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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: Taylor, JSH; Davis, Matthew H; Rastle, Kathleen;

    Reading involves transforming arbitrary visual symbols into sounds and meanings. This study interrogated the neural representations in ventral occipitotemporal cortex (vOT) that support this transformation process. Twenty-four adults learned to read 2 sets of 24 novel words that shared phonemes and semantic categories but were written in different artificial orthographies. Following 2 wk of training, participants read the trained words while neural activity was measured with functional MRI. Representational similarity analysis on item pairs from the same orthography revealed that right vOT and posterior regions of left vOT were sensitive to basic visual similarity. Left vOT encoded letter identity and representations became more invariant to position along a posterior-to-anterior hierarchy. Item pairs that shared sounds or meanings, but were written in different orthographies with no letters in common, evoked similar neural patterns in anterior left vOT. These results reveal a hierarchical, posterior-to-anterior gradient in vOT, in which representations of letters become increasingly invariant to position and are transformed to convey spoken language information. Significance Learning to read is the most important milestone in a child’s education. However, controversies remain regarding how readers’ brains transform written words into sounds and meanings. We address these by combining artificial language learning with neuroimaging to reveal how the brain represents written words. Participants learned to read new words written in 2 different alphabets. Following 2 wk of training, we found a hierarchy of brain areas that support reading. Letter position is represented more flexibly from lower to higher visual regions. Furthermore, higher visual regions encode information about word sounds and meanings. These findings advance our understanding of how the brain comprehends language from arbitrary visual symbols.

    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/ Europe PubMed Centra...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/
    Europe PubMed Central
    Article . 2019
    Data sources: PubMed Central
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    Apollo
    Article . 2020
    License: CC BY
    Data sources: Datacite
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    Apollo
    Other literature type . 2019
    License: CC BY
    Data sources: Apollo
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    Proceedings of the National Academy of Sciences
    Article . 2019 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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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/ Europe PubMed Centra...arrow_drop_down
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      Europe PubMed Central
      Article . 2019
      Data sources: PubMed Central
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      Apollo
      Article . 2020
      License: CC BY
      Data sources: Datacite
      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/
      Apollo
      Other literature type . 2019
      License: CC BY
      Data sources: Apollo
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      Proceedings of the National Academy of Sciences
      Article . 2019 . Peer-reviewed
      License: CC BY
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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: Keable, Abby; Fenna, Kate; Yuen, Ho Ming; Johnston, David A.; +9 Authors

    Deposition of amyloid β (Aβ) in the walls of cerebral arteries as cerebral amyloid angiopathy (CAA) suggests an age-related failure of perivascular drainage of soluble Aβ from the brain. As CAA is associated with Alzheimer's disease and with intracerebral haemorrhage, the present study determines the unique sequence of changes that occur as Aβ accumulates in artery walls. Paraffin sections of post-mortem human occipital cortex were immunostained for collagen IV, fibronectin, nidogen 2, Aβ and smooth muscle actin and the immunostaining was analysed using Image J and confocal microscopy. Results showed that nidogen 2 (entactin) increases with age and decreases in CAA. Confocal microscopy revealed stages in the progression of CAA: Aβ initially deposits in basement membranes in the tunica media, replaces first the smooth muscle cells and then the connective tissue elements to leave artery walls completely or focally replaced by Aβ. The pattern of development of CAA in the human brain suggests expansion of Aβ from the basement membranes to progressively replace all tissue elements in the artery wall. Establishing this full picture of the development of CAA is pivotal in understanding the clinical presentation of CAA and for developing therapies to prevent accumulation of Aβ in artery walls. This article is part of a Special Issue entitled: Vascular Contributions to Cognitive Impairment and Dementia edited by M. Paul Murphy, Roderick A. Corriveau and Donna M. Wilcock. Highlights • Lymphatic drainage of the brain is along basement membranes in the walls of arteries. • Perivascular lymphatic drainage fails with age and arteriosclerosis. • Aβ deposits in the perivascular drainage pathways of leptomeningeal arteries as CAA. • As CAA progresses, Aβ replaces all elements of the ageing artery wall. • Facilitation of perivascular drainage may prevent CAA and delay Alzheimer's disease.

