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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: Chakhoyan, Ararat; Raymond, Catalina; Chen, Jason; Goldman, Jodi; +4 Authors

    Figure S2. Comparison of arterial, venous or overlap components proportional to enhancing tumor volume at 1.5 T and 3 T. The arterial component was significantly smaller in ‘other’ group when using 1.5 T (7.59%) as compared to 3 T (17.99%, p

    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/ figsharearrow_drop_down
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    Image . 2019
    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/
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    Image . 2019
    License: CC BY
    Data sources: Datacite
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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/ figsharearrow_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 . 2019
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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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      Image . 2019
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      Data sources: Datacite
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    Authors: Herb, Brian; Shook, Molly; Fields, Christopher; Robinson, Gene;

    Table S5. Summary of samples and WGBS sequencing. (XLSX 43Â kb)

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    Dataset . 2018
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    Dataset . 2018
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    Data sources: Datacite
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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/ figsharearrow_drop_down
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      Dataset . 2018
      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/
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      Dataset . 2018
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      Data sources: Datacite
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    Authors: Flores-Aguilar, Lisi; Iulita, M. Florencia; Orciani, Chiara; Tanna, Neil; +3 Authors

    Additional file 6: Supplemental Table 5. Correlation of post-mortem interval with cytokine expression in the temporal, parietal and frontal cortices.

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    Dataset . 2021
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    Dataset . 2021
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    Data sources: Datacite
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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/ figsharearrow_drop_down
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      Dataset . 2021
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      Dataset . 2021
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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: Schutte, Iris; Slagter, Heleen A.; Collins, Anne G.E.; Frank, Michael J.; +2 Authors

    Reinforcement learning tasks are often used to assess participants' tendency to learn more from the positive or more from the negative consequences of one's action. However, this assessment often requires comparison in learning performance across different task conditions, which may differ in the relative salience or discriminability of the stimuli associated with more and less rewarding outcomes, respectively. To address this issue, in a first set of studies, participants were subjected to two versions of a common probabilistic learning task. The two versions differed with respect to the stimulus (Hiragana) characters associated with reward probability. The assignment of character to reward probability was fixed within version but reversed between versions. We found that performance was highly influenced by task version, which could be explained by the relative perceptual discriminability of characters assigned to high or low reward probabilities, as assessed by a separate discrimination experiment. Participants were more reliable in selecting rewarding characters that were more discriminable, leading to differences in learning curves and their sensitivity to reward probability. This difference in experienced reinforcement history was accompanied by performance biases in a test phase assessing ability to learn from positive vs. negative outcomes. In a subsequent large-scale web-based experiment, this impact of task version on learning and test measures was replicated and extended. Collectively, these findings imply a key role for perceptual factors in guiding reward learning and underscore the need to control stimulus discriminability when making inferences about individual differences in reinforcement learning. Probabilistic selection task data_ Exp1A_Fig2a_Fig3aData corresponds to experiment 1A and Figure 2A/3A.Probabilistic selection task data_ Exp1B_Fig2b_Fig3b_Schutte_etalData corresponds to Experiment 1B and Figure 2B/3B.Reaction time data_ Exp2_Fig5_Schutte_etalData corresponds to Experiment 2 and Figure 5Probabilistic selection task data_Exp3_Fig6_Fig7Data corresponds to experiment 3 and Figure 6 and 7.

    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/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2018
    License: CC 0
    Data sources: ZENODO
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    DANS-EASY
    Dataset . 2017
    Data sources: B2FIND
    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/ ZENODOarrow_drop_down
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      ZENODO
      Dataset . 2018
      License: CC 0
      Data sources: ZENODO
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      DANS-EASY
      Dataset . 2017
      Data sources: B2FIND
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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: Thiyagaragan Achariyar; Baoman Li; Weiguo Peng; Verghese, Philip; +9 Authors

    Lenti-EGFP effectively transduced the choroid plexus. A) Lenti-EGFP unilateral injected into the lateral ventricle preferentially transduced the choroid plexus and ependymal layer but not brain parenchyma at 1 week. DAPI (blue); EGFP (green). B-E) Lenti-EGFP expression in the choroid plexus at 1 week. Images are DAPI (blue; B), AQP1 (red; C); EGFP (green; D) and merged images (E). Scale bar 50 μm. Intraventricular injection of 3 μL lenti-EGFP (1012 TU/ml). N = 5. (EPS 75360 kb)

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    Image . 2016
    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/
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    Image . 2016
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      Image . 2016
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      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/
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      Image . 2016
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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: Kedarasetti, Ravi Teja; Turner, Kevin L.; Echagarruga, Christina; Gluckman, Bruce J.; +2 Authors

    Additional file 13: Figure S6. Deformation of the brain tissue due to the pressure changes in the PVS. Note the geometry is depicted with an unequal aspect ratio in the radial (r) and axial (z) directions for viewing convenience. a. Radial displacement contours in the brain tissue (maximum deformation, occurs at 1.16 seconds for the vasodilation profile shown in b). The brain tissue can deform by upto 1.2 µm, when the arteriole (with an initial radius of 12µm) increases its radius by 1.8 µm. b. Plot shows the change of radial displacement at the PVS-Brain interface with time. These deformations can be explained by the pressure changes in the PVS. When there is fluid outflow from the PVS, the increase in the pressure causes the brain tissue to deforms radially outward and when there is fluid influx, the brain tissue deforms radially inward. The smallest tissue displacement is at the pial surface (z = 250µm), which is the location of smallest pressure changes, as it is connected to the SAS flow resistance. The brain tissue is fixed at r = 150µm. c. Plot shows the change of radial displacement in the brain tissue at different distances from the centerline of the vessel.

