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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: Ikkai, Akiko; Dandekar, Sangita; Curtis, Clayton E.;

    Attending to a task-relevant location changes how neural activity oscillates in the alpha band (8–13Hz) in posterior visual cortical areas. However, a clear understanding of the relationships between top-down attention, changes in alpha oscillations in visual cortex, and attention performance are still poorly understood. Here, we tested the degree to which the posterior alpha power tracked the locus of attention, the distribution of attention, and how well the topography of alpha could predict the locus of attention. We recorded magnetoencephalographic (MEG) data while subjects performed an attention demanding visual discrimination task that dissociated the direction of attention from the direction of a saccade to indicate choice. On some trials, an endogenous cue predicted the target’s location, while on others it contained no spatial information. When the target’s location was cued, alpha power decreased in sensors over occipital cortex contralateral to the attended visual field. When the cue did not predict the target’s location, alpha power again decreased in sensors over occipital cortex, but bilaterally, and increased in sensors over frontal cortex. Thus, the distribution and the topography of alpha reliably indicated the locus of covert attention. Together, these results suggest that alpha synchronization reflects changes in the excitability of populations of neurons whose receptive fields match the locus of attention. This is consistent with the hypothesis that alpha oscillations reflect the neural mechanisms by which top-down control of attention biases information processing and modulate the activity of neurons in visual cortex. IkkaiDataUpload

    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/ DRYAD; ZENODO; NARCI...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/
    DRYAD; ZENODO; NARCIS
    Dataset . 2017
    License: CC 0
    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/
    DANS-EASY
    Dataset . 2016
    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/ DRYAD; ZENODO; NARCI...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/
      DRYAD; ZENODO; NARCIS
      Dataset . 2017
      License: CC 0
      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/
      DANS-EASY
      Dataset . 2016
      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: Du, Andrew; Zipkin, Andrew M.; Hatala, Kevin G.; Renner, Elizabeth; +4 Authors

    A large brain is a defining feature of modern humans, yet there is no consensus regarding the patterns, rates, and processes involved in hominin brain size evolution. We use a reliable proxy for brain size in fossils, endocranial volume (ECV), to better understand how brain size evolved at both clade- and lineage-level scales. For the hominin clade overall, the dominant signal is consistent with a gradual increase in brain size. This gradual trend appears to have been generated primarily by processes operating within hypothesized lineages – 64% or 88% depending on whether one uses a more or less speciose taxonomy, respectively. These processes were supplemented by the appearance in the fossil record of larger-brained Homo species and the subsequent disappearance of smaller-brained Australopithecus and Paranthropus taxa. When the estimated rate of within-lineage ECV increase is compared to an exponential model that operationalizes generation-scale evolutionary processes, it suggests that the observed data were the result of episodes of directional selection interspersed with periods of stasis and/or drift; all of this occurs on too fine a time scale to be resolved by the current human fossil record, thus producing apparent gradual trends within lineages. Our findings provide a quantitative basis for developing and testing scale-explicit hypotheses about the factors that led brain size to increase during hominin evolution. Appendix S1Supplementary methods, results, figures, and tables for the analysis.Du et al 2018 revised Appendix S1 R2_ESM_FINAL changes accepted.docxTable S1Excel spreadsheet with the raw data used for all analyses. Each row is a separate specimen along with its ID. Columns include the “lumper’s” and “splitter’s” taxonomy used in the random effects ANOVA to get inter-observer error (“lump.taxon” and “split.taxon”), the less and more speciose lineages used in the lower-taxonomic additive partitioning analyses (“lump.part” and “split.part”), region where each specimen comes from which aided in the allocation of specimens to lineages (“region”), grade for coding points in fig. 2 (“grade”), which specimens were excluded for the damaged specimens sensitivity analysis (“reliab.sens”), ECV replicate measurements from different researchers (“ecv1” to “ecv6”), and the various dates for each specimen (“min.date”, “max.date”, “mean.date”, and “sd.date”) and their respective age error distribution (“date.dist”).ProcB SI ECV dataset FINAL.xlsxR scriptR script for (1) running variance partitioning analyses to get inter-observer endocranial volume (ECV) error, (2) fitting evolutionary mode models to the hominin clade-level ECV data using the R package "paleoTS", (3) calculating R2 and model parameters for the gradualism model, and (4) running the lower taxonomic level additive partitioning analyses.Du et al R script_ESM.txt

