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  • Frontiers in Neuroscience

  • 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: Moody, Catherine J.; Mitchell, Derick; Kiser, Grace; Aarsland, Dag; +9 Authors

    Despite a wealth of activity across the globe in the area of longitudinal population cohorts, surprisingly little information is available on the natural biomedical history of a number of age-related neurodegenerative diseases (ND), and the scope for intervention studies based on these cohorts is only just beginning to be explored. The Joint Programming Initiative on Neurodegenerative Disease Research (JPND) recently developed a novel funding mechanism to rapidly mobilize scientists to address these issues from a broad, international community perspective. Ten expert Working Groups, bringing together a diverse range of community members and covering a wide ND landscape [Alzheimer's, Parkinson's, frontotemporal degeneration, amyotrophic lateral sclerosis (ALS), Lewy-body and vascular dementia] were formed to discuss and propose potential approaches to better exploiting and coordinating cohort studies. The purpose of this work is to highlight the novel funding process along with a broad overview of the guidelines and recommendations generated by the ten groups, which include investigations into multiple methodologies such as cognition/functional assessment, biomarkers and biobanking, imaging, health and social outcomes, and pre-symptomatic ND. All of these were published in reports that are now publicly available online.

    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/ Frontiers in Neurosc...arrow_drop_down
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    Frontiers in Neuroscience
    Report . 2017 . 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/ Frontiers in Neurosc...arrow_drop_down
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      Frontiers in Neuroscience
      Report . 2017 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Bhagwat, Nikhil; Pipitone, Jon; Winterburn, Julie L.; Guo, Ting; +6 Authors

    Recent advances in multi-atlas based algorithms address many of the previous limitations in model-based and probabilistic segmentation methods. However, at the label fusion stage, a majority of algorithms focus primarily on optimizing weight-maps associated with the atlas library based on a theoretical objective function that approximates the segmentation error. In contrast, we propose a novel method—Autocorrecting Walks over Localized Markov Random Fields (AWoL-MRF)—that aims at mimicking the sequential process of manual segmentation, which is the gold-standard for virtually all the segmentation methods. AWoL-MRF begins with a set of candidate labels generated by a multi-atlas segmentation pipeline as an initial label distribution and refines low confidence regions based on a localized Markov random field (L-MRF) model using a novel sequential inference process (walks). We show that AWoL-MRF produces state-of-the-art results with superior accuracy and robustness with a small atlas library compared to existing methods. We validate the proposed approach by performing hippocampal segmentations on three independent datasets: (1) Alzheimer's Disease Neuroimaging Database (ADNI); (2) First Episode Psychosis patient cohort; and (3) A cohort of preterm neonates scanned early in life and at term-equivalent age. We assess the improvement in the performance qualitatively as well as quantitatively by comparing AWoL-MRF with majority vote, STAPLE, and Joint Label Fusion methods. AWoL-MRF reaches a maximum accuracy of 0.881 (dataset 1), 0.897 (dataset 2), and 0.807 (dataset 3) based on Dice similarity coefficient metric, offering significant performance improvements with a smaller atlas library (< 10) over compared methods. We also evaluate the diagnostic utility of AWoL-MRF by analyzing the volume differences per disease category in the ADNI1: Complete Screening dataset. We have made the source code for AWoL-MRF public at: https://github.com/CobraLab/AWoL-MRF.

    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/ Frontiers in Neurosc...arrow_drop_down
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    Frontiers in Neuroscience
    2016 . Peer-reviewed
    Data sources: Frontiers
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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/ Frontiers in Neurosc...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/
      Frontiers in Neuroscience
      2016 . Peer-reviewed
      Data sources: Frontiers
  • 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: Brown, David D. R.; Pearson, Bret J.;

    Powerful genetic tools in classical laboratory models have been fundamental to our understanding of how stem cells give rise to complex neural tissues during embryonic development. In contrast, adult neurogenesis in our model systems, if present, is typically constrained to one or a few zones of the adult brain to produce a limited subset of neurons leading to the dogma that the brain is primarily fixed post-development. The freshwater planarian (flatworm) is an invertebrate model system that challenges this dogma. The planarian possesses a brain containing several thousand neurons with very high rates of cell turnover (homeostasis), which can also be fully regenerated de novo from injury in just 7 days. Both homeostasis and regeneration depend on the activity of a large population of adult stem cells, called neoblasts, throughout the planarian body. Thus, much effort has been put forth to understand how the flatworm can continually give rise to the diversity of cell types found in the adult brain. Here we focus on work using single-cell genomics and functional analyses to unravel the cellular hierarchies from stem cell to neuron. In addition, we will review what is known about how planarians utilize developmental signaling to maintain proper tissue patterning, homeostasis, and cell-type diversity in their brains. Together, planarians are a powerful emerging model system to study the dynamics of adult neurogenesis and regeneration.