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    Image . 2020
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    Image . 2020
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      Image . 2020
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      Data sources: Datacite
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      Image . 2020
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    Authors: Pandey, Ravi S.; Kotredes, Kevin P.; Sasner, Michael; Howell, Gareth R.; +1 Authors

    Additional file 11: Supplementary Table 6. Enrichment of Gene ontology biological processes analyses in differentially isoform usage (DTU) genes. The attached table depicts the gene 2 ontology enrichment for the differentially isoform usage genes in Trem2*R47H male and female mice compared to age and sex-matched C7BL/6 J mice.

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    Dataset . 2023
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    Authors: Mingyan Lin; Pedrosa, Erika; Hrabovsky, Anastasia; Chen, Jian; +4 Authors

    Is a figure with a heat map showing relative expression of 22q11 DEL genes in BrainSpan data in the frontal cortex. Red color indicates higher expression value, while blue means lower expression. (TIF 339Â kb)

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    Authors: Peipei Li; Ensink, Elizabeth; Lang, Sean; Marshall, Lee; +4 Authors

    Proteins exhibiting hemispheric asymmetry in PD that have corresponding gene transcripts and/or DNA methylation differences across PD hemispheres.

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    Authors: Hermeto Gerber; Mosser, Sebastien; Boury-Jamot, Benjamin; Stumpe, Michael; +6 Authors

    Table S1. (a) Summary list of 113 proteins differently expressed in APMAP ko/ko mice, compared to WT mice. (b) List of 2747 proteins identified by LFQ where at least 2 peptides have been detected and a minimum of 2 valid values per group (ko/ko vs wt/wt) was obtained. Displayed with a yellow background are the 105 differently expressed proteins revealed by statistical analysis (t-test: p-value < 0.05). (c) List of 8 differently expressed proteins identified in addition to (b) by imputing missing LFQ values with at least 2 detected peptides and a minimum of 3 valid values for at least one group (ko/ko or wt/wt; t-test: p-value < 0.05), in green left-censored imputated values. (XLSX 540 kb)

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    Authors: Chakhoyan, Ararat; Raymond, Catalina; Chen, Jason; Goldman, Jodi; +4 Authors

    Figure S2. Comparison of arterial, venous or overlap components proportional to enhancing tumor volume at 1.5 T and 3 T. The arterial component was significantly smaller in ‘other’ group when using 1.5 T (7.59%) as compared to 3 T (17.99%, p

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    Authors: Herb, Brian; Shook, Molly; Fields, Christopher; Robinson, Gene;

    Table S5. Summary of samples and WGBS sequencing. (XLSX 43Â kb)

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    Authors: Flores-Aguilar, Lisi; Iulita, M. Florencia; Orciani, Chiara; Tanna, Neil; +3 Authors

    Additional file 6: Supplemental Table 5. Correlation of post-mortem interval with cytokine expression in the temporal, parietal and frontal cortices.

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    Authors: Schutte, Iris; Slagter, Heleen A.; Collins, Anne G.E.; Frank, Michael J.; +2 Authors

    Reinforcement learning tasks are often used to assess participants' tendency to learn more from the positive or more from the negative consequences of one's action. However, this assessment often requires comparison in learning performance across different task conditions, which may differ in the relative salience or discriminability of the stimuli associated with more and less rewarding outcomes, respectively. To address this issue, in a first set of studies, participants were subjected to two versions of a common probabilistic learning task. The two versions differed with respect to the stimulus (Hiragana) characters associated with reward probability. The assignment of character to reward probability was fixed within version but reversed between versions. We found that performance was highly influenced by task version, which could be explained by the relative perceptual discriminability of characters assigned to high or low reward probabilities, as assessed by a separate discrimination experiment. Participants were more reliable in selecting rewarding characters that were more discriminable, leading to differences in learning curves and their sensitivity to reward probability. This difference in experienced reinforcement history was accompanied by performance biases in a test phase assessing ability to learn from positive vs. negative outcomes. In a subsequent large-scale web-based experiment, this impact of task version on learning and test measures was replicated and extended. Collectively, these findings imply a key role for perceptual factors in guiding reward learning and underscore the need to control stimulus discriminability when making inferences about individual differences in reinforcement learning. Probabilistic selection task data_ Exp1A_Fig2a_Fig3aData corresponds to experiment 1A and Figure 2A/3A.Probabilistic selection task data_ Exp1B_Fig2b_Fig3b_Schutte_etalData corresponds to Experiment 1B and Figure 2B/3B.Reaction time data_ Exp2_Fig5_Schutte_etalData corresponds to Experiment 2 and Figure 5Probabilistic selection task data_Exp3_Fig6_Fig7Data corresponds to experiment 3 and Figure 6 and 7.

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    ZENODO
    Dataset . 2018
    License: CC 0
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    DANS-EASY
    Dataset . 2017
    Data sources: B2FIND
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      ZENODO
      Dataset . 2018
      License: CC 0
      Data sources: ZENODO
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      DANS-EASY
      Dataset . 2017
      Data sources: B2FIND
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