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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/
    DANS-EASY
    Dataset . 2018
    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/
    DRYAD; ZENODO; NARCIS
    Dataset . 2018
    License: CC 0
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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/ DANS-EASYarrow_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/
      DANS-EASY
      Dataset . 2018
      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/
      DRYAD; ZENODO; NARCIS
      Dataset . 2018
      License: CC 0
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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: Semple, Bridgette D.; Noble-Haeusslein, Linda J.; Kwon, Yong Jun; Sam, Pingdewinde N.; +12 Authors

    Despite the life-long implications of social and communication dysfunction after pediatric traumatic brain injury, there is a poor understanding of these deficits in terms of their developmental trajectory and underlying mechanisms. In a well-characterized murine model of pediatric brain injury, we recently demonstrated that pronounced deficits in social interactions emerge across maturation to adulthood after injury at postnatal day (p) 21, approximating a toddler-aged child. Extending these findings, we here hypothesized that these social deficits are dependent upon brain maturation at the time of injury, and coincide with abnormal sociosexual behaviors and communication. Age-dependent vulnerability of the developing brain to social deficits was addressed by comparing behavioral and neuroanatomical outcomes in mice injured at either a pediatric age (p21) or during adolescence (p35). Sociosexual behaviors including social investigation and mounting were evaluated in a resident-intruder paradigm at adulthood. These outcomes were complemented by assays of urine scent marking and ultrasonic vocalizations as indices of social communication. We provide evidence of sociosexual deficits after brain injury at p21, which manifest as reduced mounting behavior and scent marking towards an unfamiliar female at adulthood. In contrast, with the exception of the loss of social recognition in a three-chamber social approach task, mice that received TBI at adolescence were remarkably resilient to social deficits at adulthood. Increased emission of ultrasonic vocalizations (USVs) as well as preferential emission of high frequency USVs after injury was dependent upon both the stimulus and prior social experience. Contrary to the hypothesis that changes in white matter volume may underlie social dysfunction, injury at both p21 and p35 resulted in a similar degree of atrophy of the corpus callosum by adulthood. However, loss of hippocampal tissue was greater after p21 compared to p35 injury, suggesting that a longer period of lesion progression or differences in the kinetics of secondary pathogenesis after p21 injury may contribute to observed behavioral differences. Together, these findings indicate vulnerability of the developing brain to social dysfunction, and suggest that a younger age-at-insult results in poorer social and sociosexual outcomes. BodyWeights_dataBody weights of mice used in this study, across time post-injury3chamber_test_dataMice injured at adolescence (postnatal day 35) and tested in the three-chamber social approach task at adulthood. Percentage time spent in each chamber was quantified.CC_volume_dataStereological analyses were performed using StereoInvestigator to determine the volume loss of the corpus callosum at adulthood after injury at either p21 or p35.Res-Intr_test_dataSocial investigation of a novel (male or female) stimulus mouse was quantified as duration spent investigating different regions (e.g. anogenital), during the resident-intruder task.Scent_mark_test_dataGrid squares containing scent marks were quantified during the scent marking test towards a novel female mouse, of sham or TBI (traumatic brain injury) mice at adulthood after injury at p21 or p35.USV_dataUltrasonic vocalizations (USVs) were recorded during encounters of the test mouse (sham or brain-injured) with (1) a novel male, (2) a novel female, or (3) soiled bedding from a novel female. Several parameters including total number of calls, high frequency calls (> 75 kHz) and # calls in bursts were quantified.

