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https://www.readbyqxmd.com/read/28227959/localizing-seizure-onset-zone-by-convolutional-transfer-entropy-from-ieeg
#1
Kang Lin, Yueming Wang, Kedi Xu, Junming Zhu, Jianmin Zhang, Xiaoxiang Zheng, Kang Lin, Yueming Wang, Kedi Xu, Junming Zhu, Jianmin Zhang, Xiaoxiang Zheng, Xiaoxiang Zheng, Junming Zhu, Yueming Wang, Kedi Xu, Kang Lin, Jianmin Zhang
Automatic localization of the seizure onset zone (SOZ) is able to output an objective result and help clinical doctors greatly in epilepsy therapy. Transfer entropy is one of the most frequently used measures based on information theory to localize the SOZ. However, if only using transfer entropy to localize the SOZ, different results can be obtained during different periods, thus humans still need to identify which one is most reasonable. This paper proposes a new method to output only a few (e.g. 1 or 2) results along a long time slot...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227909/neuromorphic-circuit-modeling-directional-selectivity-in-the-visual-cortex
#2
Saeid Barzegarjalali, Alice C Parker, Saeid Barzegarjalali, Alice C Parker, Alice C Parker, Saeid Barzegarjalali
We have designed a neuromorphic circuit that models directional selectivity in the visual cortex, where selected neurons fire depending on the direction of object motion, along with the size and orientation of the object. The neuromorphic circuit is biomimetic. It consists of neurons and synapses, and models biological mechanisms. Neurons (including the Axon Hillock and the Dendritic Arbor) are designed with CMOS technology and synapses (both excitatory and inhibitory) are designed with Carbon Nanotube Transistors...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227896/intarsia-sensorized-band-and-textrodes-for-real-time-myoelectric-pattern-recognition
#3
Shannon Brown, Max Ortiz-Catalan, Joel Petersson, Kristian Rodby, Fernando Seoane, Shannon Brown, Max Ortiz-Catalan, Joel Petersson, Kristian Rodby, Fernando Seoane, Max Ortiz-Catalan, Fernando Seoane, Kristian Rodby, Shannon Brown, Joel Petersson
Surface Electromyography (sEMG) has applications in prosthetics, diagnostics and neuromuscular rehabilitation. Self-adhesive Ag/AgCl are the electrodes preferentially used to capture sEMG in short-term studies, however their long-term application is limited. In this study we designed and evaluated a fully integrated smart textile band with electrical connecting tracks knitted with intarsia techniques and knitted textile electrodes. Real-time myoelectric pattern recognition for motor volition and signal-to-noise ratio (SNR) were used to compare its sensing performance versus the conventional Ag-AgCl electrodes...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227888/simulating-the-activation-contraction-and-movement-of-skeletal-muscles-using-the-bidomain-model
#4
A Lopez Rincon, C Cantu, R Soto, S Shimoda, A Lopez Rincon, C Cantu, R Soto, S Shimoda, A Lopez Rincon, R Soto, C Cantu, S Shimoda
A simulation of the muscle activation, contraction and movement is here presented. This system was developed based on the Bidomain mathematical model of the electrical propagation in muscles. This study shows an electrical stimuli input to a muscle and how this behave. The comparison between healthy subject and patient with muscle activation impairment is depicted, depending on whether the signal reaches a threshold. A 3D model of a bicep muscle and a forearm bone connected was constructed using OpenGL. This platform could be used for development of controllers for biomechatronic systems in future works...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227818/detecting-divisions-of-the-autonomic-nervous-system-using-wearables
#5
Annamalai Natarajan, Kevin S Xu, Brian Eriksson, Annamalai Natarajan, Kevin S Xu, Brian Eriksson, Kevin S Xu, Brian Eriksson, Annamalai Natarajan
The ability to assess a user's emotional reaction from biometrics has applications in personalization, recommendation, and enhancing user experiences, among other areas. Unfortunately, understanding the connection between biometric signals and user reactions has previously focused on black box techniques that are opaque to the underlying physiology of the user. In this paper, we explore a novel user study connecting biometric reaction to external stimuli and changes in the user's autonomic nervous system. Specifically, we focus on two competing responses, namely the sympathetic and parasympathetic nervous system, and how differing activations are related to different user responses...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227772/the-chronnectome-evaluating-replicability-of-dynamic-connectivity-patterns-in-7500-resting-fmri-datasets
#6