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    Europe PubMed Central
    Article . 2016
    Data sources: PubMed Central
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    e-Prints Soton
    Article . 2016 . Peer-reviewed
    Data sources: e-Prints Soton
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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/ Europe PubMed Centra...arrow_drop_down
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      Europe PubMed Central
      Article . 2016
      Data sources: PubMed Central
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      e-Prints Soton
      Article . 2016 . Peer-reviewed
      Data sources: e-Prints Soton
      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/
    Authors: Hatton, Sean N; Huynh, Khoa H; Bonilha, Leonardo; Abela, Eugenio; +70 Authors

    AbstractThe epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analyzed from 1,069 non-epileptic controls and 1,249 patients: temporal lobe epilepsy with hippocampal sclerosis (N=599), temporal lobe epilepsy with normal MRI (N=275), genetic generalized epilepsy (N=182) and nonlesional extratemporal epilepsy (N=193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fiber tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at p<0.001). Across “all epilepsies” lower fractional anisotropy was observed in most fiber tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. Less robust effects were seen with mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Those with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced differences in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and in mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of microstructural abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibers in a large multicentre study of epilepsy. Overall, epilepsy patients showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding new insights into pathological substrates that may be used to guide future therapeutic and genetic studies.

    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/ bioRxivarrow_drop_down
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    bioRxiv
    Preprint . 2019
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      bioRxiv
      Preprint . 2019
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    Authors: Winston, Gavin P; Cardoso, M Jorge; Williams, Elaine J; Burdett, Jane L; +5 Authors

    The hippocampus is located within the medial temporal lobe and plays a key role in learning and episodic, semantic, and spatial memory. Dysfunction has been reported in neurologic and psychiatric disorders including epilepsy (Wu et al., 2005), Alzheimer's disease (Apostolova et al., 2006), schizophrenia (Tanskanen et al., 2005), and depression (Bremner et al., 2000). Temporal lobe epilepsy (TLE) is the most common drug-resistant focal epilepsy, with seizures frequently arising from the hippocampus. In surgical series of TLE, the pathology is often hippocampal sclerosis (HS) comprising neuronal loss and gliosis and marked by atrophy and signal change on magnetic resonance imaging (Van Paesschen, 2004). Atrophy of the hippocampus through HS provides a good biomarker for the laterality of the seizure focus (Bernasconi et al., 2003), and combined with concordant neurophysiology and neuropsychological data can be sufficient to recommend surgery. Hippocampal atrophy is associated with a favorable surgical outcome (Schramm & Clusmann, 2008). Visual assessment of hippocampal volumes is unreliable, as it may be compromised by head position and primarily detects hippocampal asymmetry rather than volume loss, making bilateral atrophy difficult to identify. Hippocampal segmentation and volumetry are thus important for diagnosis and surgical planning (Watson et al., 1997). The gold standard for hippocampal segmentation is manual delineation by trained raters. This is accurate, reproducible, and sensitive but is time-consuming, requires anatomic knowledge, and is subject to interrater and intrarater variability. The hippocampus is challenging to delineate as it is small and highly variable with ill-defined margins. Many protocols exist for manual segmentation depending on which structures are included and the boundary definition (Konrad et al., 2009). Automated segmentation techniques aim to ensure operator independence, high reproducibility, and reduced demand for human time and expertise. The strongest drive for automation has come from researchers working with large cohorts of patients with Alzheimer's disease patients. Hippocampal volumes are an early marker for the disease, are related to cognitive status, and may reflect disease progression in clinical trials (Frisoni & Jack, 2011). In atlas-based segmentation approaches, a template and associated manual labels are registered (matched) to the new image (Carmichael et al., 2005). Commonly used methods, including FreeSurfer (Fischl et al., 2002), rely on a single template so that subjects that differ significantly from the template, for example HS, are poorly segmented. Segmentation of hippocampi that are sclerotic is more challenging than segmenting hippocampi in Alzheimer's disease, as the latter is associated with more prominent cerebrospinal fluid (CSF)–hippocampal boundaries, whereas the former is associated with signal change. The use of an atlas with multiple template images is more effective than a single template (Heckemann et al., 2006) and depends on the quality of registration and template selection strategy. Most previous atlas-based segmentation studies used small template databases of healthy subjects. Results obtained in TLE are significantly worse than in healthy subjects or Alzheimer's disease (Kim et al., 2012), as aside from atrophy, approximately 40% of patients with TLE demonstrate an atypical shape or position of the hippocampus (Bernasconi et al., 2005). In this study, we adapted our published method developed for use in Alzheimer's disease (Cardoso et al., 2013) to a large cohort of adult patients with epilepsy by employing accurate nonlinear registration (Modat et al., 2010) and a large template database that encompasses the range of pathology observed in epilepsy at a tertiary referral center. Manual segmentations of the most similar images from the template database are combined using a label fusion strategy based on local similarity to ensure accurate segmentation regardless of pathology. We demonstrate that this technique achieves reliable segmentation with no more variability than that seen between different expert raters. The algorithm is made freely available via an online Web-based service (https://hipposeg.cs.ucl.ac.uk). In addition, the software, scripts, and an anonymized version of the template database are available from this website.