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    DANS-EASY
    Dataset . 2014
    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/
    DRYAD; ZENODO; NARCIS
    Dataset . 2015
    License: CC 0
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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/ DANS-EASYarrow_drop_down
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      DANS-EASY
      Dataset . 2014
      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/
      DRYAD; ZENODO; NARCIS
      Dataset . 2015
      License: CC 0
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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: Avery, Michael; Nassi, Jonathan; Reynolds, John;

    Optogenetics has become an important tool for perturbing neural circuitry with unparalleled temporal precision and cell-type specificity. However, direct activation of a specific subpopulation of neurons can rapidly modulate the activity of other neurons within the network and may lead to unexpected and complex downstream effects. Here, we have developed a biologically-constrained computational model that exploits these non-intuitive network responses in order to gain insight into underlying properties of the network. We apply this model to data recorded during optogenetic stimulation in the primary visual cortex of the alert macaque. In these experiments, we found that optogenetic depolarization of excitatory neurons often suppressed neuronal responses, consistent with engagement of normalization circuitry. Our model suggests that the suppression seen in these responses may be mediated by slow excitatory and inhibitory conductance channels. Furthermore, the model predicted that the response of the network to optogenetic perturbation depends critically on the relationship between inherent temporal properties of the network and the temporal properties of the opsin. Consistent with model predictions, stimulation of the C1V1TT opsin, an opsin with a fast time constant (tau=45 ms), caused faster and stronger suppressive effects after laser offset, as compared to stimulation of the slower C1V1T opsin (tau=60ms). This work illustrates how the non-intuitive network responses that result from optogenetic stimulation can be exploited to gain insight regarding network properties that underlie fundamental neuronal computations, such as normalization. This novel hybrid opto-theoretical approach can thus enhance the power of optogenetics to dissect complex neural circuits. Electrophysiological recordings of neurons at Lenti-camkII-C1V1_T infection site141 neurons recorded at the site of infection. The most important aspect of the file is the variable 'everybindata' which is a cell array (size =141). In each cell there is a matrix of size = number of trials x time (in ms) x laser level (5 laser levels). The irradiance values (laser levels) for each recorded neuron are given in variable 'Lenti_continuous_irradiance_vals."baselinelasermod_irr_Lenticontinuous_fullraster_1msbinwidth.matElectrophysiological recordings of neurons at AAV-camkII-C1V1_TT infection site16 neurons recorded at the site of infection. The most important aspect of the file is the variable 'everybindata' which is a cell array (size =16). In each cell there is a matrix of size = number of trials x time (in ms) x laser level (5 laser levels). The irradiance values (laser levels) for each recorded neuron are given in variable 'AAV_continuous_irradiance_vals."baselinelasermod_irr_AAVcont.mat

    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/ DRYAD; ZENODO; NARCI...arrow_drop_down
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    DRYAD; ZENODO; NARCIS
    Dataset . 2018
    License: CC 0
    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/
    DANS-EASY
    Dataset . 2018
    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/ DRYAD; ZENODO; NARCI...arrow_drop_down
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      DRYAD; ZENODO; NARCIS
      Dataset . 2018
      License: CC 0
      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/
      DANS-EASY
      Dataset . 2018
      Data sources: B2FIND
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    Authors: Dang, Xiangnan; Bardhan, Neelkanth M.; Qi, Jifa; Gu, Li; +5 Authors

    Detection of biological features at the cellular level with sufficient sensitivity in complex tissue remains a major challenge. To appreciate this challenge, this would require finding tens to hundreds of cells (a 0.1 mm tumor has ~125 cells), out of ~37 trillion cells in the human body. Near-infrared optical imaging holds promise for high-resolution, deep-tissue imaging, but is limited by autofluorescence and scattering. To date, the maximum reported depth using second-window near-infrared (NIR-II: 1000–1700 nm) fluorophores is 3.2 cm through tissue. Here, we design an NIR-II imaging system, “Detection of Optically Luminescent Probes using Hyperspectral and diffuse Imaging in Near-infrared” (DOLPHIN), that resolves these challenges. DOLPHIN achieves the following: (i) resolution of probes through up to 8 cm of tissue phantom; (ii) identification of spectral and scattering signatures of tissues without a priori knowledge of background or autofluorescence; and (iii) 3D reconstruction of live whole animals. Notably, we demonstrate noninvasive real-time tracking of a 0.1 mm-sized fluorophore through the gastrointestinal tract of a living mouse, which is beyond the detection limit of current imaging modalities. Sample Dataset for HyperSpectral Imaging (HSC data)This is a sample dataset, obtained using Hyperspectral Imaging of a label-free, healthy nude mouse, using the DOLPHIN imaging system, using a wavelength-tunable laser (from 690 - 1040 nm). As a sample, only the 980 nm excitation wavelength data has been provided in this archive. Details of the DOLPHIN imaging system and the image processing techniques used for Hyperspectral Imaging are described in the aforementioned paper.Sample Dataset for HyperDiffuse Imaging (HDC data)This is a sample dataset, obtained using Hyperdiffuse Imaging of the passage of a 100 µm-sized Er-NP cluster probe through the GI tract of a healthy nude mouse, using the DOLPHIN imaging system, using a fixed wavelength of excitation (980 nm laser). Details of the DOLPHIN imaging system and the image processing techniques used for Hyperdiffuse Imaging are described in the aforementioned paper.

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    DRYAD; ZENODO; NARCIS
    Dataset . 2019
    License: CC 0
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    DANS-EASY
    Dataset . 2019
    Data sources: B2FIND
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      DRYAD; ZENODO; NARCIS
      Dataset . 2019
      License: CC 0
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      Dataset . 2019
      Data sources: B2FIND
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    Authors: Rahimpour Jounghani, Ali;

    Timing is an essential component of human actions, and is the foundation of any sort of sequential behavior, from picking up a glass to playing an instrument or dancing. Because of this, our understanding of how we represent time in the brain (i.e., the human timing system) critically relies on basic research on simple behaviors. Perception of temporal regularities is central to a wide range of basic actions, but also underpins abilities unique to humans such as the creation of complex musical scores. This dissertation is an in-depth examination of endogenously and exogenously guided timing behavior, and how context is a critical component of understanding rhythmic entrainment in humans. We previously validated “gold standard” functional magnetic resonance imaging (fMRI) findings on action-based timing behavior using functional near infrared spectroscopy (fNIRS) (Rahimpour et al., 2020). In particular, we observed significant hemodynamic responses in cortical areas in direct relation to the complexity of the behavior being performed. To do so, we probed multiple levels of contextual influence on action-based timing behavior and patterns of cortical activation as measured using fNIRS. Our findings highlighted several distinct, context-dependent parameters of specific timing behaviors. Here we further interrogate human timing abilities by introducing variations of our original experimental design, observing that subtle contextual variations have a significant impact on the degree of rhythmic entrainment given the presence/absence of metronomic input. We used electroencephalogram (EEG) to further validate our fNIRS findings, demonstrating that single trial neurobiological activity can be used to predict whether behavior is exogenously or endogenously guided. We also found that patterns of neural activity correspond to differential use of the internal timing system, and that specific differences in neural activity correlate with accuracy of action-based timing behavior. These findings emerged from our use of a novel deep learning approach to extract person-specific, neural-based features as predictors of behavioral performance. Finally, we examined whether fNIRS and EEG produced similar localization information, finding that the influence of training factors on cortical localization must be accounted for to make such comparisons.

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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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    DANS-EASY
    Dataset . 2017
    Data sources: B2FIND
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      DANS-EASY
      Dataset . 2017
      Data sources: B2FIND
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    Authors: Man, Emily Yee-May;
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    Authors: Bell, Clive; van Dillen, Susanne;

    This paper analyzes the effects of all-weather rural roads on households' net output prices, education and health in a poor, drought-prone region of India. Of 30 villages originally surveyed in 2001-02, when two had such roads, a further nine received them between January 2007 and December 2009 under the program Pradhan Mantri Gram Sadak Yojana. Cross-section comparisons involving all villages and 'before and after' comparisons in the nine yielded these findings: (i) net output prices were 5 per cent or more higher; (ii) substantially fewer days of schooling were lost due to bad weather, largely because teachers had fewer absences; (iii) the acutely sick received more timely treatment and were more likely to be treated in a hospital than in the nearest primary health clinic; and (iv) the respondents ranked the resulting benefits in the domains of health and education at least as highly as the 'commercial' ones.

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    Authors: Azevedo, Kathleen Cora Walker;
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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: Ikkai, Akiko; Dandekar, Sangita; Curtis, Clayton E.;

    Attending to a task-relevant location changes how neural activity oscillates in the alpha band (8–13Hz) in posterior visual cortical areas. However, a clear understanding of the relationships between top-down attention, changes in alpha oscillations in visual cortex, and attention performance are still poorly understood. Here, we tested the degree to which the posterior alpha power tracked the locus of attention, the distribution of attention, and how well the topography of alpha could predict the locus of attention. We recorded magnetoencephalographic (MEG) data while subjects performed an attention demanding visual discrimination task that dissociated the direction of attention from the direction of a saccade to indicate choice. On some trials, an endogenous cue predicted the target’s location, while on others it contained no spatial information. When the target’s location was cued, alpha power decreased in sensors over occipital cortex contralateral to the attended visual field. When the cue did not predict the target’s location, alpha power again decreased in sensors over occipital cortex, but bilaterally, and increased in sensors over frontal cortex. Thus, the distribution and the topography of alpha reliably indicated the locus of covert attention. Together, these results suggest that alpha synchronization reflects changes in the excitability of populations of neurons whose receptive fields match the locus of attention. This is consistent with the hypothesis that alpha oscillations reflect the neural mechanisms by which top-down control of attention biases information processing and modulate the activity of neurons in visual cortex. IkkaiDataUpload

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    DRYAD; ZENODO; NARCIS
    Dataset . 2017
    License: CC 0
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    DANS-EASY
    Dataset . 2016
    Data sources: B2FIND
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      DRYAD; ZENODO; NARCIS
      Dataset . 2017
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      Dataset . 2016
      Data sources: B2FIND
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    Authors: Du, Andrew; Zipkin, Andrew M.; Hatala, Kevin G.; Renner, Elizabeth; +4 Authors

    A large brain is a defining feature of modern humans, yet there is no consensus regarding the patterns, rates, and processes involved in hominin brain size evolution. We use a reliable proxy for brain size in fossils, endocranial volume (ECV), to better understand how brain size evolved at both clade- and lineage-level scales. For the hominin clade overall, the dominant signal is consistent with a gradual increase in brain size. This gradual trend appears to have been generated primarily by processes operating within hypothesized lineages – 64% or 88% depending on whether one uses a more or less speciose taxonomy, respectively. These processes were supplemented by the appearance in the fossil record of larger-brained Homo species and the subsequent disappearance of smaller-brained Australopithecus and Paranthropus taxa. When the estimated rate of within-lineage ECV increase is compared to an exponential model that operationalizes generation-scale evolutionary processes, it suggests that the observed data were the result of episodes of directional selection interspersed with periods of stasis and/or drift; all of this occurs on too fine a time scale to be resolved by the current human fossil record, thus producing apparent gradual trends within lineages. Our findings provide a quantitative basis for developing and testing scale-explicit hypotheses about the factors that led brain size to increase during hominin evolution. Appendix S1Supplementary methods, results, figures, and tables for the analysis.Du et al 2018 revised Appendix S1 R2_ESM_FINAL changes accepted.docxTable S1Excel spreadsheet with the raw data used for all analyses. Each row is a separate specimen along with its ID. Columns include the “lumper’s” and “splitter’s” taxonomy used in the random effects ANOVA to get inter-observer error (“lump.taxon” and “split.taxon”), the less and more speciose lineages used in the lower-taxonomic additive partitioning analyses (“lump.part” and “split.part”), region where each specimen comes from which aided in the allocation of specimens to lineages (“region”), grade for coding points in fig. 2 (“grade”), which specimens were excluded for the damaged specimens sensitivity analysis (“reliab.sens”), ECV replicate measurements from different researchers (“ecv1” to “ecv6”), and the various dates for each specimen (“min.date”, “max.date”, “mean.date”, and “sd.date”) and their respective age error distribution (“date.dist”).ProcB SI ECV dataset FINAL.xlsxR scriptR script for (1) running variance partitioning analyses to get inter-observer endocranial volume (ECV) error, (2) fitting evolutionary mode models to the hominin clade-level ECV data using the R package "paleoTS", (3) calculating R2 and model parameters for the gradualism model, and (4) running the lower taxonomic level additive partitioning analyses.Du et al R script_ESM.txt

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    DANS-EASY
    Dataset . 2018
    Data sources: B2FIND
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    DRYAD; ZENODO; NARCIS
    Dataset . 2018
    License: CC 0
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      Dataset . 2018
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      Dataset . 2018
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    Authors: Semple, Bridgette D.; Noble-Haeusslein, Linda J.; Kwon, Yong Jun; Sam, Pingdewinde N.; +12 Authors

    Despite the life-long implications of social and communication dysfunction after pediatric traumatic brain injury, there is a poor understanding of these deficits in terms of their developmental trajectory and underlying mechanisms. In a well-characterized murine model of pediatric brain injury, we recently demonstrated that pronounced deficits in social interactions emerge across maturation to adulthood after injury at postnatal day (p) 21, approximating a toddler-aged child. Extending these findings, we here hypothesized that these social deficits are dependent upon brain maturation at the time of injury, and coincide with abnormal sociosexual behaviors and communication. Age-dependent vulnerability of the developing brain to social deficits was addressed by comparing behavioral and neuroanatomical outcomes in mice injured at either a pediatric age (p21) or during adolescence (p35). Sociosexual behaviors including social investigation and mounting were evaluated in a resident-intruder paradigm at adulthood. These outcomes were complemented by assays of urine scent marking and ultrasonic vocalizations as indices of social communication. We provide evidence of sociosexual deficits after brain injury at p21, which manifest as reduced mounting behavior and scent marking towards an unfamiliar female at adulthood. In contrast, with the exception of the loss of social recognition in a three-chamber social approach task, mice that received TBI at adolescence were remarkably resilient to social deficits at adulthood. Increased emission of ultrasonic vocalizations (USVs) as well as preferential emission of high frequency USVs after injury was dependent upon both the stimulus and prior social experience. Contrary to the hypothesis that changes in white matter volume may underlie social dysfunction, injury at both p21 and p35 resulted in a similar degree of atrophy of the corpus callosum by adulthood. However, loss of hippocampal tissue was greater after p21 compared to p35 injury, suggesting that a longer period of lesion progression or differences in the kinetics of secondary pathogenesis after p21 injury may contribute to observed behavioral differences. Together, these findings indicate vulnerability of the developing brain to social dysfunction, and suggest that a younger age-at-insult results in poorer social and sociosexual outcomes. BodyWeights_dataBody weights of mice used in this study, across time post-injury3chamber_test_dataMice injured at adolescence (postnatal day 35) and tested in the three-chamber social approach task at adulthood. Percentage time spent in each chamber was quantified.CC_volume_dataStereological analyses were performed using StereoInvestigator to determine the volume loss of the corpus callosum at adulthood after injury at either p21 or p35.Res-Intr_test_dataSocial investigation of a novel (male or female) stimulus mouse was quantified as duration spent investigating different regions (e.g. anogenital), during the resident-intruder task.Scent_mark_test_dataGrid squares containing scent marks were quantified during the scent marking test towards a novel female mouse, of sham or TBI (traumatic brain injury) mice at adulthood after injury at p21 or p35.USV_dataUltrasonic vocalizations (USVs) were recorded during encounters of the test mouse (sham or brain-injured) with (1) a novel male, (2) a novel female, or (3) soiled bedding from a novel female. Several parameters including total number of calls, high frequency calls (> 75 kHz) and # calls in bursts were quantified.

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    DANS-EASY
    Dataset . 2014
    Data sources: B2FIND
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    DRYAD; ZENODO; NARCIS
    Dataset . 2015
    License: CC 0
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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/ DANS-EASYarrow_drop_down
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      DANS-EASY
      Dataset . 2014
      Data sources: B2FIND
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      DRYAD; ZENODO; NARCIS
      Dataset . 2015
      License: CC 0
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    Authors: Avery, Michael; Nassi, Jonathan; Reynolds, John;

    Optogenetics has become an important tool for perturbing neural circuitry with unparalleled temporal precision and cell-type specificity. However, direct activation of a specific subpopulation of neurons can rapidly modulate the activity of other neurons within the network and may lead to unexpected and complex downstream effects. Here, we have developed a biologically-constrained computational model that exploits these non-intuitive network responses in order to gain insight into underlying properties of the network. We apply this model to data recorded during optogenetic stimulation in the primary visual cortex of the alert macaque. In these experiments, we found that optogenetic depolarization of excitatory neurons often suppressed neuronal responses, consistent with engagement of normalization circuitry. Our model suggests that the suppression seen in these responses may be mediated by slow excitatory and inhibitory conductance channels. Furthermore, the model predicted that the response of the network to optogenetic perturbation depends critically on the relationship between inherent temporal properties of the network and the temporal properties of the opsin. Consistent with model predictions, stimulation of the C1V1TT opsin, an opsin with a fast time constant (tau=45 ms), caused faster and stronger suppressive effects after laser offset, as compared to stimulation of the slower C1V1T opsin (tau=60ms). This work illustrates how the non-intuitive network responses that result from optogenetic stimulation can be exploited to gain insight regarding network properties that underlie fundamental neuronal computations, such as normalization. This novel hybrid opto-theoretical approach can thus enhance the power of optogenetics to dissect complex neural circuits. Electrophysiological recordings of neurons at Lenti-camkII-C1V1_T infection site141 neurons recorded at the site of infection. The most important aspect of the file is the variable 'everybindata' which is a cell array (size =141). In each cell there is a matrix of size = number of trials x time (in ms) x laser level (5 laser levels). The irradiance values (laser levels) for each recorded neuron are given in variable 'Lenti_continuous_irradiance_vals."baselinelasermod_irr_Lenticontinuous_fullraster_1msbinwidth.matElectrophysiological recordings of neurons at AAV-camkII-C1V1_TT infection site16 neurons recorded at the site of infection. The most important aspect of the file is the variable 'everybindata' which is a cell array (size =16). In each cell there is a matrix of size = number of trials x time (in ms) x laser level (5 laser levels). The irradiance values (laser levels) for each recorded neuron are given in variable 'AAV_continuous_irradiance_vals."baselinelasermod_irr_AAVcont.mat

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    DRYAD; ZENODO; NARCIS
    Dataset . 2018
    License: CC 0
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    DANS-EASY
    Dataset . 2018
    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/ DRYAD; ZENODO; NARCI...arrow_drop_down
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      DRYAD; ZENODO; NARCIS
      Dataset . 2018
      License: CC 0
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      DANS-EASY
      Dataset . 2018
      Data sources: B2FIND
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    Authors: Dang, Xiangnan; Bardhan, Neelkanth M.; Qi, Jifa; Gu, Li; +5 Authors

    Detection of biological features at the cellular level with sufficient sensitivity in complex tissue remains a major challenge. To appreciate this challenge, this would require finding tens to hundreds of cells (a 0.1 mm tumor has ~125 cells), out of ~37 trillion cells in the human body. Near-infrared optical imaging holds promise for high-resolution, deep-tissue imaging, but is limited by autofluorescence and scattering. To date, the maximum reported depth using second-window near-infrared (NIR-II: 1000–1700 nm) fluorophores is 3.2 cm through tissue. Here, we design an NIR-II imaging system, “Detection of Optically Luminescent Probes using Hyperspectral and diffuse Imaging in Near-infrared” (DOLPHIN), that resolves these challenges. DOLPHIN achieves the following: (i) resolution of probes through up to 8 cm of tissue phantom; (ii) identification of spectral and scattering signatures of tissues without a priori knowledge of background or autofluorescence; and (iii) 3D reconstruction of live whole animals. Notably, we demonstrate noninvasive real-time tracking of a 0.1 mm-sized fluorophore through the gastrointestinal tract of a living mouse, which is beyond the detection limit of current imaging modalities. Sample Dataset for HyperSpectral Imaging (HSC data)This is a sample dataset, obtained using Hyperspectral Imaging of a label-free, healthy nude mouse, using the DOLPHIN imaging system, using a wavelength-tunable laser (from 690 - 1040 nm). As a sample, only the 980 nm excitation wavelength data has been provided in this archive. Details of the DOLPHIN imaging system and the image processing techniques used for Hyperspectral Imaging are described in the aforementioned paper.Sample Dataset for HyperDiffuse Imaging (HDC data)This is a sample dataset, obtained using Hyperdiffuse Imaging of the passage of a 100 µm-sized Er-NP cluster probe through the GI tract of a healthy nude mouse, using the DOLPHIN imaging system, using a fixed wavelength of excitation (980 nm laser). Details of the DOLPHIN imaging system and the image processing techniques used for Hyperdiffuse Imaging are described in the aforementioned paper.

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    DRYAD; ZENODO; NARCIS
    Dataset . 2019
    License: CC 0
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    DANS-EASY
    Dataset . 2019
    Data sources: B2FIND
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