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Functional connectivity

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https://www.readbyqxmd.com/read/28227772/the-chronnectome-evaluating-replicability-of-dynamic-connectivity-patterns-in-7500-resting-fmri-datasets
#1
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
#2
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
#3
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
#4
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
#5
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/28227759/mining-cross-frequency-coupling-microstates-cfc%C3%AE-states-from-eeg-recordings-during-resting-state-and-mental-arithmetic-tasks
#6
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
#7
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/28227751/a-time-domain-frequency-selective-multivariate-granger-causality-approach
#8
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
#9
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
#10
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/28227534/quantifying-the-human-finger-reachable-space
#11
Trieu H Pham, Pubudu N Pathirana, Trieu H Pham, Pubudu N Pathirana, Trieu H Pham, Pubudu N Pathirana
Describing the flexibility of the hand using the reachable space concept has drawn the attention of many researchers in recent years. Existing approaches involving numerical techniques to obtain the reachable space are generally computationally expensive. In this study, we propose a resource-friendly approach to determine and quantify the bidimensional reachable space of the finger. The fundamental idea of the approach connects to a set of arc formulae for the boundary of the reachable space. These formulae of the boundary result a unique description to calculate the area of the reachable space using Green's theorem...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227526/valence-dependent-changes-in-visual-arousing-elicitation-an-exploratory-study-in-eeg-gamma-oscillations
#12
Alberto Greco, Gaetano Valenza, Enzo Pasquale Scilingo, Alberto Greco, Gaetano Valenza, Enzo Pasquale Scilingo, Gaetano Valenza, Enzo Pasquale Scilingo, Alberto Greco
Emotion regulation involves several brain areas such as prefrontal cortex, amygdala, and insular cortex. However, considering different levels of arousing elicitations, how such a brain dynamics is affected by emotional pleasant/unpleasant (valence) elicitation is not fully understood. To this aim, we propose an Electroencephalographic (EEG)-based preliminary study in which 22 healthy subjects were elicited through affective pictures gathered from the International Affective Picture System. Considering 4 arousing levels, each of which including two valence levels (pleasant and unpleasant), we investigated EEG power spectra and functional connectivity...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227523/a-measure-of-cortico-cortical-potentials-evoked-by-10-hz-direct-electrical-stimulation-of-the-brain-and-by-means-of-a-differential-recording-mode-of-electrocorticographic-signals
#13
Marion Vincent, Olivier Rossel, Hugues Duffau, Francois Bonnetblanc, David Guiraud, Marion Vincent, Olivier Rossel, Hugues Duffau, Francois Bonnetblanc, David Guiraud, Olivier Rossel, David Guiraud, Francois Bonnetblanc, Hugues Duffau, Marion Vincent
Direct electrical stimulation (DES) at 60 Hz is used to perform real-time functional mapping of the brain during wide-awake neurosurgery. The electrophysiological effects of DES are largely unknown, locally and at a more remote distance. Here, by lowering the DES frequency to 10 Hz and by using a differential recording mode of electro-corticographic (ECoG) signals to improve the focality, we were able to record cortico-cortical evoked potentials easily with standard current amplitude of stimulation (2 mA). DES applied at 10 Hz and differential recording of ECoG could be used to map on-line the connectivity between different sub-cortical and cortical areas with a higher spatial accuracy...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227516/identification-of-emotion-associated-brain-functional-network-with-phase-locking-value
#14
V Gonuguntla, R Mallipeddi, K C Veluvolu, V Gonuguntla, R Mallipeddi, K C Veluvolu, V Gonuguntla, K C Veluvolu, R Mallipeddi
Recognition of discriminative brain functional network pattern and regions corresponding to emotions are important in understanding the neuron functional network underlying the human emotion process. Emotion models mapping onto brain is possible with the help of emotion-specific network patterns and its corresponding brain regions. This paper presents a method to identify emotion related functional connectivity pattern and their distinctive associated regions using EEG phase synchrony (phase locking value (PLV)) connectivity analysis...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227449/comparison-of-methods-for-the-evaluation-of-nibp-from-pulse-transit-time
#15
L Peter, N Noury, M Cerny, I Nykl, L Peter, N Noury, M Cerny, I Nykl, L Peter, I Nykl, N Noury, M Cerny
Non-invasive blood pressure measurement (NIBP) is one of the most discussed topic in cardiovascular medicine. Currently continuous measurement of blood pressure is possible by invasive methods, which makes the measurement impractical for Doctors and uncomfortable for the patients. It is possible to use special devices to measure blood pressure noninvasively continuously but there are still some problems with long time monitoring and comfort for patient. Physiologically there is connection between electrical and mechanical heart functions, propagation of pulse wave and blood pressure value...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227407/recursive-feature-elimination-for-biomarker-discovery-in-resting-state-functional-connectivity
