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459 results for “ecg”
PsPM-FER02: PSR, SCR, ECG and respiration measurements from a 3 conditions x 3 experimental sessions repeated-measures design to assess the return of fear
<p>This dataset includes pupil size response (PSR), skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements. Also included are CS and US information, keypress responses, keypress response times, key correctness and shock expectancy ratings at the end of the experiment for 74 healthy unmedicated participants (33 males and 41 females aged 24.2+/-3.9 years) participating in a 3 conditions x 3 experimental sessions repeated-measures design to assess the return of fear. CS were colored triangles (yellow/red/blue). US consisted of a 500 ms train of 250 square pulses with individual pulse width of 0.2 ms. SOA between the CS onset and US was 3.5 s. CS and US co-terminated. The ITI was randomly determined as discrete values between 7-11 seconds (mean 9 seconds).</p>
PsPM-REW2: SCR, ECG, respiration, and eyetracking measurements in a Pavlovian appetitive conditioning task with juice delivery with acquisition and recall test after one week
<p>This dataset contains skin conductance responses (SCR), electrocardyogram (ECG), respiration, pupil size (PSR), and gaze coordinates measurements for 34 healthy unmedicated participants (20 females and 14 males aged 24.9 +/- 4.1) participating in a Pavlovian differential cued rewarding conditioning experiment with 2 sessions. <br>CSs were isoluminant colored triangles presented on the screen center with grey background.<br>US was a sip of the favourite juice selected individually. SOA between the CS onset and US was 5.5 s. Participants underwent the conditioning task with CSs (CS+ 50% reinforced) and US delivery in session 1 with 2 blocks, and were tested in a retention/extinction task one week later in session 2 with 2 blocks. No US was delivered during session 2. The ITI was jittered on each trial uniformly at random between 9 to 16 s. The blocks in each session were recorded on the same day with self-paced breaks.</p>
PsPM-REW1: SCR, ECG, respiration, and eyetracking measurements in a Pavlovian appetitive conditioning task with juice delivery with acquisition and recall test after one week
<p>This dataset contains skin conductance responses (SCR), electrocardyogram (ECG), respiration, pupil size (PSR), and gaze coordinates measurements for 37 healthy unmedicated participants (26 females and 11 males aged 24.2 +/- 4.2) participating in a Pavlovian differential cued rewarding conditioning experiment with 2 sessions. <br>CSs were isoluminant colored triangles presented on the screen center with grey background.<br>US was a sip of the favourite juice selected individually. SOA between the CS onset and US was 5.5 s. Participants underwent the conditioning task with CSs (CS+ 50% reinforced) and US delivery in session 1 with 2 blocks, and were tested in a retention/extinction task one week later in session 2 with 2 blocks. No US was delivered during session 2. The ITI was jittered on each trial uniformly at random between 9 to 16 s. The blocks in each session were recorded on the same day with self-paced breaks.</p>
Dataset of Concurrent EEG, ECG, and Behavior with Multiple Doses of transcranial Electrical Stimulation - BIDS
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EEG, ECG and pupil data from young and older adults: rest and auditory cued reaction time tasks
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PsPM-HRM1-2: SCR and ECG measurements in response to white noise sounds and an auditory oddball task
<p>This dataset includes skin conductance response (SCR) and electrocardiogram (ECG) for each of 61 healthy unmedicated participants (28 males, 32 females, 1 unassigned, aged 25.8 +/- 4.6 years) in response to 20 broadband white noise sounds (HRM1) or 10 oddball tones in a oddball task (HRM2). Some participants did not did not complete HRM1 or HRM2 or were excluded from analysis such that there are 56 recordings for HRM1 and 58 recordings for HRM2. White noise sounds in HRM1 were 1 s long with 10 ms on- and offset ramp and presented at ~85 dB. Oddball and standard sounds in HRM2 were 50 ms long, with 10 ms on- and offset ramp, and presented at ~75 dB. Sound frequency was 440 Hz or 460 Hz, randomly balanced per participant to oddballs and standards. SOA between white noise sounds and oddball tones was selected randomly on each trial from 30 s, 35 s or 40 s. All stimuli were presented in one block. There is a marker for each sound onset (including standard tones) in the windaq files.</p>
PsPM-HRM5: SCR, ECG and respiration measurements in response to positive/negative IAPS pictures, and neutral/aversive sounds
<p>This dataset includes skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements for each of 19 healthy unmedicated participants (8 males and 11 females aged 26.1 +/- 5.4 years) in response to 65 dB and 85 dB sounds as well as the 60 most arousing negative and the 60 most arousing positive (excluding explicit nude) IAPS pictures, presented for 1 s each. ITI was between 4-16 s.</p>