    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/ Frontiers in Neurosc...arrow_drop_down
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    Frontiers in Neuroscience
    Report . 2017 . Peer-reviewed
    Data sources: Frontiers
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      Frontiers in Neuroscience
      Report . 2017 . Peer-reviewed
      Data sources: Frontiers
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    Authors: French, Leon; Paus, Tomáš;
    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/ Frontiers in Neurosc...arrow_drop_down
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    Frontiers in Neuroscience
    Other ORP type . 2015 . 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/ Frontiers in Neurosc...arrow_drop_down
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      Frontiers in Neuroscience
      Other ORP type . 2015 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Klinghammer, Mathias; Blohm, Gunnar; Fiehler, Katja;

    Previous research has shown that egocentric and allocentric information is used for coding target locations for memory-guided reaching movements. Especially, task-relevance determines the use of objects as allocentric cues. Here, we investigated the influence of scene configuration and object reliability as a function of task-relevance on allocentric coding for memory-guided reaching. For that purpose, we presented participants images of a naturalistic breakfast scene with five objects on a table and six objects in the background. Six of these objects served as potential reach-targets (= task-relevant objects). Participants explored the scene and after a short delay, a test scene appeared with one of the task-relevant objects missing, indicating the location of the reach target. After the test scene vanished, participants performed a memory-guided reaching movement toward the target location. Besides removing one object from the test scene, we also shifted the remaining task-relevant and/or task-irrelevant objects left- or rightwards either coherently in the same direction or incoherently in opposite directions. By varying object coherence, we manipulated the reliability of task-relevant and task-irrelevant objects in the scene. In order to examine the influence of scene configuration (distributed vs. grouped arrangement of task-relevant objects) on allocentric coding, we compared the present data with our previously published data set (Klinghammer et al., 2015). We found that reaching errors systematically deviated in the direction of object shifts, but only when the objects were task-relevant and their reliability was high. However, this effect was substantially reduced when task-relevant objects were distributed across the scene leading to a larger target-cue distance compared to a grouped configuration. No deviations of reach endpoints were observed in conditions with shifts of only task-irrelevant objects or with low object reliability irrespective of task-relevancy. Moreover, when solely task-relevant objects were shifted incoherently, the variability of reaching endpoints increased compared to coherent shifts of task-relevant objects. Our results suggest that the use of allocentric information for coding targets for memory-guided reaching depends on the scene configuration, in particular the average distance of the reach target to task-relevant objects, and the reliability of task-relevant allocentric information.

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    Frontiers in Neuroscience
    Article . 2017 . Peer-reviewed
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      Frontiers in Neuroscience
      Article . 2017 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Ahrens, Merle-Marie; Awwad Shiekh Hasan, Bashar; Giordano, Bruno L.; Belin, Pascal;

    International audience; There is not only evidence for behavioral differences in voice perception between female and male listeners, but also recent suggestions for differences in neural correlates between genders. The fMRI functional voice localizer (comprising a univariate analysis contrasting stimulation with vocal vs. non-vocal sounds) is known to give robust estimates of the temporal voice areas (TVAs). However, there is growing interest in employing multivariate analysis approaches to fMRI data (e.g., multivariate pattern analysis; MVPA). The aim of the current study was to localize voice-related areas in both female and male listeners and to investigate whether brain maps may differ depending on the gender of the listener. After a univariate analysis, a random effects analysis was performed on female (n = 149) and male (n = 123) listeners and contrasts between them were computed. In addition, MVPA with a whole-brain searchlight approach was implemented and classification maps were entered into a second-level permutation based random effects models using statistical non-parametric mapping (SnPM; Nichols and Holmes, 2002). Gender differences were found only in the MVPA. Identified regions were located in the middle part of the middle temporal gyrus (bilateral) and the middle superior temporal gyrus (right hemisphere). Our results suggest differences in classifier performance between genders in response to the voice localizer with higher classification accuracy from local BOLD signal patterns in several temporal-lobe regions in female listeners.

