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  • Neuroinformatics
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Postoyan, R.; Biemond, J.J.B.; Heemels, W.P.M.H.; van de Wouw, N.;

    International audience; The analysis of incremental stability properties typically involves measuring the distance between any pair of solutions of a given dynamical system, corresponding to different initial conditions, at the same time instant. This approach is not directly applicable for hybrid systems in general. Indeed, hybrid systems generate solutions that are defined with respect to hybrid times, which consist of both the continuous time elapsed and the discrete time, that is the number of jumps the solution has experienced. Two solutions of a hybrid system do not a priori have the same time domain, and we may therefore not be able to compare them at the same hybrid time instant. To overcome this issue, we invoke graphical closeness concepts. We present definitions for incremental stability depending on whether incremental asymptotic stability properties hold with respect to the hybrid time, the continuous time, or the discrete time, respectively. Examples are provided throughout the paper to illustrate these definitions, and the relations between these three incremental stability notions are investigated. The definitions are shown to be consistent with those available in the literature for continuous-time and discrete-time systems.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ https://hal.archives...arrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Other literature type . 2015
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Conference object . 2015 . Peer-reviewed
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Conference object . 2015
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    Conference object . 2015
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ https://hal.archives...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Hyper Article en Ligne
      Other literature type . 2015
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      Conference object . 2015 . Peer-reviewed
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      Conference object . 2015
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      Conference object . 2015
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Mourao-Miranda, J.; Reinders, A. A. T. S.; Rocha-Rego, V.; Lappin, J.; +9 Authors

    BackgroundTo date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode.MethodOne hundred patients at their first psychotic episode and 91 healthy controls had an MRI scan. Patients were re-evaluated 6.2 years (s.d.=2.3) later, and were classified as having a continuous, episodic or intermediate illness course. Twenty-eight subjects with a continuous course were compared with 28 patients with an episodic course and with 28 healthy controls. We trained each SVM classifier independently for the following contrasts: continuous versus episodic, continuous versus healthy controls, and episodic versus healthy controls.ResultsAt baseline, patients with a continuous course were already distinguishable, with significance above chance level, from both patients with an episodic course (p=0.004, sensitivity=71, specificity=68) and healthy individuals (p=0.01, sensitivity=71, specificity=61). Patients with an episodic course could not be distinguished from healthy individuals. When patients with an intermediate outcome were classified according to the discriminating pattern episodic versus continuous, 74% of those who did not develop other episodes were classified as episodic, and 65% of those who did develop further episodes were classified as continuous (p=0.035).ConclusionsWe provide preliminary evidence of MRI application in the individualized prediction of future illness course, using a simple and automated SVM pipeline. When replicated and validated in larger groups, this could enable targeted clinical decisions based on imaging data.

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    Europe PubMed Central
    Article . 2011
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    Psychological Medicine
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    Psychological Medicine
    Article . 2012
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Article . 2012
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Psychological Medicine
    Article . 2011 . Peer-reviewed
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      Article . 2011
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      Psychological Medicine
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Psychological Medicine
      Article . 2012
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      Article . 2012
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Psychological Medicine
      Article . 2011 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Cox, Roy; van Driel, J.; de Boer, Marieke; Talamini, Lucia M;

    Large-amplitude sleep slow oscillations group faster neuronal oscillations and are of functional relevance for memory performance. However, relatively little is known about the impact of slow oscillations on functionally coupled networks. Here, we provide a comprehensive view on how human slow oscillatory dynamics influence various measures of brain processing. We demonstrate that slow oscillations coordinate interregional cortical communication, as assessed by phase synchrony in the sleep spindle frequency range and cross-frequency coupling between spindle and beta activity. Furthermore, we show that the organizing role of slow oscillations is restricted to circumscribed topographical areas. These findings add importantly to our basic understanding of the orchestrating role of slow oscillations. In addition, they are of considerable relevance for accounts of sleep-dependent memory reprocessing and consolidation.