PsPM-RRM1-2: SCR, ECG, respiration and eye tracker measurements in response to electric stimulation or visual targets
<p>This dataset includes skin conductance response (SCR), electrocardiogram (ECG), respiration and eye tracker (including pupillometry) measurements for each of 29 healthy unmedicated participants (7 males and 22 females aged 23.5 +/- 3.6 years) in response to 10 discomforting electric stimulations to the forearm (RRM1) or 10 visual targets in a visual detection task (RRM2). The sample partly overlaps with data set <a href="https://doi.org/10.5281/zenodo.1292568">PsPM-FR</a>. Some participants did not take part in RRM1 or RRM2 such that there are 25 recordings for RRM1 and 26 recordings for RRM2. Electric shock stimuli are 0.2 ms wide square current pulse repeated at 500 Hz for 500 ms and individually adjusted amplitude just below the pain threshold. Visual stimuli are red crosses (+) embedded in a white digit stream; each stimulus is presented during 200 ms and separated by a 800 ms blank interval. ITI is selected randomly on each trial from 40 s, 45 s or 50 s. A baseline period with distractors but no targets concludes experiment RRM2. (This is in contrast to the methods description in Bach et al. (2016), according to which the baseline period was randomly either in the beginning or at the end of the experiment. This discrepancy was caused by an error in the code that controlled the experiment presentation.)</p>
PsPM-TC: SCR, ECG, EMG and respiration measurements in a discriminant trace fear conditioning task with visual CS and electrical US.
<p>This dataset includes skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements. Also included are CS and US information, keypress responses and keypress response times from 18 healthy unmedicated participants (8 males and 10 females aged 23.89+/-2.52 years) participating in a classical (Pavlovian) discriminant trace fear conditioning task. CS were a red and a blue rectangle presented for 3 seconds. US consisted of 0.5 s square electric pulses with 0.2 ms duration and 10 Hz frequency. SOA between the CS onset and US was 4 s. The ITI was randomly determined on each trial to be 7, 9, or 11 s.</p>
PsPM-DoxMemP: SCR, ECG and respiration measurements in a delay fear conditioning task with visual CS and electrical US.
<p>This dataset includes skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements. Also included are CS and US information, keypress responses and keypress response times for 20 healthy unmedicated participants (7 males and 13 females aged 26.15+/-4.15 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. CS were a red and a blue rectangle. US consisted of 0.5 s square electric pulses with 0.2 ms duration and 10 Hz frequency. SOA between the CS onset and US was 3.5 s. CS and US co-terminated. The ITI was randomly determined on each trial to be 7, 9, or 11 s.</p>
PsPM-FR: SCR, ECG and respiration measurements in a delay fear conditioning task with visual CS and electrical US.
<p>This dataset includes skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements. Also included are CS and US information, keypress responses and keypress response times for 31 healthy unmedicated participants (09 males and 23 females aged 23.32+/-3.61 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. CS were a red and a blue rectangle. US consisted of 0.5 s square electric pulses with 0.2-ms duration and 10 Hz frequency. SOA between the CS onset and US was 3.5 s. CS and US co-terminated. During extinction phase, an auditory startle probe (ST) was delivered 3.8 s after CS onset via headphones (100 dB, 50 ms duration with 2ms on- and offset ramp). The ITI was randomly determined on each trial to be 7, 9, or 11 s.</p> <p> </p>
PsPM-SC4B: SCR, ECG, EMG, PSR and respiration measurements in a delay fear conditioning task with auditory CS and electrical US
<p>This dataset includes pupil size response (PSR), skin conductance response (SCR), electrocardiogram (ECG), electromyogram (EMG) and respiration measurements. Also included are CS and US information, keypress responses, keypress response times, key correctness and shock ratings for each of 21 healthy unmedicated participants (10 males and 11 females aged 22.9+/-3.0 years; discrepancies to published studies are due to misprints and exclusion of a subject with incomplete data, which was excluded in all conducted studies as well as here) participating in a classical (Pavlovian) discriminant delay fear conditioning task. Two pairs of CS+ and CS-, either complex or simple, were delivered with headphones (HD518, Sennheiser, Wedemark-Wennebostel, Germany) at about 68 dB. Complex stimuli were a sequence of four rising (400 to 800 Hz) or falling (800 to 400 Hz) sounds lasting 1 s each. Simple stimuli were tones with constant frequency (400 or 800 Hz) presented for 4 s. US consisted of square electric pulses with 0.2-ms duration and 10 Hz frequency, resulting in a total US duration of 0.5 s. SOA betwen the CS and US was 3.5 s. The ITI was randomly determined on each trial to be 7, 9, or 11 s.</p>
PsPM-DoxMem1: SCR, ECG and respiration measurements in an RCT using doxycycline/placebo during delay fear conditioning and retention.
