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426 results for “Stimuli”
The exercise paradox: Avoiding physical inactivity stimuli requires higher response inhibition
<p><strong>Dataset related to the paper on Response inhibition to physical inactivity stimuli using go/no-go tasks. </strong></p> <p>This dataset includes:</p> <p><strong>1) A codebook (including the name of the main variables)</strong></p> <p>--> "code_book_Go_noGo_Miller.xlsx"</p> <p><strong>2) Raw data of the behavioral outcomes (i.e., reaction times) of the affective go/no-go task</strong></p> <p>--> "corrected.behavioral.data.csv"</p> <p>--> "correct_Order.csv"</p> <p><strong>3) Self-reported data </strong></p> <p>--> "Self_report_data.csv"</p> <p><strong>3) EEG data </strong></p> <p>--> "gng_data"</p> <p><strong>5) R script for the data management (i.e., from the raw data to data ready to be analyzed)</strong></p> <p>--> "Data_management_Self_report_go_no_go_Miller.R" for the self-reported data (return the file: "Data_SR_final.RData")</p> <p>--> "Data_management_behav_go_no_go_Miller.R" for the behavioral outcomes (return the file: "Data_GNG_behav.RData")</p> <p>--> Data ready to be analyzed "Data_GNG_final_all.RData"</p> <p><strong>6) Eprime script for the affective go/no-go task ("Go_no_go_task.zip")</strong></p> <p>--> Images depicting physical activity and physical inactivity stimuli were kindly Share by Kullmann et al. (2014)</p> <p><strong>7) R script for the models tested</strong></p> <p><strong>--> "</strong>Models_GoNogo_Miller_VZenodo.R" for behavioral data</p> <p>--> "Models_EEG_GoNogo.R" for EEG data</p>
Data to "Human shape perception spontaneously discovers the biological origin of novel, but natural, stimuli"
<p>This record contains analysis scripts (written in Matlab) as well as raw and processed data to reproduce the results shown in:</p> <p>Dehn, K.<strong>†</strong>, Maiello, G.<strong>†</strong>, Hartmann, F., Morgenstern, Y., Hawkins, S.J., Offner, T., Walter, J., Hassenklöver, T., Manzini, I., Fleming, R.W. (2024) Human shape perception spontaneously discovers the biological origin of novel, but natural, stimuli. bioRxiv, 2024-12. https://doi.org/10.1101/2024.12.21.629735 </p> <p><em><strong>†</strong>Co-first author</em></p>
Dataset of "Moving hands feel stimuli before stationary hands"
<p>In the flash lag effect (FLE), a moving object is seen to be ahead of a brief flash that is presented at the same spatial location; a haptic analogue of the FLE has also been observed. Some accounts of the FLE relate the effect to temporal delays in the processing of the stationary stimulus as compared to that of the moving stimulus [3–5]. We tested for movement-related processing effects in haptics. People judged the temporal order of two vibrotactile stimuli at the two hands: One hand was stationary, the other hand was executing a fast, medium, or slow hand movement. Stimuli at the moving hand had to be presented around 36 ms later, to be perceived to be simultaneous with stimuli at the stationary hand. In a control condition, where both hands were stationary, perceived simultaneity corresponded to physical simultaneity. We conclude that the processing of haptic stimuli at moving hands is accelerated as compared to stationary ones–in line with assumptions derived from the FLE.</p> <p>The dataset contains individual points of subjective simultaneity and just noticeable differences for each movement condition (stationary, fast , medium, slow) and individual response frequencies as a function of stimulus onset asynchrony (SOA) and movement condition.</p>
Auditory stimuli suppress contextual fear responses in safety learning independent of a possible safety meaning
<p>This repository stores the raw data that gave rise to the study by Mombelli et al. (2024) (Title: Auditory stimuli suppress contextual fear responses in safety learning independent of a possible safety meaning; DOI: 10.3389/fnbeh.2024.1415047, Journal: Frontiers in Behavioral Neuroscience). Below we supply information on the provided metadata files which, in turn, refer to individual raw data files.</p> <p><strong>General structure of the repository:</strong></p> <p>· the raw data is organized in 5 subsets defined by the figures or supplementary figures they contribute to. Each subset is documented by its own metadata file. Raw data files were compressed into ZIP archives, one per subset;</p> <p>· the metadata files listing names of the individual data files are provided in “.csv” format, one per data subset. Field separator: comma;</p> <p>· the dataset is accessible at the following doi: 10.5281/zenodo.13524007</p> <p> </p> <p><strong>Description of the non-textual data formats:</strong></p> <p>· video recordings of animal behavior were provided as unmodified ".wmv" files created by the VideoFreeze acquisition software (Med Associates Inc). Video stream parameters: wmv3 codec, color space yuv420p, 320x240 pixels, 30 fps, bitrate 300 kb/s.</p> <p>· movement traces were obtained from the videos, as described in the Methods section (Mombelli et al., 2024).</p>
Examining effects of arousal on responses to salient and non-salient stimuli in younger and older adults
Open the record for dataset details and reuse information.
