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https://www.readbyqxmd.com/read/28227751/a-time-domain-frequency-selective-multivariate-granger-causality-approach
#1
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/28227105/quantifying-connectivity-in-a-physiology-based-model-using-adaptive-dynamic-causal-modelling
#2
W Xiang, C Yang, A Karfoul, R Le Bouquin Jeannes, W Xiang, C Yang, A Karfoul, R Le Bouquin Jeannes, A Karfoul, W Xiang, C Yang
This paper proposes an Adaptive Dynamic Causal Modelling based approach to detect and quantify effective connectivity in human brain structures injured by epileptic activities. The identification of the parameters in the physiology based model subtended the Electroencephalographic observations is performed by improving the optimization step in the Expectation Maximization algorithm. Considering unidirectional flow propagation, we show the efficiency of our proposed approach compared to the conventional technique...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226817/effective-connectivity-matrix-for-neural-ensembles
#3
Qi She, Winnie K Y So, Rosa H M Chan, Qi She, Winnie K Y So, Rosa H M Chan, Rosa H M Chan, Qi She, Winnie K Y So
In this paper, we present an efficient framework to study the directional interactions within the multiple-input multiple-output (MIMO) biological neural network from spiketrain data. We used an efficient generalized linear model (GLM) with Laguerre basis functions to model a MIMO neural system, and developed an Effective Connectivity Matrix (ECM) to visualize excitatory and inhibitory connections within the neural network. A new causality representation was developed based on system dynamics. Statistical test was applied to identify the significance of the measured causality...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226692/tle-lateralization-using-whole-brain-structural-connectivity
#4
Esmaeil Davoodi-Bojd, Kost V Elisevich, Jason Schwalb, Ellen Air, Hamid Soltanian-Zadeh, Esmaeil Davoodi-Bojd, Kost V Elisevich, Jason Schwalb, Ellen Air, Hamid Soltanian-Zadeh, Hamid Soltanian-Zadeh, Kost V Elisevich, Esmaeil Davoodi-Bojd, Ellen Air, Jason Schwalb
A prerequisite of temporal lobe epilepsy (TLE) surgery is to lateralize the disease. Recent studies have shown the capability of diffusion weighted MRI (DWMRI) in lateralizing TLE patients. This has been achieved by analyzing diffusion parameters of specific white matter tracts or regions known to be involved in the disease; however, other brain regions and connections have not been investigated for TLE lateralization. Whole brain structural connectivity using DWMRI provides a wealth of information regarding the structural connections in the brain...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226600/analysis-of-magnetoencephalography-signals-from-alzheimer-s-disease-patients-using-granger-causality
#5
Celia Juan-Cruz, Carlos Gomez, Jesus Poza, Alberto Fernandez, Roberto Hornero, Celia Juan-Cruz, Carlos Gomez, Jesus Poza, Alberto Fernandez, Roberto Hornero, Roberto Hornero, Celia Juan-Cruz, Carlos Gomez, Jesus Poza, Alberto Fernandez
The aim of this study was to analyze resting-state magnetoencephalography (MEG) activity in Alzheimer's disease (AD) by means of Granger Causality (GC), an effective connectivity measure that provides an estimation of the information flow between brain regions. For this task, five minutes of MEG recordings were acquired with a 148-channel whole-head magnetometer from 36 AD patients and 26 healthy controls. Abnormalities in AD connectivity were found in the five typical frequency bands: delta (δ, 1-4 Hz), theta (θ, 4-8 Hz), alpha (α, 8-13 Hz), beta (β, 13-30 Hz), and gamma (γ, 30-65 Hz)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226598/estimation-of-resting-state-effective-connectivity-in-epilepsy-using-direct-directed-transfer-function
#6
Biswajit Maharathi, Jeffrey A Loeb, James Patton, Biswajit Maharathi, Jeffrey A Loeb, James Patton, Biswajit Maharathi, James Patton, Jeffrey A Loeb
There has been an increasing demand among neuroscientists to understand the complex network of functionally connected neural assemblies in the human brain. For this purpose, computational EEG research is widely used by researchers due to its remarkable advantage in providing high temporal resolution, and ease of analysis across different frequency bands. Here we analyzed Electrocorticographic (ECoG) signals of electrodes placed on frontal-parietal neocortex brain region of 8 pediatric epileptic patients. In order to evaluate the directed causal relationship among different brain regions, we employed a Granger causality based multivariate connectivity estimator named direct Directed Transfer Function (dDTF) to identify signal propagations among the selected set of electrode in the frequency range 1-50Hz...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226440/measuring-the-agreement-between-brain-connectivity-networks