<p>This dataset includes skin conductance response (SCR), electrocardiogram (ECG), respiration and electromyogramm (EMG, only relevant for retention phase) measurements. Also included are CS and US information, keypress responses and keypress response times for 78 healthy participants (40 males and 38 females aged 23.3+/-3.6 years) under either doxycycline or placebo during a classical (Pavlovian) discriminant delay fear conditioning task. CS were a red and a blue screen. US consisted of 0.5 s square electric pulses with participant-specific duration and 500 Hz frequency. SOA between the CS onset and US was 3.5 s. CS and US co-terminated. Before the fear conditioning task, participants completed an N-back task and several questionnaires. During the retention/extinction phase one week after learning and without drug, an auditory startle probe (ST) and no US was delivered 3.5 s after CS onset via headphones (100 dB, 50 ms duration with 2ms on- and offset ramp). In an immediately following re-learning phase, the ST was omitted and the CS reinforced with the same schedule as during acquisition. The ITI was randomly determined on each trial to be 7, 9, or 11 s.</p>
PsPM-LI: SCR, ECG, PSR and respiration measurements in a delay fear conditioning task with auditory CS and electrical US.
<p>This dataset includes pupil size response (PSR), skin conductance response(SCR), electrocardiogram (ECG) and respiration measurements for each of 20 healthy unmedicated participants (8 males and 12 females aged 22.8+/-3.3 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. (One additional participant in the initial sample in Korn et al. (2017) - but who did not finish the experiment and was not included into the analysis - is not contained in this dataset.) The acquisition data is separated into two sessions which were recorded consecutively with a break of approximately 5 min. CS consist of two sine tones with constant frequency (220 Hz or 440 Hz, 50-ms onset and offset ramp) and last for 6.5 s. US is a 0.5 s train of electric square pulses delivered with a constant current stimulator (Digitimer DS7A, Digitimer, Welwyn Garden City, UK) on participants' dominant forearm through a pin-cathode/ring-anode configuration. SOA betwen the CS and US is 6 s. The ITI is randomly determined on each trial to be 7, 9, or 11 s.</p>
CODE-test: An annotated 12-lead ECG dataset
<pre># Annotated 12 lead ECG dataset Contain 827 ECG tracings from different patients, annotated by several cardiologists, residents and medical students. It is used as test set on the paper: "Automatic diagnosis of the 12-lead ECG using a deep neural network". https://www.nature.com/articles/s41467-020-15432-4. It contain annotations about 6 different ECGs abnormalities: - 1st degree AV block (1dAVb); - right bundle branch block (RBBB); - left bundle branch block (LBBB); - sinus bradycardia (SB); - atrial fibrillation (AF); and, - sinus tachycardia (ST). Companion python scripts are available in: https://github.com/antonior92/automatic-ecg-diagnosis -------- Citation ``` Ribeiro, A.H., Ribeiro, M.H., Paixão, G.M.M. et al. Automatic diagnosis of the 12-lead ECG using a deep neural network. Nat Commun 11, 1760 (2020). https://doi.org/10.1038/s41467-020-15432-4 ``` Bibtex: ``` @article{ribeiro_automatic_2020, title = {Automatic Diagnosis of the 12-Lead {{ECG}} Using a Deep Neural Network}, author = {Ribeiro, Ant{\^o}nio H. and Ribeiro, Manoel Horta and Paix{\~a}o, Gabriela M. M. and Oliveira, Derick M. and Gomes, Paulo R. and Canazart, J{\'e}ssica A. and Ferreira, Milton P. S. and Andersson, Carl R. and Macfarlane, Peter W. and Meira Jr., Wagner and Sch{\"o}n, Thomas B. and Ribeiro, Antonio Luiz P.