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Eeg Brain Connectivity

Christine Beauchene, Subhradeep Roy, Rosalyn Moran, Alexander Leonessa, Nicole Abaid
OBJECTIVE: The objective of this paper is to didactically compare resting state connectivity networks computed using two different methods called Phase Locking Value (PLV) and Convergent Cross-Mapping (CCM). PLV is a ubiquitous measure of connectivity in electrophysiological research, but is less often applied to fMRI BOLD time series since this model-based metric assumes that oscillatory coupling is a sufficient condition for connectivity. Alternatively, CCM is a model-free method, which detects potentially nonlinear causal influences based on the ability to estimate one time-series with another and does not assume an oscillatory structure...
August 10, 2018: Journal of Neural Engineering
Selenia di Fronso, Gabriella Tamburro, Claudio Robazza, Laura Bortoli, Silvia Comani, Maurizio Bertollo
The aim of this study was to examine EEG coherence before, during, and after time to exhaustion (TTE) trials in an endurance cycling task, as well as the effect of effort level and attentional focus (i.e., functional external, functional internal, and dysfunctional internal associative strategies-leading to Type 1, Type 2, and Type 3 performances) on brain functional connectivity. Eleven college-aged participants performed the TTE test on a cycle-ergometer with simultaneous EEG and rate of perceived exertion (RPE) monitoring...
2018: Frontiers in Psychology
Paula C Salamone, Sol Esteves, Vladimiro J Sinay, Indira García-Cordero, Sofía Abrevaya, Blas Couto, Federico Adolfi, Miguel Martorell, Agustín Petroni, Adrián Yoris, Kathya Torquati, Florencia Alifano, Agustina Legaz, Fátima P Cassará, Diana Bruno, Andrew H Kemp, Eduar Herrera, Adolfo M García, Agustín Ibáñez, Lucas Sedeño
Multiple sclerosis (MS) patients present several alterations related to sensing of bodily signals. However, no specific neurocognitive impairment has yet been proposed as a core deficit underlying such symptoms. We aimed to determine whether MS patients present changes in interoception-that is, the monitoring of autonomic bodily information-a process that might be related to various bodily dysfunctions. We performed two studies in 34 relapsing-remitting, early-stage MS patients and 46 controls matched for gender, age, and education...
August 4, 2018: Human Brain Mapping
Fadi N Karameh, Ziad Nahas
Model-based network discovery measures, such as the brain effective connectivity, require fitting of generative process models to measurements obtained from key areas across the network. For distributed dynamic phenomena, such as generalized seizures and slow-wave sleep, studying effective connectivity from real-time recordings is significantly complicated since (i) outputs from only a subnetwork can be practically measured, and (ii) exogenous subnetwork inputs are unobservable. Model fitting, therefore, constitutes a challenging blind module identification or model inversion problem for finding both the parameters and the many unknown inputs of the subnetwork...
August 4, 2018: Brain Topography
Francesca Miraglia, Fabrizio Vecchio, Paolo Maria Rossini
The aim of the present study was to understand whether modeling brain function in terms of network structure makes it possible to find markers of prediction of motor learning performance in a sensory motor learning task. By applying graph theory indexes of brain segregation - such as modularity and transitivity - to functional connectivity data derived from electroencephalographic (EEG) rhythms, we further studied pre- (baseline) versus post-task brain network architecture to understand whether motor learning induces changes in functional brain connectivity...
July 19, 2018: Neural Networks: the Official Journal of the International Neural Network Society
Dong Cui, Shunai Qi, Guanghua Gu, Xiaoli Li, Zhaohui Li, Lei Wang, Shimin Yin
Type 2 diabetes mellitus (T2DM) increases the risk of amnestic mild cognitive impairment (aMCI) and Alzheimer's disease(AD). aMCI is the transitory stage from normal cognition to AD, which seriously impacts the quality of human life, especially for old people. Electroencephalography (EEG) coherence can assess the functional connectivity between different brain regions, which is an effective way to research the pathogenesis of aMCI and distinguish aMCI patients from normal cognitive subjects. In this paper, we propose a new EEG coherence approach named magnitude squared coherence based on weighted canonical correlation analysis (WCCA-MSC) which improves the accuracy in coherence estimation by the means of weighting...
August 2, 2018: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Laura Anna van de Pol, Charlotte van 't Westende, Inge Zonnenberg, Esther Koedam, Ineke van Rossum, Willem de Haan, Marjan Steenweg, Elisabeth Catharina van Straaten, Cornelis Jan Stam
Fetal and neonatal brain connectivity development is highly complex. Studies have shown that functional networks change dramatically during development. The purpose of the current study was to determine how the mean phase lag index (mPLI), a measure of functional connectivity (FC), assessed with electroencephalography (EEG), changes with postmenstrual age (PMA) during the early stages of brain development after birth. Neonates ( N = 131) with PMA 27.6-45.3 weeks who underwent an EEG for a medical reason were retrospectively studied...