#7
J Toppi, N Sciaraffa, Y Antonacci, A Anzolin, S Caschera, M Petti, D Mattia, L Astolfi, J Toppi, N Sciaraffa, Y Antonacci, A Anzolin, S Caschera, M Petti, D Mattia, L Astolfi, D Mattia, L Astolfi, Y Antonacci, A Anzolin, S Caschera, M Petti, N Sciaraffa, J Toppi
Investigating the level of similarity between two brain networks, resulting from measures of effective connectivity in the brain, can be of interest from many respects. In this study, we propose and test the idea to borrow measures of association used in machine learning to provide a measure of similarity between the structure of (un-weighted) brain connectivity networks. The measures here explored are the accuracy, Cohen's Kappa (K) and Area Under Curve (AUC). We implemented two simulation studies, reproducing two contexts of application that can be particularly interesting for practical applications, namely: i) in methodological studies, performed on surrogate data, aiming at comparing the estimated network with the corresponding ground-truth network; ii) in applications to real data, when it is necessary to compare the structure of a network obtained in a specific subject with a reference (e...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226306/task-dependent-modulation-of-amygdala-connectivity-in-social-anxiety-disorder
#8
Lora Minkova, Ronald Sladky, Georg S Kranz, Michael Woletz, Nicole Geissberger, Christoph Kraus, Rupert Lanzenberger, Christian Windischberger
Increased amygdala activation is consistently found in patients suffering from social anxiety disorder (SAD), a psychiatric condition characterized by an intense fear of social situations and scrutiny. Disruptions in the amygdalar-frontal network in SAD may explain the inability of frontal regions to appropriately down-regulate amygdalar hyper-activation. In this study, we measured 15 SAD patients and 15 healthy controls during an affective counting Stroop task with emotional faces to assess the interaction of affective stimuli with a cognitive task in SAD, as well as to investigate the causal interactions between the amygdala and the medial orbitofrontal cortex (OFC) using dynamic causal modeling (DCM)...
February 9, 2017: Psychiatry Research
https://www.readbyqxmd.com/read/28224285/abnormal-effective-connectivity-in-the-brain-is-involved-in-auditory-verbal-hallucinations-in-schizophrenia
#9
Baojuan Li, Long-Biao Cui, Yi-Bin Xi, Karl J Friston, Fan Guo, Hua-Ning Wang, Lin-Chuan Zhang, Yuan-Han Bai, Qing-Rong Tan, Hong Yin, Hongbing Lu
Information flow among auditory and language processing-related regions implicated in the pathophysiology of auditory verbal hallucinations (AVHs) in schizophrenia (SZ) remains unclear. In this study, we used stochastic dynamic causal modeling (sDCM) to quantify connections among the left dorsolateral prefrontal cortex (inner speech monitoring), auditory cortex (auditory processing), hippocampus (memory retrieval), thalamus (information filtering), and Broca's area (language production) in 17 first-episode drug-naïve SZ patients with AVHs, 15 without AVHs, and 19 healthy controls using resting-state functional magnetic resonance imaging...
February 21, 2017: Neuroscience Bulletin
https://www.readbyqxmd.com/read/28212570/altered-amygdala-and-hippocampus-effective-connectivity-in-mild-cognitive-impairment-patients-with-depression-a-resting-state-functional-mr-imaging-study-with-granger-causality-analysis
#10
Li Juan Zheng, Gui Fen Yang, Xin Yuan Zhang, Yun Fei Wang, Ya Liu, Gang Zheng, Guang Ming Lu, Long Jiang Zhang, Ying Han
Neuroimaging studies have demonstrated that the major depression disorder would increase the risk of dementia in the older with amnestic cognitive impairment. We used granger causality analysis algorithm to explore the amygdala- and hippocampus-based directional connectivity patterns in 12 patients with major depression disorder and amnestic cognitive impairment (mean age: 69.5 ± 10.3 years), 13 amnestic cognitive impairment patients (mean age: 72.7 ± 8.5 years) and 14 healthy controls (mean age: 64.7 ± 7...