}, year = {2020}, volume = {11}, pages = {1760}, doi = {https://doi.org/10.1038/s41467-020-15432-4}, journal = {Nature Communications}, number = {1} } ``` ----- ## Folder content: - `ecg_tracings.hdf5`: The HDF5 file containing a single dataset named `tracings`. This dataset is a `(827, 4096, 12)` tensor. The first dimension correspond to the 827 different exams from different patients; the second dimension correspond to the 4096 signal samples; the third dimension to the 12 different leads of the ECG exams in the following order: `{DI, DII, DIII, AVR, AVL, AVF, V1, V2, V3, V4, V5, V6}`. The signals are sampled at 400 Hz. Some signals originally have a duration of 10 seconds (10 * 400 = 4000 samples) and others of 7 seconds (7 * 400 = 2800 samples). In order to make them all have the same size (4096 samples) we fill them with zeros on both sizes. For instance, for a 7 seconds ECG signal with 2800 samples we include 648 samples at the beginning and 648 samples at the end, yielding 4096 samples that are them saved in the hdf5 dataset. All signal are represented as floating point numbers at the scale 1e-4V: so it should be multiplied by 1000 in order to obtain the signals in V. In python, one can read this file using the following sequence: ```python import h5py with h5py.File(args.tracings, "r") as f: x = np.array(f['tracings']) ``` - The file `attributes.csv` contain basic patient attributes: sex (M or F) and age. It contain 827 lines (plus the header). The i-th tracing in `ecg_tracings.hdf5` correspond to the i-th line. - `annotations/`: folder containing annotations csv format. Each csv file contain 827 lines (plus the header). The i-th line correspond to the i-th tracing in `ecg_tracings.hdf5` correspond to the in all csv files. The csv files all have 6 columns `1dAVb, RBBB, LBBB, SB, AF, ST` corresponding to weather the annotator have detect the abnormality in the ECG (`=1`) or not (`=0`). 1. `cardiologist[1,2].csv` contain annotations from two different cardiologist. 2. `gold_standard.csv` gold standard annotation for this test dataset. When the cardiologist 1 and cardiologist 2 agree, the common diagnosis was considered as gold standard. In cases where there was any disagreement, a third senior specialist, aware of the annotations from the other two, decided the diagnosis. 3. `dnn.csv` prediction from the deep neural network described in the paper. THe threshold is set in such way it maximizes the F1 score. 4. `cardiology_residents.csv` annotations from two 4th year cardiology residents (each annotated half of the dataset). 5. `emergency_residents.csv` annotations from two 3rd year emergency residents (each annotated half of the dataset). 6. `medical_students.csv` annotations from two 5th year medical students (each annotated half of the dataset). </pre>
PsPM-FER01: PSR, SCR, ECG and respiration measurements from a discriminant delay fear conditioning task with visual CS and electrical US.
