User:Inxi/sandbox

= Introduction =

1000 Functional Connectomes Project is a project collecting resting-state functional magnetic resonance imaging data around the world to build a neuroimaging database for further research. It demonstrates open sharing of R-fMRI data and aims to emphasize the aggregation and sharing of well-phenotyped datasets.

The 1000 Functional Connectomes dataset aims to:
 * establish the presence of a universal functional architecture in the brain, consistently detectable across centers;
 * investigate the influence of center on R-fMRI measures;
 * explore the potential impact of demographic variables on R-fMRI measures; and
 * demonstrate the use of an intersubject variance–based method for identifying putative boundaries between functional networks.

It is the parent project for ABIDE, ADHD-200 (ADHD200), INDI, CORR, NKI-Rockland (NKI), Healthy Brain Network (HBN) and other projects.

The project is described in the article by Bharat B. Biswal et al.

The image repository for the ‘1000 Functional Connectomes’ Project is located at here, which is a fully open downloadable database of over 1200 resting state fMRI datasets collected from 35 sites around the world.

Project Specifications
Related information about datasets in this project.

Data Source
All datasets have been generously donated by the principal investigators from the member sites, for the purpose of providing the broader imaging community complete access to a large-scale functional imaging dataset.

Age, sex and imaging center information are provided for each of the datasets included in the repository.

Functional imaging datasets are uniformly organized using the NIFTI image format (orientation: RPI; TR information set in files). All functional datasets provided by contributors have been added to the repository without modification, with the exception of conversion to NIFTI format and to a uniform orientation. Anatomical images have undergone face scrambling to protect the identity of participants. Data from each site in the repository can be downloaded individually to provide maximal flexibility to users.

The‘1000 Functional Connectomes’ Project datasets are provided freely without assurance or qualifications, regardless of data quality or appropriateness for specific uses by repository data recipients.

As the data-release is unrestricted, researchers are free to publish with any portion of the dataset they choose.

Comments
Below are some comments from the users.
 * Need more examples
 * More scripts for statistical methods will be helpful.
 * Everything was well organized and documented providing a trove of available data.
 * This is a great resource for resting state research. Adequate documentation of the data is lacking though. It would be nice to have more information about the scanning protocols used to acquire each data set. An online searchable database interface would be nice as well. Great project!
 * What an excellent resource. It&#39;s great to have this data available. The data downloads simply enough, but it would be good to be able to search for specific studies (by field, MR sequence parameters, etc.).
 * Clean and simple organization. Enough documentation provided. It would be good to add references to papers that use the data that is shared for each site.

Support
You may get support from their forums and trackers.

Forums

 * open-discussion: General Discussion


 * help: Get Public Help


 * processing-scripts: Discuss any problems, issues, thoughts about the processing scripts


 * indi: Discussing Regarding INDI Data Releases

Trackers

 * Bugs: Bug Tracking System


 * Support: Tech Support Tracking System


 * Patches: Patch Tracking System


 * Feature Requests: Feature Request Tracking System

Similar Projects

 * Alzheimer's Disease Neuroimaging Initiativehomepage


 * Open Access Series of Imaging Studies (OASIS)


 * Cambridge Centre for Ageing and Neuroscience (Cam-CAN)


 * The fMRI Data Center (fMRIDC)


 * Functional Imaging BIRN (fBIRN)

= Usage =

Phenotypic Data
Phenotypic data are all kinds of clinical information regarding patients’ disease symptoms, as well as relevant demographic data, such as age, ethnicity and sex.

This type of information is collected and stored by patient registries and biobanks.

The benefits of establishing patient registries are evident in rare diseases, especially the ultra-rare ones, for which expertise is available in a very small number of centres worldwide.

No single institution, and in many cases no single country, has sufficient numbers of patients to conduct generalizable research or clinical trials. For most rare diseases, there is no existing therapy, and clinical trial are often the only chance for patients to receive any kind of treatment.

Data stored in patient registries help to prepare clinical trials and recruit patients with a given disease or even a particular set of symptoms.