February 15, 2017: Oncotarget
https://www.readbyqxmd.com/read/28205364/altered-neural-mechanisms-of-cognitive-control-in-patients-with-primary-progressive-multiple-sclerosis-an-effective-connectivity-study
#11
Ekaterina Dobryakova, Maria Assunta Rocca, Paola Valsasina, John DeLuca, Massimo Filippi
Primary progressive multiple sclerosis (PPMS) leads to physical and cognitive disability. Specifically, cognitive deficits in PPMS have been explained by both grey matter atrophy and white matter lesions. However, existing research still lacks in the understanding of how the brain of a patient with PPMS functions under cognitive control demands. Thus, the aim of the current study was to examine information integration in patients with PPMS using a search-based effective connectivity method. Fourteen patients with PPMS and 22 age- and gender-matched healthy controls (HC) performed the Stroop task, a cognitively demanding interference task that taxes neural resources required for cognitive control and response inhibition...
February 16, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28167926/disrupted-causal-connectivity-anchored-in-the-posterior-cingulate-cortex-in-amnestic-mild-cognitive-impairment
#12
Hong Yang, Chengwei Wang, Yumei Zhang, Liming Xia, Zhan Feng, Deqiang Li, Shunliang Xu, Haiyan Xie, Feng Chen, Yushu Shi, Jue Wang
Amnestic mild cognitive impairment (aMCI) is a transitional stage between normal cognitive aging and Alzheimer's disease. Previous studies have found that neuronal activity and functional connectivity impaired in many functional networks, especially in the default mode network (DMN), which is related to significantly impaired cognitive and memory functions in aMCI patients. However, few studies have focused on the effective connectivity of the DMN and its subsystems in aMCI patients. The posterior cingulate cortex (PCC) is considered a crucial region in connectivity of the DMN and its key subsystem...
2017: Frontiers in Neurology
https://www.readbyqxmd.com/read/28150911/cerebellar-contributions-to-biological-motion-perception-in-autism-and-typical-development
#13
Allison Jack, Cara M Keifer, Kevin A Pelphrey
Growing evidence suggests that posterior cerebellar lobe contributes to social perception in healthy adults. However, they know little about how this process varies across age and with development. Using cross-sectional fMRI data, they examined cerebellar response to biological (BIO) versus scrambled (SCRAM) motion within typically developing (TD) and autism spectrum disorder (ASD) samples (age 4-30 years old), characterizing cerebellar response and BIO > SCRAM-selective effective connectivity, as well as associations with age and social ability...
February 2, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28131891/from-connectome-to-cognition-the-search-for-mechanism-in-human-functional-brain-networks
#14
Ravi D Mill, Takuya Ito, Michael W Cole
Recent developments in functional connectivity research have expanded the scope of human neuroimaging, from identifying changes in regional activation amplitudes to detailed mapping of large-scale brain networks. However, linking network processes to a clear role in cognition demands advances in the theoretical frameworks, algorithms, and experimental approaches applied. This would help evolve the field from a descriptive to an explanatory state, by targeting network interactions that can mechanistically account for cognitive effects...
January 26, 2017: NeuroImage
https://www.readbyqxmd.com/read/28113682/exploring-the-epileptic-brain-network-using-time-variant-effective-connectivity-and-graph-theory
#15
Silvia Storti, Ilaria Boscolo Galazzo, Sehresh Khan, Paolo Manganotti, Gloria Menegaz
The application of time-varying measures of causality between source time series can be very informative to elucidate the direction of communication among the regions of an epileptic brain. The aim of the study was to identify the dynamic patterns of epileptic networks in focal epilepsy by applying multivariate adaptive directed transfer function (ADTF) analysis and graph-theory to high-density electroencephalographic (hdEEG) recordings. The cortical network was modeled after source reconstruction and topology modulations were detected during interictal spikes...
