Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
117
datasets available to search
ShareScore release 0.9.0
Dataset results
117 results for “reaction time”
ASRT (alternating serial reaction time)
Open the record for dataset details and reuse information.
EEG, ECG and pupil data from young and older adults: rest and auditory cued reaction time tasks
Open the record for dataset details and reuse information.
Can a knee sleeve influence ground reaction forces and knee joint power during a step-down hop in participants following ACL reconstruction? Discrete and time-continuous datasets
<p>Using a cross-over design, we estimated GRF and knee kinematics and kinetics during a step-down hop for 30 participants (age 26.1 [SD 6.7] years, 14 women) following ACL reconstruction (median 16 months post-surgery) with and without wearing a knee sleeve. In a subsequent randomised clinical trial, participants in the ‘Sleeve Group’ (n=9) then wore the sleeve for 6 weeks at least 1 hour daily, while a ‘Control Group’ (n=9) did not wear the sleeve. Statistical parametric mapping (SPM) was used to compare (1) GRF trajectories in the three planes as well as knee joint power between three conditions at baseline (uninjured side, unsleeved injured and sleeved injured side); (2) within-participant changes for GRF and knee joint power trajectories from baseline to follow-up between groups. We also compared discrete peak GRFs and power, rate of (vertical) force development, and mean knee joint power in the first 5% of stance phase. Time-continuous and discrete data are included in this dataset.</p>
Data supplementing Einhäuser, W., Neubert, C. R., Grimm, S., & Bendixen, A. (2024). High visual salience of alert signals can lead to a counterintuitive increase of reaction times. Scientific Reports, 14, 8858.
<p>These files supplement the publication <br>Einhäuser, W., Neubert, C. R., Grimm, S., & Bendixen, A. (2024). High visual salience of alert signals can lead to a counterintuitive increase of reaction times. <em>Scientific Reports, </em>14, 8858. https://doi.org/10.1038/s41598-024-58953-4</p> <p>The files data_expX.mat, where X is the experiment number (1-4), contain the data as described below. </p> <p>The files dataTraining_expX.mat contain the data of the first (training) block of each experiment. They are needed only for the supplemental material. </p> <p>To exemplify the usage, the functions figure2and3.m, figure4.m, figure5.m, figure6.m and Table1.m output the paper's figures and the data of Table 1, respectively; figureS2.m, figureS3.m, figureS4.m and figureS5.m output the figures of the supplemental material (figure S1 needs substantial amounts of external source code to compute the salience maps and is therefore not included).</p> <p><br>data_exp1.mat contains the following variables<br>For alert trials, variable of dimensions subjects x blocks x alert trials (20x10x64); note that only used participants and blocks with alert trials (2 through 11) are included in the data set:<br>alert_aud - the salience level of the alert tone (1-8, corresponding to 54dB(A) through 89 dB(A))<br>alert_vis - the salience level of the alert frame (1-8, corresponding to 0.10 to 8.50 Weber contrasts in logarithmic steps)<br>alert_side - the side on which the alert frame and the tone were presented (1-left, 2-right)<br>alert_fixOk - derived from eye movement data, was the first fixation closer to the alert square than to the center?<br>alert_primaryRT - primary-task reaction time (for alert trials)<br>alert_alertRT - alert-task reaction time <br>alert_correctAlert - was the response (up/down) to the alert correct?<br>alert_intrusionAlert - was there an intrusion (left/right pressed before up or down)?<br>alert_correctPrimary - was the primary task conducted correctly?<br>alert_intrusionPrimary - was there an intrusion for the primary task?<br>alert_timeToFixation - time to first fixation on alert square <br>alert_fixationToResp - time from beginning of fixation to response to the alert <br>alert_fixDur - duration of first fixation after trial onset</p> <p>For no-alert trials, variable of dimensions subjects x blocks x no-alert trials (20x10x448):<br>noalert_correctPrimary - was the primary task conducted correctly?<br>noalert_intrusionPrimary - was there an intrusion for the primary task? (i.e., up/down pressed before left/right)?</p> <p>For all trials, variable of dimensions subjects x blocks x no-alert trials (20x10x512):<br>all_correctPrimary - was the primary task conducted correctly?<br>all_intrusionPrimary - was there an intrusion for the primary task? (i.e., up/down pressed before left/right)?