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Dataset results
17 results for “resting-state fMRI”
Which multiband factor should you choose for your resting-state fMRI study? The Emory Multiband Dataset
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A high resolution 7-Tesla resting-state fMRI test-retest dataset with cognitive and physiological measures
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An isotropic EPI database for rat brain resting-state fMRI
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Resting-state fMRI data for locating causal hubs of memory consolidation in spontaneous brain network
<p>The mouse fMRI data for the paper "<strong>Locating causal hubs of memory consolidation in spontaneous brain network in male mice</strong>"<strong> </strong>published in <strong>Nature Communications </strong>(DOI: 10.1038/s41467-023-41024-z)<strong>. </strong>This includes longitudinal resting-state fMRI data in mice after behavioural training for 1-Day or 5-Day Active Place Avoidance (APA) task, acquired at post-training day 1 and day 8. Due to the large datasets, each group has been packed into several 2GB zip files. They need to be downloaded into the same folder and unpacked together (e.g. 1-Day APA Post training day 1 has five zip files starting with "1DAPA_PostDay1"). The structural and EPI templates and the ROI labels in the AMBMC atlas space are provided in the AMBMC_label.zip. </p>
Data from: The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation
<p>Included are raw neuroimaging and preprocessed neural recording data from "The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation" (see Related Works section; citation will be updated after publication). Please cite this paper if you use any of these data. Refer to the linked github repository for associated code.</p> <p>Neuroimaging data is organized in BIDS format and saved as NIfTI files. We used MION (monocrystalline iron oxide nanoparticle) as a contrast agent. Functional resting state files can be found in the 'func' folder for each imaging session. The final six runs are resting state data (the first two/three are short EPI sequences used to test that MION is present in the brain; all resting state data used in our analyses consist of 300 volumes). The first three of these six runs consist of baseline data with no drug treatment. Four through six are resting state data recorded after I.M. injection of vehicle (2% DMSO in saline), dechloroclozapine (DCZ) or clozapine-N-oxide (CNO). </p> <p>Neural recording data is separated into LFP data, organized by folder, and putative single units, organized the 'Sorted neurons' folder. LFP data folders are named by subject's intial and date of recording. Single units are labeled according to this same system. All data are stored in .mat format and can be opened in MATLAB. KB2.mat files store timing information: the first event in the KBD2 file indicates the start of baseline, pre-injection data acquisition, and the second event indicates the start of post-injection treatment data. The KB3.mat files contains the timing information of the drug injection. As with the fMRI data, we treated animals with I.M. injection of vehicle, DCZ, or CNO. </p> <p>Treatment information for both modalities is as follows. Neuroimaging: 2020/03/16 Animal L DCZ 1; 2020/05/27 Animal H vehicle 1; 2020/06/01 Animal L vehicle 1; 2020/06/08 Animal H DCZ 1; 2020/06/22 Animal L DCZ 2; 2020/06/24 Animal H vehicle 2; 2020/07/06 Animal L vehicle 2; 2020/07/08 Animal H DCZ 2; 2021/10/25 Animal L CNO; 2022/01/13 Animal H CNO. Neural recordings: 2022/04/14 Animal H DCZ 1; 2022/04/21 Animal H vehicle 1; 2022/05/12 Animal H DCZ 2; 2022/05/24 Animal H vehicle 2; 2022/06/03 Animal H CNO; 2022/08/18 Animal L vehicle 1; 2022/08/25 Animal L DCZ 1; 2022/09/01 Animal L DCZ 2; 2022/09/08 Animal L vehicle 2; 2022/09/22 Animal L CNO.</p>
Multi-echo resting-state fMRI networks of healthy volunteers
<p>The dataset contains the resting-state networks of 16 healthy volunteers following multi-echo combination methods: 1) optimal combination 2) tSNR-weighted combination 3) tCNR-weighted combination (PAID method) 4) second echo only (single-echo) After echo combination by one of the methods (or the second echo) 30 independent components were extracted using group ICA and dual regression.</p> <p>Image format: Gunzipped NIfTI (.nii.gz)</p> <p>Time-series format: text file (.txt)</p> <p>The structure of the uploaded folder:</p> <p>- Layer 1: PilmeyerEtAl_ICA_maps_and_timeseries - main folder</p> <p>- Layer 2 (combination method): OC - optimal combination, SE- second echo, tCNR - temporal contrast-to-noise, tSNR - temporal signal-to-noise</p> <p>- Layer 3: groupICA_desc-XX - contains the group ICA maps and time-series before dual regression, sub-YY - folders for each of the 16 subjects</p> <p>- Layer 4: sub-YY_desc_XX - contains the individual extracted ICA maps and time-series</p> <p> </p> <p> </p> <p> </p>
Data from: Ultra-slow oscillations in fMRI and resting-state connectivity: Neuronal and vascular contributions and technical confounds
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fMRI free-viewing data, resting-state and structural in macaques associated with publication 'Social prediction modulates activity of macaque superior temporal cortex'
<p>Using a free-viewing and functional magnetic resonance imaging, we show that activity in a region of the macaque middle superior temporal (midSTS) cortex was specifically modulated by the predictability of social interactions. This region could be distinguished from other temporal regions involved in face processing. Using resting-state fMRI in anesthetized macaques, we showed that the connectivity between the face-responsive areas and the social prediction area was more integrated in macaques than in humans. We reproduce the social prediction results in a replication study and provide a control to rule out oculomotor implication through the FEF in the social prediction activity of the midSTS, using Transcranial Ultrasound Stimulation. Using standard geometric shape movement stimuli, we also show that macaques do not attribute mental state to shapes.</p>
Can we Use Resting-state fMRI and CSD Fiber Tractography for Presurgical Mapping?