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    Europe PubMed Central
    Article . 2013
    Data sources: PubMed Central
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    Epilepsia
    Article . 2013 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Epilepsia
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      Europe PubMed Central
      Article . 2013
      Data sources: PubMed Central
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      Epilepsia
      Article . 2013 . Peer-reviewed
      License: CC BY
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      Epilepsia
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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
    Preprint . 2016
    Data sources: bioRxiv
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    Scientific Reports
    Article . 2017
    Data sources: PubMed Central
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    Europe PubMed Central
    Article . 2018
    Data sources: PubMed Central
    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/
    CORE (RIOXX-UK Aggregator)
    Article . 2017
    License: CC BY
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    Scientific Reports
    Article . 2017
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    Scientific Reports
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      bioRxiv
      Preprint . 2016
      Data sources: bioRxiv
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      Scientific Reports
      Article . 2017
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      Europe PubMed Central
      Article . 2018
      Data sources: PubMed Central
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      Article . 2017
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      Scientific Reports
      Article . 2017
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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/
      Scientific Reports
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    Authors: Patricia M, Gough; Emily L, Connally; Peter, Howell; David, Ward; +2 Authors

    Purpose Previous studies have reported that the planum temporale – a language-related structure that normally shows a leftward asymmetry – had reduced asymmetry in people who stutter (PWS) and reversed asymmetry in those with severe stuttering. These findings are consistent with the theory that altered language lateralization may be a cause or consequence of stuttering. Here, we re-examined these findings in a larger sample of PWS. Methods We evaluated planum temporale asymmetry in structural MRI scans obtained from 67 PWS and 63 age-matched controls using: 1) manual measurements of the surface area; 2) voxel-based morphometry to automatically calculate grey matter density. We examined the influences of gender, age, and stuttering severity on planum temporale asymmetry. Results The size of the planum temporale and its asymmetry were not different in PWS compared with Controls using either the manual or the automated method. Both groups showed a significant leftwards asymmetry on average (about one-third of PWS and Controls showed rightward asymmetry). Importantly, and contrary to previous reports, the degree of asymmetry was not related to stuttering severity. In the manual measurements, women who stutter had a tendency towards rightwards asymmetry but men who stutter showed the same degree of leftwards asymmetry as male Controls. In the automated measurements, Controls showed a significant increase in leftwards asymmetry with age but this relationship was not observed in PWS. Conclusions We conclude that reduced planum temporale asymmetry is not a prominent feature of the brain in PWS and that the asymmetry is unrelated to stuttering severity. Highlights • Planum temporale asymmetry was compared in 67 people who stutter and 63 age-matched controls. • Size or asymmetry of the planum temporale did not differ between people who stutter and controls. • The asymmetry of the planum temporale was not affected by stuttering severity. • Differences in asymmetry of the planum temporale are not a cause, consequence or correlate of developmental stuttering.

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    Europe PubMed Central
    Article . 2018
    Data sources: PubMed Central
    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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    Article . 2018
    License: CC BY
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    Oxford University Research Archive
    Other literature type . 2017
    License: CC BY
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    Journal of Fluency Disorders
    Article . 2018 . Peer-reviewed
    License: CC BY
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      Europe PubMed Central
      Article . 2018
      Data sources: PubMed Central
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      Article . 2018
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      Oxford University Research Archive
      Other literature type . 2017
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      Journal of Fluency Disorders
      Article . 2018 . Peer-reviewed
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    Authors: Catherine McCaig; Paris Ataliotis; Anan Shtaya; Ayan S Omar; +8 Authors

    Nitrones (e.g. α-phenyl-N-tert-butyl nitrone; PBN) are cerebroprotective in experimental stroke. Free radical trapping is their proposed mechanism. As PBN has low radical trapping potency, we tested Sgk1 induction as another possible mechanism. PBN was injected (100 mg/kg, i.p.) into adult male rats and mice. Sgk1 was quantified in cerebral tissue by microarray, quantitative RT-PCR and western analyses. Sgk1+/+ and Sgk1−/− mice were randomized to receive PBN or saline immediately following transient (60 min) occlusion of the middle cerebral artery. Neurological deficit was measured at 24 h and 48 h and infarct volume at 48 h post-occlusion. Following systemic PBN administration, rapid induction of Sgk1 was detected by microarray (at 4 h) and confirmed by RT-PCR and phosphorylation of the Sgk1-specific substrate NDRG1 (at 6 h). PBN-treated Sgk1+/+ mice had lower neurological deficit ( p < 0.01) and infarct volume ( p < 0.01) than saline-treated Sgk1+/+ mice. PBN-treated Sgk1−/− mice did not differ from saline-treated Sgk1−/− mice. Saline-treated Sgk1−/− and Sgk1+/+ mice did not differ. Brain Sgk3:Sgk1 mRNA ratio was 1.0:10.6 in Sgk1+/+ mice. Sgk3 was not augmented in Sgk1−/− mice. We conclude that acute systemic treatment with PBN induces Sgk1 in brain tissue. Sgk1 may play a part in PBN-dependent actions in acute brain ischemia.

