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https://www.readbyqxmd.com/read/28334998/spatiotemporal-mapping-of-epileptic-spikes-using-simultaneous-eeg-functional-mri
#1
Jennifer M Walz, Mangor Pedersen, Amir Omidvarnia, Mira Semmelroch, Graeme D Jackson
Epileptic spikes occur on the sub-second timescale and are known to involve not only epileptic foci but also large-scale distributed brain networks. There is likely to be a sequence of neural activity in multiple brain regions that occurs within the duration of a single spike, but standard electroencephalography-functional magnetic resonance imaging analyses, which use only the timing of the spikes to model the functional magnetic resonance imaging data, cannot determine the sequence of these activations. Our aim in this study is to temporally resolve these spatial activations to observe the spatiotemporal dynamics of the spike-related neural activity at a sub-second timescale...
February 20, 2017: Brain: a Journal of Neurology
https://www.readbyqxmd.com/read/28334882/decreased-integration-and-information-capacity-in-stroke-measured-by-whole-brain-models-of-resting-state-activity
#2
Mohit H Adhikari, Carl D Hacker, Josh S Siegel, Alessandra Griffa, Patric Hagmann, Gustavo Deco, Maurizio Corbetta
While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks...
February 20, 2017: Brain: a Journal of Neurology
https://www.readbyqxmd.com/read/28325028/tracking-intrinsic-connectivity-brain-network-features-during-successive-pseudo-resting-states-and-interoceptive-task-fmri
#3
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/28325001/reliability-of-a-cortical-surface-based-analysis-with-subcortical-regression-in-the-identification-of-resting-state-functional-networks
#4
R Lopes, P Besson, R Viard, C Bournonville, C Delmaire, X Leclerc
Many methods exist for identifying brain networks in resting-state functional magnetic resonance imaging. During the last decade, there was a growing interest in functional connectivity using surface-based analysis. However, the advantages of this approach against volume-based analysis in a data-driven model are unclear. In this study, we propose an independent component analysis based method to extract the resting-state networks directly on the cortical surface. The components associated with the subcortical regions are identified by multiple linear regressions between the signals in subcortical voxels and independent components time courses...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28323164/mapping-the-pharmacological-modulation-of-brain-oxygen-metabolism-the-effects-of-caffeine-on-absolute-cmro2-measured-using-dual-calibrated-fmri
#5
Alberto Merola, Michael A Germuska, Esther Ah Warnert, Lewys Richmond, Daniel Helme, Sharmila Khot, Kevin Murphy, Peter J Rogers, Judith E Hall, Richard G Wise
This study aims to map the acute effects of caffeine ingestion on grey matter oxygen metabolism and haemodynamics with a novel MRI method. Sixteen healthy caffeine consumers (8 males, age = 24.7±5.1) were recruited to this randomised, double-blind, placebo-controlled study. Each participant was scanned on two days before and after the delivery of an oral caffeine (250mg) or placebo capsule. Our measurements were obtained with a newly proposed estimation approach applied to data from a dual calibration fMRI experiment that uses hypercapnia and hyperoxia to modulate brain blood flow and oxygenation...
March 17, 2017: NeuroImage
https://www.readbyqxmd.com/read/28321965/robust-presurgical-functional-mri-at-7-t-using-response-consistency
#6
Pedro Lima Cardoso, Florian Ph S Fischmeister, Barbara Dymerska, Alexander Geißler, Moritz Wurnig, Siegfried Trattnig, Roland Beisteiner, Simon Daniel Robinson
Functional MRI is valuable in presurgical planning due to its non-invasive nature, repeatability, and broad availability. Using ultra-high field MRI increases the specificity and sensitivity, increasing the localization reliability and reducing scan time. Ideally, fMRI analysis for this application should identify unreliable runs and work even if the patient deviates from the prescribed task timing or if there are changes to the hemodynamic response due to pathology. In this study, a model-free analysis method-UNBIASED-based on the consistency of fMRI responses over runs was applied, to ultra-high field fMRI localizations of the hand area...
March 21, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28320846/working-memory-load-strengthens-reward-prediction-errors
#7
Anne G E Collins, Brittany Ciullo, Michael J Frank, David Badre
Reinforcement learning in simple instrumental tasks is usually modeled as a monolithic process in which reward prediction errors are used to update expected values of choice options. This modeling ignores the different contributions of different memory and decision-making systems thought to contribute even to simple learning. In an fMRI experiment, we asked how working memory and incremental reinforcement learning processes interact to guide human learning. Working memory load was manipulated by varying the number of stimuli to be learned across blocks...
