1 - 16 of 16 results

Open Source Brain

Allows visualization, simulation, dissemination and collaborative development of standardized models of neurons and circuits. Open Source Brain is an open source web-based resource that stores published neuronal and circuit models from multiple brain regions including the neocortex, cerebellum and hippocampus. It also provides tools to visualize, analyze and simulate models through standard web browsers. Registered users can manage multiple simulations and perform analyses on them.

DIADEM / DIgital reconstruction of Axonal and DEndritic Morphology

A selection of six data set collections from different animal species, brain regions, neuron types, and visualization methods. The DIADEM data sets were compiled during the DIADEM Challenge, a competition to raise awareness of the problem of automated neuronal reconstruction, spur development of automated and semi-automated algorithms, and to gauge the state of the art in the field. The DIADEM data underwent extensive curation, including quality control, metadata annotation, and format standardization, to focus the challenge on the most substantial technical obstacles. This data set package is freely released to train, test, and aid development of automated reconstruction algorithms.


Focuses on the development of an XML (eXtensible Markup Language) based description language that provides a common data format for defining and exchanging descriptions of neuronal cell and network models. The current scope of NeuroML focuses on models which are based on the biophysical and anatomical properties of real neurons, i.e. which include informations of the detailed neuronal morphologies, the membrane conductance which underly action potential generation (conductance based models), and which are based on known anatomical connectivity. The NeuroML model description language is being developed in Levels, where each Level concentrates on a particular biophysical scale.

Cognitive Atlas

Provides a knowledge base for cognitive neuroscience. Cognitive Atlas aims to provide such a resource that reflects the views of the entire community. It can become the standard ontology for mental function. The database provides the basic functionality for specification of knowledge about cognitive processes and tasks. It uses standard mechanisms to enable programmatic access to the database which allows other sites or databases to use the content in an automated manner.

Brain Modulyzer

Allows users to explore and analyze modular functional brain connectivity data. Brain Modulyzer makes possible to apply visualization techniques to all relevant data representations. It uses automated analysis methods for detailed exploration of brain network data. This tool is able to combine statistical and visual data analysis. It explores whether statistical insights can inform the visualization process and whether visual presentations can also lead to refined statistical analysis.

DICCCOL / Dense Individualized and Common Connectivity-based Cortical Landmarks

Consists of a dense and consistent map of 358 cortical landmarks. Each DICCCOL is defined by group-wise consistent white-matter fiber connection patterns derived from diffusion tensor imaging (DTI) data. These 358 landmarks are remarkably reproducible over more than one hundred human brains and possess accurate intrinsically established structural and functional cross-subject correspondences validated by large-scale functional magnetic resonance imaging data. In particular, these 358 cortical landmarks can be accurately and efficiently predicted in a new single brain with DTI data. Thus, this set of 358 DICCCOL landmarks comprehensively encodes the common structural and functional cortical architectures, providing opportunities for many applications in brain science including mapping human brain connectomes.

CORR / Consortium for Reliability and Reproducibility

An open science resource for functional and structural connectomics. The CoRR repository allows the: (i) establishment of test-retest reliability and reproducibility for commonly used MR-based connectome metrics, determination of the range of variation in the reliability and reproducibility of these metrics across imaging sites and retest study designs, creation of a standard/benchmark test-retest dataset for the evaluation of novel metrics.

1000 Functional Connectomes Project

This compilation of neural data aggregates existing R-fMRI data to provide an initial demonstration of the ability to pool functional data across centers. The 1000 Functional Connectomes dataset aims to (i) establish the presence of a universal functional architecture in the brain, consistently detectable across centers; (ii) investigate the influence of center on R-fMRI measures; (iii) explore the potential impact of demographic variables on R-fMRI measures; and (iv) demonstrate the use of an intersubject variance–based method for identifying putative boundaries between functional networks.

UMCD / USC Multimodal Connectivity Database

An interactive web-based platform for brain connectivity matrix sharing and analysis. UMCD enables users to download connectivity matrices shared by other users, upload matrices from their own published studies, or select a specific matrix and perform a real-time graph theory-based analysis and visualization of network properties. The data shared on the UMCD span a broad spectrum of functional and structural brain connectivity information from humans across the entire age range (fetal to age 89), representing an array of different neuropsychiatric and neurodegenerative disease populations (autism spectrum disorder, ADHD, and APOE-4 carriers). An analysis combining 7 different datasets shared on the site illustrates the diversity of the data and the potential for yielding deeper insight by assessing new connectivity matrices with respect to population-wide network properties represented in the UMCD.