Current Biology

ISSN: 0960-9822
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Datasets associated with articles published in Current Biology
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  • The full description of this data-set will be provided shortly.
    Data Types:
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    • Document
  • This is the raw dataset of all the figures described in the manuscript. The research hypothesis is to study the protective effects of the C. elegans natural microbiota against pathogen infection. The raw data includes the data from Worm Population Growth experiments and Worm survival experiments, which show the microbiota mediated protective effects on the worms. The raw data also includes in vitro disc diffusion experiments, which show the antagonistic properties of the microbiota isolates against the pathogen. The raw data also includes the "Smurf" assay data, which shows the effects of the microbiota isolates on the worm pathophysiology. The data also includes the detailed statistical analyses used for ever experiment.
    Data Types:
    • Tabular Data
    • Dataset
  • spike analysis, spike processing code, creating sound stimuli
    Data Types:
    • Software/Code
    • Dataset
  • Individual mean angles and inversions for each experiment and condition. NA : This information is Not Applicable to the current experiment
    Data Types:
    • Tabular Data
    • Dataset
  • Supplementary data for manuscript "Female social feedback reveals non-imitative mechanisms of vocal learning in zebra finches". Complete data set of all subjects’ behavioral measures across trials, averages across development, and final song learning measures. ‘MaleNum’ refers to the ID number of the individual subject. ‘Condition’ refers to experimental condition, either Contingent (Cont) or Yoked. ‘Group’ indicates the cohort to which each male belongs, with each group having one Contingent and one Yoked genetic brother. ‘T’ indicates trial number (5, 10, 15, 20, or 25) with proceeding labels referring to behaviors during that trial’s experimental session, and ‘Avg’ to the averaged value across all trials. ‘SongDuration’ refers to time spent singing, in seconds. ‘xCount’ (e.g. SongCount, FluffCount) is number of observations of the respective behavior during the session. ‘ContVidCount’ is number of videos played contingent on the song of CC birds, while ‘RemVidCount’ is number of times a video was played after 5 minutes without song. ‘PerchDuration’ refers to amount of time, in seconds, subjects spent on the perch nearest to the video monitor. All fields ending with ‘Prop’ indicate the proportion of one behavior to another (e.g. FluffToSongProp refers to the number of fluff-ups per song bout). ‘xAfterVidStart’ and ‘xAfterVidEnd’ refers to the number of times behavior ‘x’ occurred within a second of the stimulus video being triggered and within a second of the video playback ending, respectively. ‘FluffedAfter’ refers to number of times on or more fluff-ups occurred following an event, while ‘TotalFluffsAfter’ is a count of the total number of fluffs following the event. ‘AccCont’ refers to number of times a video played, by chance, following the song of a Yoked subject (‘accidental contingency’), while ‘NonCon’ is number of non-contingent videos viewed by Yoked subjects. ‘TotalFluffsWipes’ is the sum of fluff-ups and beak wipes in a given trial. ‘ALLContProp’ is the overall proportion of contingent video playbacks to all songs.
    Data Types:
    • Tabular Data
    • Dataset
  • These are the original morphological data resulted from X-ray micro-computed tomographical analysis of a delicately preserved arthropod fossil (specimen number: YKLP 16201) from the early Cambrian Chengjiang biota. The related manuscript will be published in Current Biology. The specimen is housed in Yunnan Key Laboratory for Palaeobiology, Yunnan University, PRC.
    Data Types:
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    • File Set
  • In each of five subject folders: 1. *_PixelBehMI_nuns_not.mat • “Ipixe_beh” stores the pixel-wise MI value . • “TH” is the statistic threshold for the pixel-wise MI (FWER p . • “TH” is the statistical threshold for the pixel-wise MI (FWER p < 0.001, one-tailed). 3. *_FeatureMegMI.mat • “Ifeat” is the 3D time-by-feature-by-voxel MI matrix. • “TH” is the statistical threshold (FWER p < 0.05, one-tailed). 4. *_BrainFeatures.mat • ‘nuns_feat’: Indices of diagnostic brain features for the perception of “the nuns”. • ‘volt_feat’.: Indices of diagnostic brain features for the perception of “Voltaire”. • ‘nondiag_feat’: Indices of nondiagnostic brain features. 5. *_FullICA_LP_B_NMF_*.PDF • Brain features obtained from the NMF analysis. 6. *_Redundancy_nuns_volt_not.mat • “Ired” is the 3D redundancy matrix (time point x feature × voxel), using all trials. • “TH” is the statistical threshold (FWER p < 0.05, one-tailed). • “time” stores the post-stimulus time (in seconds) for each time point. 7. *_Redundancy_nuns_not.mat • “Ired” is the 3D redundancy matrix (time point x feature × voxel), using “the nuns” and “don’t know” trials. • “TH” is the statistical threshold (FWER p < 0.05, one-tailed). 8. *_Redundancy_volt_not.mat • “Ired” is the 3D redundancy matrix (time point x feature × voxel), using “Voltaire” and “don’t know” trials. • “TH” is the statistical threshold (FWER p < 0.05, one-tailed).
    Data Types:
    • Software/Code
    • Dataset
    • Document
  • Meerkat (Suricata suricatta) sunning call times. The calls are marked as "focal" - recorded recognised individual and "background" - sunning calls emitted by neighbouring conspecifics. The data specifies meerkat social group, focal ID and timing of the calls within the recording.
    Data Types:
    • Tabular Data
    • Dataset
  • The matlab file 'PERCEIVED SURFACE SHADING.m' generates the images used in Experiment 1 and 2 and Experiment 2 data.
    Data Types:
    • Dataset
    • File Set
  • In large limbs, changing motor neuron activity typically controls within-movement velocity. For example, sequential agonist-antagonist-agonist motor neuron firing typically underlies the slowing often present at the end of human reaches. In physiological movements of large limbs, antagonistic muscle passive torque is generally negligible. In small limbs, alternatively, passive torques can determine limb rest position, generate restoring movements to it, and decrease agonist-generated movement amplitude and velocity maxima. These observations suggest that in small limbs passive forces might also control velocity changes within movements. We investigated this issue in stick insect middle leg femur-tibia (FT) joint. During swing, the FT joint extensor muscle actively shortens and the flexor muscle passively lengthens. As in human reaching, after its initial acceleration, FT joint velocity continuously decreases. We measured flexor passive forces during imposed stretches spanning the ranges of FT joint angles, angular velocities, and movement amplitudes present in leg swings. The viscoelastic “transient” passive force that occurs during and soon after stretch depended on all three variables, and could be tens of times larger than the “steady-state” passive force commonly measured long after stretch end. We combined these data, the flexor and extensor moment arms, and an existing extensor model to simulate FT joint swing. To measure only passive (flexor) muscle-dependent effects, we used constant extensor activations in these simulations. In simulations using data from ten flexor muscles, flexor passive torque could always produce swings with, after swing initiation, continuously decreasing velocities. Antagonist muscle passive torques alone can thus control within-movement velocity.
    Data Types:
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    • Document
    • File Set
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