Speech stimuli (ACI experiment)
<p>Speech stimuli involved in the Auditory Classification Image experiment (Alda/Alga/Arda/Arga). Male speaker, wav format, 48 kHz</p>
Effects of Auditory Stimuli During Submaximal Exercise on Cerebral Oxygenation
<p>Manuscript, supplementay files, raw and proprocessed data, code, and materials for the associated registered report.</p>
Dataset for Human visual gamma for color stimuli
<p>This repository contains per-trial data and R analysis code reported in Stauch, B., Peter, A., Ehrlich, I., Nolte, Z., and Fries, P. (2022), <em>Human visual gamma for color stimuli.</em> eLife 11:e75897. doi: <a href="https://doi.org/10.7554/eLife.75897"> 10.7554/eLife.75897</a>. If you want to have a look at the full analysis outcomes, start with analysis_notebook.html. The underlying code is in analysis_notebook.rmd.<br> </p> <p>Additionally, Matlab code that was used to extract per-trial data from the raw data is provided as preprocessingCode.zip.</p>
Test Stimuli for Context Based Evaluation of the OPUS Audio Codec
<p>A dataset that includes the 360° video .mp4 files and Ambisonic audio .wav files used in the listening tests for "Context Based Evaluation of the OPUS Audio Codec for Spatial Audio Content in Virtual Reality".</p>
Infant N290 event-related potentials and stimulus-specific adaptation to face stimuli
<p>Data for publication: "Neural specialization to human faces at the age of 7 months".</p> <p>Further details will be available at: https://github.com/yrttiahoS/ssa/</p> <p> </p> <p>Metadata:</p> <p>I. Event-related potentials</p> <p>The current study investigated both cortical sensitivity and categorical specificity through event-related potentials (ERPs) previously implicated in face processing in 7-month-old infants (N290) and adults (N170). Using a category-specific repetition/adaptation paradigm, cortical specificity to human faces, or control stimuli (cat faces), was operationalized as changes in ERP amplitude between conditions where a face probe was alternated with categorically similar or dissimilar adaptors. In adults, increased N170 for human vs. cat faces and category-specific release from adaptation for face probes alternated with cat adaptors was found. In infants, a larger N290 was found for cat vs. human probes. Category-specific repetition effects were also found in infant N290 and the P1-N290 peak-to-peak response where latter indicated category-specific release from adaptation for human face probes resembling that found in adults.</p> <p>*Dataset files: N290_P1_infant, N170_P1_adult.sav</p> <p> </p> <p>*EEG data in EEGLAB’s format,</p> <p>Filenames indicate type of data with:</p> <p>1) Initial numerical code indicating (anonymized) participant number, "adult/infant" indicating participant group</p> <p>2) f1/c2/f3/c3 indicating stimulus conditions probe:face, adaptor:face / probe:cat, adaptor:cat / probe:face, adaptor:cat / probe:cat,adaptor:face, respectively</p> <p> 3) Final number _1_ or _2_ indicates block number for adult participants (in the order of presentation)</p> <p>Files with only codes 1) and 2) are continuous data with all triggers included</p> <p> </p> <p>*video-based Quality Control is listed in file: anon_vQC2022-09-22.xlsx*video-based Quality Control is listed in file: anon_vQC2022-09-22.xlsx</p> <p> </p> <p>*Analysis syntax: https://github.com/yrttiahoS/ssa/</p> <p> </p> <p>*Dataset updates: TBA at https://github.com/yrttiahoS/ssa/</p> <p> </p> <p> </p> <p>II. Temperament questionnaire</p> <p>*Data collection: Temperament data were collected from participants of an infant event-related potential (ERP) study as potential correlate of outcome variables and as a descriptor of the participant group. Participants were 7-month-old infants from families volunteering in the brain research study, which were contacted through information from a population registry sample. Infant temperament was assessed by parent-reported IBQ-R short form (Putnam, S. P., Helbig, A., Gartstein, M.A., Rothbart, M.K. & Leerkes, E. M. (2014). <em>Development and assessment of short and very short forms of the Infant Behavior Questionnaire-Revised.