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9 results for “Numerosity perception”
Dataset for "Quantum spin models for numerosity perception"
<p>Data to recreate the figures 2-3, 6-9 of the manuscript "Quantum spin models for numerosity perception". For figure 5, we provide all of the numerically simulated data for the time evolution of our system whose average, spectrum and analysis is presented in the figure.</p> <p>The data is structured in individual folders for every figure and we provide a README file for each folder.</p>
Typical Crossmodal Numerosity Perception in Preterm Newborns
<p>Columns are described within the .xlsx file </p>
Symmetry as a grouping cue for numerosity perception
<p>For the numerosity experiments: each file contains a matrix called “a”. Each row of the matrix “a” is a trial. </p> <p>The columns contain the following information:</p> <ul> <li>1st: Numerosity of test stimulus</li> <li>2nd: Log10 of numerosity of test stimulus divided by the standard numerosity</li> <li>3rd: Participant response (0 = standard stimulus; 1 = test stimulus)</li> <li>4th: 200</li> <li>5th: Standard numerosity </li> <li>6th: Dots size in pixels</li> <li>7th: 10</li> <li>8th: Condition (0= symmetry condition; 1= random condition)</li> <li>9th: Standard-Test order (1 = standard first; 2 = standard second)</li> <li>10th: Response time</li> </ul> <p>For the control experiment: each file contains a matrix called “a”. Each row of the matrix “a” is a trial. </p> <p>The columns contain the following information:</p> <ul> <li>1st: Numerosity of test stimulus</li> <li>2nd: Log10 of numerosity of test stimulus divided by the standard numerosity</li> <li>3rd: Participant response (0 = standard stimulus; 1 = test stimulus)</li> <li>4th: 200</li> <li>5th: Standard numerosity </li> <li>6th: Dots size in pixels</li> <li>7th: 10</li> <li>8th: 0= standard stimulus symmetric and test stimulus random</li> <li>9th: Standard-Test order (1 = standard first; 2 = standard second)</li> <li>10th: Response time</li> </ul>
data set related to article Independent adaptation mechanisms for numerosity and size perception provide evidence against a common sense of magnitude
<p>This record contains raw data related to article Independent adaptation mechanisms for numerosity and size perception provide evidence against a common sense of magnitude</p>
Implicit visuospatial attention shapes numerosity adaptation and perception
<ul> <li>The folder Dataset contains two subfolders referring to the main experiments. Each subfolder contains additional subfolders In which are stored the single subjects’ data for each experimental condition.</li> </ul> <p>In Experiment 1 each file contains two matlab tables called “TBase” and “TAdapt”. Each row of the table is a trial and each column contains the following information:</p> <p>1<sup>st</sup>: Numerosity of the test stimulus</p> <p>2<sup>nd</sup>: Response</p> <p>3<sup>rd</sup>: Reaction Times</p> <p>4<sup>th</sup>: Accuracy </p> <p>5<sup>th</sup>: Test/Adapt side</p> <p>6<sup>th</sup>: N° of presented Adaptors</p> <p> </p> <p>In Experiment 2 each file contains a single table called “T”. Each row of the table is a trial and each column contains the following information:</p> <p>1<sup>st</sup>: Numerosity of the test stimulus</p> <p>2<sup>nd</sup>: Response</p> <p>3<sup>rd</sup>: Stimulus position</p> <p>4<sup>th</sup>: N° of presented stimuli</p>
EEG signature of grouping strategies in numerosity perception
<p><strong>Behavioral Data</strong></p> <p>The excel file contains for each row data from individual participant. We reported the average response (columns B-E) and precision index (Weber fractions; columns G-J) for 6 and 8 items, both grouped and ungrouped.</p> <p> </p> <p><strong>EEG Data</strong></p> <p>The excel file contains for each row data from individual participant. We reported the N1 latency (columns B-K), N1 amplitude (columns M-V) and P2p amplitude (columns X-AG). Values are reported for the subitizing range (3 and 4 items) and the estimation range (6 and 8 items). In the estimation range values are separately reported for spatial arrangement (grouped and ungrouped) and number of subgroups (3 or 4 subgroups).</p>
Feature selective adaptation of numerosity perception
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Fast saccadic eye-movements in humans suggest that numerosity perception is automatic and direct.
<p><span>Fast saccades are rapid automatic oculomotor responses to salient and ecologically important visual stimuli such as animals and faces. Discriminating the number of friends, foe or prey may also have an evolutionary advantage. In this study participants were asked to saccade rapidly towards the more numerous of two arrays. Participants could discriminate numerosities with high accuracy and great speed, as fast as 190 ms. Intermediate numerosities were more likely to elicit fast saccades than very low or very high numerosities. Reaction-times for vocal responses (collected in a separate experiment) were slower, did not depend on numerical range, and correlated only with the slow, not the fast saccades, pointing to different systems. The short saccadic-reaction times we observe are surprising given that discrimination using numerosity estimation is thought to require a relatively complex neural circuit, with several relays of information through parietal and pre-frontal cortex. Our results suggest that fast numerosity-driven saccades may be generated on a single feed-forward pass of information recruiting a primitive system that cuts through the cortical hierarchy and rapidly transforms the numerosity information into a saccade command.</span></p>
Fast saccadic eye-movements in humans suggest that numerosity perception is automatic and direct.
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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.
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DANDI Archive for NWB datasets
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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.