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Electrophysiological evidence suggested primarily the involvement of area MT in depth cue integration in macaques, as opposed to human imaging data pinpointing area V3B/KO. To clarify this conundrum, we decoded monkey fMRI responses evoked by stimuli signaling near or far depths defined by binocular disparity, relative motion and their combination, and we compared results with those from an identical experiment previously performed in humans.Responses in macaque area MT are more discriminable when two cues concurrently signal depth, and information provided by one cue is diagnostic of depth indicated by the other. This suggests that monkey area MT computes fusion of disparity and motion depth signals, exactly as shown for human area V3B/KO. Hence, these data reconcile previously reported discrepancies between depth processing in human and monkey by showing the involvement of the dorsal stream in depth cue integration using the same technique, despite the engagement of different regions. data describing fig 1-8 and sfig 1-12data.zip

Perception adapts to mismatching multisensory information, both when different cues appear simultaneously and when they appear sequentially. While both multisensory integration and adaptive trial-by-trial recalibration are central for behavior, it remains unknown whether they are mechanistically linked and arise from a common neural substrate. To relate the neural underpinnings of sensory integration and recalibration, we measured whole-brain magnetoencephalography while human participants performed an audio-visual ventriloquist task. Using single-trial multivariate analysis, we localized the perceptually-relevant encoding of multisensory information within and between trials. While we found neural signatures of multisensory integration within temporal and parietal regions, only medial superior parietal activity encoded past and current sensory information and mediated the perceptual recalibration within and between trials. These results highlight a common neural substrate of sensory integration and perceptual recalibration, and reveal a role of medial parietal regions in linking present and previous multisensory evidence to guide adaptive behavior. PARK_KAYSER_RecalMEG_2019Please see README file.

Dogs were present in the Americas prior to the arrival of European colonists, but the origin and fate of these pre-contact dogs are largely unknown. We sequenced 71 mitochondrial and seven nuclear genomes from ancient North American and Siberian dogs spanning ~9,000 years. Our analysis indicates that American dogs were not domesticated from North American wolves. Instead, American dogs form a monophyletic lineage that likely originated in Siberia and dispersed into the Americas alongside people. After the arrival of Europeans, native American dogs almost completely disappeared, leaving a minimal genetic legacy in modern dog populations. Remarkably, the closest detectable extant lineage to pre-contact American dogs is the canine transmissible venereal tumor, a contagious cancer clone derived from an individual dog that lived up to 8,000 years ago. Mitochondrial DNA FASTA fileFASTA file containing 1166 dog mtDNA genomes used in this studyfull_mtDNA_alignment.fastaNEXUS treeMaximum likelihood tree (RAxML) of 1166 dogs mtDNA genomes used in this studyfull_mtDNA_alignment.treExcel sheetPublication source of the 1166 mtDNA genomes used in this studyfull_mtDNA_alignment.xlsxPlink (bed) fileContains genotype for dogs 54 dogsfull_data.bedPlink file (bim)Contains genotype for 54 dogsfull_data.bimPlink file (fam)Contains genotype for 54 dogsfull_data.famNJ tree in Figure 2bNJ tree in Figure 2b (see Table S2 for more info)Figure_b.treNexus fileNexus file used for producing Figure S12 (MKV model in MrBayes)Binary_char_MKV.nexNEXUS treeBayesian tree in Figure S12 (see Table S2 for more info)Figure_S12.tre

Mitochondrial and Y-chromosomal sequences of orangutans associated with the following publication: Nater A, Mattle-Greminger MP, Nurcahyo A, et al. (2017) Morphometric, behavioral, and genomic evidence for a new orangutan species. Current Biology. http://dx.doi.org/10.1016/j.cub.2017.09.047 For details on samples and methods, please see source publication. Additional Supporting Information are available from MorphoBank at http://morphobank.org/permalink/?P2591.