March 20, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28316564/functional-circuitry-effect-of-ventral-tegmental-area-deep-brain-stimulation-imaging-and-neurochemical-evidence-of-mesocortical-and-mesolimbic-pathway-modulation
#8
Megan L Settell, Paola Testini, Shinho Cho, Jannifer H Lee, Charles D Blaha, Hang J Jo, Kendall H Lee, Hoon-Ki Min
Background: The ventral tegmental area (VTA), containing mesolimbic and mesocortical dopaminergic neurons, is implicated in processes involving reward, addiction, reinforcement, and learning, which are associated with a variety of neuropsychiatric disorders. Electrical stimulation of the VTA or the medial forebrain bundle and its projection target the nucleus accumbens (NAc) is reported to improve depressive symptoms in patients affected by severe, treatment-resistant major depressive disorder (MDD) and depressive-like symptoms in animal models of depression...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28316255/a-bayesian-double-fusion-model-for-resting-state-brain-connectivity-using-joint-functional-and-structural-data
#9
Hakmook Kang, Hernando Ombao, Christopher Fonnesbeck, Zhaohua Ding, Victoria L Morgan
Current approaches separately analyze concurrently acquired diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) data. The primary limitation of these approaches is that they do not take advantage of the information from DTI that could potentially enhance estimation of resting state functional connectivity (FC) between brain regions. To overcome this limitation, we develop a Bayesian hierarchical spatio-temporal model that incorporates structural connectivity into estimating FC. In our proposed approach, structural connectivity (SC) based on DTI data is used to construct an informative prior for functional connectivity based on resting state fMRI data via the Cholesky decomposition...
March 19, 2017: Brain Connectivity
https://www.readbyqxmd.com/read/28295824/wavelet-entropy-of-bold-time-series-an-application-to-rolandic-epilepsy
#10
Lalit Gupta, Jacobus F A Jansen, Paul A M Hofman, René M H Besseling, Anton J A de Louw, Albert P Aldenkamp, Walter H Backes
PURPOSE: To assess the wavelet entropy for the characterization of intrinsic aberrant temporal irregularities in the time series of resting-state blood-oxygen-level-dependent (BOLD) signal fluctuations. Further, to evaluate the temporal irregularities (disorder/order) on a voxel-by-voxel basis in the brains of children with Rolandic epilepsy. MATERIALS AND METHODS: The BOLD time series was decomposed using the discrete wavelet transform and the wavelet entropy was calculated...
March 11, 2017: Journal of Magnetic Resonance Imaging: JMRI
https://www.readbyqxmd.com/read/28290073/prefrontal-dysconnectivity-links-to-working-memory-deficit-in-first-episode-schizophrenia
#11
Xiaojing Fang, Yulin Wang, Luqi Cheng, Yuanchao Zhang, Yuan Zhou, Shihao Wu, Huan Huang, Jilin Zou, Cheng Chen, Jun Chen, Huiling Wang, Tianzi Jiang
Working memory (WM) deficit is a core feature of schizophrenia and is characterized by abnormal functional integration in the prefrontal cortex, including the dorsolateral prefrontal cortex (dLPFC), dorsal anterior cingulate cortex (dACC), and ventrolateral prefrontal cortex (vLPFC). However, the specific mechanism by which the abnormal neuronal circuits that involve these brain regions contribute to this deficit is still unclear. Therefore, this study focused on these regions and sought to answer which abnormal causal relationships in these regions can be linked to impaired WM in schizophrenia...
March 13, 2017: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/28287976/network-optimization-of-functional-connectivity-within-default-mode-network-regions-to-detect-cognitive-decline
#12
Wanpracha Art Chaovalitwongse, Daehan Won, Onur Seref, Paul Borghesani, Mary Katie Askren, Sherry Willis, Tom Grabowski
The rapid aging of the world's population is causing an increase in the prevalence of cognitive decline and degenerative brain disease in the elderly. Current diagnoses of amnestic and nonamnestic Mild Cognitive Impairment (MCI), which may represent early stage Alzheimer's disease or related degenerative conditions, are based on clinical grounds. The recent emergence of advanced network analyses of functional Magnetic Resonance Imaging (fMRI) data taken at cognitive rest has provided insight that declining functional connectivity of the default mode network (DMN) may be correlated with neurological disorders, and particularly prodromal Alzheimer's disease...
