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Dataset results
36 results for “distractor”
PsPM-trSP1: SCR, and heart beat measurement in response to aversive/neutral IAPS pictures while subjected to auditory distractors
<p>This dataset includes skin conductance response (SCR) and pulse time stamp (HB) measurements for each of 60 healthy unmedicated participants (30 males and 30 females aged 23.7 +/- 4.8 years) in response to the 45 most arousing negative, and 45 least arousing neutral IAPS pictures, each presented for 1 s each, while listening to regular or random distractor sounds, as described in Bach et al. (2015). ITI was selected randomly on each trial from 7.65 s, 9 s, or 10.35 s. The experiment was preceded by a 2-minute resting period and divided into 3 blocks, separated by resting periods. Each resting period begins and ends with an event marker in the psychophysiological recordings.</p>
The effects of visual distractors on serial dependence
<p>Datasets and analysis script for two experiments on behavioral serial dependence, using discrimination & orientation adjustment tasks.<br> The datasets are used and described in:<br> Title: "The effects of visual distractors on serial dependence"<br> Authors: Christian Houborg, David Pascucci, Ömer Daglar Tanrikulu & Árni Kristjánsson<br> Year: 2023<br> Journal: Journal of Vision<br> The link and DOI to the related paper will be available soon.</p>
PsPM-trSP4: SCR measurement in response to face photographs withangry, neutral, and fearful expression while subjected to auditory distractors
<p>This dataset includes skin conductance response (SCR) measurements for each of 42 healthy unmedicated participants (21 males and 21 females aged 25.2 +/- 4.0 years) in response to 38 face photographs (modified from the Karolinska Directed Emotional Faces set, KDEF), each presented once with angry, neutral, and fearful expression for 1 s each. Meanwhile, participants were listening to regular or random distractor sounds, as described in Bach et al. (2015). ITI was selected randomly on each trial from 7.5 s, 9.0 s, or 10.5 s (misprinted in the publications), plus a variable delay of around 0.1 s for image loading. The experiment was preceded by a 2-minute resting period and divided into 3 blocks, separated by resting periods. Each resting period begins and ends with an event marker in the SCR recordings.</p>
PsPM-trSP3: SCR measurement in response to aversive/arousing/neutral IAPS pictures while subjected to auditory distractors
<p>This dataset includes skin conductance response (SCR) measurements for each of 40 healthy unmedicated participants (20 males and 20 females aged 21.9 +/- 3.8 years) in response to the 16 most arousing negative, and most arousing positive (excluding explicit nude) and 16 least arousing neutral IAPS pictures, presented for 1 s each in 1 block, while listening to regular or random distractor sounds, as described in Bach et al. (2015). ITI was 4 s, plus a variable delay of around 0.4 s for image loading.</p>
PsPM-trSP2: SCR measurement in response to neutral IAPS pictures while subjected to auditory distractors
<p>This dataset includes skin conductance response (SCR) measurements for each of 61 healthy unmedicated participants (30 males and 31 females, misprinted in Bach et al. 2015, aged 25.7 +/- 4.5 years) in response to the 45 least arousing neutral IAPS pictures, presented for 1 s each in 3 blocks, while listening to regular or random distractor sounds, as described in Bach et al. (2015). Inter stimulus interval was randomly determined as 7.65 s, 9 s, or 10.35 s. Each recording starts with a 2-minute baseline interval.</p>
Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
<p>There has been debate about whether addition of an irrelevant distractor option to an otherwise binary decision influences which of the two choices is taken. We show that disparate views on this question are reconciled if distractors exert two opposing but not mutually exclusive effects. Each effect predominates in a different part of decision space: 1) a positive distractor effect predicts high-value distractors improve decision-making; 2) a negative distractor effect, of the type associated with divisive normalisation models, entails decreased accuracy with increased distractor values. Here, we demonstrate both distractor effects coexist in human decision making but in different parts of a decision space defined by the choice values. We show disruption of the medial intraparietal area (MIP) by transcranial magnetic stimulation (TMS) increases positive distractor effects at the expense of negative distractor effects. Furthermore, individuals with larger MIP volumes are also less susceptible to the disruption induced by TMS. These findings also demonstrate a causal link between MIP and the impact of distractors on decision-making via divisive normalisation.</p>
Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
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Visual-Cortical Enhancement by Acoustic Distractors
<p>This dataset contains the data aggregated for the repeated measures univariate ANOVAs describe in the main text of the paper (under revision): ‘Visual-Cortical Enhancement by Acoustic Distractors: The Effects of Endogenous Spatial Attention and Visual Working Memory Load’. We analyzed the amplitude of sound-elicited ACOP as a function of visual working memory load and endogenous spatial attention.</p> <p>The files: ‘accuracy’, ‘reaction times’, and ‘k-capacity’ refer to behavioral performance. All these files contain data aggregated for the repeated measures univariate ANOVA with factors of correspondence (same/different side relative to sound location) and load (low/high).</p> <p>The other files refer to the ERP components of interest, namely the CDA, the N1 and the ACOP.