Anees Abrol, Charlotte Chaze, Eswar Damaraju, Vince D Calhoun, Anees Abrol, Charlotte Chaze, Eswar Damaraju, Vince D Calhoun, Vince D Calhoun, Eswar Damaraju, Anees Abrol, Charlotte Chaze
Functional fMRI data are typically analyzed under the assumption that participants experience one long, continuous connectivity state throughout rest scan sessions. The chronnectome is a model that takes into account the temporal variance in connectivity throughout a scan session. In this work, we evaluate the repeatability of properties of functional network connectivity (FNC) dynamics assessed using sliding-windowed correlations in 28 independent age-matched large samples of 250 subjects. This approach revealed that multiple discrete, reoccurring connectivity states arise during rest, and that subjects tend to remain in one connectivity state for long periods of time before transitioning to another...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227771/tracking-intrinsic-connectivity-brain-network-features-during-successive-pseudo-resting-states-and-interoceptive-task-fmri
#7
Behnaz Jarrahi, Dante Mantini, Behnaz Jarrahi, Dante Mantini, Behnaz Jarrahi, Dante Mantini
Advanced multivariate analyses of functional magnetic resonance imaging (fMRI) data based on blood oxygen level-dependent (BOLD) contras have revealed that the human brain organizes its activities into multiple intrinsic connectivity networks (ICNs). Several fMRI studies have evaluated the modulations of these networks during different cognitive or emotional tasks using blind source separation techniques particularly the independent component analysis (ICA). In this exploratory study, we applied ICA methodology to examine ICN modulations under different interoceptive conditions...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227770/randomness-in-resting-state-functional-connectivity-matrices
#8
Victor M Vergara, Vince Calhoun, Victor M Vergara, Vince Calhoun, Vince Calhoun, Victor M Vergara
Separate brain regions exhibit synchronous intrinsic activity used to assess connectivity patterns known to appear among brain areas. Connectivity is evaluated from functional magnetic resonance imaging (fMRI) measuring the blood oxygen level dependent signal (BOLD) signal. Extensive research has revealed a distinctive pattern of connectivity among brain areas that can be visualized through a functional connectivity matrix (FCM) matrix. As in any measurement, BOLD signals are subject to contamination from noise and nuisances unrelated to brain's intrinsic activity...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227769/identifying-the-effects-of-visceral-interoception-on-human-brain-connectome-a-multivariate-analysis-of-covariance-of-fmri-data
#9
Behnaz Jarrahi, Dante Mantini, Behnaz Jarrahi, Dante Mantini, Behnaz Jarrahi, Dante Mantini
Sources of variations in the neural circuitry of the human brain and interrelationship between intrinsic connectivity networks (ICNs) are still a matter of debate and ongoing research. Here, we applied a multivariate analysis of covariance (MANCOVA) based on high-dimensional independent component analysis (ICA) to identify the effects of interoception and related variables on human brain connectome. Fifteen healthy right-handed subjects (all females, age range 21 - 48 years; mean age = 30.3, SD = 8.7 years) underwent a blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) that included continuous intravesical saline infusion and drainage...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227768/measures-of-the-brain-functional-network-that-correlate-with-alzheimer-s-neuropsychological-test-scores-an-fmri-and-graph-analysis-study
#10
Soroosh Golbabaei, Amin Dadashi, Hamid Soltanian-Zadeh, Soroosh Golbabaei, Amin Dadashi, Hamid Soltanian-Zadeh, Soroosh Golbabaei, Amin Dadashi, Hamid Soltanian-Zadeh
Neural degeneration in Alzheimer's disease (AD) leads to structural topology deformation that in turn changes brain functionality. The main aim of the present study is to find the brain's functional connectivity network (FCN) correlates of Alzheimer's psychological test scores. To this end, the brain's FCN is extracted from the resting state functional magnetic resonance images (rs-fMRI) of healthy controls and patients with AD and represented as a graph. Then, network measures are calculated from the graphs...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227766/short-association-bundle-atlas-based-on-inter-subject-clustering-from-hardi-data
#11
C Roman, M Guevara, D Duclap, A Lebois, C Poupon, J-F Mangin, P Guevara, C Roman, M Guevara, D Duclap, A Lebois, C Poupon, J-F Mangin, P Guevara, J-F Mangin, C Roman, D Duclap, C Poupon, A Lebois, P Guevara, M Guevara
