| Name | Description | Availability |
| Autism Brain Imaging Data Exchange (ABIDE) | Access to the BIDSDataset for ABIDE, stored on Datalad | Restricted. Request Needed |
| 1000 Genomes Project | 99% of SNP variants with a frequency of >1% for a variety of ancestries.”}”>The 1000 Genomes Project provides a comprehensive description of common human variation by applying a combination of whole-genome sequencing, deep exome sequencing and dense microarray genotyping to a diverse set of 2504 individuals from 26 populations. Over 88 million variants are characterised, including >99% of SNP variants with a frequency of >1% for a variety of ancestries. | Generally open |
| Alzheimer’s Mouse Models | This dataset has data files from 5-Choice, Pairwise Visual Discrimination (PVD), and Paired-Associates Learning (PAL) cognitive behavioral tasks in which male and female mice from 3 Alzheimer’s mouse models (3xTG-AD, 5XFAD, APP/PS1) were tested using touchscreen technology at two different sites (e.g. University of Western Ontario and University of Guelph). Both aggregated data and trial-by-trial data are provided in this dataset | Generally open |
| Big Brain | The BigBrain is the brain of a 65 year old man with no neurological or psychiatric diseases in clinical records at time of death. The brain was embedded in parafin and sectioned in 7404 coronal histological sections (20 microns), stained for cell bodies. The BigBrain is the digitized reconstruction of the hi-res histological sections (20 microns isotropic). | Generally open |
| BigBrain – 3D Classified Volumes (derived dataset) | The Dataset contains the 3D Classified volumes for basic tissue classes at multiple isotropic resolutions derived from the BigBrain dataset. | Generally open |
| BigBrain – 3D Surfaces (derived dataset) | The BigBrain 3D Surfaces dataset contains the 3D surfaces of white and gray matter derived from the BigBrain dataset. | Generally open |
| BigBrain – A3D (derived dataset) | The BigBrain A3D dataset contains Atelier3D client files for viewing the BigBrain model. | Generally open |
| BigBrain – Hippocampus Segmentation (derived dataset) | The BigBrain Hippocampus Segmentation dataset contains hippocampus segmentation derived from the BigBrain dataset. | Generally open |
| BigBrain – Layer Segmentation (derived dataset) | The BigBrain Layer Segmentation dataset contains all layer segmentation files derived from the BigBrain datase. | Generally open |
| BigBrain-MRISIM (derived dataset) | Volumes that were used in the comparison study between CIVET-2.1 and FreeSurfer-6.0 for the extraction of cortical surfaces on high-resolution volumes, with the BigBrain serving as the gold standard | Generally open |
| BigBrain-RawData | The BigBrain raw data dataset contains post-mortem MRI aligned to the block faces and raw sections from the BigBrain dataset, a digitized reconstruction of high-resolution histological sections of the brain of a 65 years old man with no history of neurological or psychiatric diseases. | Generally open |
| BigBrain-Surface Parcellations (derived dataset) | The BigBrain Surface Parcellations dataset contains surface parcellations derived from the BigBrain dataset | Generally open |
| BigBrain – MRI Coregistration | This dataset includes co-registration of the BigBrain dataset to the MNI PD25 atlas and the ICBM152 2009b atlases.The data include deformed BigBrain atlases and manual subcortical segmentations in MINC2 and NIFTI-1 formats, as well as relevant spatial transformation in MINC transformation format.The segmented subcortical structures include: red nucleus, subthalamic nucleus, substantia nigra, caudate, putamen, globus pallidus externa, globus pallidus interna, thalamus, hippocampus | Generally open |
| BrainSpan: Atlas of the Developing Human Brain | This resource describes an anatomically comprehensive atlas of the mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high-resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser-microdissected brain regions. | Generally open |
| Calgary Campinas Brain MRI | The dataset is currently composed of 3D, T1-weighted reconstructed brain MR images and segmentation masks for certain structures. It also has brain MR raw data (i.e., k-space). | Generally open |
| Calgary Preschool MRI Dataset | Calgary Preschool MRI Dataset: The DTI dataset here comprises 396 unprocessed b750 diffusion weighted MRI scans from 120 participants aged 2-8 years. | Generally open |
| CFMM-7T: MP2RAGE T1 mapping | BIDS-formatted 7T MRI MP2RAGE and Sa2RAGE data acquired at the Centre for Functional and Metabolic Mapping in London (Ontario, Canada) + Snakemake workflow for analyses as performed in ‘Effects of MP2RAGE B1+ sensitivity on inter-site T1 reproducibility and morphometry at 7T’ | Generally open |