</em> Journal of Personality Assessment, 96, 445-458. Finnish translation: Professor Katri Räikkönen-Talvitie and the Developmental Psychology Research Group University of Helsinki, Finland)</p> <p>*Authors of the dataset: Santeri Yrttiaho, Mikko Peltola, Anneli Kylliäinen, Tiina, Parviainen, Jari Hietanen</p> <p>*Site of data collection: Human Information Processing laboratory, Tampere University, Finland</p> <p>*Funding: Emil Aaltonen Foundation, Tampere University, Academy of Finland</p> <p>*Participant demographics: Participant group is described by age of M(SD) = 30.5(0.5) weeks. Participants were from Tampere metropolitan area, Finland. Data were collected during Fall 2020 (October 16th – December 7th, 2020).</p> <p>*Data content. Initial data will contain group level statistics and the individual data will be made available as additional files after publication of study results in a peer-reviewed article. Data is anonymized. Individual data contains IBQ-R short form items, scales, and factors as well as participant gender and age in weeks. Data also includes variable indicating whether the participant was included in the final ERP analysis after EEG quality control.</p> <p>*variable names: see 'Scale abbreviations.docx' and for full discussion the original article by Putnam et al. (2014).</p> <p>*Dataset files</p> <p>1. IBQ-R-short-Finnish_dataset.sav / data of items, scales, and factors</p> <p>2. SSA_infant_ibq-r_summary.sps / syntax for computing scores</p> <p>3. IBQ-R-short-Finnish_descriptives.spv / output of descriptive statistics</p> <p>4. Scale abbreviations.docx / explanation of variable names</p> <p> </p> <p> </p> <p> </p> <p> </p>
Visual and Auditory vection stimuli reduce motion sickness
<p>This is the raw data and the full data set from all of our participants included in the analysis for this experiment. </p> <p>The raw data represents the data recorded throughout the experience. Motion Sickness scores, performance on reading task, performance on attention task. </p> <p>While the full data set (Final1) additionally includes questionnaire data (SSQ, NASA TLX, IPQ,...) as well as demographic data of the participants. </p>
Modeling Autonomic Pupillary Responses from External Stimuli Using Machine Learning - Dataset
<p>This page contains the data collected for the paper: <em><strong>Modeling Autonomic Pupillary Responses from External Stimuli Using Machine Learning </strong></em>(<a href="https://doi.org/10.26717/BJSTR.2019.20.003446">DOI:10.26717/BJSTR.2019.20.003446</a>). The dataset consists of spectral and pupillometric data collected during three outdoor/indoor walks. The folders “raw”, “merged”, and “cleaned” contain data collected by the Konica Minolta CL-500A Illuminance Spectrophotometer and Tobii Pro Glasses 2 at three different stages in the data preparation process. The “raw” folder contains uncleaned and unsynchronized .csv/.json files. The “merged” folder contains uncleaned, but synchronized light and ocular data in .csv format. The “cleaned” folder contains a single .csv of cleaned and synchronized data with the derived variables: average pupil diameter and pupil diameter difference. </p> <p>The best choice of data files will depend on desired analysis. More guidance on how to handle this data can be found in the readMe files located in each subsequent folder. More information on the sensing devices used here can be found at the Minolta and Tobii information links below. </p> <p><strong>Minolta Information</strong>: <a href="https://sensing.konicaminolta.us/uploads/cl-500a_instruction217a_eng-250cl60686.pdf">https://sensing.konicaminolta.us/uploads/cl-500a_instruction217a_eng-250cl60686.pdf</a></p> <p><strong>Tobii Information</strong>: <a href="https://www.tobiipro.com/siteassets/tobii-pro/user-manuals/tobii-pro-glasses-2-user-manual.pdf/?v=1.1.3">https://www.tobiipro.com/siteassets/tobii-pro/user-manuals/tobii-pro-glasses-2-user-manual.pdf/?v=1.1.3</a></p> <p>The codes used to prepare, analyze, and visualize this data is available in the LightOcular GitHub Repository linked below. </p> <p><strong>LightOcular GitHub Repo</strong>: <a href="https://github.com/mi3nts/LightOcular">https://github.com/mi3nts/LightOcular</a></p>