<p>This dataset includes pupil size response (PSR), skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements. Also included are CS and US information and shock expectancy ratings at the end of the experiment for 30 healthy unmedicated participants (12 males and 18 females aged 23.9+/-4.4 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. Fear acquisition consisted of 10 CS- and 32 CS+ trials (16 CSa+/16 CSb+). Half of the CS+ trials were paired with an electric shock. CS were colored triangles (yellow/red/blue). US consisted of a 500 ms train of 250 square pulses with individual pulse width of 0.2 ms. SOA between the CS onset and US was 3.5 seconds. CS and US co-terminated. The ITI was randomly determined as discrete values between 7-11 seconds (mean 9 seconds).</p> <p> </p>
Surface electrocardiogram (ECG) dataset recorded during relaxation in 70 healthy subjects
<p><strong>Study Sample and Ethics Statement</strong></p> <p>The sample consisted of 71 university students, average age 20.38 years (<em>SD</em> = 2.96), 78.8% female. Subjects with previous cardio-vascular disorders and irregular ECG were excluded. The study has been approved by the Institutional Review Board of the Department of Psychology, University of Belgrade No. 2018-19. All participants signed Informed Consents in accordance with the Declaration of Helsinki.</p> <p>In the course of visual examination, it was decided to discard ECG from one subject due to the presence of bigeminial arythmia, so further analysis was performed on 70 subjects instead of 71.</p> <p><strong>Measurement Setup</strong></p> <p>BIOPAC sensors (Biopac Systems Inc., Camino Goleta, CA, USA) were used for recording biosignals in another study (<a href="http://empirijskaistrazivanja.org/wp-content/uploads/2021/04/EIP2020_conf_proceedings.pdf#page=17">Bjegojević et al., 2020</a>). Here, we used only ECG signals recorded in sitting relaxed position from standard bipolar Lead I using the BIOPAC MP150 unit with AcqKnowledge software and ECG 100C module with surface H135SG Ag/AgCl electrodes (Kendall/Covidien, Dublin, Ireland). In order to decrease skin-electrode impedance, the skin was cleaned with Nuprep gel (Weaver & Co., Aurora, USA) to reduce skin-electrode impedance. The sampling frequency was set at 2000 Hz and the gain was set to 1000.</p> <p>ECG signals were recorded during relaxation in a sitting position and data were recorded during 2 min long intervals. More information is available in the article [<a href="https://onlinelibrary.wiley.com/doi/10.1111/anec.12919">1</a>].</p> <p><strong>Dataset, Code, and Feature Extraction Instructions</strong></p> <ol> <li><a href="https://zenodo.org/record/5736849/files/analysisECG.R?download=1">analysisECG.R</a>, function with analysis procedures written in <a href="https://www.r-project.org/">R programming language</a></li> <li><a href="https://zenodo.org/record/5736849/files/anec12919-sup-0001-supinfo.pdf?download=1">anec12919-sup-0001-supinfo.pdf</a>, detailed ECG processing and feature extraction procedure (also available as <a href="https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2Fanec.12919&file=anec12919-sup-0001-Supinfo.docx">supplementary material</a> for article [<a href="https://onlinelibrary.wiley.com/doi/10.1111/anec.12919">1</a>])</li> <li><a href="https://zenodo.org/record/5736849/files/ecg_70.txt?download=1">ecg_70.txt</a>, .txt data file, text format</li> <li><a href="https://zenodo.org/record/5736849/files/mainECG.R?download=1">mainECG.R</a>, a main program written in R programming language</li> <li><a href="https://zenodo.org/record/5736849/files/R-studio-version-info.txt?download=1">R-studio-version-info.txt</a>, the version of <a href="https://www.rstudio.com/">R Studio</a> where the code was tested</li> <li><a href="https://zenodo.org/record/5736849/files/R-version-info.txt?download=1">R-version-info.txt</a><a href="https://zenodo.org/api/files/aa8d999e-1b08-44b5-883f-0540afe8feb8/R-version-info.txt"> </a>, the version of R programming language where the code was tested</li> </ol> <p>For ECG-based feature extraction, we used the following R packages:</p> <ol> <li><strong>signal</strong> - Signal Processing Functions (signal developers (2014). <em>signal: Signal processing</em>. <a href="http://r-forge.r-project.org/projects/signal/">http://r-forge.r-project.org/projects/signal/</a>)</li> <li><strong>pracma</strong> - Practical Numerical Math Functions ( Borchers, H. W. (2019). <em>Package ‘pracma’: Practical numerical math functions</em>. R package version, 2(1). <a href="https://CRAN.R-project.org/package=pracma">https://CRAN.R-project.org/package=pracma</a>)</li> </ol> <p>Please, note that the results of personality trait tests are not available in the current dataset. We are planning to open them in our future research. For more information and planned availability in open access, please, contact the corresponding author of [<a href="https://onlinelibrary.wiley.com/doi/10.1111/anec.12919">1</a>] by e-mail (<a href="mailto:nadica.miljkovic@etf.bg.ac.rs">nadica.miljkovic@etf.bg.ac.rs</a>).