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    Article . 2014
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    Europe PubMed Central
    Other literature type . 2014
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    Journal of Neuroscience
    Article . 2014 . Peer-reviewed
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Article . 2014
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      Europe PubMed Central
      Other literature type . 2014
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      Journal of Neuroscience
      Article . 2014 . Peer-reviewed
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      Article . 2014
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    Contains fulltext : 251957.pdf (Publisher’s version ) (Open Access) Human language stands out in the natural world as a biological signal that uses a structured system to combine the meanings of small linguistic units (e.g., words) into larger constituents (e.g., phrases and sentences). However, the physical dynamics of speech (or sign) do not stand in a one-to-one relationship with the meanings listeners perceive. Instead, listeners infer meaning based on their knowledge of the language. The neural readouts of the perceptual and cognitive processes underlying these inferences are still poorly understood. In the present study, we used scalp electroencephalography (EEG) to compare the neural response to phrases (e.g., the red vase) and sentences (e.g., the vase is red), which were close in semantic meaning and had been synthesized to be physically indistinguishable. Differences in structure were well captured in the reorganization of neural phase responses in delta (approximately <2 Hz) and theta bands (approximately 2 to 7 Hz),and in power and power connectivity changes in the alpha band (approximately 7.5 to 13.5 Hz). Consistent with predictions from a computational model, sentences showed more power, more power connectivity, and more phase synchronization than phrases did. Theta-gamma phase-amplitude coupling occurred, but did not differ between the syntactic structures. Spectral–temporal response function (STRF) modeling revealed different encoding states for phrases and sentences, over and above the acoustically driven neural response. Our findings provide a comprehensive description of how the brain encodes and separates linguistic structures in the dynamics of neural responses. They imply that phase synchronization and strength of connectivity are readouts for the constituent structure of language. The results provide a novel basis for future neurophysiological research on linguistic structure representation in the brain, and, together with our simulations, support time-based binding as a mechanism of structure encoding in neural dynamics. 40 p.

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    Article . 2022
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    MPG.PuRe
    Article . 2022
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    Radboud Repository
    Article . 2022
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    PLoS Biology
    Article . 2022
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    PLoS Biology
    Article . 2022 . Peer-reviewed
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    PLoS Biology
    Article . 2022
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      PLoS Biology
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    Authors: Hofstee, Marissa; Huijding, Jorg; Cuevas, Kimberly; Dekovic, Maja; +2 Authors

    AbstractIntegrating behavioral and neurophysiological measures has created new and advanced ways to understand the development of self‐regulation. Electroencephalography (EEG) has been used to examine how self‐regulatory processes are related to frontal alpha power during infancy and early childhood. However, findings across previous studies have been inconsistent. To address this issue, the current meta‐analysis synthesized all prior literature examining associations between individual differences in self‐regulation and frontal EEG alpha power (baseline and/or task). In total, 23 studies consisting of 1275 participants between 1 month and 6 years of age were included, which yielded 149 effect sizes. Findings of the three‐level meta‐analytic model demonstrated a non‐significant overall association between self‐regulation and frontal alpha power. Yet, significant moderating effects were found for self‐regulation construct (emotion regulation, effortful control, executive function), self‐regulation measurement (behavioral task, computer assessment, lab observation, questionnaire), and children's mean age. Self‐regulation was only significantly correlated with frontal alpha power when studies focused on the executive functioning construct. Moreover, the use of behavioral tasks or questionnaires and a higher mean age of the children resulted in small but significant effect size estimates. Higher frontal alpha power values were related to higher order top‐down mechanisms of self‐regulation, indicating that these mechanisms might become stronger when the frontal cortex is sufficiently developed. The findings of the current meta‐analysis highlight the importance of longitudinal analyses and multimethod approaches in future work to reach a more comprehensive understanding of the role of frontal EEG alpha activity in the etiology of individual differences in early self‐regulation.Research Highlights The first meta‐analysis of individual differences in self‐regulation and frontal EEG alpha power during infancy and early childhood demonstrated a non‐significant overall association. Moderation analyses revealed that variations in frontal alpha power were significantly associated with executive function, but not with effortful control and emotion regulation. Frontal alpha power was related to variations in self‐regulation when measured by behavioral tasks and questionnaires, but not via computer assessments and lab observations. The association between individual differences in self‐regulation and frontal alpha power becomes significantly stronger with age.

