clear-cut. We hypothesize that this may reflect differences in electrode location within the NBM, type and timing of stimulation, and the lack of a biomarker for determining the stimulation’s effectiveness in real time. In this article, we propose a methodology to address these issues in an effort to effectively interface with this powerful cognitive nucleus for the treatment of dementia. Specifically, we propose the use of diffusion tensor imaging to identify the nucleus and its tracts, quantitative electroencephalography (QEEG) to identify the physiologic response to stimulation during programming, and investigation of stimulation parameters that incorporate the phase locking and cross frequency coupling of gamma and slower oscillations characteristic of the NBM’s innate physiology. We propose that modulating the baseline gamma burst stimulation frequency, specifically with a slower rhythm such as theta or delta will pose more effective coupling between NBM and different cortical regions involved in many learning processes

Nucleus Basalis of Meynert Stimulation for Dementia: Theoretical and Technical Considerations

<p>Deep brain stimulation (DBS) of nucleus basalis of Meynert (NBM) is currently being evaluated as a potential therapy to improve memory and overall cognitive function in dementia. Although, the animal literature has demonstrated robust improvement in cognitive functions, phase 1 trial results in humans have not been as clear-cut. We hypothesize that this may reflect differences in electrode location within the NBM, type and timing of stimulation, and the lack of a biomarker for determining the stimulation’s effectiveness in real time. In this article, we propose a methodology to address these issues in an effort to effectively interface with this powerful cognitive nucleus for the treatment of dementia. Specifically, we propose the use of diffusion tensor imaging to identify the nucleus and its tracts, quantitative electroencephalography (QEEG) to identify the physiologic response to stimulation during programming, and investigation of stimulation parameters that incorporate the phase locking and cross frequency coupling of gamma and slower oscillations characteristic of the NBM’s innate physiology. We propose that modulating the baseline gamma burst stimulation frequency, specifically with a slower rhythm such as theta or delta will pose more effective coupling between NBM and different cortical regions involved in many learning processes.</p

Enhancing Optical Character Recognition on Images with Mixed Text Using Semantic Segmentation

Optical Character Recognition has made large strides in the field of recognizing printed and properly formatted text. However, the effort attributed to developing systems that are able to reliably apply OCR to both printed as well as handwritten text simultaneously, such as hand-filled forms, is lackadaisical. As Machine printed/typed text follows specific formats and fonts while handwritten texts are variable and non-uniform, it is very hard to classify and recognize using traditional OCR only. A pre-processing methodology employing semantic segmentation to identify, segment and crop boxes containing relevant text on a given image in order to improve the results of conventional online-available OCR engines is proposed here. In this paper, the authors have also provided a comparison of popular OCR engines like Microsoft Cognitive Services, Google Cloud Vision and AWS recognitions. We have proposed a pixel-wise classification technique to accurately identify the area of an image containing relevant text, to feed them to a conventional OCR engine in the hopes of improving the quality of the output. The proposed methodology also supports the digitization of mixed typed text documents with amended performance. The experimental study shows that the proposed pipeline architecture provides reliable and quality inputs through complex image preprocessing to Conventional OCR, which results in better accuracy and improved performance

Insights into Diversity and Imputed Metabolic Potential of Bacterial Communities in the Continental Shelf of Agatti Island.

Marine microbes play a key role and contribute largely to the global biogeochemical cycles. This study aims to explore microbial diversity from one such ecological hotspot, the continental shelf of Agatti Island. Sediment samples from various depths of the continental shelf were analyzed for bacterial diversity using deep sequencing technology along with the culturable approach. Additionally, imputed metagenomic approach was carried out to understand the functional aspects of microbial community especially for microbial genes important in nutrient uptake, survival and biogeochemical cycling in the marine environment. Using culturable approach, 28 bacterial strains representing 9 genera were isolated from various depths of continental shelf. The microbial community structure throughout the samples was dominated by phylum Proteobacteria and harbored various bacterioplanktons as well. Significant differences were observed in bacterial diversity within a short region of the continental shelf (1-40 meters) i.e. between upper continental shelf samples (UCS) with lesser depths (i.e. 1-20 meters) and lower continental shelf samples (LCS) with greater depths (i.e. 25-40 meters). By using imputed metagenomic approach, this study also discusses several adaptive mechanisms which enable microbes to survive in nutritionally deprived conditions, and also help to understand the influence of nutrition availability on bacterial diversity

Spatial distribution of bacterial isolates.

<p>The figure depicts the spatial distribution of the representative bacterial isolates across the sampling depths.</p

Phylum level bacterial richness at various depths.

<p>The X-axis represents the number of phyla (sum of the values given for presence/absence (binary values) of the particular phylum at respective depth), while Y axis represents the samples.</p

Phylum level bacterial diversity across various depths.

<p>The diagram depicts the distribution of the first 15 dominant phyla identified across the samples. The Y-axis represents the percent relative abundance of each phylum. A break is introduced on Y-axis at 0.89 to resolve the Y-axis within the range of 0.9–1.0.</p

Distribution of functional genes across the samples.

<p>(a) Distribution of ABC transporter genes across the samples (p = 0.0050), showing a high abundance in the depths <20 meters. (b) Distribution of TonB protein coding genes, seen more abundant in the lower depths (p = 0.0147). (c) Distribution of polyamines coding genes across the samples, observed to be abundant in the depths < 20 meters (p = 0.0053).</p