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    Europe PubMed Central
    Article . 2017
    Data sources: PubMed Central
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    Journal of Cerebral Blood Flow & Metabolism
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    License: CC BY NC
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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
    Journal of Cerebral Blood Flow & Metabolism
    Article . 2017 . Peer-reviewed
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      Europe PubMed Central
      Article . 2017
      Data sources: PubMed Central
      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/
      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/
      Journal of Cerebral Blood Flow & Metabolism
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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
      Journal of Cerebral Blood Flow & Metabolism
      Article . 2017 . Peer-reviewed
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    Authors: J. B. Vielfaure; S. D. Vergani; J. Japelj; Johan P. U. Fynbo; +22 Authors

    Context. The identification of the sources that reionized the Universe and their specific contribution to this process are key missing pieces of our knowledge of the early Universe. Faint star-forming galaxies may be the main contributors to the ionizing photon budget during the epoch of reionization, but their escaping photons cannot be detected directly due to inter-galactic medium opacity. Hence, it is essential to characterize the properties of faint galaxies with significant Lyman continuum (LyC) photon leakage up to z ∼ 4 to define indirect indicators allowing analogs to be found at the highest redshift. Aims. Long gamma-ray bursts (LGRBs) typically explode in star-forming regions of faint, star-forming galaxies. Through LGRB afterglow spectroscopy it is possible to detect directly LyC photons. Our aim is to use LGRBs as tools to study LyC leakage from faint, star-forming galaxies at high redshift. Methods. Here we present the observations of LyC emission in the afterglow spectra of GRB 191004B at z = 3.5055, together with those of the other two previously known LyC-leaking LGRB host galaxies (GRB 050908 at z = 3.3467, and GRB 060607A at z = 3.0749), to determine their LyC escape fraction and compare their properties. Results. From the afterglow spectrum of GRB 191004B we determine a neutral hydrogen column density at the LGRB redshift of log(NH I/cm−2) = 17.2 ± 0.15, and negligible extinction (AV = 0.03 ± 0.02 mag). The only metal absorption lines detected are C IV and Si IV. In contrast to GRB 050908 and GRB 060607A, the host galaxy of GRB 191004B displays significant Lyman-alpha (Lyα) emission. From its Lyα emission and the non-detection of Balmer emission lines we constrain its star-formation rate (SFR) to 1 ≤ SFR ≤ 4.7 M⊙ yr−1. We fit the Lyα emission with a shell model and find parameters values consistent with the observed ones. The absolute (relative) LyC escape fractions we find for GRB 191004B, GRB 050908 and GRB 060607A are of 0.35−0.11+0.10 (0.43−0.13+0.12), 0.08−0.04+0.05 (0.08−0.04+0.05) and 0.20−0.05+0.05 (0.45−0.15+0.15), respectively. We compare the LyC escape fraction of LGRBs to the values of other LyC emitters found from the literature, showing that LGRB afterglows can be powerful tools to study LyC escape for faint high-redshift star-forming galaxies. Indeed we could push LyC leakage studies to much higher absolute magnitudes. The host galaxies of the three LGRBs presented here have all M1600 > −19.5 mag, with the GRB 060607A host at M1600 > −16 mag. LGRB hosts may therefore be particularly suitable for exploring the ionizing escape fraction in galaxies that are too faint or distant for conventional techniques. Furthermore, the time involved is minimal compared to galaxy studies. © J.-B. Vielfaure et al. 2020 This work is part of the BEaPro project (PI: S.D. Vergani) funded by the French Agence Nationale de la Recherche (ANR-16-CE31-0003). We thank Giancarlo Ghirlanda for providing useful information. JBV and SDV thank Anne Verhamme for useful discussions. SDV acknowledges financial support from the French Space Agency (CNES). MG was supported by NASA through the NASA Hubble Fellowship grant HST-HF2-51409 and acknowledges support from HST grants HST-GO-15643.017-A, HST-AR-15039.003-A, and XSEDE grant TG-AST180036. The Cosmic DAWN center is funded by the DNRF. JPUF thanks the Carlsberg foundation for support. DBM acknowledges support from VILLUM FONDEN research grant 19054. NRT acknowledges support from STFC via grant ST/N000757/1. DAK acknowledges support from Spanish research project RTI2018-098104-J-I00 (GRBPhot). The PanSTARRS1 Surveys (PS1) and the PS1 public science archive have been made possible through contributions by the Institute for Astronomy, the University of Hawaii, the Pan-STARRS Project O ffice, the Max-Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg and the Max Planck Institute for Extraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, the Queen's University Belfast, the Harvard-Smithsonian Center for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, the National Aeronautics and Space Administration under Grant No. NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the National Science Foundation Grant No. AST-1238877, the University of Maryland, Eotvos Lorand University (ELTE), the Los Alamos National Laboratory, and the Gordon and Betty Moore Foundation. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium).Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. The NumPy (van der Walt et al. 2011), SciPy (Virtanen et al. 2020) and matplotlib (Hunter 2007) packages have been extensively used for the preparation and presentation of this work. Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Peer reviewed