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    Frontiers in Neuroscience
    Article . 2014 . Peer-reviewed
    Data sources: Frontiers
    Hal-Diderot
    Article . 2014
    Data sources: Hal-Diderot
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    Authors: Chen, Ji-Hong; Wang, Xuan-Yu; Liu, Louis W. C.; Yu, Wenzhen; +3 Authors

    A patient with early achalasia presented spontaneous strong rhythmic non-propulsive contractions at ~7/min, independent of swallows. Our aim was to evaluate characteristics of the rhythmic contractions, provide data on the structure of pacemaker cells in the esophagus and discuss a potential role for interstitial cells of Cajal (ICC) in the origin of rhythmicity. We hypothesize that intramuscular ICC (ICC-IM) are the primary pacemaker cells. The frequency but not the amplitude of the rhythmic contractions was inhibited by the phosphodiesterase inhibitor drotaverine consistent with cAMP inhibiting pacemaker currents in ICC-IM. The frequency increased by wet swallows but not dry swallows, consistent with stretch causing increase in slow wave frequency in ICC-IM. New studies on archival material showed that ICC-IM were present throughout the human esophageal musculature and were not diminished in early achalasia. Although ICC-IM exhibited a low density, they were connected to PDGFRα-positive fibroblast-like cells with whom they formed a dense gap junction coupled network. Nitrergic innervation of ICC was strongly diminished in early achalasia because of the loss of nitrergic nerves. It therefore appears possibly that ICC-IM function as pacemaker cells in the esophagus and that the network of ICC and PDGFRα-positive cells allows for coupling and propagation of the pacemaker activity. Loss of nitrergic innervation to ICC in achalasia may render them more excitable such that its pacemaker activity is more easily expressed. Loss of propagation in achalasia may be due to loss of contraction-induced aboral nitrergic inhibition.

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    Frontiers in Neuroscience
    Report . 2013 . Peer-reviewed
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      Frontiers in Neuroscience
      Report . 2013 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Taube Navaraj, William; García Núñez, Carlos; Shakthivel, Dhayalan; Vinciguerra, Vincenzo; +3 Authors

    This paper presents novel Neural Nanowire Field Effect Transistors (υ-NWFETs) based\ud hardware-implementable neural network (HNN) approach for tactile data processing\ud in electronic skin (e-skin). The viability of Si nanowires (NWs) as the active material\ud for υ-NWFETs in HNN is explored through modeling and demonstrated by fabricating\ud the first device. Using υ-NWFETs to realize HNNs is an interesting approach as by\ud printing NWs on large area flexible substrates it will be possible to develop a bendable\ud tactile skin with distributed neural elements (for local data processing, as in biological\ud skin) in the backplane. The modeling and simulation of υ-NWFET based devices show\ud that the overlapping areas between individual gates and the floating gate determines\ud the initial synaptic weights of the neural network - thus validating the working of\ud υ-NWFETs as the building block for HNN. The simulation has been further extended to\ud υ-NWFET based circuits and neuronal computation system and this has been validated\ud by interfacing it with a transparent tactile skin prototype (comprising of 6 × 6 ITO\ud based capacitive tactile sensors array) integrated on the palm of a 3D printed robotic\ud hand. In this regard, a tactile data coding system is presented to detect touch gesture\ud and the direction of touch. Following these simulation studies, a four-gated υ-NWFET\ud is fabricated with Pt/Ti metal stack for gates, source and drain, Ni floating gate, and\ud Al2O3 high-k dielectric layer. The current-voltage characteristics of fabricated υ-NWFET\ud devices confirm the dependence of turn-off voltages on the (synaptic) weight of each\ud gate. The presented υ-NWFET approach is promising for a neuro-robotic tactile sensory\ud system with distributed computing as well as numerous futuristic applications such as\ud prosthetics, and electroceuticals.

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    DOAJ-Articles
    Article . 2017
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    Article . 2017
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    Frontiers in Neuroscience
    Article . 2017 . Peer-reviewed
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      DOAJ-Articles
      Article . 2017
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      DOAJ
      Article . 2017
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      Frontiers in Neuroscience
      Article . 2017 . 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: Mohammadi, Siawoosh; Carey, Daniel; Dick, Fred; Diedrichsen, Joern; +4 Authors

    The g-ratio, quantifying the ratio between the inner and outer diameters of a fiber, is an important microstructural characteristic of fiber pathways and is functionally related to conduction velocity. We introduce a novel method for estimating the MR g-ratio non-invasively across the whole brain using high-fidelity magnetization transfer (MT) imaging and single-shell diffusion MRI. These methods enabled us to map the MR g-ratio in vivo across the brain's prominent fiber pathways in a group of 37 healthy volunteers and to estimate the inter-subject variability. Effective correction of susceptibility-related distortion artifacts was essential before combining the MT and diffusion data, in order to reduce partial volume and edge artifacts. The MR g-ratio is in good qualitative agreement with histological findings despite the different resolution and spatial coverage of MRI and histology. The MR g-ratio holds promise as an important non-invasive biomarker due to its microstructural and functional relevance in neurodegeneration.