R-fMRI, DTI, sMRI
The joint multivariate analysis of multiple data types (e.g., resting state fMRI, task-related fMRI, DTI, and sMRI) will improve our ability to understand brain diseases.(Combination of resting state fMRI, DTI, and sMRI data to discriminate schizophrenia by N-way MCCA + jICA )

Structural and functional brain scans
Present a dataset of functional magnetic resonance imaging (fMRI) data covering the adult lifespan that includes structural MRI and resting-state functional MRI. Four hundred ninety-four healthy adults (age range: 19-80 years; Males= 187) were recruited and completed two multi-modal MRI scan sessions at the Brain Imaging Center of Southwest University, Chongqing, China.(Structural and functional brain scans from the cross-sectional Southwest University adult lifespan dataset)

Behavioral assessments and phenotypic information
This dataset consists of the subjects used in the 2011 PLoS ONE study by Adelstein et al., entitled, “Personality is reflected in the brain’s intrinsic functional architecture.” We are releasing these data to the public so that investigators can include them in their own dataset so that they can reproduce our results or conduct a similar investigation with improved methodology. The dataset consists of male and female adults, all healthy controls with no psychiatric history. Subjects were scanned in a Siemens 3T Allegra scanner using a continuous eyes-open protocol while fixating on the word “Relax.” Details are found in the accompanying materials.

Data download &amp; Retrieval

 * Accessable Data: Already released


 * Ongoing Data: Pilot Samples &amp; Ongoing


 * Coming Soon Data: Coming soon

Brain imaging data structure (BIDS)
Neuroimaging experiments result in complicated data that can be arranged in many different ways.

So far there is no consensus how to organize and share data obtained in neuroimaging experiments. Even two researchers working in the same lab can opt to arrange their data in a different way. Lack of consensus (or a standard) leads to misunderstandings and time wasted on rearranging data or rewriting scripts expecting certain structure.

Here we describe a simple and easy to adopt way of organizing neuroimaging and behavioral data.

A good introduction to the BIDS standard can be found in the paper published in Nature Scientific Data

Age, sex and imaging center information are provided for each of the datasets.

Related tools
There are file transfer programs that can handle S3 natively and will allow you to navigate through the data using a file browser. Cyberduck is one such program that works with Windows and Mac OS X. Cyberduck also has a command line version that works with Windows, Mac OS X, and Linux.

Download from Amazon S3

= Other Related Studies = The 1000 Functional Connectomes Project's organization platform, funding structures, standardized methodologies, and open datasharing approaches have been used in a number of different studies(Database Foundation & Article Studying).

Databases related

 * Southwest University Adult Lifespan Dataset (SALD) : A Multi-model Dataset from A Large, Cross-sectional Adult Lifespan Sample.The goals of the SALD are to give researchers the opportunity to map the structural and functional changes the human brain undergoes throughout adulthood and to replicate previous findings.
 * Cambridge_Buckner : Brain Genomics Superstruct Project initial data release with structural, functional, and behavioral measures.
 * Cleveland CCF : In addition to the resting state scan this sample includes physiological measurements (heart rate and breathing) obtained during the resting state scan.

Articles related

 * Standardizing the intrinsic brain: Towards robust measurement of inter-individual variation in 1000 functional connectomes : Article Keywords: Functional connectomics, Standardization, Test¨Cretest reliability, Resting-state fMRI, Data aggregation
 * Functional connectivity density mapping : Aiming to determine the location of the functional connectivity hubs in the human brain by using data from the ¡°1000 Functional Connectomes Project¡±
 * Network-specific sex differentiation of intrinsic brain function in males with autism : A study of sex differentiation of intrinsic brain function in males with autism.
 * Mindcontrol: A web application for brain segmentation quality control : A web application for brain segmentation quality control
 * Replication of Resting State-Task Network Correspondence and Novel Findings on Brain Network Activation During Task fMRI in the Human Connectome Project Study : Study use of open access neuroimaging datasets to conduct replication studies.
 * On wakefulness fluctuations as a source of BOLD functional connectivity dynamics : Human brain dynamics and functional connectivity fluctuate Study.