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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/

    A total of 668 single units were recorded in the mouse periaqueductal gray (PAG) and adjacent deep mesencephalic nucleus (DpMe) in order to determine their role in the switching of sleep-wake states, i.e. wakefulness (W), slow-wave sleep (SWS), and paradoxical (or rapid eye movement) sleep (PS) in general, and, in particular, to determine whether PS-on and PS-off neurons involved in PS state switching are present in these structures and to identify neuronal substrates for the SWS-PS switching mediated by DpMe neurons. Both structures were found to contain similar percentages of W/PS-active neurons, which discharge at a higher rate during W and PS than during SWS, while W-active neurons, which discharge maximally during W, were found mainly in the PAG. Both also contained similar percentages of SWS/PS-active neurons, which discharge at higher rates during SWS and PS than during W, and PS-active neurons, which discharge maximally during PS, while SWS-active neurons, which discharge maximally during SWS were found almost exclusively in the PAG. Both structures contained virtually no PS-on or PS-off neurons, which, respectively, discharge or cease firing selectively and tonically just prior to, and during, PS. Unlike the PAG, the DpMe contained many SWS/PS-on neurons, which discharge selectively at high rates during SWS and PS, but show a decrease in discharge rate at the transition from SWS to PS. Analysis of discharge profiles and trends in spike activity at the state transitions strongly suggests that PAG and DpMe neurons play an important role in the W-SWS, SWS-PS, and/or PS-W switches.

    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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    Dataset . 2018
    License: CC 0
    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
    License: CC 0
    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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      Dataset . 2018
      License: CC 0
      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
      License: CC 0
      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/
    Authors: Fengjiao Wu; Zou, Qiang; Xiaodan Ding; Dongyan Shi; +4 Authors

    Time-lapse recordings of the intravascular rolling and adhesion of leukocytes in WT C57BL/6J mice after intraventricular LPS injection (4 h). Rolling leukocytes were defined as those cells moving at a velocity less than that of erythrocytes. Cells were considered adherent if they remained stationary for at least 30 s in a distance of 100 μm. (MOV 798 kb)

    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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    Audiovisual . 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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    Audiovisual . 2016
    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
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      Audiovisual . 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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      Audiovisual . 2016
      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/
    Authors: Veitschegger, Kristof;

    Abstract Background The evolution of larger brain volumes relative to body size in Mammalia is the subject of an extensive amount of research. Early on palaeontologists were interested in the brain of cave bears, Ursus spelaeus, and described its morphology and size. However, until now, it was not possible to compare the absolute or relative brain size in a phylogenetic context due to the lack of an established phylogeny, comparative material, and phylogenetic comparative methods. In recent years, many tools for comparing traits within phylogenies were developed and the phylogenetic position of cave bears was resolved based on nuclear as well as mtDNA. Results Cave bears exhibit significantly lower encephalization compared to their contemporary relatives and intraspecific brain mass variation remained rather small. Encephalization was correlated with the combined dormancy-diet score. Body size evolution was a main driver in the degree of encephalization in cave bears as it increased in a much higher pace than brain size. In Ursus spelaeus, brain and body size increase over time albeit differently paced. This rate pattern is different in the highest encephalized bear species within the dataset, Ursus malayanus. The brain size in this species increased while body size heavily decreased compared to its ancestral stage. Conclusions Early on in the evolution of cave bears encephalization decreased making it one of the least encephalized bear species compared to extant and extinct members of Ursidae. The results give reason to suspect that as herbivorous animals, cave bears might have exhibited a physiological buffer strategy to survive the strong seasonality of their environment. Thus, brain size was probably affected by the negative trade-off with adipose tissue as well as diet. The decrease of relative brain size in the herbivorous Ursus spelaeus is the result of a considerable increase in body size possibly in combination with environmental conditions forcing them to rest during winters.

    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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    Collection . 2017
    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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    Collection . 2017
    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
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      Collection . 2017
      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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      Collection . 2017
      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/
    Authors: D. Louis Collins; Devenyi, Gabriel Allan; Raihaan Patel; Tullo, Stephanie; +2 Authors

    Legend for label values of final atlas labels for the striatum, globus pallidus, and thalamus.

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    Dataset . 2018
    License: CC 0
    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
    License: CC 0
    Data sources: Datacite
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      Dataset . 2018
      License: CC 0
      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
      License: CC 0
      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/
    Authors: Chiang, Jason; Diaz, Alexander K.; Makepeace, Lydia; Li, Xiaoyu; +11 Authors

    Additional file 1: Figure S1. Heatmap of unsupervised cluster analysis using the 5000 most variable probes.