</p> <p>Each row always corresponds to a participant. Column codes are described below for each file, together with further details:</p> <p><strong>Accuracy</strong>: is reported on a scale 0-1. Column1= participant id number; Column2= High load/different; Column3= High load/same; Column4= Low load/different; Column5= Low load/same</p> <p><strong>Reaction times</strong>: mean rts for trials with correct responses or responses that were within 2 SD from each observer’s mean. Column1= participant id number; Column2= High load/different; Column3= High load/same; Column4= Low load/different; Column5= Low load/same</p> <p><strong>k-capacity</strong>: estimate of participants’ visual working memory capacity, computed using Pashler’s formula. Column1= participant id number; Column2= High load/different; Column3= Low load/different; Column4= High load/same; Column5= Low load/same</p> <p><strong>CDA</strong>: it corresponds to the file ANOVA with factors of hemisphere (contralateral/ipsilateral in relation to where the cue arrow pointed) and load (low/high) for the mean CDA amplitudes (300-900 ms time window, time-locked to the memory array onset). Column1= participant id number; Column2= Low load/ ipsilateral; Column3= Low load/ contralateral; Column4= High load/ ipsilateral; Column5= High load/ contralateral</p> <p><strong>ACOP</strong>: it corresponds to the file ANOVA with factors of hemisphere (contralateral/ipsilateral to side of sound), load (low/high), and correspondence with cued side (same/different) for the mean ACOP amplitudes (280-500 ms time window, time-locked to the sound onset). Column1= participant id number; Column2= Low load/same/ipsilateral; Column3= Low load/different/ipsilateral; Column4= High load/same/ipsilateral; Column5= High load/different/ipsilateral; Column6= Low load/same/contralateral; Column7= Low load/different/contralateral; Column8= High load/same/contralateral; Column9= High load/different/contralateral</p> <p><strong>N1</strong>: it corresponds to the file ANOVA with factors of hemisphere (contralateral/ipsilateral to side of sound), load (low/high), and correspondence with cued side (same/different) for the mean N1 amplitudes (80-150 ms time window, time-locked to the sound onset). Column1= participant id number; Column2= Low load/same/ipsilateral; Column3= Low load/different/ipsilateral; Column4= High load/same/ipsilateral; Column5= High load/different/ipsilateral; Column6= Low load/same/contralateral; Column7= Low load/different/contralateral; Column8= High load/same/contralateral; Column9= High load/different/contralateral</p>
RDK-IAPS paradigm EEG, target vs distractor
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Consistent patterns of distractor effects during decision making
The value of a third potential option or distractor can alter the way in which decisions are made between two other options. Two hypotheses have received empirical support: that a high value distractor improves the accuracy with which decisions between two other options are made and that it impairs accuracy. Recently, however, it has been argued that neither observation is replicable. Inspired by neuroimaging data showing that high value distractors have different impacts on prefrontal and parietal regions, we designed a dual route decision-making model that mimics the neural signals of these regions. Here we show in the dual route model and empirical data that both enhancement and impairment effects are robust phenomena but predominate in different parts of the decision space defined by the options' and the distractor's values. However, beyond these constraints, both effects co-exist under similar conditions. Moreover, both effects are robust and observable in six experiments.
Microsaccades inhibition triggered by a repetitive visual distractor is not subject to habituation: implications for the programming of reflexive saccades
<p>Dataset relative to the manuscript entitled "<strong>Microsaccades inhibition triggered by a repetitive visual distractor is not subject to habituation: implications for the programming of reflexive saccades</strong>"</p>
Suppression of distractors of different luminance through habituation process
<p>Data and analyses of experiments 1 and 2</p> <p>Suppression of distractors of different luminance through habituation process</p>
Habituation to onsets is controlled by spatially selective distractor expectation
<p>Dataset pertaining to the paper "Habituation to onsets is controlled by spatially selective distractor expectation", to appear in the Journal of Experimental Psychology: HPP. </p> <p>The root folder contain a txt file named "AADescription.txt", which contains a detailed explanation of the dataset.</p>
Inhibition of Distractors: The Interaction between Stimuli Characteristics and Habituation
<p><span><span>Data and analysis of the manuscript </span></span></p>
Dataset from "Cueing distraction: Electrophysiological evidence for anticipatory active suppression of distractor location"
<p>Dataset from the following publication:</p> <p>Heuer, A., & Schubö, A. (2019). Cueing distraction: Electrophysiological evidence for anticipatory active suppression of distractor location. <em>Psychological Research. </em>doi: 10.1007/s00426-019-01211-4. </p>
Pedicle Screws Placement Accuracy in Thoracolumbar Spine Using O-arm Navigation VS Standard Cervical Distractor Screws
ClinicalTrials.gov study NCT04196153. IPD Sharing: UNDECIDED. Countries: 1. Publications: 14.
Study Assessing Safety and Performance of OrtoWell Distractor in Patients Undergoing Spinal Surgery
ClinicalTrials.gov study NCT03501810. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Use of a Modified Dentoalveolar Distractor to Retract Maxillary Canines
ClinicalTrials.gov study NCT02332421. IPD Sharing: Not stated. Countries: 1. Publications: 6.
The Effect of Attention Distractor on the Quality of Chest Compression
ClinicalTrials.gov study NCT03124290. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Consistent patterns of distractor effects during decision making
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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.