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    Developmental Science
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    Developmental Science
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    Authors: Szabolcs David; Anneriet M. Heemskerk; Francesco Corrivetti; Michel Thiebaut de Schotten; +12 Authors

    International audience; Fiber tractography (FT) using diffusion magnetic resonance imaging (dMRI) is widely used for investigating microstructural properties of white matter (WM) fiber-bundles and for mapping structural connections of the human brain. While studying the architectural configuration of the brain's circuitry with FT is not without controversy, recent progress in acquisition, processing, modeling, analysis, and visualization of dMRI data pushes forward the reliability in reconstructing WM pathways. Despite being aware of the well-known pitfalls in analyzing dMRI data and several other limitations of FT discussed in recent literature, we present the superoanterior fasciculus (SAF), a novel bilateral fiber tract in the frontal region of the human brain that-to the best of our knowledge-has not been documented. The SAF has a similar shape to the anterior part of the cingulum bundle, but it is located more frontally. To minimize the possibility that these FT findings are based on acquisition or processing artifacts, different dMRI data sets and processing pipelines have been used to describe the SAF. Furthermore, we evaluated the configuration of the SAF with complementary methods, such as polarized light imaging (PLI) and human brain dissections. The FT results of the SAF demonstrate a long pathway, consistent across individuals, while the human dissections indicate fiber pathways connecting the postero-dorsal with the antero-dorsal cortices of the frontal lobe.

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    ACU Research Bank
    Article . 2019
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    Frontiers in Neuroanatomy
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    Authors: Suzanne L Franklin; Sophie Schmid; Clemens Bos; Matthias J.P. van Osch;

    PurposeIn this study, the influence of the cardiac cycle on the amount of label produced by a velocity‐selective (VSASL) and acceleration‐selective arterial spin labeling (AccASL) module was investigated.MethodsA short‐PLD sequence was developed where a single VSASL‐ or AccASL‐module was preceded by pCASL labeling to isolate the arterial blood pool. ASL subtraction was performed with label/control images with similar cardiac phase and time‐of‐measurement, followed by retrospective binning in 10 cardiac phase bins. ASL signal variation over the heart cycle was evaluated and tested for significance using a permutation test.ResultsVSASL and AccASL showed significant arterial signal fluctuations over the cardiac cycle of up to ~36% and ~64%, respectively, mainly in areas containing large arteries. pCASL also showed significant signal fluctuations, of up to ~25% in arteries. Raw label/control images confirmed that the observed signal fluctuations were caused by the amount of label produced during the cardiac cycle, rather than inflow‐effects, because the raw images did not all show equal cardiac phase dependence.No significant effects of the cardiac cycle were found on the gray matter ASL‐signal.ConclusionSignificant influence of the cardiac cycle on the generated label was found for spatially nonselective ASL‐sequences. Hence, to become independent of the cardiac cycle, sufficient averages need to be taken. Alternatively, these findings could be highly interesting for the purpose of quantifying pulsatility more distally in the vascular tree.

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    Europe PubMed Central
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    Magnetic Resonance in Medicine; NARCIS
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    Authors: Fahrenfort, Johannes Jacobus; Grubert, Anna; Olivers, Christian N. L.; Eimer, Martin;

    Abstract The primary electrophysiological marker of feature-based selection is the N2pc, a lateralized posterior negativity emerging around 180-200 ms. As it relies on hemispheric differences, its ability to discriminate the locus of focal attention is severely limited. Here we demonstrate that multivariate analyses of raw EEG data provide a much more fine-grained spatial profile of feature-based target selection. When training a pattern classifier to determine target position from EEG, we were able to decode target positions on the vertical midline, which cannot be achieved using standard N2pc methodology. Next, we used a forward encoding model to construct a channel tuning function that describes the continuous relationship between target position and multivariate EEG in an eight-position display. This model can spatially discriminate individual target positions in these displays and is fully invertible, enabling us to construct hypothetical topographic activation maps for target positions that were never used. When tested against the real pattern of neural activity obtained from a different group of subjects, the constructed maps from the forward model turned out statistically indistinguishable, thus providing independent validation of our model. Our findings demonstrate the power of multivariate EEG analysis to track feature-based target selection with high spatial and temporal precision. Significance Statement Feature-based attentional selection enables observers to find objects in their visual field. The spatiotemporal profile of this process is difficult to assess with standard electrophysiological methods, which rely on activity differences between cerebral hemispheres. We demonstrate that multivariate analyses of EEG data can track target selection across the visual field with high temporal and spatial resolution. Using a forward model, we were able to capture the continuous relationship between target position and EEG measurements, allowing us to reconstruct the distribution of cortical activity for target locations that were never shown during the experiment. Our findings demonstrate the existence of a temporally and spatially precise EEG signal that can be used to study the neural basis of feature-based attentional selection.