September 9, 2016: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28112466/tinnitus-distress-is-linked-to-enhanced-resting-state-functional-connectivity-from-the-limbic-system-to-the-auditory-cortex
#16
Yu-Chen Chen, Wenqing Xia, Huiyou Chen, Yuan Feng, Jin-Jing Xu, Jian-Ping Gu, Richard Salvi, Xindao Yin
The phantom sound of tinnitus is believed to be triggered by aberrant neural activity in the central auditory pathway, but since this debilitating condition is often associated with emotional distress and anxiety, these comorbidities likely arise from maladaptive functional connections to limbic structures such as the amygdala and hippocampus. To test this hypothesis, resting-state functional magnetic resonance imaging (fMRI) was used to identify aberrant effective connectivity of the amygdala and hippocampus in tinnitus patients and to determine the relationship with tinnitus characteristics...
January 23, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28108394/unsmoothed-functional-mri-of-the-human-amygdala-and-bed-nucleus-of-the-stria-terminalis-during-processing-of-emotional-faces
#17
Ronald Sladky, Nicole Geissberger, Daniela M Pfabigan, Christoph Kraus, Martin Tik, Michael Woletz, Katharina Paul, Thomas Vanicek, Bastian Auer, Georg S Kranz, Claus Lamm, Rupert Lanzenberger, Christian Windischberger
Functional neuroimaging of the human amygdala has been of great interest to uncover the neural underpinnings of emotions, mood, motivation, social cognition, and decision making, as well as their dysfunction in psychiatric disorders. Yet, several factors limit in vivo imaging of amygdalar function, most importantly its location deep within the temporal lobe adjacent to air-filled cavities that cause magnetic field inhomogeneities entailing signal dropouts. Additionally, the amygdala and the extended amygdalar region consist of several substructures, which have been assigned different functions and have important implications for functional and effective connectivity studies...
January 17, 2017: NeuroImage
https://www.readbyqxmd.com/read/28077184/abnormalities-in-the-effective-connectivity-of-visuothalamic-circuitry-in-schizophrenia
#18
S J Iwabuchi, L Palaniyappan
BACKGROUND: Sensory-processing deficits appear crucial to the clinical expression of symptoms of schizophrenia. The visual cortex displays both dysconnectivity and aberrant spontaneous activity in patients with persistent symptoms and cognitive deficits. In this paper, we examine visual cortex in the context of the remerging notion of thalamic dysfunction in schizophrenia. We examined specific regional and longer-range abnormalities in sensory and thalamic circuits in schizophrenia, and whether these patterns are strong enough to discriminate symptomatic patients from controls...
January 12, 2017: Psychological Medicine
https://www.readbyqxmd.com/read/28073788/dopamine-controls-parkinson-s-tremor-by-inhibiting-the-cerebellar-thalamus
#19
Michiel F Dirkx, Hanneke E M den Ouden, Esther Aarts, Monique H M Timmer, Bastiaan R Bloem, Ivan Toni, Rick C Helmich
Parkinson's resting tremor is related to altered cerebral activity in the basal ganglia and the cerebello-thalamo-cortical circuit. Although Parkinson's disease is characterized by dopamine depletion in the basal ganglia, the dopaminergic basis of resting tremor remains unclear: dopaminergic medication reduces tremor in some patients, but many patients have a dopamine-resistant tremor. Using pharmacological functional magnetic resonance imaging, we test how a dopaminergic intervention influences the cerebral circuit involved in Parkinson's tremor...
January 9, 2017: Brain: a Journal of Neurology
https://www.readbyqxmd.com/read/28065836/learning-effective-connectivity-from-fmri-using-autoregressive-hidden-markov-model-with-missing-data
#20
Shilpa Dang, Santanu Chaudhury, Brejesh Lall, Prasun Kumar Roy
BACKGROUND: Effective connectivity (EC) analysis of neuronal groups using fMRI delivers insights about functional-integration. However, fMRI signal has low-temporal resolution due to down-sampling and indirectly measures underlying neuronal activity. NEW METHOD: The aim is to address above issues for more reliable EC estimates. This paper proposes use of autoregressive hidden Markov model with missing data (AR-HMM-md) in dynamically multi-linked (DML) framework for learning EC using multiple fMRI time series...
January 5, 2017: Journal of Neuroscience Methods
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