March 7, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28286475/neural-networks-for-time-perception-and-working-memory
#13
Sertaç Üstün, Emre H Kale, Metehan Çiçek
Time is an important concept which determines most human behaviors, however questions remain about how time is perceived and which areas of the brain are responsible for time perception. The aim of this study was to evaluate the relationship between time perception and working memory in healthy adults. Functional magnetic resonance imaging (fMRI) was used during the application of a visual paradigm. In all of the conditions, the participants were presented with a moving black rectangle on a gray screen. The rectangle was obstructed by a black bar for a time period and then reappeared again...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28282414/cognitive-control-attention-and-the-other-race-effect-in-memory
#14
Thackery I Brown, Melina R Uncapher, Tiffany E Chow, Jennifer L Eberhardt, Anthony D Wagner
People are better at remembering faces from their own race than other races-a phenomenon with significant societal implications. This Other Race Effect (ORE) in memory could arise from different attentional allocation to, and cognitive control over, same- and other-race faces during encoding. Deeper or more differentiated processing of same-race faces could yield more robust representations of same- vs. other-race faces that could support better recognition memory. Conversely, to the extent that other-race faces may be characterized by lower perceptual expertise, attention and cognitive control may be more important for successful encoding of robust, distinct representations of these stimuli...
2017: PloS One
https://www.readbyqxmd.com/read/28275697/a-robust-biomarker-of-large-scale-network-failure-in-alzheimer-s-disease
#15
Daniela A Wiepert, Val J Lowe, David S Knopman, Bradley F Boeve, Jonathan Graff-Radford, Ronald C Petersen, Clifford R Jack, David T Jones
INTRODUCTION: Biomarkers for Alzheimer's disease (AD) pathophysiology have been developed that focus on various levels of brain organization. However, no robust biomarker of large-scale network failure has been developed. Using the recently introduced cascading network failure model of AD, we developed the network failure quotient (NFQ) as a biomarker of this process. METHODS: We developed and optimized the NFQ using our recently published analyses of task-free functional magnetic resonance imaging data in clinically normal (n = 43) and AD dementia participants (n = 28) from the Alzheimer's Disease Neuroimaging Initiative...
2017: Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring
https://www.readbyqxmd.com/read/28269497/reconstructing-multivariate-causal-structure-between-functional-brain-networks-through-a-laguerre-volterra-based-granger-causality-approach
#16
Andrea Duggento, Gaetano Valenza, Luca Passamonti, Maria Guerrisi, Riccardo Barbieri, Nicola Toschi
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/28269091/improving-quality-and-intelligibility-of-speech-using-single-microphone-for-the-broadband-fmri-noise-at-low-snr
#17
Chetan Vahanesa, Chandan K A Reddy, Issa M S Panahi
Functional Magnetic Resonance Imaging (fMRI) is used in many diagnostic procedures for neurological related disorders. Strong broadband acoustic noise generated during fMRI scan interferes with the speech communication between the physician and the patient. In this paper, we propose a single microphone Speech Enhancement (SE) technique which is based on the supervised machine learning technique and a statistical model based SE technique. The proposed algorithm is robust and computationally efficient and has capability to run in real-time...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28265121/brain-structural-and-functional-signatures-of-impulsive-compulsive-behaviours-in-parkinson-s-disease
#18
F Imperiale, F Agosta, E Canu, V Markovic, A Inuggi, M Jecmenica-Lukic, A Tomic, M Copetti, S Basaia, V S Kostic, M Filippi
This study assessed brain structural and functional alterations in patients with Parkinson's disease and impulsive-compulsive behaviours (PD-ICB) compared with controls and PD no-ICB cases. Eighty-five PD patients (35 PD-ICB) and 50 controls were recruited. All subjects underwent three-dimensional T1-weighted, diffusion tensor (DT), and resting state functional magnetic resonance imaging (RS fMRI). We assessed cortical thickness with surface-based morphometry, subcortical volumes using FIRST, DT MRI metrics using region of interest and tractography approaches, and RS fMRI using a model free approach...
March 7, 2017: Molecular Psychiatry
https://www.readbyqxmd.com/read/28261045/a-statistical-method-to-distinguish-functional-brain-networks
#19
André Fujita, Maciel C Vidal, Daniel Y Takahashi
One major problem in neuroscience is the comparison of functional brain networks of different populations, e.g., distinguishing the networks of controls and patients. Traditional algorithms are based on search for isomorphism between networks, assuming that they are deterministic. However, biological networks present randomness that cannot be well modeled by those algorithms. For instance, functional brain networks of distinct subjects of the same population can be different due to individual characteristics...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28256520/multistability-of-the-brain-network-for-self-other-processing
#20
Yi-An Chen, Tsung-Ren Huang
Early fMRI studies suggested that brain areas processing self-related and other-related information were highly overlapping. Hypothesising functional localisation of the cortex, researchers have tried to locate "self-specific" and "other-specific" regions within these overlapping areas by subtracting suspected confounding signals in task-based fMRI experiments. Inspired by recent advances in whole-brain dynamic modelling, we instead explored an alternative hypothesis that similar spatial activation patterns could be associated with different processing modes in the form of different synchronisation patterns...
March 3, 2017: Scientific Reports
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