Stimuli Responsive and Antimicrobial Cellulose-Chitosan Hydrogels Containing Polydiacetylene Nanosheets
<p>Hydrogels were prepared by esterification of chitosan (Cs) with monochloroacetic acid to produce CMCs which was then crosslinked to HEC using citric acid as the crosslinking agent. To impart a stimuli responsiveness property to the hydrogels, polydiacetylene-zinc oxide (PDA-ZnO) nanosheets were synthesized in-situ during the crosslinking reaction followed by photopolymerization of the resultant composite. First, 10,12-pentacosadiynoic acid (PCDA) head groups were stabilized with ZnO nanoparticles in the presence of CMCs-HEC hydrogels in petroleum ether. This was followed by irradiating the composite with Uv radiation to photopolymerize the PCDA to PDA within the hydrogel matrix so as to impart thermal and pH responsiveness to the hydrogel</p>
Dataset and stimuli: Perception of saturation in natural objects
<p><strong>This dataset contains observer data and stimulus information for the below publication. Refer to this manuscript for more details.</strong></p> <p>Laysa Hedjar, Matteo Toscani, and Karl R. Gegenfurtner, "Perception of saturation in natural objects," Journal of the Optical Society of American A <strong>40</strong>(3), A190-A198 (2023), doi:10.1364/JOSAA.476874.</p> <p> </p> <p>Participant data is available in two files: <em>fruit_pt_data.csv </em>and <em>blob_pt_data.csv</em></p> <ul> <li><em>fruit_pt_data.csv</em>: <ul> <li>fruit name: name of fruit pair</li> <li>object or swatch: whether the stimulus pair were whole objects or 8x8 swatches</li> <li>participant ID: given participant identification number</li> <li>proportion positive: proportion of trials in which participant chose the positive stimulus as more saturated (out of 10 total trials per stimulus pair)</li> </ul> </li> <li><em>blob_pt_data.csv</em>: <ul> <li>blob hue (radians - LAB): hue in radians of the blob pair, as defined in LAB-LCH color space</li> <li>object or swatch: whether the stimulus pair were whole objects or 8x8 swatches</li> <li>matched or unmatched: whether the stimulus pair were matched in terms of blob ID (refers to spatial configuration)</li> <li>positive stimulus ID: identification number of the positive LC-slope stimulus (refers to spatial configuration)</li> <li>negative stimulus ID: identification number of the negative LC-slope stimulus (refers to spatial configuration) <ul> <li>note that the above two IDs should be identical if the stimulus is a 'matched' pair</li> </ul> </li> <li>participant ID: given participant identification number</li> <li>proportion positive: proportion of trials in which participant chose the positive stimulus as more saturated (out of 5 total trials per stimulus pair)</li> </ul> </li> </ul> <p> </p> <p>Stimuli pngs are in the zip file s<em>timuli.zip</em>. Pngs are not gamma-corrected. Blob and fruit stimulus sets are separated by folder; object and swatch stimulus sets are also separated by folder.</p> <p>Fruit pngs are labeled:</p> <p> fruit_[object/swatch]_[fruitName]-[negative/positive].png</p> <p>For blob pngs, six possible spatial configurations for each hue were used. An ID was given for each configuration. Blob pngs are labeled:</p> <p> blob_[object/swatch]_hue[hueInRadians]_ID[1-6]-[negative/positive].png</p> <p> </p> <p>Statistics of the stimulus images are presented in the files <em>fruit_stats_objects.csv</em>, <em>fruit_stats_swatches.csv</em>, <em>blob_stats_objects.csv</em>, and <em>blob_stats_swatches.csv</em>. Each column represents a different stimulus image. Each row represents a different statistic taken across the distribution of pixels. Calculations were made in CIELAB-LCH color space ('white point' defined as white of monitor: CIE1931 xyY 0.3328, 0.3343, 142.35).</p>