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    MPG.PuRe
    Article . 2015
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    UCL Discovery
    Article . 2015
    Data sources: UCL Discovery
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    MPG.PuRe
    Article . 2015
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    Frontiers in Neuroscience
    Article . 2015 . Peer-reviewed
    Data sources: Frontiers
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      MPG.PuRe
      Article . 2015
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      UCL Discovery
      Article . 2015
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      MPG.PuRe
      Article . 2015
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      Frontiers in Neuroscience
      Article . 2015 . Peer-reviewed
      Data sources: Frontiers
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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: Baldassarre, L; Pontil, M; Mourão-Miranda, J;

    Structured sparse methods have received significant attention in neuroimaging. These methods allow the incorporation of domain knowledge through additional spatial and temporal constraints in the predictive model and carry the promise of being more interpretable than non-structured sparse methods, such as LASSO or Elastic Net methods. However, although sparsity has often been advocated as leading to more interpretable models it can also lead to unstable models under subsampling or slight changes of the experimental conditions. In the present work we investigate the impact of using stability/reproducibility as an additional model selection criterion1 on several different sparse (and structured sparse) methods that have been recently applied for fMRI brain decoding. We compare three different model selection criteria: (i) classification accuracy alone; (ii) classification accuracy and overlap between the solutions; (iii) classification accuracy and correlation between the solutions. The methods we consider include LASSO, Elastic Net, Total Variation, sparse Total Variation, Laplacian and Graph Laplacian Elastic Net (GraphNET). Our results show that explicitly accounting for stability/reproducibility during the model optimization can mitigate some of the instability inherent in sparse methods. In particular, using accuracy and overlap between the solutions as a joint optimization criterion can lead to solutions that are more similar in terms of accuracy, sparsity levels and coefficient maps even when different sparsity methods are considered.

    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/ UCL Discoveryarrow_drop_down
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    UCL Discovery
    Article . 2017
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    MPG.PuRe
    Article . 2017
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    Frontiers in Neuroscience
    Article . 2017 . Peer-reviewed
    Data sources: Frontiers
    MPG.PuRe
    Article . 2017
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      UCL Discovery
      Article . 2017
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      MPG.PuRe
      Article . 2017
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      Frontiers in Neuroscience
      Article . 2017 . Peer-reviewed
      Data sources: Frontiers
      MPG.PuRe
      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/
    Authors: Moody, Catherine J.; Mitchell, Derick; Kiser, Grace; Aarsland, Dag; +9 Authors

    Despite a wealth of activity across the globe in the area of longitudinal population cohorts, surprisingly little information is available on the natural biomedical history of a number of age-related neurodegenerative diseases (ND), and the scope for intervention studies based on these cohorts is only just beginning to be explored. The Joint Programming Initiative on Neurodegenerative Disease Research (JPND) recently developed a novel funding mechanism to rapidly mobilize scientists to address these issues from a broad, international community perspective. Ten expert Working Groups, bringing together a diverse range of community members and covering a wide ND landscape [Alzheimer's, Parkinson's, frontotemporal degeneration, amyotrophic lateral sclerosis (ALS), Lewy-body and vascular dementia] were formed to discuss and propose potential approaches to better exploiting and coordinating cohort studies. The purpose of this work is to highlight the novel funding process along with a broad overview of the guidelines and recommendations generated by the ten groups, which include investigations into multiple methodologies such as cognition/functional assessment, biomarkers and biobanking, imaging, health and social outcomes, and pre-symptomatic ND. All of these were published in reports that are now publicly available online.