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    Image . 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/
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    Image . 2020
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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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      Image . 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/
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      Image . 2020
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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: Noristani, Harun; Sabourin, Jean; Boukhaddaoui, Hassan; Chan-Seng, Emilie; +2 Authors

    Specific eGFP expression of astroglial cells in Aldh1l1-EGFP mice. Confocal micrographs showing astrocytic eGFP expression in Aldh1l1-EGFP mice that was confirmed using GFAP immunostaining (A–C). Fluorescent micrographs showing lack of eGFP expression in microglia/macrophages (Iba1, D&E), oligodendrocytes (MBP, F) and neuronal (MAP2, G) populations in Aldh1l1-EGFP mice. Scale bars (A, F&G): 50 μm, (B&C): 10 μm, (D): 30 μm, (E): 15 μm. Representative flow cytometry analysis dot plot displaying control (H) and eGFP-expressing astrocytic profiles from un-injured (I) as well as after injury (J). Surrounded areas, designed as “P4”, correspond to the eGFP-expressing astrocytes. The X-axis represents fluorescent intensity and the Y axis cell size. RNA quality isolated from FACSed astrocytes (K). (TIF 20779 kb)

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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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    Data sources: Datacite
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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/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: Parker, Aimée; Romano, Stefano; Ansorge, Rebecca; Aboelnour, Asmaa; +11 Authors

    Abstract Background Altered intestinal microbiota composition in later life is associated with inflammaging, declining tissue function, and increased susceptibility to age-associated chronic diseases, including neurodegenerative dementias. Here, we tested the hypothesis that manipulating the intestinal microbiota influences the development of major comorbidities associated with aging and, in particular, inflammation affecting the brain and retina. Methods Using fecal microbiota transplantation, we exchanged the intestinal microbiota of young (3 months), old (18 months), and aged (24 months) mice. Whole metagenomic shotgun sequencing and metabolomics were used to develop a custom analysis workflow, to analyze the changes in gut microbiota composition and metabolic potential. Effects of age and microbiota transfer on the gut barrier, retina, and brain were assessed using protein assays, immunohistology, and behavioral testing. Results We show that microbiota composition profiles and key species enriched in young or aged mice are successfully transferred by FMT between young and aged mice and that FMT modulates resulting metabolic pathway profiles. The transfer of aged donor microbiota into young mice accelerates age-associated central nervous system (CNS) inflammation, retinal inflammation, and cytokine signaling and promotes loss of key functional protein in the eye, effects which are coincident with increased intestinal barrier permeability. Conversely, these detrimental effects can be reversed by the transfer of young donor microbiota. Conclusions These findings demonstrate that the aging gut microbiota drives detrimental changes in the gut–brain and gut–retina axes suggesting that microbial modulation may be of therapeutic benefit in preventing inflammation-related tissue decline in later life. Video abstract Graphical abstract

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    Authors: Li, Cheng-Yu; Hofmann, Hans A.; Harris, Melissa L.; Earley, Ryan L.;

    Understanding how the brain processes social information and generates adaptive behavioural responses is a major goal in neuroscience. We examined behaviour and neural activity patterns in socially relevant brain nuclei of hermaphroditic mangrove rivulus fish (Kryptolebias marmoratus) provided with different types of social stimuli: stationary model opponent, regular mirror, non-reversing mirror and live opponent. We found that: (i) individuals faced with a regular mirror were less willing to interact with, delivered fewer attacks towards and switched their orientation relative to the opponent more frequently than fish exposed to a non-reversing mirror image or live opponent; (ii) fighting with a regular mirror image caused higher expression of immediate-early genes (IEGs: egr-1 and c-Fos) in the teleost homologues of the basolateral amygdala and hippocampus, but lower IEG expression in the preoptic area, than fighting with a non-reversing mirror image or live opponent; (iii) stationary models elicited the least behavioural and IEG responses among the four stimuli; and (iv) the non-reversing mirror image and live opponent drove similar behavioural and neurobiological responses. These results suggest that the various stimuli provide different types of information related to conspecific recognition in the context of aggressive contests, which ultimately drive different neurobiological responses.