This paper is focused on the study of short brain association fibers. We present an automatic method to identify short bundles of the superficial white matter based on inter-subject hierarchical clustering. Our method finds clusters of similar fibers, belonging to the different subjects, according to a distance measure between fibers. First, the algorithm obtains representative bundles and subsequently we perform an automatic labeling based on the anatomy, of the most stable connections. The analysis was applied to two independent groups of 37 subjects...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227763/network-effects-and-pathways-in-deep-brain-stimulation-in-parkinson-s-disease
#12
N Koirala, V Fleischer, O Granert, G Deuschl, M Muthuraman, S Groppa, N Koirala, V Fleischer, O Granert, G Deuschl, M Muthuraman, S Groppa
Deep brain stimulation of subthalamic nucleus (STN-DBS) became a standard therapeutic option in Parkinson's disease (PD), even though the underlying modulated network of STN-DBS is still poorly described. Probabilistic tractography and connectivity analysis as derived from diffusion tensor imaging (DTI) were performed together with modelling of implanted electrode positions and linked postoperative clinical outcome. Fifteen patients with idiopathic PD without dementia were selected for DBS treatment. After pre-processing, probabilistic tractography was run from cortical and subcortical seeds of the hypothesized network to targets represented by the positions of the active DBS contacts...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227761/application-of-dti-connectivity-in-lateralization-of-mtle
#13
Mohammad R Nazem-Zadeh, Susan M Bowyer, John E Moran, Esmaeil Davoodi-Bojd, Andrew Zillgitt, Hassan Bagher-Ebadian, Fariborz Mahmoudi, Kost V Elisevich, Hamid Soltanian-Zadeh, Mohammad R Nazem-Zadeh, Susan M Bowyer, John E Moran, Esmaeil Davoodi-Bojd, Andrew Zillgitt, Hassan Bagher-Ebadian, Fariborz Mahmoudi, Kost V Elisevich, Hamid Soltanian-Zadeh, Susan M Bowyer, Hassan Bagher-Ebadian, Esmaeil Davoodi-Bojd, Andrew Zillgitt, Fariborz Mahmoudi, John E Moran, Hamid Soltanian-Zadeh, Kost V Elisevich, Mohammad R Nazem-Zadeh
Diffusion tensor imaging (DTI) is a noninvasive imaging method for measuring the diffusion properties of the underlying white matter tracts through which epileptiform activity is propagated. This study investigates the structural abnormalities quantified by DTI in mesial temporal lobe epilepsy (mTLE). Fiber tracts passing through 54 anatomical sites in 12 adult mTLE patients and 12 age- and gender-matched controls were identified using DTI tractography. DTI nodal degree (ND) and laterality index were then calculated...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227759/mining-cross-frequency-coupling-microstates-cfc%C3%AE-states-from-eeg-recordings-during-resting-state-and-mental-arithmetic-tasks
#14
Stavros I Dimitriadis, Yu Sun, Nitish Thakor, Anastasios Bezerianos, Stavros I Dimitriadis, Yu Sun, Nitish Thakor, Anastasios Bezerianos, Stavros I Dimitriadis, Yu Sun, Nitish Thakor, Anastasios Bezerianos
The functional brain connectivity has been studied by analyzing synchronization between dynamic oscillations of identical frequency or between different frequencies of distinct brain areas. It has been hypothesized that cross-frequency coupling (CFC) between different frequency bands is the carrier mechanism for the coordination of global and local neural processes and hence supports the distributed information processing in the brain. In the present study, we attempt to study the dynamic evolution of CFC at resting-state and during a mental task...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227758/mining-cross-frequency-coupling-microstates-from-resting-state-meg-an-application-to-mild-traumatic-brain-injury
#15
Marios Antonakakis, Stavros I Dimitriadis, Michalis Zervakis, Andrew C Papanicolaou, George Zouridakis, Marios Antonakakis, Stavros I Dimitriadis, Michalis Zervakis, Andrew C Papanicolaou, George Zouridakis, Michalis Zervakis, Marios Antonakakis, George Zouridakis, Andrew C Papanicolaou, Stavros I Dimitriadis
Recent studies have investigated the possible role of dynamic functional connectivity and the role of cross-frequency coupling (CFC) to provide the substrate for reliable biomarkers of brain disorders. In this study, we analyzed time-varying CFC profiles from resting state Magnetoencephal-ographic recordings of 30 mild Traumatic Brain Injury (mTBI) patients and 50 normal controls. Interactions among sensors at specific pairs of frequency bands were computed via estimation of phase-to-amplitude couplings. We then computed time-varying functional connectivity graphs that were described in terms of segregation (local efficiency, LE) and integration (global efficiency, GE) and mapped those graphs to time series of GE/LE estimates...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227753/statistically-significant-time-varying-neural-connectivity-estimation-using-generalized-partial-directed-coherence