</p> <p><strong>Citing Instruction</strong></p> <p>If you find these signals and code useful for your own research or teaching class, please cite relevant dataset and supporting publications:</p> <ol> <li> <p>Boljanić, T., Miljković, N., Lazarević, L. B., Knežević, G., & Milašinović, G. (2021). Relationship between electrocardiogram-based features and personality traits: Machine learning approach. <em>Annals of Noninvasive Electrocardiology</em>, 00, e12919. <a href="https://doi.org/10.1111/anec.12919">https://doi.org/10.1111/anec.12919</a></p> </li> <li> <p>Bjegojević, B., Milosavljević, N., Dubljević, O., Purić, D., & Knežević, G. (2020). <a href="http://empirijskaistrazivanja.org/wp-content/uploads/2021/04/EIP2020_conf_proceedings.pdf#page=17">In pursuit of objectivity: Physiological measures as a means of emotion induction procedure validation</a>. <em>XXIVI Scientific Conference on Empirical Studies in Psychology</em>, p. 17-19.</p> </li> <li> <p>Boljanić, T., Miljković, N., Lazarević B. Lj., Knežević, G., & Milašinović, G. (2021). Surface electrocardiogram (ECG) dataset recorded during relaxation in 70 healthy subjects (Version 1) [Data set]. <em>Zenodo</em>. <a href="https://doi.org/10.5281/zenodo.5599239">https://doi.org/10.5281/zenodo.5599239</a></p> </li> </ol>
PsPM-RRM3: SCR, ECG and respiration measurement in response to aversive/arousing IAPS pictures, and neutral/aversive sounds
<p>This dataset includes skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements for each of 20 healthy unmedicated participants (10 males and 10 females aged 25.3 +/- 5.1 years; male/female numbers were misprinted in Bach et al. 2016) in response to negatively and positively arousing IAPS pictures and neutral (65 dB) and aversive (85 dB) white noise sounds. All stimuli had 1 s duration. ITI was selected randomly on each trial from 40 s, 45 s or 50 s.</p>
PsPM-DoxMem2: Pupil, SCR, ECG, EMG and respiration measurement in a classical pavlovian discriminant delay fear conditioning task, reminder under doxycycline/placebo, retention and re-learning
<p>This dataset includes eyetracker, skin conductance response (SCR), electrocardiogram (ECG), respiration and electromyogram (EMG, only relevant for retention phase) measurements. Also included are CS and US information, keypress responses and keypress response times for 79 healthy participants (40 males and 39 females aged 24.8+/-4.9 years). Participants underwent a classical (Pavlovian) discriminant delay fear conditioning task with 1 CS- and 2 CS+ (50% reinforcement), were reminded of one CS+ one week later under either doxycycline or placebo, and were tested in a retention/extinction and re-learning task another week later. CS were isoluminant coloured triangles. US consisted of 0.5 s square electric pulses with 0.2 ms duration and 500 Hz frequency. SOA between the CS onset and US was 3.5 s. CS and US co-terminated. Before the fear conditioning task, participants completed several questionnaires. During the retention/extinction phase, an auditory startle probe (ST) and no US was delivered 3.5 s after CS onset via headphones (102 dB, 40 ms duration with 2 ms on- and offset ramp). In an immediately following re-learning phase, the ST was omitted and the CS reinforced with the same schedule as during acquisition. The ITI was randomly determined on each trial to be 7, 9, or 11 s.</p> <p> </p>
PsPM-VIS: SCR, ECG, respiration and eyetracker measurements in a delay fear conditioning task with visual CS and electrical US
<p>This dataset consists of a three-block experiment conducted with 29 healthy unmedicated participants (17 females and 12 males aged 25.3 +/- 3.7). The experiment contains a classical (Pavlovian) discriminant delay fear conditioning test. CSs are 2 full-screen fractals of approximate brightness, contrast, and spatial frequency. US is a train of electric square pulses delivered with a constant current stimulator on participants' dominant forearm through a pin-cathod/ring-anode configuration. SOA between the CS and US is 3.5 s. The first 2 blocks are fear acquisition, with 15 CS+US+, 15 CS+US-, and 30 CS- in each block, and the last block is an extinction phase with 20 CS- and 20 CS+ trials without US delivery. The order of trials in each block was randomized. No fixation cross was presented during CS. ITI is randomly determined on each trial to be an integer between 7 - 11 s. During ITI, a black fixation cross was presented in the center of a grey background (RGB 0.7, 0.7, 0.7). The blocks were recorded on the same day with a self-paced break. For all three blocks this dataset contains skin conductance responses (SCR), electrocardyogram (ECG), respiration, pupil size (PSR), and gaze coordinates measurements.</p>
ScienceDex guides
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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.