In previous papers, we introduced a normative scheme for scene construction and epistemic (visual) searches based upon active inference. This scheme provides a principled account of how people decide where to look, when categorising a visual scene based on its contents. In this paper, we use active inference to explain the visual searches of normal human subjects; enabling us to answer some key questions about visual foraging and salience attribution. First, we asked whether there is any evidence for 'epistemic foraging'; i.e. exploration that resolves uncertainty about a scene. In brief, we used Bayesian model comparison to compare Markov decision process (MDP) models of scan-paths that did - and did not - contain the epistemic, uncertainty-resolving imperatives for action selection. In the course of this model comparison, we discovered that it was necessary to include non-epistemic (heuristic) policies to explain observed behaviour (e.g., a reading-like strategy that involved scanning from left to right). Despite this use of heuristic policies, model comparison showed that there is substantial evidence for epistemic foraging in the visual exploration of even simple scenes. Second, we compared MDP models that did - and did not - allow for changes in prior expectations over successive blocks of the visual search paradigm. We found that implicit prior beliefs about the speed and accuracy of visual searches changed systematically with experience. Finally, we characterised intersubject variability in terms of subject-specific prior beliefs. Specifically, we used canonical correlation analysis to see if there were any mixtures of prior expectations that could predict between-subject differences in performance; thereby establishing a quantitative link between different behavioural phenotypes and Bayesian belief updating. We demonstrated that better scene categorisation performance is consistently associated with lower reliance on heuristics; i.e., a greater use of a generative model of the scene to direct its exploration. Scan-path dataThis file contains the scan-paths of the subjects that performed the "Scene construction task" described in the paper "Human visual exploration reduces uncertainty about the sensed world". There are some additional files that can be used to regenerate the figures and results in this paper.

Background: Individuals living in malaria-endemic regions develop naturally acquired immunity against severe malarial disease, but it is unclear whether immunity that affects the establishment of infections develops following continuous natural exposure. Methods: We cleared schoolchildren in Burkina Faso of possible sub-patent infections and examined them weekly for incident infections by PCR. Plasma samples collected at enrolment were used to quantify antibodies to the pre-eryhrocytic-stage antigens circumsporozoite protein (CSP) and liver stage antigen. Sporozoite gliding inhibition by naturally acquired antibodies was assessed using Plasmodium falciparum NF54 sporozoites; hepatocyte invasion was assessed using the human HC-04 hepatoma cell line and NF54 sporozoites. The associations between these functional pre-erythrocytic immunity phenotypes and time to PCR-detected infection were studied. Results: A total of 51 children were monitored; the median time to first detection of infection by PCR or development of clinical symptoms was 28 days. Anti-CSP antibody titres showed a strong positive association with sporozoite gliding motility inhibition (P<0.0001, Spearman’s ρ=0.76). In vitro hepatocyte invasion was inhibited by naturally acquired antibodies (median invasion inhibition, 19.4% [IQR 15.2-40.9%]), and there was a positive correlation between gliding and invasion inhibition (P=0.02, Spearman’s ρ=0.60). Survival analysis indicated longer time to infection in individuals displaying higher-than-median sporozoite gliding inhibition activity (P=0.01). Conclusions: In summary, functional antibodies against the pre-erythrocytic stages of malaria infection are acquired in children who are repeatedly exposed to Plasmodium parasites. This immune response does not prevent them from becoming infected during a malaria transmission season, but might delay the appearance of blood stage parasitaemia and consequently needs to be considered in the evaluation of malaria vaccines. Sensitivity AnalysisThis file describes additional survival analyses that show that functional responses against pre-erythrocytic stages are also associated with infection risk when different parasite density thresholds are used to define infection.Sensitivity_Analysis.docxLegends of supplementary figuresThe file contains the legends of supplementary figures S1 to S5.Legends_v2.docxFigure S1Correlation analyses of naturally acquired sporozoite-specific IgG and IgM antibodiesFigure_S1.docxFigure S2Antibody specificity and in vitro gliding inhibition by naturally acquired antibodies.Revised_Figure_S2.docxFigure S3Inhibition of in vitro sporozoite invasion of hepatocytes by antibodies from children in Burkina Faso.Revised_Figure_S3.docxFigure S4CSP antibody levels versus immune responses against asexual stage antigens.New_Figure_S4.docxFigure S5Distribution of immune phenotypes.Figure_S5.docxData used in survival analysisThis file contains the data used in the survival analysis. There are 6 variables and 51 observations, corresponding to the 51 study participants included in this analysis. The variable 'Delay' represents the time to infection detection. The variable 'Infection' has value 1 if the study participant had infection detected during follow-up. The other variables represent results of immunological assays.Data.xlsxELISA and sporozoite gliding inhibition dataThis file contains individual-level data on antibody titers against circumsporozoite protein (CSP), Liver stage antigen-1 (LSA-1) and asexual parasite lysate as well as functional data on sporozoite gliding inhibition

