1,720,995 research outputs found
Adaptive Detection of Beta Bursts of Local Field Potentials Recorded from Subthalamic Nucleus in Patients with Parkinson’s Disease
No full textParkinson's Disease (PD) affects 1% of the world population, with this number expected to increase within the following years. Local field potentials (LFPs) recorded from deep brain stimulation (DBS) leads placed into the motor territory of the subthalamic nucleus (STN) can be used to investigate the mechanism of PD and allows for further development of new therapeutic strategies. Beta band activity, which typically presents itself as bursts, has been continuously found in the LFP recordings of PD patients. These oscillations of neural activity have been shown to correlate with motor impairment and can be suppressed by dopaminergic medication and stimulation of the brain. A novel adaptive technique we developed uses local cosine packets to detect beta bursts in LFPs and segments the data appropriately using nondyadic segmentation. We show that the spectral entropy of these adaptively captured bursts previse patient symptoms accurately and may outperform the basic beta suppression approach, such as thresholding.
In this work, 120s of LFP data recorded in the resting state from chronic DBS leads of nine PD patients were segmented adaptively by entropy minimization. Using the recently developed algorithm, we performed the following: (i) adaptively segment STN LFP recordings into segments of 125ms or multiples of it, (ii) determine the entropy distribution of different time windows, (iii) correlate the change in entropy between unmedicated (OFF) and medicated (ON) states in different time windows with Unified Parkison's Disease Rating Scale (UPDRS) and computer-based measurements of bradykinesia. We found that as segment size increased, the difference in entropy between OFF and ON states enlarged. Based on entropy distribution, it was possible to determine whether a patient improved after the administration of medication. Similarly, the change of entropy in segments ≥375ms was highly correlated with the UPDRS and keyboard scores. These findings suggest that beta bursts can be adaptively segmented without the use of a predetermined threshold, therefore allowing for robust quantification of disease severity. This could enable future closed-loop DBS algorithms to become more efficient and effective when stimulating based on beta bursts detection.Biomedical Engineering, Department o
Use of Motion Artifact for the Detection of Respiratory Effort in Polysomnography
No full textMeasuring respiratory effort is critical when diagnosing sleep disordered breathing. In this thesis work, the use of detecting respiratory effort by using the movement artifact found in the electromyographic (EMG) and electrocardiographic (ECG) recordings used in polysomnography was investigated. The resulting signals were compared to effort measured with respiratory inductance plethysmography (RIP). The EMG and ECG signals were filtered using the Savitzy-Golay method of smoothing and differentiation of data by simplified least squares to extract the movement artifact. The validity of each resultant waveform was measured using a Pearson product moment correlation coefficient and were studied to determine the most reliable signal. A total of 12 subjects were recorded in a clinical setting, all being evaluated for obstructive sleep apnea. The ability to detect respiratory effort using movement artifact was found to perform best in the masseter. This work shows that movement artifact recovered from the EMG and ECG may be a reliable alternative for the detection of respiratory effort.Biomedical Engineering, Department o
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Space and Time Frequency-Dependent Interactions in Subthalamic Nucleus Local Field Potentials in Parkinson's Disease
No full textParkinson’s disease (PD) is the second most common neurodegenerative disorder in the US, with a prevalence of 1% in the population over 60 years old and an annual economic impact estimated in 23 billion dollars in direct costs only. Deep Brain Stimulation (DBS) is an effective surgical treatment for advanced PD in patients who developed a resistance to the pharmacological medication. DBS procedure allows the recording of electrophysiological signals known as Local Field Potentials (LFP) from deep brain structures such as the Subthalamic Nucleus (STN). LFP represent the synchronized activity of a relatively large population of neurons and have been shown to correlate with many PD symptoms and contribute with their use to the success of DBS practice. However, the pathophysiology of PD remains unclear.
In this work, long-term STN LFP recordings of ten PD patients were analyzed using classical as well as recently developed methods to investigate: (i) the spatial distribution of spectral activity and nonlinear cross-frequency coupling in the STN in medicated and unmedicated conditions, (ii) the pattern of spectral changes following medication intake, and (iii) the correlation of features extracted from LFP with clinical scores and sensory data during resting state and movement execution. The main findings showed that cross-frequency coupling is stronger in the superior part of STN and that the timings of changes in LFP spectral power after pharmacological treatment are frequency-dependent. The results support and integrate existing evidence that LFP analysis may assist in the target localization during DBS surgery and contribute to the development of smarter algorithms for next generation closed-loop DBS applications.Computer Science, Department o
Red Blood Cell Image Classification Using Model Observers
No full textHealthy red blood cells (RBCs) undergo a gradual morphological transformation during storage. From original healthy discocytes, RBCs gradually lose membrane surface area and cell volume, eventually turning into ghost (lysed cell). The degree of deterioration varies from cell to cell. These cells can be classified into 7 classes: discocyte, stomatocyte, echinocyte 1, echinocyte 2, echinocyte 3, sphero-echinocyte and spherocyte. Currently, researchers categorize a blood cell into different class by visual inspection. This work is laborious and inefficient. The limitation on the sample size is a problem for the evaluation of the blood unit quality and other research.
Our objective was to test linear discriminants for classification work. The images we used were provided by Nate and his colleagues who fabricated a microfluidic device that can take image of RBCs. We extract features based on cell shape and surface texture. The overall accuracy of our system is 69.4%.Biomedical Engineering, Department o
Improving Reaching Tasks of a Simulated Fetch Robot Using Demonstrations along with Hindsight Experience Replay
No full textSimple day-to-day activities like picking up or reaching out to an object seem easy for a human, but they are extremely difficult to teach to a robot. In order for the robot to do human-like activities with similar efficiency, the most popular option is Reinforcement Learning (RL). RL heavily relies on rewards to understand its surroundings. Most of the real-world tasks are naturally specified with sparse rewards and finding these rewards becomes extremely difficult as the task horizon and action dimensionality increases.
These sparse rewards cause most of the RL algorithms to perform poorly. In order to achieve optimal performance while obtaining rewards, the proposed method utilizes demonstrations on top of Deep Deterministic Policy Gradients (DDPG) along with Hindsight Experience Replay, which substantially speeds up the training for simulated Robotics tasks.Electrical and Computer Engineering, Department o
Correlation Analysis of Reward Modulation in Motor Cortex of Nonhuman Primates
No full textReward modulation is represented in the motor cortex and can be used to implement more accurate decoding models to improve brain machine interfaces. Analyzing the trial-to-trial noise correlations between units in the presence of rewarding and non-rewarding stimuli adds to our understanding of cortical network dynamics and provides a clearer picture of the neural encoding involved in reward. Using Pearson’s correlation coefficient to measure shared variability between units indicates significantly higher noise correlation in non-rewarding trials. This pattern is evident in multiple NHPs during both manual tasks and action observation. The isolation of reward discriminatory units demonstrates similar changes in correlation, further supporting the hypothesis that correlation affects encoding accuracy and can be used as a tool in interpreting modulatory neural responses.Biomedical Engineering, Department o
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