SSVEP database elicited by four visual stimuli types
<ul> <li>The database consists of 108 electroencephalographic files from 27 participants performing a 5-target selection task. </li> <li>Each participant performed one experimental session.</li> <li>All datasets were collected on channels PO7, PO3, POz, PO4, PO8, O1, Oz, and O2, according to the 10–20 EEG electrode placement standard.</li> <li>For the visual stimuli, we consider the On-Off and Checkerboard patterns with luminance modulated by rectangular and sinusoidal functions, resulting in a total of four types of visual stimuli: Checkerboard pattern with the rectangular modulated signal (Sxx-C.txt); Checkerboard pattern with sinusoidal modulated signal (Sxx-mC.txt); On-Off pattern with sinusoidal modulated signal (Sxx-mOO.txt) and On-Off pattern with rectangular modulated signal (Sxx-OO.txt), where "Sxx" represents the subject number and 01 <= xx <= 27.</li> <li>In each file columns 1 to 8 correspond to EEG data and column 9 corresponds to the marks channel.</li> <li>Each phase of the experiment block is identified with a marker.</li> <li>The phases of one experiment trial are Fixation(201), Target Presentation(202), Preparation(203), Stimulation(101-105), and Rest(200).</li> <li>Marker numbers 101, 102, 103, 104, and 105, encodes de target frequency applied during the "Stimulation" stage in a trial. They are associated with the stimulation frequencies as follows: 101 - 24 Hz; 102 - 20 Hz; 103 - 15 Hz; 104 - 10.909 Hz and, 105 - 8.57 Hz</li> <li>Files can be easily accessible with EEG-dedicated MATLAB toolboxes, such as Fieldtrip and EEGLAB.</li> </ul>
Assesment of the visual stimuli properties in P300 paradigm
Open the record for dataset details and reuse information.
Listening experiment and Stimuli for: Adjustable Deterministic Pseudonymization of Speech
<p>Web pages for listening experiment, with stimuli included, as reported in: Adjustable Deterministic Pseudonymization of Speech</p> <p>The listening experiments can be run locally offline. After unpacking the files, the listening experiment can be run locally or in a web site by pointing a web browser to the index.html file.</p> <p>A report discussing the pseudonymization results can be found at doi: 10.5281/zenodo.3773931</p> <p>A dataset created with this expriment can be found at doi: 10.5281/zenodo.3773936</p> <p>The <em>akouste</em> listening experiment software can be found at doi: 10.5281/zenodo.3712142 on Github</p> <p>The <em>Pseudonymize</em> <em>Speech</em> <em>Praat</em> script can be found at doi: 10.5281/zenodo.3712140</p> <p>The <em>Praat</em> speech software can be found at <em>www.praat.org</em></p>
"The Veiled Virgin illustrates visual segmentation of shape by cause": Stimuli and Experimental Data
<p>Stimuli and raw experimental data from the experiments reported in PNAS article "The Veiled Virgin illustrates visual segmentation of shape by cause"</p>
Standstill to the beat: Differences in involuntary movement responses to simple and complex rhythms (SOUND STIMULI)
<p>Sound stimuli used in the 2019 "Nordic Championship of Standstill" experiment, presented in the paper titled "Standstill to the beat: Differences in involuntary movement responses to simple and complex rhythms".</p>
"Mapping specific mental content during musical imagery" - Musical stimuli
<p>Six instrumental melodies composed by Joe Hisaishi, used as stimuli in the paper "<strong>Mapping the contents of consciousness during musical imagery"</strong></p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.