#16
Hariharan Ravishankar, Radhika Madhavan, Rakesh Mullick, Teena Shetty, Luca Marinelli, Suresh E Joel, Hariharan Ravishankar, Radhika Madhavan, Rakesh Mullick, Teena Shetty, Luca Marinelli, Suresh E Joel, Suresh E Joel, Teena Shetty, Luca Marinelli, Rakesh Mullick, Hariharan Ravishankar, Radhika Madhavan
Biomarker discovery involves finding correlations between features and clinical symptoms to aid clinical decision. This task is especially difficult in resting state functional magnetic resonance imaging (rs-fMRI) data due to low SNR, high-dimensionality of images, inter-subject and intra-subject variability and small numbers of subjects compared to the number of derived features. Traditional univariate analysis suffers from the problem of multiple comparisons. Here, we adopt an alternative data-driven method for identifying population differences in functional connectivity...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227403/abnormal-interhemispheric-resting-state-functional-connectivity-in-primary-open-angle-glaucoma
#17
Peng Zhou, Jieqiong Wang, Ting Li, Ningli Wang, Junfang Xian, Huiguang He, Peng Zhou, Jieqiong Wang, Ting Li, Ningli Wang, Junfang Xian, Huiguang He, Ningli Wang, Junfang Xian, Huiguang He, Ting Li, Jieqiong Wang, Peng Zhou
Glaucoma is the second leading cause of blindness and it has been the topic of massive studies to explore the underlying mechanisms of the disease. Resting-state neuroimaging studies have been widely applied to investigate the functional damage of the brain, but little is known about the alterations of the interhemispheric resting-state functional connectivity (RSFC) in patients with primary open-angle glaucoma (POAG). In the present study, we used a newly developed voxel-mirrored homotopic connectivity (VMHC) method to explore the interhemispheric RSFC of the brain in POAG patients...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227399/functional-connectivity-analysis-using-whole-brain-and-regional-network-metrics-in-ms-patients
#18
V C Chirumamilla, V Fleischer, A Droby, T Anjum, M Muthuraman, F Zipp, S Groppa, V C Chirumamilla, V Fleischer, A Droby, T Anjum, M Muthuraman, F Zipp, S Groppa, A Droby, S Groppa, F Zipp, V C Chirumamilla, T Anjum, V Fleischer, M Muthuraman
In the present study we investigated brain network connectivity differences between patients with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC) as derived from functional resonance magnetic imaging (fMRI) using graph theory. Resting state fMRI data of 18 RRMS patients (12 female, mean age ± SD: 42 ± 12.06 years) and 25 HC (8 female, 29.2 ± 5.38 years) were analyzed. In order to obtain information of differences in entire brain network, we focused on both, local and global network connectivity parameters...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227395/impaired-episodic-memory-network-in-subjects-at-high-risk-for-alzheimer-s-disease
#19
Yafeng Zhan, Jianhua Ma, Kaibin Xu, Yanhui Ding, Yue Cui, Zhengyi Yang, Yong Liu, Yafeng Zhan, Jianhua Ma, Kaibin Xu, Yanhui Ding, Yue Cui, Zhengyi Yang, Yong Liu, Yanhui Ding, Kaibin Xu, Yue Cui, Yafeng Zhan, Jianhua Ma, Zhengyi Yang, Yong Liu
Episodic memory dysfunction is one of the hallmark symptoms of Alzheimer's disease (AD) and mild cognitive impairment (MCI). This cognitive impairment may be related to abnormal brain structure and activity. Functional connectivity mapping (FCM) analysis provides a powerful tool for exploring the topology of human brain function using magnetic resonance imaging (MRI). Thus, it would be advantageous to investigate the changes in functional connectivity within the episodic memory network in a longitudinal MCI dataset, as it may be helpful in identifying a potential marker of disease progress...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227293/complex-network-analysis-of-resting-state-fmri-of-the-brain
#20
Abdul Rauf Anwar, Muhammad Yousaf Hashmy, Bilal Imran, Muhammad Hussnain Riaz, Sabtain Muhammad Muntazir Mehdi, Makii Muthalib, Stephane Perrey, Gunther Deuschl, Sergiu Groppa, Muthuraman Muthuraman, Abdul Rauf Anwar, Muhammad Yousaf Hashmy, Bilal Imran, Muhammad Hussnain Riaz, Sabtain Muhammad Muntazir Mehdi, Makii Muthalib, Stephane Perrey, Gunther Deuschl, Sergiu Groppa, Muthuraman Muthuraman, Bilal Imran, Makii Muthalib, Gunther Deuschl, Sergiu Groppa, Abdul Rauf Anwar, Stephane Perrey, Muhammad Hussnain Riaz, Muthuraman Muthuraman, Muhammad Yousaf Hashmy
Due to the fact that the brain activity hardly ever diminishes in healthy individuals, analysis of resting state functionality of the brain seems pertinent. Various resting state networks are active inside the idle brain at any time. Based on various neuro-imaging studies, it is understood that various structurally distant regions of the brain could be functionally connected. Regions of the brain, that are functionally connected, during rest constitutes to the resting state network. In the present study, we employed the complex network measures to estimate the presence of community structures within a network...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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