<br>all_RT - reaction time in the primary task<br>all_isAlertTrial - was the trial an alert trial? (useful to map no-alert trials and alert trials on all trials)</p> <p>In addition, there are some raw eye movement data for the alert blocks:<br>alert_eyeX, alert_eyeY - dimension 20 x 10 x 64 x 6000; x and y position in pixel coordinates relative to trial (and alert) onset, 1ms/sample, ends at conclusion of trials, filled up with NaN if duration was less than 6000ms <br>alert_eyeFixX, alert_eyeFixY, alert_eyeFixTon, alert_eyeFixDur - 20 x 10 x 64 x 15; x and y position, onset (in ms relative to trial onset) and duration of fixations during the trial (from onset to primary-task response), filled with NaN when less than 15 fixations were made. Note that the first entry of alert_eyeFixDur along the forth dimension will usually equal the alert_fixDur</p> <p><br>data_exp2.mat contains the same variables as data_exp1.mat with the following exceptions:<br>alert_vis - contains only two levels (1 and 2) corresponding to Weber contrasts of 0.10 and 2.39, respectively<br>alert_dur - the level of duration of the alert frame (1 through 8, corresponding to 25ms, 50ms, 100ms, 200ms, 300ms, 400ms, 600ms, 800ms)<br>alert_aud is not included (all tones were at 54 dB(A))<br>there are only 19 participants; hence the variables are of size 19 x ...<br>note: block 8 for subject 6 contains only 450 trials (57 alert trials), the remainder is filled with NaN.</p> <p><br>data_exp3.mat contains the same variables as data_exp1.mat with the following exceptions:<br>alert_aud - contains only two levels (1 and 2) corresponding to sound levels of 54 dB(A) and 79 dB(A) respectively<br>alert_dur - the level of duration of the alert tone (1 through 8, corresponding to 25ms, 50ms, 100ms, 200ms, 300ms, 400ms, 600ms, 800ms)<br>alert_vis is not included (all alert frames were at 0.10 contrast)</p> <p> </p> <p>data_exp4.mat contains the same variables as data_exp1.mat with the following exceptions:<br>alert_aud - contains only two levels (1 and 2) corresponding to sound levels of 54 dB(A) and 79 dB(A) respectively<br>alert_vis is not included and replaced by<br>alert_condBefore - alert frame contrast level before the saccade (1 - 0.10 contrast, 2 - 2.39 contrast)<br>alert_condAfter - alert frame contrast level after the saccade (1 - 0.10 contrast, 2 - 2.39 contrast)</p> <p><br>dataTraining_expX.mat contains for the first (training) block of experiment X (X being 1, 2, 3 or 4) the following variables of size 20x512 (participant x trial) [19x512 in case of Experiment 2]:<br>all_correctPrimary - was the primary task conducted correctly?<br>all_RT - reaction time in the primary task<br>[Note that there are no alert trials in this block and these data are only used in the supplementary material (part 4)]</p>
Data from: Operando Proton Transfer Reaction-Time of Flight-Mass Spectrometry of Carbon Dioxide Reduction Electrocatalysis
<p>Seven top-level folders</p> <p>GC-PTR-TOF-MS<br> - Raw data and Jupyter Notebook used for analysis of GC-PTR-TOF-MS data</p> <p>LSV-PTR-TOF-MS<br> - Raw data and Jupyter Notebook used for analysis of PTR-TOF-MS data under linear sweep voltammetry</p> <p>MSCP-PTR-TOF-MS<br> - Raw data and Jupyter Notebook used for analysis of PTR-TOF-MS data under multi-step chronopotentiometry</p> <p>PTR-TOF-MS-Calibration<br> - Raw data and Jupyter Notebook used for analysis of PTR-TOF-MS calibration data</p> <p>SEM<br> - Raw images from scanning electron microscope</p> <p>Stability<br> - Raw data of electrochemical stability</p> <p>TEM<br> - Raw images from transmission electron microscopy</p>
Dataset of Reaction Times for the Study of Differential Functional Changes in Visual Performance During Acute Exposure to Microgravity Analogue and their Potential Links with Spaceflight-Associated Neuro-Ocular Syndrome
<p><strong>Title</strong>: "Dataset of Reaction Times for the Study of Differential Functional Changes in Visual Performance During Acute Exposure to Microgravity Analogue and their Potential Links with Spaceflight-Associated Neuro-Ocular Syndrome"<br>Zenodo DOI: 10.5281/zenodo.11840654</p> <p><strong>Contains</strong>: simple-reaction-times-VBRHDT-data.csv<br>Dateset of SRT (simple reaction time) values to visual stimuli in different positions in visual field, binocularly observed, in a microgravity analogue study, in four body positions (vertical, horizontal, -6 deg tild, -15 deg tilt). <br>Total records contained: 3584.</p> <p><strong>Institutional Review Board Statement</strong>: The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee “Carol Davila” University of Medicine and Pharmacy Bucharest, Romania, 14877/26.05.2023. Data was collected in SpaceMed Laboratory , CIeH (Center for Innovation and eHealth) of UMF Carol Davila Bucharest, Romania.