| Brainstem cholinergic-deficient mouse model dataset | Male mice and their wild-type controls were evaluated at 7-10 months of age using the 5-Choice Serial Reaction Time (5-CSRT) task to assess attention. Immediately after (approximately at 9-12 months of age) these same mice were evaluated using the Extinction task to assess their ability to extinguish a response. A different cohort of male mice and their wild-type controls were evaluated at 11-13 months of age in the Pairwise visual discrimination (PVD) task to assess discrimination and reversal learning. Immediately after (still within 11-13 months of age) these same mice were evaluated using the Pairwise Associate Learning (PAL) task to assess learning and memory. | Generally open |
| Mouse models that differ in neurotransmitter release from striatal cholinergic interneurons | This dataset has data files from 5-Choice Serial Reaction Time (5-CSRT), Pairwise Visual Discrimination (PVD), and Extinction cognitive behavioral tasks for 4 mouse lines that differ in neurotransmitter release from striatal cholinergic interneurons (ACh or Glu). D2CreVGLUT3fx and ChATIRESVGLUT3fx mice and their wild-type controls were evaluated at 3-7 months of age in the PVD task to assess discrimination and reversal learning. Immediately after (still within 3-7 months of age) these same mice were evaluated using the Extinction task to assess their ability to extinguish a response. D2CreVAChTfx mice and their wild-type controls were evaluated at 5-7 months of age in the 5-CSRT task to assess attention. Immediately after (still within 3-7 months of age) these same mice were evaluated using the Extinction task. VAChTfx control mice that were virally injected with GFP or Cre in the dorsal striatum were evaluated at 6-12 months in the PVD task, followed by the 5-CSRT task (approximately at 8-14 months of age). | Generally open |
| HCPUR100: Healthy Adult human Brain Diffusion Template | A diffusion fibre orientation template created from 100 unrelated subjects of the Human Connectome Project scanned at 3 Tesla | Generally open |
| Hippocampal morphology and cytoarchitecture in the 3D BigBrain | This project’s preprint can be found here: https://www.biorxiv.org/content/10.1101/599571v1. The goal of this project is to characterize the complex mesoscale folding of the hippocampus as well as histological features which define the hippocampal subfields using the open source dataset 3D BigBrain. | Generally open |
| Homo sapiens reference genome sequences | Homo sapiens reference genome sequences and annotation file, as stored in the International Nucleotide Sequence Database. | Generally open |
| Learning Naturalistic Structure: Processed fMRI dataset | In this dataset, subjects were scanned while watching repeated presentations of intact and scrambled clips from Wes Anderson’s 2014 film, The Grand Budapest Hotel. Scrambled clips were presented in either a ‘fixed’ (i.e., consistent scrambling from run to run) or ‘random’ (i.e., random scrambling from run to run) condition. An overview of the experimental design is shown in this figure from Aly and colleagues (2018) | Generally open |
| MICA-MICs: a dataset for Microstructure-Informed Connectomics | The MICA-MICs dataset provides raw and fully processed multimodal neuroimaging data acquired in 50 healthy control participants at a filed strength of 3T. Modalities include high-resolution anatomical (T1-weighted), microstructurally-sensitive (quantitative T1), diffusion-weighted and resting-state functional imaging. In addition, MICA-MICs provides ready-to-use connectomes built across multiple parcellation schemes based on brain anatomy, function, and histology (18 parcellations in total). Processed matrices are available for each imaging modality across a range of parcellation scales. | Generally open |
| MiceImmune | Longitudinal structural MRI and behavioural data for mice prenatally exposed to maternal immune activation either early or late in gestation | Generally open |
| Multimodal data with wide-field GCaMP imaging | UBC Brain Circuits research cluster data on FRDR | Generally open |
| Intracellular Recordings of Murine Neocortical Neurons | This dataset contains intracellular electrophysiological current clamp recordings from murine neocortical neurons. | Generally open |
| MRI and unbiased averages of wild muskrats (Ondatra zibethicus) and red squirrels (Tamiasciurus hudsonicus) | Altered neurotransmission and neuroimaging biomarkers of chronic arsenic poisoning in wild muskrats (Ondatra zibethicus) and red squirrels (Tamiasciurus hudsonicus) breeding near the City of Yellowknife, Northwest Territories (Canada) | |