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    Authors: Roberto Toro;

    These are author versions of the figures of the article "Functional coactivation map of the human brain", https://doi.org/10.1093/cercor/bhn014 Fig. 1 (fig1v2.tif) Characterization of the experiments used in the coactivation map. Distribution of the different cognitive domains represented by the experiments after the BrainMap classification (A). Histogram of the number of locations per experiment (B). Experiments reported on average 8 locations, and a decreasing number of experiments reported large numbers of locations. Fig. 2 (fig2v2.tif) Reproducibility of the coactivation map. Pairs of partial coactivation maps computed from disjoint random subsets of the total database of experiments were progressively more similar as the number of experiments increased. The plot shows the distribution of the correlation coefficient for 20 pairs of partial coactivation maps computed from independent sets of 500, 700, 900, 1100, 1300, 1500, and 1700 experiments. Fig. 3 (fig-symm.tif) Symmetric interhemispheric coactivations. Coactivations of regions in the left hemisphere included most of the time the symmetric region in the right hemisphere, and vice versa. The figure shows 3-dimensional reconstructions (A, B) and stereotaxic slices of 4 networks corresponding to 4 seed-voxels in the axial plane z = 28 (C), and 4 networks in the coronal plane y = −6 (D). The network clusters are isosurfaces for P = 0.01, and the location of the seed-voxels is indicated by white squares in the stereotaxic slices. Fig. 4 (fig-ipsl.tif) Fronto-parietal “attention” network. Three-dimensional reconstruction and axial (z = 48) and para-sagittal (x = 30) stereotaxic slices of the network recovered with a seed-voxel at the left intraparietal sulcus (IPS, x = −26, y = −58, z = 48). It includes the supplementary motor area (SMA) and preSMA, left and right anterior insula (aIns), frontal eye fields (FEF), dorsolateral prefrontal cortex (DLPFC), inferior precentral sulcus (iPCS), ventral occipital cortex (vOC), inferior parietal lobule (iPL), and the ventral IPS (vIPS). The network clusters are isosurfaces for P = 0.01, and the location of the seed-voxel is indicated in the axial slice by a white square. Fig. 5 (fig-acc.tif) Cingulo-parietal “resting state” network. Three-dimensional reconstructions and sagittal stereotaxic slice (x = −2) of the network recovered with a seed-voxel at the anterior cingulate cortex (aCC, x = −2, y = 46, z = −4). It includes the posterior cingulate cortex (pCC), nucleus accumbens (NA), lateral parietal cortex (LPC), inferior temporal cortex (iTC), and the superior frontal cortex (SFC). The network clusters are isosurfaces for P = 0.01 (strong red), and P = 0.5 (in transparency). The location of the seed-voxel is indicated by a white square in the sagittal slice. Fig. 6 (fig-motor.tif) Cortico-diencephalo-cerebellar “motor” network. Three-dimensional reconstructions and coronal (y = −26) and para-sagittal (x = −34) stereotaxic slices of the network recovered with a seed-voxel at the dorsal part of the left central sulcus (CS, x = −34, y = −26, z = 60). The network includes the right central sulcus, caudal cingulate motor area (CMA), ipsilateral putamen (Pu), thalamus (Th), and left cerebellum (Cb-L), and the contralateral anterior lobe of the cerebellum (aCb). The network clusters are isosurfaces for P = 0.01, and the seed-voxel is indicated by white squares in the coronal and sagittal slices.

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    Authors: Houwing, Maite E.; Grohssteiner, Rowena L.; Dremmen, Marjolein H. G.; Ferdows Atiq; +6 Authors

    Abstract Background and purpose Silent cerebral infarcts (SCIs) are the most common neurological complication in children and adults with sickle cell disease (SCD). In this systematic review, we provide an overview of studies that have detected SCIs in patients with SCD by cerebral magnetic resonance imaging (MRI). We focus on the frequency of SCIs, the risk factors involved in their development and their clinical consequences. Methods The databases of Embase, MEDLINE ALL via Ovid, Web of Science Core Collection, Cochrane Central Register of Trials via Wiley and Google Scholar were searched from inception to June 1, 2019. Results The search yielded 651 results of which 69 studies met the eligibility criteria. The prevalence of SCIs in patients with SCD ranges from 5.6 to 80.6% with most studies reported in the 20 to 50% range. The pooled prevalence of SCIs in HbSS and HbSβ0 SCD patients is 29.5%. SCIs occur more often in patients with the HbSS and HbSβ0 genotype in comparison with other SCD genotypes, as SCIs are found in 9.2% of HbSC and HbSβ+ patients. Control subjects showed a mean pooled prevalence of SCIs of 9.8%. Data from included studies showed a statistically significant association between increasing mean age of the study population and mean SCI prevalence. Thirty-three studies examined the risk factors for SCIs. The majority of the risk factors show no clear association with prevalence, since more or less equal numbers of studies give evidence for and against the causal association. Conclusions This systematic review and meta-analysis shows SCIs are common in patients with SCD. No clear risk factors for their development were identified. Larger, prospective and controlled clinical, neuropsychological and neuroimaging studies are needed to understand how SCD and SCIs affect cognition.