</p> <p><strong>Citation and</strong> <strong>Detailed description:</strong> see "<em>Differential functional changes in visual performance during acute exposure to microgravity analogue and their potential links with Spaceflight-Associated Neuro-Ocular Syndrome</em>", 2024, by Iftime A, Tofolean IT, Pintilie V, Călinescu O, Busnatu S, Papacocea IR, Diagnostics ,2024; 14(17):1918. doi: 10.3390/diagnostics14171918 <br>https://pubmed.ncbi.nlm.nih.gov/39272703/</p> <p><strong>Structure</strong>: Dataset is in CSV (Comma-Separated Values) format, UTF-8 encoded, text field delimited with quotation marks, in tidy format; one row is one record from the SRT task, variables values are in columns). The first row is the variable name. The variable are:</p> <p>1) "live_row"<br>- type: integer numbers, sequential;<br>- values: the index (order) of each SRT measurement performed in a body position, by a participant (ID). The value is C-based (first measurement is "0", second measurement is "1", etc).</p> <p>2) "response_time"<br>- type: real numbers, continuous values;<br>- values: response time recorded from the participant; values in miliseconds.</p> <p>3) "target_position_x_deg"<br>- type: real numbers, categorical (4 values: +/- 18.478, +/- 0.75);<br>- values: horizontal visual angle, in visual degrees in the visual field, of the position of the stimulus. Screen coordinates are computed from "0" position, foveal fixation, positive values to the right, negative values to the left.</p> <p>4) "target_position_y_deg"<br>- type: real numbers, categorical (2 values: -0.75, -7.654);<br>- values: vertical visual angle, in visual degrees in the visual field, of the position of the stimulus. Screen coordinates are computed from "0" position, foveal fixation, positive values downward, negative values upward.<br>-Note: For the equivalent polar coordinates (as in planimetry testing) see Figure 2 of the mentioned paper. </p> <p>5) "Contrast_Weber_calibrated"<br>- type: real numbers, categorical (2 values: 50.58, 99.3);<br>- values: Measured Weber contrast of the visual stimulus shown, values in percents.</p> <p>6) "hand"<br>- type: categorical, 1 value ("right");<br>- values: hand used by the participant during SRT task.</p> <p>7) "body_position"<br>- type: categorical (4 values: "vertical (90 deg)", "horizontal (0 deg)", "inclined (-6 deg)", "inclined (-15 deg)" );<br>- values: Body position during the SRT task.</p> <p>8) "ID(anon)"<br>- type: integer number, categorical, 8 values;<br>- values: anonymized ID of the participants in the study (8 persons).</p>
Data from: A reaction norm for flowering time plasticity reveals physiological footprints of maize adaptation
<div> <p>Understanding how plant phenotypes are shaped by their environments is crucial for addressing questions about crop adaptation to new environments. This study investigated the interplay between developmental responses to temperature fluctuations and photoperiod perception in maize that contribute to genotype-by-environment variation in flowering time. We present a physiological reaction norm for flowering time plasticity (PRN-FTP) for studying large collections of genotypes tested in multi-environment trial (MET) networks. Using a new variable for computational envirotyping of sensed photoperiod, it was found that, at high latitudes, different genotypes in the same environment can experience hours-long differences in photoperiod. This emphasizes the importance of considering genotype-specific differences in the experienced environment when investigating plasticity. A statistical framework is introduced for modeling the PRN-FTP as a non-linear response function, with parameters putatively linked to different regulatory modules for flowering time. Applying the PRN-FTP to a sample of global breeding material for maize showed that tropical and temperate maize occupy distinct territories of the trait space for PRN-FTP parameters, supporting that the geographical spread and adaptation of maize was differentially mediated by exogenous and endogenous pathways for flowering time regulation. Our results have implications for understanding crop adaptation and for future crop improvement efforts.</p> </div>
Fig. 3 in Species-level identification of trypanosomes infecting Australian wildlife by High-Resolution Melting - Real Time Quantitative Polymerase Chain Reaction (HRM-qPCR)
Fig. 3. Phylogenetic tree of seven Trypanosome species and subsequent genotypes constructed with sequences of the amplicons generated by the HRMqPCR primers.