| Quantifying Neural-Cognitive Relationships Across the Brain | https://portal.conp.ca/dataset?id=projects/Quantifying_Neural_Cognitive_Relationships_Across_the_Brain | |
| Parkinson’s Disease Datasets – Neurocon | The data are comprised of 27 PD patients and 16 age-matched normal controls which include both T1 and resting-state scans. | |
| The Effect of Neurorehabilitation on Multiple Sclerosis | Resting-state fMRI time-series data of sixty multiple sclerosis patients before and after neurorehabilitation treatment. fMRI is a well-established modality for studying neurological conditions, allowing for a broad spectrum of analytical approaches and, therefore, benefits for the wider scientific community. We believe the publication of this dataset will promote research and improve the reproducibility of future reports. | |
| NIH Blueprint Non-Human Primate Atlas | The NIH Blueprint Non-Human Primate (NHP) Atlas consists of a suite of gene expression and neuroanatomical data for exploring the cellular and molecular architecture of the developing rhesus macaque brain. | Generally open |
| PreventAD Open Data | The PREVENT-AD (Pre-symptomatic Evaluation of Experimental or Novel Treatments for Alzheimer Disease) cohort is composed of cognitively healthy participants over 55 years old, at risk of developing Alzheimer Disease (AD) as their parents and/or siblings were/are affected by the disease. | Restricted. Request Needed |
| SIMON | The Single Individual volunteer for Multiple Observations across Networks (SIMON) MRI dataset is a sample of convenience of one ambidextrous healthy male aged between 29 and 46 years old, scanned in 73 sessions at multiple sites and with various scanner models. Each of these sessions includes at least an anatomical T1-weighted image, in addition to other modalities (T1, T2- and PD-weighted, T2-star, diffusion, resting state fMRI, susceptibility, arterial spin labelling), which vary from one session to another . | Generally open |
| SPINS Travelling Human Phantoms | Social Processes Initiative in Neurobiology of the Schizophrenia(s) Travelling Human Phantoms | Generally open |
| Parkinson’s Disease Datasets – Taowu | The data are comprised of 20 PD patients and 20 age-matched controls which include both T1 and resting-state scans. | Generally open |
| VFA T1 mapping | The preliminary variable flip angle (VFA) T1 mapping data acquired using: 1. Fully-open (https://bit.ly/qMRPullseq) 3D spoiled gradient-echo based RTHawk application 2. Siemens stock sequence 3D FLASH | Generally open |
| Visual working memory: Study of Task fMRI and Behavioural response | Nineteen right-handed healthy adults (aged from 18-28 years old) participated in this study on the same 3 T MRI scanner. Axial 3D T1-weighted images were acquired as well as three runs of bold task MRI with the recording of their related behavioural data. | Generally open |
| Human Connectome Project (HCP), 1200 Subjects | The 1200 Subjects Release (S1200) includes behavioral and 3T MR imaging data from 1206 healthy young adult participants (1113 with structural MR scans) collected in 2012-2015. In addition to 3T MR scans, 184 subjects have multimodal 7T MRI scan data and 95 subjects also have some resting-state MEG (rMEG) and/or task MEG (tMEG) data available. | Restricted. Request Needed |
| UK Biobank | UK Biobank is a large-scale biomedical database and research resource, containing in-depth genetic and health information from half a million UK participants. | Restricted. Request Needed |
| OpenPain-BrainNetworkChange_Mano | See http://openpain.org for more information. | Generally open |
| OpenPain-cbp_resting | See http://openpain.org for more information. | Generally open |
| OpenPain-placebo_1 | See http://openpain.org for more information. | Generally open |
| OpenPain-placebo_predict_tetreault | See http://openpain.org for more information. | Generally open |
| OpenPain-subacute_longitudinal_study | See http://openpain.org for more information. | Generally open |
| OpenPain-thermal | See http://openpain.org for more information. | Generally open |
Datasets
The NeuroHub platform is a node of several national and international datasets. Many datasets are public and immediately available, such as those available on the Canadian Open Neuroscience Platform (CONP). However, some datasets, such as the UK Biobank or Human Connectome Project, are restricted and access must be granted by the respective bodies. Email support@neurohub.ca to inquire about accessing restricted datasets. Once access is approved, the data will be made available to you via your NeuroHub account.
Raw and processed data is available on NeuroHub, saving hours or days of download and processing time. You can connect to high performance computing infrastructure via CBRAIN for analysis, taking advantage of our large compute allocation.