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    A total of 668 single units were recorded in the mouse periaqueductal gray (PAG) and adjacent deep mesencephalic nucleus (DpMe) in order to determine their role in the switching of sleep-wake states, i.e. wakefulness (W), slow-wave sleep (SWS), and paradoxical (or rapid eye movement) sleep (PS) in general, and, in particular, to determine whether PS-on and PS-off neurons involved in PS state switching are present in these structures and to identify neuronal substrates for the SWS-PS switching mediated by DpMe neurons. Both structures were found to contain similar percentages of W/PS-active neurons, which discharge at a higher rate during W and PS than during SWS, while W-active neurons, which discharge maximally during W, were found mainly in the PAG. Both also contained similar percentages of SWS/PS-active neurons, which discharge at higher rates during SWS and PS than during W, and PS-active neurons, which discharge maximally during PS, while SWS-active neurons, which discharge maximally during SWS were found almost exclusively in the PAG. Both structures contained virtually no PS-on or PS-off neurons, which, respectively, discharge or cease firing selectively and tonically just prior to, and during, PS. Unlike the PAG, the DpMe contained many SWS/PS-on neurons, which discharge selectively at high rates during SWS and PS, but show a decrease in discharge rate at the transition from SWS to PS. Analysis of discharge profiles and trends in spike activity at the state transitions strongly suggests that PAG and DpMe neurons play an important role in the W-SWS, SWS-PS, and/or PS-W switches.

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    Authors: Fengjiao Wu; Zou, Qiang; Xiaodan Ding; Dongyan Shi; +4 Authors

    Time-lapse recordings of the intravascular rolling and adhesion of leukocytes in WT C57BL/6J mice after intraventricular LPS injection (4 h). Rolling leukocytes were defined as those cells moving at a velocity less than that of erythrocytes. Cells were considered adherent if they remained stationary for at least 30 s in a distance of 100 μm. (MOV 798 kb)

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    Audiovisual . 2016
    License: CC BY
    Data sources: Datacite
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    Audiovisual . 2016
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      Audiovisual . 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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      Audiovisual . 2016
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    Authors: Veitschegger, Kristof;

    Abstract Background The evolution of larger brain volumes relative to body size in Mammalia is the subject of an extensive amount of research. Early on palaeontologists were interested in the brain of cave bears, Ursus spelaeus, and described its morphology and size. However, until now, it was not possible to compare the absolute or relative brain size in a phylogenetic context due to the lack of an established phylogeny, comparative material, and phylogenetic comparative methods. In recent years, many tools for comparing traits within phylogenies were developed and the phylogenetic position of cave bears was resolved based on nuclear as well as mtDNA. Results Cave bears exhibit significantly lower encephalization compared to their contemporary relatives and intraspecific brain mass variation remained rather small. Encephalization was correlated with the combined dormancy-diet score. Body size evolution was a main driver in the degree of encephalization in cave bears as it increased in a much higher pace than brain size. In Ursus spelaeus, brain and body size increase over time albeit differently paced. This rate pattern is different in the highest encephalized bear species within the dataset, Ursus malayanus. The brain size in this species increased while body size heavily decreased compared to its ancestral stage. Conclusions Early on in the evolution of cave bears encephalization decreased making it one of the least encephalized bear species compared to extant and extinct members of Ursidae. The results give reason to suspect that as herbivorous animals, cave bears might have exhibited a physiological buffer strategy to survive the strong seasonality of their environment. Thus, brain size was probably affected by the negative trade-off with adipose tissue as well as diet. The decrease of relative brain size in the herbivorous Ursus spelaeus is the result of a considerable increase in body size possibly in combination with environmental conditions forcing them to rest during winters.

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    Collection . 2017
    License: CC BY
    Data sources: Datacite
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    Collection . 2017
    License: CC BY
    Data sources: Datacite
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      Collection . 2017
      License: CC BY
      Data sources: Datacite
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      Collection . 2017
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    Authors: D. Louis Collins; Devenyi, Gabriel Allan; Raihaan Patel; Tullo, Stephanie; +2 Authors

    Legend for label values of final atlas labels for the striatum, globus pallidus, and thalamus.

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    Dataset . 2018
    License: CC 0
    Data sources: Datacite
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    Dataset . 2018
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      Dataset . 2018
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      Dataset . 2018
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