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    Authors: Pineda-Pardo, J; Brun tild a, R; Woolrich, M; Marcos, A; +3 Authors

    Whole brain resting state connectivity is a promising biomarker that might help to obtain an early diagnosis in many neurological diseases, such as dementia. Inferring resting-state connectivity is often based on correlations, which are sensitive to indirect connections, leading to an inaccurate representation of the real backbone of the network. The precision matrix is a better representation for whole brain connectivity, as it considers only direct connections. The network structure can be estimated using the graphical lasso (GL), which achieves sparsity through l1-regularization on the precision matrix. In this paper, we propose a structural connectivity adaptive version of the GL, where weaker anatomical connections are represented as stronger penalties on the corresponding functional connections. We applied beamformer source reconstruction to the resting state MEG recordings of 81 subjects, where 29 were healthy controls, 22 were single-domain amnestic Mild Cognitive Impaired (MCI), and 30 were multiple-domain amnestic MCI. An atlas-based anatomical parcellation of 66 regions was obtained for each subject, and time series were assigned to each of the regions. The fiber densities between the regions, obtained with deterministic tractography from diffusion-weighted MRI, were used to define the anatomical connectivity. Precision matrices were obtained with the region specific time series in five different frequency bands. We compared our method with the traditional GL and a functional adaptive version of the GL, in terms of log-likelihood and classification accuracies between the three groups. We conclude that introducing an anatomical prior improves the expressivity of the model and, in most cases, leads to a better classification between groups. Highlights • We propose an anatomy-driven method for functional connectivity estimation in MEG. • Structural prior contributes to a better representation of the functional connectivity. • The proposed method is shown to be useful as a biomarker for classification of MCI.

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    Authors: Michael E. Rule; David Schnoerr; Matthias H. Hennig; Guido Sanguinetti;

    Large-scale neural recording methods now allow us to observe large populations of identified single neurons simultaneously, opening a window into neural population dynamics in living organisms. However, distilling such large-scale recordings to build theories of emergent collective dynamics remains a fundamental statistical challenge. The neural field models of Wilson, Cowan, and colleagues remain the mainstay of mathematical population modeling owing to their interpretable, mechanistic parameters and amenability to mathematical analysis. Inspired by recent advances in biochemical modeling, we develop a method based on moment closure to interpret neural field models as latent state-space point-process models, making them amenable to statistical inference. With this approach we can infer the intrinsic states of neurons, such as active and refractory, solely from spiking activity in large populations. After validating this approach with synthetic data, we apply it to high-density recordings of spiking activity in the developing mouse retina. This confirms the essential role of a long lasting refractory state in shaping spatiotemporal properties of neonatal retinal waves. This conceptual and methodological advance opens up new theoretical connections between mathematical theory and point-process state-space models in neural data analysis. Author summary Developing statistical tools to connect single-neuron activity to emergent collective dynamics is vital for building interpretable models of neural activity. Neural field models relate single-neuron activity to emergent collective dynamics in neural populations, but integrating them with data remains challenging. Recently, latent state-space models have emerged as a powerful tool for constructing phenomenological models of neural population activity. The advent of high-density multi-electrode array recordings now enables us to examine large-scale collective neural activity. We show that classical neural field approaches can yield latent state-space equations and demonstrate that this enables inference of the intrinsic states of neurons from recorded spike trains in large populations.

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