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http://www.cdtdb.brain.riken.jp/CDT/Top.jsp

Transcriptomic information (spatiotemporal gene expression profile data) on the postnatal cerebellar development of mice (C57B/6J & ICR). It is a tool for mining cerebellar genes and gene expression, and provides a portal to relevant bioinformatics links. The mouse cerebellar circuit develops through a series of cellular and morphological events, including neuronal proliferation and migration, axonogenesis, dendritogenesis, and synaptogenesis, all within three weeks after birth, and each event is controlled by a specific gene group whose expression profile must be encoded in the genome. To elucidate the genetic basis of cerebellar circuit development, CDT-DB analyzes spatiotemporal gene expression by using in situ hybridization (ISH) for cellular resolution and by using fluorescence differential display and microarrays (GeneChip) for developmental time series resolution. The CDT-DB not only provides a cross-search function for large amounts of experimental data (ISH brain images, GeneChip graph, RT-PCR gel images), but also includes a portal function by which all registered genes have been provided with hyperlinks to websites of many relevant bioinformatics regarding gene ontology, genome, proteins, pathways, cell functions, and publications. Thus, the CDT-DB is a useful tool for mining potentially important genes based on characteristic expression profiles in particular cell types or during a particular time window in developing mouse brains.

Proper citation: Cerebellar Development Transcriptome Database (RRID:SCR_013096) Copy   

•   Source: SciCrunch Registry

http://findlab.stanford.edu/functional_ROIs.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 29,2023. Atlas of functional ROIs (fROIs) containing 499 regions, with extensive gray matter coverage. Atlases are available for download directly from the website.

Proper citation: 499 fROI atlas (RRID:SCR_014756) Copy   

•   Source: SciCrunch Registry

https://senselab.med.yale.edu/MicroCircuitDB/

A database for storing and efficiently retrieving realistic computational models of brain microcircuits and networks. The focus is on microcircuits that are based on experimentally demonstrated properties of neurons and their connectivity.

Proper citation: MicrocircuitDB (RRID:SCR_014577) Copy   

•   Source: SciCrunch Registry

https://www.mcdb.ucla.edu/Research/Hartenstein/dbla/index.html

Atlas providing structure and development of Drosophila brain lineages. Used to learn about projection pattern of lineages as first step towards reconstructing and understanding all neurons.

Proper citation: Drosphila Brain Lineage Atlas (RRID:SCR_017507) Copy   

•   Source: SciCrunch Registry

https://wiki.helsinki.fi/display/twineng/Twinstudy

Twin panel consists of three nationwide samples of Finnish twin pairs. Major studies include nicotine dependence, eating disorders and brain imaging and alcohol use.

Proper citation: Finnish Twin Cohort Study (RRID:SCR_017477) Copy   

•   Source: SciCrunch Registry

http://connectivity.brain-map.org/transgenic

Data detailing transgene expression in Cre and other driver lines for adult and developing brain. Experiments include colorimetric in situ hybridization, fluorescent in situ hybridization and other histological methods. Expression maps of transgenic Cre and other driver lines in mice.

Proper citation: Allen Brain Atlas expression map of Cre and other drivers (RRID:SCR_017510) Copy   

•   Source: SciCrunch Registry

http://www.brain-connectivity-toolbox.net

A large selection of complex network measures in Matlab that are increasingly used to characterize structural and functional brain connectivity datasets. Several people have contributed to the toolbox, and if you wish to contribute with a new function or set of functions, please contact Olaf Sporns. All efforts have been made to avoid errors, but users are strongly urged to independently verify the accuracy and suitability of toolbox functions for the chosen application. Please report bugs or substantial improvements.

Proper citation: Brain Connectivity Toolbox (RRID:SCR_004841) Copy   

•   Source: SciCrunch Registry

http://ki.se/ki/jsp/polopoly.jsp?d=29350&a=36311&l=en

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Study to investigate symptoms of Attention Deficit Hyperactivity Disorder (ADHD) according to DSM-IV in adults with special focus on attention deficit. Information is used from the Swedish Twin study of Adults: genes and Environment (STAGE) from the Swedish Twin Registry. ADHD-discordant and concordant samples of pairs of twins for ADHD are selected from STAGE for studies of brain structure and function with Functional Magnetic Resonance Imaging (fMRI).

Proper citation: KI Biobank STAGE-ADHD (RRID:SCR_005921) Copy   

•   Source: SciCrunch Registry

http://ki.se/imm/cefalo-studien

Saliva taken from participants in a study investigating the association between environmental exposures and brain tumors in children aged 7-19 years and the interaction between these risk factors and genetic polymorphisms, which may confer susceptibility to effects of exogenous agents. Sample types: * Saliva Number of sample donors: 886 (sample collection completed)

Proper citation: KI Biobank - CEFALO (RRID:SCR_006034) Copy   

•   Source: SciCrunch Registry

http://www.neuroskills.com/

A topical portal and providers of brain injury rehabilitation services. Resources * