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29 results for “Rivalry”
Dataset supplementing Schütz, I. & Einhäuser, W. (2018) Visual awareness in binocular rivalry modulates induced pupil fluctuations.
<p>This dataset supplements the publication:</p> <p>Schütz, I. & Einhäuser, W. (2018). Visual awareness in binocular rivalry modulates induced pupil fluctuations.</p> <p><br> Raw data are available in two formats: the actual raw EDF data files as returned by the eyetracking device (*.edf) for reference, and as MATLAB files into which all relevant information has been extracted (*.mat) for analysis.</p> <p>Variables in the pft_*.mat files include<br> - raw eye position in the variable scan (t,x,y,p), where t is the timestamp of the eyetracker, x/y the position on the screen and p the pupil diameter in arbitrary units<br> - fixation, saccade and blink events in variables fix, sac and blink<br> - raw button presses in cell arrays buttonDn and buttonUp (6 - left button, 7 - right button) including timestamps<br> - stimulus presentation cycle timestamps in the variable stimperiod<br> - timestamps for auditory attentional instruction in the variable attends</p> <p>For analysis, data from all participants and sessions is imported into pftdata.mat, where it is stored in cell arrays of the format "samples{subject_no, condition}".</p> <p><br> Data Files<br> ==========</p> <p>- rawdata.zip<br> - rawdata/*.edf: raw EyeLink 2000 EDF data files<br> - rawdata/*.mat: EyeLink data converted to MATLAB data file</p> <p>- analysis.zip<br> - pftdata.mat: preprocessed eye tracking and response data for analysis<br> - face.png, house.png: stimulus images used for the experiment<br> - resp_anova.csv: response data for ANOVA (generated by preprocessing.m)<br> - fig4_anova.csv: complex plane data for R T-Test (generated by figure4_complex_plane.m)<br> - analysis code files, see below</p> <p><br> Analysis Functions<br> ==================</p> <p>Run the following functions in the listed order to reproduce figures and data in results/.</p> <p>- preprocessing.m:<br> - convert EDF data files to ASCII using SR-Research edf2asc, import into MATLAB<br> - remove EyeLink detected blinks and interpolate (cubic spline)<br> - z-score pupil data within each experimental block<br> - add button press / reported percept to sample data<br> - save response data for RM-ANOVA in R</p> <p>- figure1_methods.m:<br> - recreates Figure 1 (stimulus figure from images)</p> <p>- figure2_example_plot.m:<br> - recreate Figure 2 (example data from one participant)</p> <p>- figure3_averaged_response.m<br> - recreates Figure 2 (averaged F1 FFT component by condition)</p> <p>- figure4_complex_plane.m:<br> - recreates Figure 4 (complex plane analysis of pupil response)</p> <p>- stats_auc_decoding.m:<br> - moment-by-moment decoding analysis using AUC<br> - recreates stats_AUC.txt</p> <p>- pft_statistics.R:<br> - R statistics, recreates stats_responses.txt and stats_Zvalues.txt</p> <p><br> Output Files<br> ============</p> <p>results/<br> - Paper Figures (not layouted): figure1.tif, figure2.png, figure3.png, figure4.png<br> - stats_responses.txt: behavioral analyses results,<br> - stats_Zvalues.txt: complex plane analysis results<br> - stats_AUC.txt: moment-by-moment AUC decoding results</p> <p> </p>
Dataset supplementing the article Einhäuser, W., Methfessel, P., & Bendixen, A. (2017). Newly acquired audio-visual associations bias perception in binocular rivalry. Vision Research, 133, 121-129.
<p>This dataset supplements the publication<br> Einhäuser, W., Methfessel, P., & Bendixen, A. (2017). Newly acquired audio-visual associations bias perception in binocular rivalry. Vision Research, 133, 121-129. doi: 10.1016/j.visres.2017.02.001</p> <p>Use is free for scientific purposes, provided the aforementioned reference is appropriately cited.<br> Description of files<br> - conditionsByObserver.csv<br> contains for each of the 16 observers the color and grating direction that had been coupled to either the low-pitch or the high-pitch tone<br> column 1: observer number<br> column 2: color associated with low-pitch tone<br> column 3: color associated with high-pitch tone<br> column 4: drift direction associated with low-pitch tone<br> column 5: drift direction associated with high-pitch tone</p> <p>- conditionsByObserver.mat contains the same information as matlab variables (as four vectors/cell arrays with one entry per observer)</p> <p>- toneByBlockAndTrial.csv<br> contains the conditions for all 18 rivalry trials (6 rivalry blocks with 3 trials each) for each observer<br> column 1: observer number<br> column 2: block number<br> column 3: trial number<br> column 4: tone (low [pitch], high [pitch], none) played in this trial<br> Note that due to a technical error for observer #16, block 6 was presented first, followed by 1,2,3,4,5; for all other observers blocks were used in the order given (1,2,3,4,5,6).</p> <p>- toneByBlockAndTrial.mat contains the same information as a 16x6x3 matrix named toneByBlockAndTrial ; tones are coded numerically (1-low pitch,2-high pitch,3-none)</p> <p>- eyeTraces.mat contains three cell arrays of dimensions 16x6x3 (observer x rivalry block x rivalry trial) called xEye, oknGain, and timeSinceTrialStart;</p> <p>o each entry of xEye contains the horizontal eye position for<br> the respective trial in eye-tracker coordinates (which correspond to screen pixels, except that (1/1) is the upper right rather than the upper left and values increase from right to left due to the setup configuration)</p> <p>o oknGain contains the gain computed from these eye positions.</p> <p>o timeSinceTrialStart contains the time in seconds since onset of the trial</p> <p><br> For all variables, the sampling rate is 500 Hz, in eye-tracker coordinates the speed of the grating is 240 units/ms. Blinks were removed from both eye-data variables, fast-phases were removed from the gain data. Removed data were set to NaN in eye-data variables.</p> <p>- Matlab functions figure1d.m, figure 2.m, figure3.m and figure4.m compute raw versions of the aforementioned paper's figures from the datafiles to exemplify their usage.</p> <p>[Note: In the originally published version of the article, the first two means and their standard errors of section 3.3 were stated incorrectly. All figures and statistical analyses are based on the correct data].</p>
Dataset supplementing Marx, S., Gruenhage, G., Walper, D., Rutishauser, U., Einhäuser, W. (2015). Competition with and without priority control: linking rivalry to attention through winner-take-all networks with memory. Annals of the New York Academy of Sciences. 1339, 138-153.
<p>Data supplementing the paper Marx, S., Gruenhage, G., Walper, D., Rutishauser, U., Einhäuser, W. (2015). Competition with and without priority control: linking rivalry to attention through winner-take-all networks with memory. <em>Annals of the New York Academy of Sciences. 1339, </em>138-153. doi: 10.1111/nyas.12575 The files can be freely used for scientific purposes, provided this reference is appropriately cited.</p> <p>Files contain the behavioral data, the model can be found at https://doi.org/10.5281/zenodo.573026</p> <p> </p> <p>The following files are contained in this folder:</p> <p>dataExp1.mat contains the data of experiment 1</p> <p>The variables durationLeft and durationRight contain 5 x 6 x 6 cell arrays with the dominance durations for the left and right grating, respectively. Dimensions are subject x contrast level left x contrast level right.</p> <p><br> dataExp2.mat contains the data of experiment 2</p> <p>Variables buttonStart, buttonEnd and whichButton contain 3x4x5 (contrast levels x blank duration levels x subjects) cell arrays that contain the start time and end time of each button press, and which button (1/2) was pressed, respectively.</p> <p>Variables presStart and presEnd contain 3x4x5 (contrast levels x blank duration levels x subjects) cell arrays that contain start and end of each blank period. All time stamps refer to the onset of the first blanking trial (end of continuous presentation)</p> <p>Variable prevPerz contains the percept (button) that was pressed at the end of the continuous presentation period.</p> <p><br> figure3_human.m, figure4_human.m and figure6_human.m exemplify the usage of the data by re-plotting the figures containing human data of the aforementioned paper</p>
Dataset supplementing the publication Einhäuser, W., Thomassen, S., & Bendixen, A. (2017). Using binocular rivalry to tag foreground sounds: towards an objective visual measure for auditory multistability. Journal of Vision, 17:34, 1-19.
<p>These files supplement the publication Einhäuser, W., Thomassen, S., & Bendixen, A. (2017). Using binocular rivalry to tag foreground sounds: towards an objective visual measure for auditory multistability. Journal of Vision, 17:34, 1-19. The data are free for scientific use, provided this reference is appropriately cited.</p> <p>exp1_data.mat contains all the data of experiment 1 as cell arrays of size 8x16x8 (subject x block x trial) or 8x16 (subject x block). Specifically:<br> xEye: the horizontal eye position in raw (pixel coordinates)<br> gain: the OKN slow phase gain computed from the xEye data as described in the paper; in audio-visual blocks the sign is chosen such that positive gain corresponds to the direction of the grating associated with the low tone; in unambiguous visual blocks (1,16) positive sign corresponds to the direction of the grating.<br> ixLow, ixHigh, ixNone, ixBoth: indices for xEye and gain of the same subject and block for which the button corresponding to the low tone, the high tone, both buttons or no button was pressed.</p> <p>exp2_data.mat and exp3_data.mat contain the data of experiment 2 and experiment 3, respectively, and are organized analogously to exp1_data.mat.</p> <p>figure3.m through figure6.m use these data to plot the respective paper figures to exemplify usage of the data.</p> <p> </p>
Dataset supplementing "Marx, S., & Einhäuser, W. (2015). Reward modulates perception in binocular rivalry. Journal of Vision, 15(1):11, 1–13, http://www.journalofvision.org/content/15/1/11, doi:10.1167/15.1.11."
<p>These data supplement the publication</p> <p>Marx, S., & Einhäuser, W. (2015). Reward modulates perception in binocular rivalry. Journal of Vision, 15(1):11, 1–13, http://www.journalofvision.org/content/15/1/11, doi:10.1167/15.1.11.</p> <p>and be used freely for scientific purposes provided the aforementioned paper is appropriately cited.</p> <p>exp1_data.mat contains data of experiment 1</p> <p>exp2_data.mat contains data of experiment 2</p> <p>figure2_3.m and figure4_5.m exemplify usage of the data and reproduce the figures 2-5 of the aforementioned article.</p>
Does V1 response suppression initiate binocular rivalry?
<p><strong>Using this dataset</strong></p> <p>As Cell Press authors, we share all of the data and original code we report in our paper with the research community. This dataset contains stimulus-locked multi-units responses for each recording session analyzed and reported in the associated manuscript at iScience.</p> <p>Please download and extract eventTriggeredData.zip into a file on your MATLAB path.</p> <p>For generating the figures reported in the manuscript, please use our custom MATLAB repository published on GitHub at: https://github.com/BrockMCarlson/BMC_AdaptdcosFigures.</p> <p>Download the GitHub repository, follow the setup instructions in the ReadMe, and run the Controller_iScienceSubmission.mlx live script. </p> <p>IDX_iScienceSubmission.mat, JASP_sustained.csv, & JASP_transient.csv are files created by Controller_iScienceSubmission.mlx. You do not need to download them, but they are included in this Zenodo directory for your reference.</p> <p> </p> <p><em><strong>Does V1 response suppression initiate binocular rivalry?</strong></em></p> <p><strong>HIGHLIGHTS</strong></p> <ul> <li>The role of primary visual cortex (V1) for binocular rivalry (BR) is unclear.</li> <li>V1 population spiking is reduced at the onset of BR, providing a potential trigger.</li> <li>However, this broad spiking suppression in does not occur for a variant of BR.</li> <li>The BR variant reduces subpopulation responses, a potential alternate trigger.</li> </ul> <p> </p> <p><strong>SUMMARY</strong></p> <p>In binocular rivalry (BR) only one’s view is perceived. The neural underpinnings of BR are debated. Recent studies suggest that primary visual cortex (V1) initiates BR. One such trigger might be response-suppression across most V1 neurons at the onset of BR. Here we utilize a variant of BR called binocular rivalry flash suppression (BRFS) to test this hypothesis. BRFS is identical to binocular rivalry, except stimuli are shown with a ~1s delay. If V1 response suppression was required to initiate BR, it should occur during BRFS as well. To test this hypothesis, we compared V1 spiking in two macaques observing BRFS. We found that BRFS resulted in response-facilitation rather than response-suppression across V1 neurons. However, BRFS still reduces responses in a subset of V1 neurons due to the adaptive effects of asynchronous stimulus presentation. We argue that this selective response suppression could serve as an alternate initiator of BR.</p>
Sibling rivalry: Males with more brothers develop larger testes
<p>When females mate with multiple partners in a reproductive cycle, the relative number of competing sperm from rival males is often the most critical factor in determining paternity. Gamete production is directly related to testis size in most species, and is associated with both mating behavior and perceived risk of competition. Deer mice, <i>Peromyscus maniculatus</i>, are naturally promiscuous and males invest significantly more in sperm production than males of <i>P. polionotus</i>, their monogamous sister‐species. Here, we show that the larger testes in <i>P. maniculatus</i> are retained after decades of enforced monogamy in captivity. While these results suggest that differences in sperm production between species with divergent evolutionary histories can be maintained in captivity, we also show that the early rearing environment of males can strongly influence their testis size as adults. Using a second‐generation hybrid population to increase variation within the population, we show that males reared in litters with more brothers develop larger testes as adults. Importantly, this difference in testis size is also associated with increased fertility. Together, our findings suggest that sperm production may be both broadly shaped by natural selection over evolutionary timescales and also finely tuned during early development.</p>
Color_rivalry_fMRI
<p> </p> <p>Color rivalry fMRI dataset.</p> <p>color1 : Magenta - Green color pair rivalry data</p> <p>color2: Blue - Orange color pair rivalry data</p> <p>replay: Magenta - Green color pair replay data (without rivalry) </p> <p>train: 8 DKL color training data</p> <p># The number in front of each file denotes observer number.</p> <p> </p> <p> </p> <p> </p>
'Proto-rivalry': how the binocular brain identifies gloss
<p>Dataset relative to the following publication:</p> <p>Muryy, A. A., Fleming, R. W., & Welchman, A. E. (2016). ‘Proto-rivalry’: how the binocular brain identifies gloss. <em>Proceedings of the Royal Society B, 283(1830)</em>: 20160383.</p> <p>Each folder contains *.mat files with the data relative to the respective experiment(s) and a matlab script for loading and plotting the data. The matlab scripts also include comments regarding the data files.</p>
The duration effect of short-term monocular deprivation measured by binocular rivalry and binocular combination
<p>Full dataset and analysis script (Python) of the data presented in the paper "The duration effect of short-term monocular deprivation measured by binocular rivalry and binocular combination" by Prosper, Pasqualetti, Morrone & Lunghi (https://doi.org/10.1016/j.visres.2023.108278).</p> <p>Dataset and full description in README file.</p> <p>Analysis description in "analysis_notebook" file.</p>
Data from: Sibling rivalry: males with more brothers develop larger testes
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Rivalry_Tagging
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Dataset and analysis script for the manuscript "Status, rivalry and admiration-seeking in narcissism and depression: a behavioral study"
<p><em>Datasets and analysis script for the manuscript "Status, rivalry and admiration-seeking in narcissism and depression: a behavioral study".</em></p> <p><em>The attached R script begins with a read-me section with a short explanation of all variables present in the datasets. This information is also uploaded as a separate readMe in .txt format. Analyses are organized with respect to their order of appearance in the preprint (<a href="https://doi.org/10.31234/osf.io/mxve9">https://doi.org/10.31234/osf.io/mxve9</a>).</em></p> <p><em>The data is uploaded in two datasets: a long-format one (ds_pooled.csv) employed in the trial-by-trial regression models and a wide-format one for supplemental subject-level analyses (ds_pooled_wide.csv). The script contains code to further generate separate datasets for Samples 1 and 2 in both the long- and the wide-format. Please, refer to the manuscript for detailed information about how the data has been collected and analyzed.</em></p> <p><em>Note: The ds_items.zip file contains datasets with item scores of the included psychometric scales (trait-dominance, narcissism scales and depression scales). These files are only used in a short section of the script to compute reliability coefficients.</em></p>
Data from: Consequences of sibling rivalry vary across life in a passerine bird
Many studies have assessed the costs of sibling rivalry in systems where offspring always have competitors, but conclusions about sibling rivalry in these species are restricted to interpreting the cost of changes in the relative level of competition and are often complicated by the expression of potentially costly rivalry related traits. Additionally, the majority of studies focus on early-life sibling rivalry, but the costs of competition can also affect later-life performance. We test a suite of hypothesized immediate (early-life body mass, telomere length, and survival) and delayed (adult reproductive potential and lifespan) costs of sibling rivalry for offspring of differing competitive ability in Seychelles warblers, where most offspring are raised singly and hence competitor success can be compared to a competition-free scenario. Compared to those raised alone, all competing nestlings had lower body mass and weaker competitors experienced reduced survival. However, the stronger competitors appeared to have longer adult breeding tenures and lifespan than those raised alone. We propose that comparisons with competition-free groups, as well as detailed fitness measures across entire lifetimes, are needed to understand the evolution of sibling rivalry and thus individual reproductive strategy in wild systems.
Measuring the reliability of binocular rivalry
<p>The dataset holds a Matlab structure m, with all the data published in Acquafredda et al., JoV 2023.<br>m = structure containing average data for generating the analyses and figures reported in the manuscript. It contains separate fields for the four different experiments and two experimental sessions, session1 and session2, where the variables below were measured.<br>Each of these fields has subfields containing the information detailed below, coded with the format (N x M) with N = number of participants and M = 1. <br>Variables reported in the structure:<br>OD: % Ocular dominance defined as the proportion of exclusive right-eye dominance (please see formula in the paper)<br>Mpd: % Mean durations of exclusive dominance phases<br>Mixed_prop: % proportion of the total testing time spent reporting mixed percepts <br>Bootstrapped_SE_ses1: %For each trial of session1 we represented perceptual reports as a list of phases, each linked with its duration and type (left eye, right eye, mixed). This list was resampled 10,000 times with reinsertion; for each resampling, we estimated the three parameters of interest. Finally, we took the standard deviation across these 10,000 values as a measure of standard error and combined standard errors across trials by taking the median. <br>Bootstrapped_SE_ses2: % same as described above, but for each trial of session2. <br>Bootstrapped_SE_diff: % for each of the 10000 resamplings described above, we computed the difference between the parameters of interest across the two session. This was repeated for each trial (trial 1 session 1 minus trial 1 in session 2, trial 2 in session 1 minus trial 2 in session 2, etc...). We took the standard deviation across these 10,000 differences as a measure of standard error and combined standard errors across trials by taking the median. We used this value as indicative of internal consistency.</p>
Pupil and gaze during binocular rivalry
<p><span><span><span><span><span><span><span><span><span><span><span>The pupil provides a rich, non-invasive measure of the neural bases of perception and cognition, and has been of particular value in uncovering the role of arousal-linked neuromodulation, which alters cortical processing as well as pupil size. But pupil size is subject to a multitude of influences, which complicates unique interpretation. We measured pupils of observers experiencing perceptual multistability -- an ever-changing subjective percept in the face of unchanging but inconclusive sensory input. In separate conditions the endogenously generated perceptual changes were either task-relevant or not, allowing a separation between perception-related and task-related pupil signals. Perceptual changes were marked by a complex pupil response that could be decomposed into two components: a dilation tied to task execution and plausibly indicative of an arousal-linked noradrenaline surge, and an overlapping constriction tied to the perceptual transient and plausibly a marker of altered visual cortical representation. Constriction, but not dilation, amplitude systematically depended on the time interval between perceptual changes, possibly providing an overt index of neural adaptation. These results show that the pupil provides a simultaneous reading on interacting but dissociable neural processes during perceptual multistability, and suggest that arousal-linked neuromodulation shapes action but not perception in these circumstances.</span></span></span></span></span></span></span></span></span></span></span></p>
Mexican cartels form a network of alliances and rivalries
<p><span>Mexican cartels lose many members due to conflict with other cartels and arrests. Yet, despite their losses, cartels managed to increase violence for years. We address this puzzle by leveraging data on homicides, missing persons and arrests in Mexico for the past decade, along with information on cartel interactions. We model recruitment, state incapacitation, conflict and saturation as sources of cartel size variation. Results show that by 2022, cartels counted 160,000–185,000 units, becoming a top employer. Recruiting at least 350 people per week is essential to avoid their collapse due to aggregate losses. Furthermore, we show that increasing incapacitation would increase both homicides and cartel members. Conversely, reducing recruitment could substantially curtail violence and lower cartel size.</span></p>
Data from: Consequences of sibling rivalry vary across life in a passerine bird
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Pupil and gaze during binocular rivalry
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Mexican cartels form a network of alliances and rivalries
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