2018: Frontiers in Human Neuroscience
Changcheng Sun, Fei Yang, Chunfang Wang, Zhonghan Wang, Ying Zhang, Dong Ming, Jingang Du
Post-stroke depression (PSD) is the most common stroke-related emotional disorder, and it severely affects the recovery process. However, more than half cases are not correctly diagnosed. This study was designed to develop a new method to assess PSD using EEG signal to analyze the specificity of PSD patients' brain network. We have 107 subjects attended in this study (72 stabilized stroke survivors and 35 non-depressed healthy subjects). A Hamilton Depression Rating Scale (HDRS) score was determined for all subjects before EEG data collection...
2018: Frontiers in Human Neuroscience
Iñaki Iturrate, Ricardo Chavarriaga, Michael Pereira, Huaijian Zhang, Tiffany Corbet, Robert Leeb, José Del R Millán
Hand grasping is a sophisticated motor task that has received much attention by the neuroscientific community, which demonstrated how grasping activates a network involving parietal, pre-motor and motor cortices using fMRI, ECoG, LFPs and spiking activity. Yet, there is a need for a more precise spatio-temporal analysis as it is still unclear how these brain activations over large cortical areas evolve at the sub-second level. In this study, we recorded ten human participants (1 female) performing visually-guided, self-paced reaching and grasping with precision or power grips...
July 26, 2018: NeuroImage
Seyed Amir Hosseini, Abbas Sohrabpour, Mehmet Akcakaya, Bin He
: Adaptive beamformer methods, which have been extensively used for functional brain imaging using EEG/MEG signals, are sensitive to model mismatches. We propose a robust minimum variance beamformer (RMVB) technique, which explicitly incorporates the uncertainty of the lead field matrix into estimation of spatial-filter weights that are subsequently used to perform the imaging. : The uncertainty of the lead field is modeled by ellipsoids in the RMVB method; these hyper-ellipsoids (ellipsoids in higher dimensions) define regions of uncertainty for a given nominal lead field vector...
July 24, 2018: IEEE Transactions on Bio-medical Engineering
Karthik Soman, Vignesh Muralidharan, V Srinivasa Chakravarthy
Oscillatory phenomena are ubiquitous in the brain. Although there are oscillator-based models of brain dynamics, their universal computational properties have not been explored much unlike in the case of rate-coded and spiking neuron network models. Use of oscillator-based models is often limited to special phenomena like locomotor rhythms and oscillatory attractor-based memories. If neuronal ensembles are taken to be the basic functional units of brain dynamics, it is desirable to develop oscillator-based models that can explain a wide variety of neural phenomena...
2018: Frontiers in Computational Neuroscience
Lana Vasung, Esra Abaci Turk, Silvina L Ferradal, Jason Sutin, Jeffrey N Stout, Banu Ahtam, Pei-Yi Lin, P Ellen Grant
Early brain development, from embryonic period to infancy, is characterized by rapid structural and functional changes. These changes can be studied using structural and physiological neuroimaging methods. In order to optimally acquire and accurately interpret this data, concepts from adult neuroimaging cannot be directly transferred. Instead, one must have a basic understanding of fetal and neonatal structural and physiological brain development, and understand important modulators of this process. Here, we first review the major developmental milestones of transient cerebral structures and structural connectivity (axonal connectivity) followed by a summary of the contributions from ex vivo and in vivo MRI...
July 21, 2018: NeuroImage
Mattia F Pagnotta, Mukesh Dhamala, Gijs Plomp
Brain function arises from networks of distributed brain areas whose directed interactions vary at subsecond time scales. To investigate such interactions, functional directed connectivity methods based on nonparametric spectral factorization are promising tools, because they can be straightforwardly extended to the nonstationary case using wavelet transforms or multitapers on sliding time window, and allow estimating time-varying spectral measures of Granger-Geweke causality (GGC) from multivariate data. Here we systematically assess the performance of various nonparametric GGC methods in real EEG data recorded over rat cortex during unilateral whisker stimulations, where somatosensory evoked potentials (SEPs) propagate over known areas at known latencies and therefore allow defining fixed criteria to measure the performance of time-varying directed connectivity measures...
July 20, 2018: NeuroImage
Han Yuan, Raquel Phillips, Chung Ki Wong, Vadim Zotev, Masaya Misaki, Brent Wurfel, Frank Krueger, Matthew Feldner, Jerzy Bodurka
Posttraumatic stress disorder (PTSD) is a trauma- and stressor-related disorder that may emerge following a traumatic event. Neuroimaging studies have shown evidence of functional abnormality in many brain regions and systems affected by PTSD. Exaggerated threat detection associated with abnormalities in the salience network, as well as abnormalities in executive functions involved in emotions regulations, self-referencing and context evaluation processing are broadly reported in PTSD. Here we aimed to investigate the behavior and dynamic properties of fMRI resting state networks in combat-related PTSD, using a novel, multimodal imaging approach...