#16
Pedro L C Rodrigues, Luiz A Baccala, Pedro L C Rodrigues, Luiz A Baccala, Pedro L C Rodrigues, Luiz A Baccala
This paper illustrates the effectiveness of generalized partial directed coherence (gPDC) in characterizing time-varying neural connectivity by properly extrapolating its single trial asymptotic statistical results to a multi trial setting. Time-varying estimation is performed with a sliding-window procedure based on the proposal in [1], whereby a time-frequency map of the connectivity between channels is built. The technique is validated on a non-linear toy model generating simulated EEG and then applied to a publicly available real EEG dataset for benchmarking purposes...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227751/a-time-domain-frequency-selective-multivariate-granger-causality-approach
#17
Lutz Leistritz, Herbert Witte, Lutz Leistritz, Herbert Witte, Lutz Leistritz, Herbert Witte
The investigation of effective connectivity is one of the major topics in computational neuroscience to understand the interaction between spatially distributed neuronal units of the brain. Thus, a wide variety of methods has been developed during the last decades to investigate functional and effective connectivity in multivariate systems. Their spectrum ranges from model-based to model-free approaches with a clear separation into time and frequency range methods. We present in this simulation study a novel time domain approach based on Granger's principle of predictability, which allows frequency-selective considerations of directed interactions...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227750/detecting-spatially-highly-resolved-network-modules-a-multi-subject-approach
#18
Britta Pester, Feliberto de la Cruz, Karl-Jurgen Bar, Herbert Witte, Lutz Leistritz, Britta Pester, Feliberto de la Cruz, Karl-Jurgen Bar, Herbert Witte, Lutz Leistritz, Karl-Jurgen Bar, Britta Pester, Lutz Leistritz, Herbert Witte, Feliberto De La Cruz
The connectivity analysis of spatially highly resolved data results in networks comprising an immense number of nodes and edges which makes it hard or even impossible to investigate the high-dimensional (HD) network as a whole. A solution to this problem is offered by a connectivity-based segmentation of the HD networks into subsets of functionally similar nodes (network modules) that exhibit pronounced interaction. However, an investigation of the results at group level is problematic as identified modules are not assigned to each other across different subjects...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227749/reconstructing-multivariate-causal-structure-between-functional-brain-networks-through-a-laguerre-volterra-based-granger-causality-approach
#19
Andrea Duggento, Gaetano Valenza, Luca Passamonti, Maria Guerrisi, Riccardo Barbieri, Nicola Toschi, Andrea Duggento, Gaetano Valenza, Luca Passamonti, Maria Guerrisi, Riccardo Barbieri, Nicola Toschi, Andrea Duggento, Nicola Toschi, Maria Guerrisi, Luca Passamonti, Riccardo Barbieri, Gaetano Valenza
Classical multivariate approaches based on Granger causality (GC) which estimate functional connectivity in the brain are almost exclusively based on autoregressive models. Nevertheless, information available from past samples is limited due to both signal autocorrelation and necessarily low model orders. Consequently, multiple time-scales interactions are usually unaccounted for. To overcome these limitations, in this study we propose the use of discrete-time orthogonal Laguerre basis functions within a Wiener-Volterra decomposition of the BOLD signals to perform effective GC assessments of brain functional connectivity...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227688/development-of-a-finger-like-mechanism-of-end-effector-for-micro-surgery
#20
S M Kim, C M Park, J H Yoo, K Kim, S M Kim, C M Park, J H Yoo, K Kim, J H Yoo, K Kim, C M Park, S M Kim
Neurosurgery had been considered nearly impossible due to its technical difficulty and the danger to its special target organ, but with endoscopic methods, many such surgeries can be made safely through the nose. Endoscopic neurosurgery is limited by available instruments, however, and there remain some areas of the human body inaccessible to standard surgical tools. To overcome some of these limitations, in this study we developed a simple mechanism that could form a high curvature in a narrow space. The end product is a finger-like mechanism consisting of five body parts and four joints...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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