ClinicalTrials.gov study NCT06040580. IPD Sharing: NO. Countries: 1. Publications: 2.
A dataset of long-term consistency values of resting-state fMRI connectivity maps in a single individual derived at multiple sites and vendors using the Canadian Dementia Imaging Protocol
<p>This dataset contains preprocessed resting state fMRI data (.nii.gz) with accompanying confound files (.tsv) from the Single Individual volunteer for Multiple Observations across Networks (SIMON; http://fcon_1000.projects.nitrc.org/indi/retro/SIMON.html) dataset that has been minimally preprocessed using the NeuroImaging Analysis Kit (NIAK; http://niak.simexp-lab.org/build/html/PREPROCESSING.html). Preprocessing steps included: (1) Slice timing correction; (2) Estimation of rigid-body motion in fMRI runs, both within- and between sessions; (3) Linear or non-linear coregistration of the structural scan in stereotaxic space; (4) Individual coregistration between structural and functional scans; (5) Resampling of functional scans in stereotaxic space. Confound files (.tsv) have been included for purposes of scrubbing and regression of confounds using NIAK or other analysis software, allowing for further processing without conflicts.</p>
A Clinical Study of Epilepsy Localization and Prognosis Based on PET and Resting-state fMRI
ClinicalTrials.gov study NCT05567042. IPD Sharing: UNDECIDED. Countries: 0. Publications: 1.
Human Connectome Project resting-state fMRI Connectivity Matrices (Young Adult + Aging)
<p>This database contains the connectivity matrices of the resting-state functional MRI scans that were collected in two databases of the Human Connectome Project, Young Adult and Aging. These matrices contain the functional connectivity between brain regions (here, several different brain atlases were used, leading to several different connectivity matrices for each subject). The connectivity matrices are symmetrical <em>n x n </em>matrices. Here, <em>n</em><em> </em>indicates the number of regions present in the atlas, and any number <em>n<sub>i,j </sub></em>in the matrix is generated by calculating a simple Pearson correlation coefficient between the functional time series that describe the functional activation of regions <em>i </em>and <em>j</em> throughout the resting-state functional scan. The matrices presented in this database are present as .pconn.nii files (which can be handled using software like wb_command) or as .txt file. </p> <p>A full explanation of the database and the brain atlases used here, as well as all the scripts used to generate these connectivity matrices can be found on the GitHub page of this project: <a href="https://github.com/floristijhuis/HCP-rfMRI-repository">floristijhuis/HCP-rfMRI-repository (github.com)</a>.</p>
A Spinal Functional Magnetic Resonance Imagine (fMRI) Study of Resting-State, Motor Task and Acupoint Stimulation
ClinicalTrials.gov study NCT00629655. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Modulation of functional activity and connectivity by acupuncture in patients with Alzheimer disease as measured by resting-state fMRI
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Resting-State fMRI Study of Functional Connectivity After Gamma Knife Radiosurgery in Trigeminal Neuralgia
ClinicalTrials.gov study NCT07357025. IPD Sharing: NO. Countries: 0. Publications: 0.
dataset related to article "Resting-State fMRI in Chronic Patients with Disorders of Consciousness The Role of Lower-Order Networks for Clinical Assessment"
<p>This database contains xls. sheets describing:</p> <ol> <li>patient demographics;</li> <li>clinical data; </li> <li>Coma Recovery Scale-Revised (CRS-R) scores;</li> <li>rs-fMRI ICA rating; </li> <li>rs-fMRI seed rating;</li> <li>rs-fMRI seed mean intensity;</li> <li>rs-fMRI ICA mean intensity;</li> <li>MRI rating</li> </ol>
Dataset related to article: Resting-state fMRI functional connectome of C9orf72 mutation status
<p><span>The database includes clinical and connectome data from a sample of ALS patients carrying the C9orf72 mutation (ALSC9+), non-mutation-carriers ALS patients (ALSC9-), and ALS mimics (ALSmimics). The reported data consist of:<span> </span>demographic data (i.e., Age and Sex assigned at birth), clinical data (i.e., Bulbar/spinal onset, ALSFRS, Survival, disease duration, and King's Staging System scores), and connectome results.</span><span></span></p>
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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.