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    Frontiers in Neuroscience
    Report . 2017 . Peer-reviewed
    Data sources: Frontiers
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      Frontiers in Neuroscience
      Report . 2017 . Peer-reviewed
      Data sources: Frontiers
  • 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: Bhagwat, Nikhil; Pipitone, Jon; Winterburn, Julie L.; Guo, Ting; +6 Authors

    Recent advances in multi-atlas based algorithms address many of the previous limitations in model-based and probabilistic segmentation methods. However, at the label fusion stage, a majority of algorithms focus primarily on optimizing weight-maps associated with the atlas library based on a theoretical objective function that approximates the segmentation error. In contrast, we propose a novel method—Autocorrecting Walks over Localized Markov Random Fields (AWoL-MRF)—that aims at mimicking the sequential process of manual segmentation, which is the gold-standard for virtually all the segmentation methods. AWoL-MRF begins with a set of candidate labels generated by a multi-atlas segmentation pipeline as an initial label distribution and refines low confidence regions based on a localized Markov random field (L-MRF) model using a novel sequential inference process (walks). We show that AWoL-MRF produces state-of-the-art results with superior accuracy and robustness with a small atlas library compared to existing methods. We validate the proposed approach by performing hippocampal segmentations on three independent datasets: (1) Alzheimer's Disease Neuroimaging Database (ADNI); (2) First Episode Psychosis patient cohort; and (3) A cohort of preterm neonates scanned early in life and at term-equivalent age. We assess the improvement in the performance qualitatively as well as quantitatively by comparing AWoL-MRF with majority vote, STAPLE, and Joint Label Fusion methods. AWoL-MRF reaches a maximum accuracy of 0.881 (dataset 1), 0.897 (dataset 2), and 0.807 (dataset 3) based on Dice similarity coefficient metric, offering significant performance improvements with a smaller atlas library (< 10) over compared methods. We also evaluate the diagnostic utility of AWoL-MRF by analyzing the volume differences per disease category in the ADNI1: Complete Screening dataset. We have made the source code for AWoL-MRF public at: https://github.com/CobraLab/AWoL-MRF.

    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/ Frontiers in Neurosc...arrow_drop_down
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    Frontiers in Neuroscience
    2016 . Peer-reviewed
    Data sources: Frontiers
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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/
      Frontiers in Neuroscience
      2016 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Brown, David D. R.; Pearson, Bret J.;

    Powerful genetic tools in classical laboratory models have been fundamental to our understanding of how stem cells give rise to complex neural tissues during embryonic development. In contrast, adult neurogenesis in our model systems, if present, is typically constrained to one or a few zones of the adult brain to produce a limited subset of neurons leading to the dogma that the brain is primarily fixed post-development. The freshwater planarian (flatworm) is an invertebrate model system that challenges this dogma. The planarian possesses a brain containing several thousand neurons with very high rates of cell turnover (homeostasis), which can also be fully regenerated de novo from injury in just 7 days. Both homeostasis and regeneration depend on the activity of a large population of adult stem cells, called neoblasts, throughout the planarian body. Thus, much effort has been put forth to understand how the flatworm can continually give rise to the diversity of cell types found in the adult brain. Here we focus on work using single-cell genomics and functional analyses to unravel the cellular hierarchies from stem cell to neuron. In addition, we will review what is known about how planarians utilize developmental signaling to maintain proper tissue patterning, homeostasis, and cell-type diversity in their brains. Together, planarians are a powerful emerging model system to study the dynamics of adult neurogenesis and regeneration.

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    Frontiers in Neuroscience
    Report . 2017 . Peer-reviewed
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      Frontiers in Neuroscience
      Report . 2017 . Peer-reviewed
      Data sources: Frontiers
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    Authors: French, Leon; Paus, Tomáš;
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    Frontiers in Neuroscience
    Other ORP type . 2015 . Peer-reviewed
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      Frontiers in Neuroscience
      Other ORP type . 2015 . Peer-reviewed
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    Authors: Klinghammer, Mathias; Blohm, Gunnar; Fiehler, Katja;

