BrainHack 2013

The Neuro Bureau is proud to announce the 2013 Brainhack, to be held from October 23-26, 2013 at the  Centre International d’Études Pédagogiques, Sèvres, France (just outside of Paris). Brainhack 2013 is a unique event with the goals of fostering interdisciplinary collaboration and...

Big Quality Control

Summary: MRI data quality control over a wide range of acquisition parameters A reliable and automatic quality control of MRI data is still an important challenge. Here we propose to address this question on a large and heterogeneous dataset : all the data acquired at the CENIR (CEnter...

Reproduce existing r...

Summary: NiLearn is a Python module, still under development, for fast and easy statistical learning on NeuroImaging data. It leverages the scikit-learn Python toolbox for multivariate statistics with applications such as predictive modeling, classification, decoding, or connectivity...

Consortium for Reproducibility and Reliability (CoRR) Oct24

Consortium for Repro...

Summary: The overarching goal of CoRR is to create an open science resource for the imaging community that will facilitate the assessment of test-retest reliability and reproducibility for functional and structural connectomics. In order to accomplish this, we will aggregate resting...

Fear circuits

Summary: Who’s afraid of the big, bad wolf? Fear processing circuit connectivity strength and anxiety changes across the lifespan Recent diffusion tensor imaging (DTI) research has demonstrated a subcortical pathway in the human brain proposed to mediate fast orienting of visual...

HCP pre-processed

Summary: At Brainhack 2012, we started a project on the idea to segment the cortex of the cerebellum as a surface. One year later we have been able to apply this method as part of the CBS High Resolution Processing Tools to the data from the Human Connectome Project (Q1), producing...

Brain parcellation

Summary: Most connectivity-based clustering studies focus on choosing an appropriate clustering method or finding the optimal parameters given a specific clustering algorithm. However, before clustering is applied, many decisions are taken that can greatly affect the outcome of the...

Video Decoding and R...

Summary: In 2011, Jack Gallant’s paper “Reconstructing visual experiences from brain activity evoked by natural movies” had left a profound impact on our lab. Using a straight-forward Bayesian encoder/decoder model, movies subjects watched inside the fMRI scanner could be...

Categorical and dime...

Summary: The project we propose for Brainhack intends to build a tutorial on machine learning methods for rsfMRI data. As a minimum, we will use two different machine learning methods for classification and regression, Gaussian Naive Bayes and Support Vector Machine. We will focus on...

Multitasking

Summary: How to best utilize a large (N~170) and comprehensive dataset to identify the neural, behavioural and trait correlates of emotional control – Developing analysis approaches for naturalistic and multivariate task-based fMRI. With the advent of statistically powerful...

NeuroDebian

NeuroDebian provides a turnkey software platform for neuroscience that is created by integrating research tools with the Debian operating system. If you are using such software on Debian or its derivatives, such as Ubuntu, chances are that you are already using NeuroDebian. URL:...

OpenMind

Summary ——- https://github.com/jaseg/OpenMind-micro The OpenMind project aims to create easy-to-use high-quality open source EEG boards which may e.g. be used in conjunction with an Arduino to build a OpenSource EEG. We use integrated analog frontends with 24 bit precision for data...

fMRI quality control

Summary: With the emergence of large fMRI databases, there is a need for tools for high-throughput quality control. Although a few tools (such as mit-art) exist to detect outliers in fMRI databases, most standard packages propose no solution besides the visual inspection of individual results....

Beautiful Brain Proj...

Since a picture says more than a thousand words, researchers strive to bring their A-game when it comes to making pictures, graphs, renderings etc. in the process of disseminating their scientific results. At brainhack we would like to launch a project that aims to take rendering imaging...

Neuroscience Information Framework Jul27

Neuroscience Informa...

The Neuroscience Information Framework is a dynamic inventory of Web-based neuroscience resources: data, materials, and tools accessible via any computer connected to the Internet. An initiative of the NIH Blueprint for Neuroscience Research, NIF advances neuroscience research by enabling...

Resting-state fMRI &...

Summary This project aims to create an online repository of slides and figures for presenting both introductory and advanced materials related to resting-state fMRI and connectivity methodologies. In addition, we aim to create a set of teaching materials and ‘courses’ for learning...

Neuroimaging Data Sharing Hall of Fame Jun25

Neuroimaging Data Sh...

Quite often when I advocate for data sharing I am missing good examples of scientific work that would not be possible or would be much more expensive if data would not be shared. Therefore I thought it would beneficial for our cause to have a little database of papers that are using publicly...

Brainhack 2012 Unconference

The Neuro Bureau is proud to announce the 2012 Brainhack, to be held from September 1-4 at the Max Plank Institute for Human Cognitive and Brain Sciences, Leipzig, Germany. Brainhack 2012 is a unique workshop with the goals of fostering interdisciplinary collaboration and open neuroscience. The structure builds from the concepts of an unconference and a hackathon: The term “unconference” refers to the fact that most of the content will be dynamically created by the participants — a hackathon is an event where participants collaborate intensively on science-related projects. Participants from all disciplines related to neuroimaging...

INDI Feb08

INDI

INDI or the International Neuroimaging Datasharing Initiative is dedicated to accelerating our understanding of the brain’s functional architecture through the implementation of open data-sharing and discovery-based science. Extending the original 1000 Functional Connectomes project,...

ADHD200 – prep...

The ADHD-200 consortium has released a large database of structural MRI, resting-state functional MRI raw datasets, along with phenotypic data acquired on a large cohort of children and adolescents, both for typically developing individuals as well as patients diagnosed with an attention...

neurosynth.org

NeuroSynth is a platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. What can I do ? Currently you can download most of the images on the website by clicking on the ‘Download image’ link under the corresponding image. In the near future, you’ll also be able to download coordinate and study lists. Data dumps of the full coordinate database and various image datasets will also be made available shortly. All data available on this site are released under an Open Data Commons Open Database License (ODbL). This means that while the data are free to...

OpenfMRI.org Nov25

OpenfMRI.org

The OpenfMRI project was established in 2010 to provide a resource for researchers interested in making their fMRI data openly available to the research community. What can I do ? You can contribute an fMRI database to the project. How can I join ? Create an account on openfmri.org. Who are...

ADHD-200 Nov25

ADHD-200

The ADHD-200 Sample is a grassroots initiative, dedicated to accelerating the scientific community’s understanding of the neural basis of Attention Deficit Hyperactivity Disorder (ADHD) through the implementation of open data-sharing and discovery-based science. Towards this goal, the ADHD-200 consortium has publicly released 776 resting-state fMRI and anatomical datasets aggregated across 8 independent imaging sites, 491 of which were obtained from typically developing individuals and 285 in children and adolescents with ADHD (ages: 7-21 years old). Accompanying phenotypic information includes: diagnostic status, dimensional ADHD...