Fig. 4 in Species-level identification of trypanosomes infecting Australian wildlife by High-Resolution Melting - Real Time Quantitative Polymerase Chain Reaction (HRM-qPCR)
Fig. 4. Amplification plots, melt curves and standard curves of T. copemani, T. vegrandis G7 and T. noyesi G8 prepared from a plasmid containing trypanosome species.
Fig. 5. A-D in Species-level identification of trypanosomes infecting Australian wildlife by High-Resolution Melting - Real Time Quantitative Polymerase Chain Reaction (HRM-qPCR)
Fig. 5. A-D: Derivative melt curves showing mock mixed infections generated from plasmid clones containing the following DNA: (A) T. noyesi G8 and T. copemani; (B) T. vegrandis G7 and T. copemani; (C) T. vegrandis G7 and T. noyesi G8; (D) T. vegrandis G7, T. noyesi G8 and T. copemani.
Fig. 1 in Species-level identification of trypanosomes infecting Australian wildlife by High-Resolution Melting - Real Time Quantitative Polymerase Chain Reaction (HRM-qPCR)
Fig. 1. Multiple sequence alignment of a portion of the 18S rDNA of seven Trypanosome species and subsequent genotypes used to design the HRM-qPCR assays.
Data from: A reaction norm for flowering time plasticity reveals physiological footprints of maize adaptation
Open the record for dataset details and reuse information.
Adaptation to hand-tapping affects sensory processing of numerosity directly: evidence from reaction times and confidence
<p>Each file contains a matrix called “MatriceRisultati”. Each row of the matrix “MatriceRisultati” is a trial. </p> <p>The columns contain the following information:</p> <ul> <li>1<sup>st</sup>: Number of trial</li> <li>2<sup>nd</sup>: Test numerosity</li> <li>3<sup>rd</sup>: Subject response on numerosity </li> <li>4<sup>th</sup>: Subject response on their confidence level</li> <li>5<sup>th</sup>: Response time</li> <li>6<sup>th</sup>: 0 if the test numerosity< 16; 1 if the test numerosity> 16</li> </ul>
Real time, in-situ deuteriding of uranium encapsulated in grout; effects of temperature on the uranium-deuterium reaction
<p>To accurately predict the initiation and evolution of uranium hydride potentially present in nuclear waste containers, studies of simulated conditions are required. Here, for the first time, the uranium-deuterium reaction was examined in-situ, in real time, whilst within grouted media. A deuterium gas control rig and stainless steel-quartz glass reaction cell were configured on a synchrotron beam line to collect X-ray diffraction and X-ray tomography data. It was found that deuteride formation, and thus hydride formation, was limited by the uranium and grout thermal conductivities and deuteride initiation only commenced above a threshold temperature. Strong adherence between uranium oxide and grout was also observed.</p>
Monitoring the evolution of relative product populations at early times during a photochemical reaction
<p class="MsoNormal"><span>Identifying multiple rival reaction products and transient species formed during ultrafast photochemical reactions and determining their time-evolving relative populations are key steps towards understanding and predicting photochemical outcomes. Yet, most contemporary ultrafast studies struggle with clearly identifying and quantifying competing molecular structures/species amongst the emerging reaction products. Here, we show that mega-electronvolt ultrafast electron diffraction in combination with <em>ab initio</em> molecular dynamics calculations offers a unique route to determine <em>time-resolved </em>populations of the various isomeric products formed after UV (266 nm) excitation of the five-membered heterocyclic molecule thiophenone. This strategy reveals an unexpectedly high (~50%) yield of an episulfide isomer containing a strained 3-membered ring within ~1 ps at early times and rapid interconversions between the rival photoproducts. </span></p>
An orally angiotensin - (1 – 7) inclusion compound reduce time to reaction in 2 stroop task and modify heart rate variability after continuous test in mountain 3 bike cyclists