    Previous research has shown that egocentric and allocentric information is used for coding target locations for memory-guided reaching movements. Especially, task-relevance determines the use of objects as allocentric cues. Here, we investigated the influence of scene configuration and object reliability as a function of task-relevance on allocentric coding for memory-guided reaching. For that purpose, we presented participants images of a naturalistic breakfast scene with five objects on a table and six objects in the background. Six of these objects served as potential reach-targets (= task-relevant objects). Participants explored the scene and after a short delay, a test scene appeared with one of the task-relevant objects missing, indicating the location of the reach target. After the test scene vanished, participants performed a memory-guided reaching movement toward the target location. Besides removing one object from the test scene, we also shifted the remaining task-relevant and/or task-irrelevant objects left- or rightwards either coherently in the same direction or incoherently in opposite directions. By varying object coherence, we manipulated the reliability of task-relevant and task-irrelevant objects in the scene. In order to examine the influence of scene configuration (distributed vs. grouped arrangement of task-relevant objects) on allocentric coding, we compared the present data with our previously published data set (Klinghammer et al., 2015). We found that reaching errors systematically deviated in the direction of object shifts, but only when the objects were task-relevant and their reliability was high. However, this effect was substantially reduced when task-relevant objects were distributed across the scene leading to a larger target-cue distance compared to a grouped configuration. No deviations of reach endpoints were observed in conditions with shifts of only task-irrelevant objects or with low object reliability irrespective of task-relevancy. Moreover, when solely task-relevant objects were shifted incoherently, the variability of reaching endpoints increased compared to coherent shifts of task-relevant objects. Our results suggest that the use of allocentric information for coding targets for memory-guided reaching depends on the scene configuration, in particular the average distance of the reach target to task-relevant objects, and the reliability of task-relevant allocentric information.

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    Frontiers in Neuroscience
    Article . 2017 . Peer-reviewed
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      Frontiers in Neuroscience
      Article . 2017 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Ahrens, Merle-Marie; Awwad Shiekh Hasan, Bashar; Giordano, Bruno L.; Belin, Pascal;

    International audience; There is not only evidence for behavioral differences in voice perception between female and male listeners, but also recent suggestions for differences in neural correlates between genders. The fMRI functional voice localizer (comprising a univariate analysis contrasting stimulation with vocal vs. non-vocal sounds) is known to give robust estimates of the temporal voice areas (TVAs). However, there is growing interest in employing multivariate analysis approaches to fMRI data (e.g., multivariate pattern analysis; MVPA). The aim of the current study was to localize voice-related areas in both female and male listeners and to investigate whether brain maps may differ depending on the gender of the listener. After a univariate analysis, a random effects analysis was performed on female (n = 149) and male (n = 123) listeners and contrasts between them were computed. In addition, MVPA with a whole-brain searchlight approach was implemented and classification maps were entered into a second-level permutation based random effects models using statistical non-parametric mapping (SnPM; Nichols and Holmes, 2002). Gender differences were found only in the MVPA. Identified regions were located in the middle part of the middle temporal gyrus (bilateral) and the middle superior temporal gyrus (right hemisphere). Our results suggest differences in classifier performance between genders in response to the voice localizer with higher classification accuracy from local BOLD signal patterns in several temporal-lobe regions in female listeners.

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    Frontiers in Neuroscience
    Article . 2014 . Peer-reviewed
    Data sources: Frontiers
    Hal-Diderot
    Article . 2014
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    Authors: Chen, Ji-Hong; Wang, Xuan-Yu; Liu, Louis W. C.; Yu, Wenzhen; +3 Authors

    A patient with early achalasia presented spontaneous strong rhythmic non-propulsive contractions at ~7/min, independent of swallows. Our aim was to evaluate characteristics of the rhythmic contractions, provide data on the structure of pacemaker cells in the esophagus and discuss a potential role for interstitial cells of Cajal (ICC) in the origin of rhythmicity. We hypothesize that intramuscular ICC (ICC-IM) are the primary pacemaker cells. The frequency but not the amplitude of the rhythmic contractions was inhibited by the phosphodiesterase inhibitor drotaverine consistent with cAMP inhibiting pacemaker currents in ICC-IM. The frequency increased by wet swallows but not dry swallows, consistent with stretch causing increase in slow wave frequency in ICC-IM. New studies on archival material showed that ICC-IM were present throughout the human esophageal musculature and were not diminished in early achalasia. Although ICC-IM exhibited a low density, they were connected to PDGFRα-positive fibroblast-like cells with whom they formed a dense gap junction coupled network. Nitrergic innervation of ICC was strongly diminished in early achalasia because of the loss of nitrergic nerves. It therefore appears possibly that ICC-IM function as pacemaker cells in the esophagus and that the network of ICC and PDGFRα-positive cells allows for coupling and propagation of the pacemaker activity. Loss of nitrergic innervation to ICC in achalasia may render them more excitable such that its pacemaker activity is more easily expressed. Loss of propagation in achalasia may be due to loss of contraction-induced aboral nitrergic inhibition.

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    Frontiers in Neuroscience
    Report . 2013 . Peer-reviewed
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      Frontiers in Neuroscience
      Report . 2013 . Peer-reviewed
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