chicken.all_samples.galGal3.tpm.refgene.oscData for the analysis of the chicken chromosome Z. FANTOM5 chicken libraries consisted of 25 CAGE libraries including: chicken aortic smooth muscles, hepatocytes, mesenchymal stem cells, leg buds, wing buds, embryo extra-embryonic tissue (day 7 and day 15), and whole body developmental time course (from 5 hours 30 minutes to 20 days). The number of available datapoints to which TPM was normalized was limited by the number of annotated chicken RefSeq transcripts (which was approximately six times smaller than human, N = 4,426 on autosomes, and N = 241 on chromosome Z). Consequently, the cutoff for a gene to be classified as “on” was adjusted six times higher to 60 TPM.human.primary_cell.hCAGE.hg19.tpm.refgene.oscThe FANTOM5 dataset for human primary cells.human.cell_line.hCAGE.hg19.tpm.refgene.oscThe FANTOM5 dataset for human cancer cell-lines.human.tissue.hCAGE.hg19.tpm.refgene.oscThe FANTOM5 dataset for human tissue. CAGE tags were mapped to RefSeq transcripts +/-500 base pairs (bps) from their TSSes and normalized to tags per million (TPM), as previously described [37,45]. The signal of ten TPM was chosen as the cutoff for a gene to be classified as “on” (this cutoff was accepted as the standard for human data throughout the consortium). FANTOM5 is the most comprehensive expression dataset ever generated, including 952 human and 396 mouse tissues, primary cells and cancer cell-lines. FANTOM5 is based on cap analysis of gene expression (CAGE) a unique technology that characterizes TSSes across the entire genome in an unbiased fashion and at a single-base resolution level [21]. CAGE automatically sums expression levels of all transcripts beginning at a given transcription start site.raw_Z_Exp_Anc_LData for Fig 2 "The comparison of change in gene expression (Z) since the human-Chimpanzee common ancestor for five somatic tissues."SUPPLEMENTARY TABLESData in Table S3 underlies Figure 4. Data in Table S7 partially underlies Fig 1. Data in Tables S4 underlies Fig 3. Data in Tables S10-12 underlies Fig S1.data for Fig1R environment containing data underlying Fig1. The environment contains the following variables sorted identically as the gene list in refSeqs: chromosome (chromosomal location), chromosome_short (location on autosomes,chrX, or chrY?), data_matrix (F5 data matrix in TPM for human tissues)‚ MAX (maximal expression for each RefSeq)‚ max (maximal expression for each tissue)‚ strata_classification (strata classification for genes on chromosome X)‚ refSeqs_2entrezIDs (entrez ids mapped to refseqs)‚ boe (the breadth of expression)env_fig1GC-contents data for for Fig S6 and S7This R environment contains GC-contents data for either proximal promoters or isochore around the TSS (marked as big). The data is calculated for either masked or unmasked genome seqeuence.env_gc_contentsdata for Fig S3numbers of ENCODE transcription factor binding sites mapped to TSSes of RefSeq genes in symmetrical windows of different sizes (from 250 to 20000 bps) and depending on ENCODE quality cut-off (strict or all).FigS3_data.txtdata underlying Fig S8Breadth of expression and maximal expression is compared in three groups of observations: (1) autosomal paralogs of X-linked genes, (2) other autosomal paralogs matched by age, (3) X-linked paralogs. Newly formed paralogs are defined as those mapped by phylogenetic timing to taxa Theria or younger. Pre-existing duplications are defined as those descending from duplication notes mapped by phylogenetic timing to taxa Amniota or older.FigS8_data.txtdata underlying Fig7Fig7_data.txtTreeFam data for timing of gene duplications in R environmentsThese files are R environments. Use load() to load them into your R session! You ls() to view contents. You may use attach() syntax to load the namespace or access data members of the environment using the "$" reference operator. There is no warranty for this softwareenv_duplicator_baseAdditional TreeFam gene duplication data with duplication timingenv_duplicator_vectors X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X’s gene content, gene expression, and evolution.

Original files for the microscopy images in Figures 6 and 7