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    bioRxiv
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    Scientific Reports
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    Article . 2018
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    Authors: Buijsen, Ronald; Sellier, C; Severijnen, Lies-anne; Oulad-Abdelghani, M; +5 Authors

    Fragile X-associated Tremor/Ataxia syndrome (FXTAS), a late-onset monogenetic neurodegenerative disorder, is caused by a CGG-repeat expansion (55-200) in the 5′ UTR of the fragile-X mental retardation 1 gene (FMR1) on the X-chromosome [1]. The prevalence of the FMR1 premutation (PM) is about 1:855 in males and 1:291 in females [2]. Approximately 45.5% of male and 16.5% of female PM carriers older than 50 years will develop signs of FXTAS [3]. In addition to the core features of tremor and gait ataxia, unexplained medical co-morbidities have been reported, including thyroid disease, cardiac arrhythmias, hypertension, migraine, impotence, and neuropathy [4]. PM carriers have increased levels of FMR1 mRNA (2 to 8 fold in leucocytes) and normal to slightly reduced FMR1 protein (FMRP) levels [5]. The current hypothesis is that FXTAS is caused by an RNA gain-of-function mechanism. Ubiquitin-positive intranuclear inclusions, are found in both brain and non-central nervous system (CNS) organs of patients with FXTAS [6,7]. So far, it is not clear whether these inclusions are protective or toxic. Recently, it has been hypothesized that repeat-associated non-AUG (RAN) translation plays a role in disease process and inclusion formation. Todd et al. [8] demonstrated that through initiation at a near-ATG codon located in the 5′UTR of the FMR1 gene a polyGlycine-containing protein, FMRpolyG, is expressed. This protein accumulates in ubiquitin-positive inclusions in Drosophila, cell culture, mouse disease models and brain from FXTAS patients. To investigate the link between FMRpolyG expression and the co-morbid medical problems associated with the PM we have developed two novel mouse monoclonal antibodies against polyGlycine; 8FM and 9FM (for epitopes and specificity see Additional file 1: Figure S1), and performed immunostaining in CNS as well as in non-CNS organs of FXTAS patient J.L. (case 6 in [7]; other cases not available). To establish antibody specificity, we performed immunostaining with both antibodies on brain sections from FXTAS patient J.L., healthy non-demented controls (n = 3) and a patient with Parkinson disease, Alzheimer disease, or C9FTD. In hippocampus and cerebellum from FXTAS patient J.L. we identified FMRpolyG-positive inclusions with both 8FM (1:10) and 9FM (1:10) antibody (Figure 1a-b, Additional file 2: Figure S2a-b), as was described previously [8]. None of the controls showed FMRpolyG-positive inclusions (data not shown). Next, we studied the immunolocalization of FMRpolyG protein in heart, kidney, adrenal gland and thyroid in patient J.L. with 8FM (1:10) and 9FM (1:10), compared to post mortem non-CNS somatic organ tissues from 3 healthy controls. We also examined tissues for FMRP (mouse T1A; 1:200) expression and ubiquitin-positive inclusions (DAKO, ZO458; 1:200). Consistent with our previous report [7], ubiquitin-positive intranuclear inclusions were identified along with a normal distribution of FMRP (data not shown). Intranuclear FMRpolyG-positive inclusions could be detected in all organs examined (Figure 1c-h, Additional file 2: Figure S2c-h). No control tissues showed any FMRpolyG-positive inclusions (data not shown). Colocalization of ubiquitin- and FMRpolyG-positive inclusions was visualized and quantified by immunofluorescent double staining using antibodies against ubiquitin and FMRpolyG (8FM) (Figure 2a-f). For hippocampus, cerebellum and the non-CNS organs most inclusions are positive for both FMRpolyG and ubiquitin, although some rare inclusions positive for only one of the proteins could also be detected (Figure 2g, n = 100 inclusions). In conclusion, using two novel antibodies the present report not only confirms the existence of FMRpolyG-positive aggregates in CNS tissue from a FXTAS individual but also demonstrates for the first time the presence of FMRpolyG-positive intranuclear inclusions in post mortem non-CNS material of a PM carrier with FXTAS. Furthermore, colocalization of FMRpolyG and ubiquitin is found in the vast majority of inclusions. The presence of FMRpolyG-positive intranuclear inclusions in heart, kidney, adrenal gland and thyroid is consistent with the unexplained medical co-morbidities reported in some patients with FXTAS, including thyroid disease, cardiac arrhythmias, hypertension, migraine, impotence, and neuropathy. We hypothesize that the underlying pathological mechanisms of the medical co-morbidities in systemic tissues share common features (protein toxic gain-of-function) with CNS pathology of patients with FXTAS. Our report suggests that in addition to elevated levels of FMR1 mRNA containing an expanded CGG repeat, and ubiquitin-positive inclusions, FMRpolyG expression might also play a role in a toxic gain-of-function mechanism in medical co-morbidities in FXTAS (RNA versus FMRpolyG toxic gain-of-function). Interestingly, a very recent report suggests that RAN translation products in C9FTD/ALS, toxic dipeptide repeat proteins (poly-(glycine-arginine) and poly-(proline-arginine)), are toxic in Drosophila [9]. Further research is needed to understand how FMRpolyG may elicit toxicity in both CNS and non-CNS organs and its precise role in co-morbidities in PM carriers. Importantly, if FMRpolyG production is important for cellular toxicity this will open new avenues for therapeutic intervention studies for FXTAS by developing drugs that block this aberrant translation. Figure 1 9FM FMRpolyG-positive intranuclear inclusions in hippocampus, cerebellum and non-CNS tissues of a FXTAS patient. FMRpolyG-positive (9FM) intranuclear inclusions in a hippocampus, b cerebellum, c glomeruli and d distal tubule of the kidney, e zona glomerulosa ... Figure 2 Colocalization of FMRpolyG (8FM) and ubiquitin in intranuclear inclusions in hippocampus, cerebellum and of non-CNS tissues of a FXTAS patient. Staining for ubiquitin (green), FMRpolyG (8FM; red) and DAPI (blue). Colocalization of ubiquitin and FMRpolyG ...