2018: NeuroImage: Clinical
Lena Trebaul, Pierre Deman, Viateur Tuyisenge, Maciej Jedynak, Etienne Hugues, David Rudrauf, Manik Bhattacharjee, François Tadel, Blandine Chanteloup-Foret, Carole Saubat, Gina Catalina Reyes Mejia, Claude Adam, Anca Nica, Martin Pail, François Dubeau, Sylvain Rheims, Agnès Trébuchon, Haixiang Wang, Sinclair Liu, Thomas Blauwblomme, Mercedes Garcés, Luca De Palma, Antonio Valentin, Eeva-Liisa Metsähonkala, Ana Maria Petrescu, Elizabeth Landré, William Szurhaj, Edouard Hirsch, Luc Valton, Rodrigo Rocamora, Andreas Schulze-Bonhage, Ioana Mindruta, Stefano Francione, Louis Maillard, Delphine Taussig, Philippe Kahane, Olivier David
In patients with pharmaco-resistant focal epilepsies investigated with intracranial electroencephalography (iEEG), direct electrical stimulations of a cortical region induce cortico-cortical evoked potentials (CCEP) in distant cerebral cortex, which properties can be used to infer large scale brain connectivity. In 2013, we proposed a new probabilistic functional tractography methodology to study human brain connectivity. We have now been revisiting this method in the F-TRACT project ( by developing a large multicenter CCEP database of several thousand stimulation runs performed in several hundred patients, and associated processing tools to create a probabilistic atlas of human cortico-cortical connections...
July 17, 2018: NeuroImage
Michael Siniatchkin, Jan Moehring, Bianca Kroeher, Andreas Galka, Gisela von Ondarza, Friederike Moeller, Stephan Wolff, Enzo Tagliazucchi, Elisabeth Steinmann, Rainer Boor, Ulrich Stephani
OBJECTIVE: Multifocal epileptic activity is an unfavourable feature of a number of epileptic syndromes (Lennox-Gastaut syndrome, West syndrome, severe focal epilepsies) which suggests an overall vulnerability of the brain to pathological synchronization. However, the mechanisms of multifocal activity are insufficiently understood. This explorative study investigates whether pathological connectivity within brain areas of the default mode network as well as thalamus, brainstem and retrosplenial cortex may predispose individuals to multifocal epileptic activity...
July 5, 2018: European Journal of Paediatric Neurology: EJPN
Aurélie L Manuel, Nicolas Nicastro, Armin Schnider, Adrian G Guggisberg
Procedural memory refers to skills acquired through practice and depends on cortico-striatal and cortico-cerebellar circuits. These circuits are typically affected in Parkinson's disease (PD), leading to impaired skill learning, including defective offline consolidation, early in the course of the disease. Evidence points to a role of slow oscillations (<4 Hz) during sleep for offline consolidation. However recent studies showed consolidation over the course of the day, suggesting that consolidation may arise during wakefulness, too...
June 21, 2018: Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
Fabrizio Vecchio, Francesca Miraglia, Francesco Iberite, Giordano Lacidogna, Valeria Guglielmi, Camillo Marra, Patrizio Pasqualetti, Francesco Danilo Tiziano, Paolo Maria Rossini
Mild cognitive impairment (MCI) is a condition intermediate between physiological brain aging and dementia. Amnesic-MCI (aMCI) subjects progress to dementia (typically to Alzheimer-Dementia=AD) at an annual rate which is 20 times higher than that of cognitively intact elderly. The present study aims to investigate whether EEG network Small World properties (SW) combined with Apo-E genotyping, could reliably discriminate aMCI subjects who will convert to AD after approximately a year. 145 aMCI subjects were divided into two sub-groups and, according to the clinical follow-up, were classified as Converted to AD(C-MCI, 71) or Stable(S-MCI, 74)...
July 16, 2018: Annals of Neurology
Mona Farokhzadi, Gholam-Ali Hossein-Zadeh, Hamid Soltanian-Zadeh
Exploring brain networks is an essential step towards understanding functional organization of the brain, which needs characterization of linear and nonlinear connections based on measurements like EEG or MEG. Conventional measures of connectivity are mostly linear and bivariate. This paper proposes an effective connectivity measure called Adaptive Neuro-Fuzzy Inference System Granger Causality (ANFISGC). The proposed measure is based on the symplectic geometry embedding dimension, Adaptive Neuro-Fuzzy Inference System (ANFIS) predictor, and Granger Causality (GC)...
July 18, 2018: NeuroImage
Erika L Juárez-Martinez, Ida A Nissen, Sander Idema, Demetrios N Velis, Arjan Hillebrand, Cornelis J Stam, Elisabeth C W van Straaten
In some patients with medically refractory epilepsy, EEG with intracerebrally placed electrodes (stereo-electroencephalography, SEEG) is needed to locate the seizure onset zone (SOZ) for successful epilepsy surgery. SEEG has limitations and entails risk of complications because of its invasive character. Non-invasive magnetoencephalography virtual electrodes (MEG-VEs) may overcome SEEG limitations and optimize electrode placement making SOZ localization safer. Our purpose was to assess whether interictal activity measured by MEG-VEs and SEEG at identical anatomical locations were comparable, and whether MEG-VEs activity properties could determine the location of a later resected brain area (RA) as an approximation of the SOZ...
2018: NeuroImage: Clinical
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