<p>data for An orally angiotensin - (1 – 7) inclusion compound reduce time to reaction in 2 stroop task and modify heart rate variability after continuous test in mountain 3 bike cyclists,<br> </p> <p>Recently our group showed that hydroxypropyl β-cyclodextrin (HPβ-CD)-Angiotensin-(1-7) (HPβ-CD-Ang-[1-7]) oral formulation affects performance and decreases the perceived effort of mountain bike (MTB) athletes.</p> <p>Twenty-one male MTB practitioners were divided into a continuous protocol time trial and repeated sprint groups. Three hours before a 20-km cycling time trial or 4×30-s repeated all-out sprints on a leg cycle ergometer, the athletes received HPβ-CD-Ang-(1-7) (0.8 mg) or HPβ-CD-placebo (only HPβ-CD) oral capsules over a 7-day interval randomized crossover design. At rest and immediately after the exercise protocol, the ratings of perceived recovery and the visual analog scale were assessed, and the volunteers completed the Stroop task (ST). Heart rate variability was measured at rest and peak effort. There were no differences in the perceived variables. The ST showed that HPβ-CD-Ang-(1-7) supplementation reduced the reaction time (rest 1032±331 ms vs. after protocol 902±286 ms, p=0.05) after the continuous time trial. The withdrawal of the parasympathetic components in the peak effort to the continuous protocol was not different from that of rest in the HPβ-CD-Ang-(1-7) condition. The results are pioneering, especially in humans, but indicate that Angiotensin-(1-7) potentially affects reaction time and the parasympathetic withdrawal after continuous protocol time trial.</p>
Assessment of Chiropractic Treatment Using Reaction and Response Times in Members of the Special Operation Forces (ACT2)
ClinicalTrials.gov study NCT02168153. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Time and spatially-resolved Fourier-Transform Infrared (FTIR) Spectromicroscopy of cellulose in buffered reactions with Trichoderma reesei Cel7A
Open the record for dataset details and reuse information.
Monitoring the evolution of relative product populations at early times during a photochemical reaction
Open the record for dataset details and reuse information.
Proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS) as a tool for studying animal volatile organic compound (VOC) emissions
<p>1. Chemical sensing in vertebrates is crucial in their lives, and efforts are undertaken towards deciphering their chemical language. Volatile organic compounds (VOCs) is a group of chemicals believed to play an essential role in a wide variety of animal interactions. Therefore, understanding what animals sense themselves and untangling the ecological role of their volatile cues can be accomplished by analysing VOC emissions. A Proton-Transfer Reaction Time-of-Flight Mass Spectrometer (PTR-TOF-MS) is an instrument that measures VOCs in real-time in an air sample. Since this technique acts as a hyper-sensitive 'nose' it has a similar potential in deciphering the chemical language of vertebrates.</p> <p>2. Here, we validate the use of PTR-TOF-MS as a tool to measure VOCs from vertebrates, which in turn will help resolve vertebrate interactions through VOCs. The instrument monitors and records the full spectrum of VOCs emitted by an individual with a high accuracy and low detection limit, including transient VOC emissions. We propose and test diverse measuring configurations that allow for measurement of VOC emissions from different vertebrates and their exudates: full body, specific parts of the body, urine and femoral pores. In addition, we test configurations for sudden and short-lasting processes as VOCs emitted during adder skin shedding as well as the emissions of skin secretions upon mechanical and physiological stimulation in amphibia. Our configurations work in tandem with Gas Chromatography Mass Spectrometry (GC-MS) to allow compound structure verification.</p> <p>3. We discuss the configurations and methodologies used and conclude with recommendations for further studies, such as the choice of chamber size and flow. We also report the results of the measurements on vertebrates —that are novel to science— and discuss their ecological meaning.</p> <p>4. We argue that PTR-TOF-MS has a high potential to resolve important unanswered questions in vertebrate chemical ecology with great adaptability to a wide range of experimental setups. If combined with a structure verification tool, such as GC-MS, the creative deployment of PTR-TOF-MS in various future study designs will lead to the identification of ecologically relevant VOCs.</p>
ScienceDex guides
Understand access before you commit
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.