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    Europe PubMed Central
    Article . 2014
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    Acta Neuropathologica Communications
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    Authors: Chantal M. W. Tax; Tom C. J. Dela Haije; Andrea Fuster; Carl-Fredrik Westin; +3 Authors

    The question whether our brain pathways adhere to a geometric grid structure has been a popular topic of debate in the diffusion imaging and neuroscience societies. Wedeen et al. (2012a, b) proposed that the brain's white matter is organized like parallel sheets of interwoven pathways. Catani et al. (2012) concluded that this grid pattern is most likely an artifact, resulting from methodological biases that cause the tractography pathways to cross in orthogonal angles. To date, ambiguities in the mathematical conditions for a sheet structure to exist (e.g. its relation to orthogonal angles) combined with the lack of extensive quantitative evidence have prevented wide acceptance of the hypothesis. In this work, we formalize the relevant terminology and recapitulate the condition for a sheet structure to exist. Note that this condition is not related to the presence or absence of orthogonal crossing fibers, and that sheet structure is defined formally as a surface formed by two sets of interwoven pathways intersecting at arbitrary angles within the surface. To quantify the existence of sheet structure, we present a novel framework to compute the sheet probability index (SPI), which reflects the presence of sheet structure in discrete orientation data (e.g. fiber peaks derived from diffusion MRI). With simulation experiments we investigate the effect of spatial resolution, curvature of the fiber pathways, and measurement noise on the ability to detect sheet structure. In real diffusion MRI data experiments we can identify various regions where the data supports sheet structure (high SPI values), but also areas where the data does not support sheet structure (low SPI values) or where no reliable conclusion can be drawn. Several areas with high SPI values were found to be consistent across subjects, across multiple data sets obtained with different scanners, resolutions, and degrees of diffusion weighting, and across various modeling techniques. Under the strong assumption that the diffusion MRI peaks reflect true axons, our results would therefore indicate that pathways do not form sheet structures at every crossing fiber region but instead at well-defined locations in the brain. With this framework, sheet structure location, extent, and orientation could potentially serve as new structural features of brain tissue. The proposed method can be extended to quantify sheet structure in directional data obtained with techniques other than diffusion MRI, which is essential for further validation.

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    NeuroImage
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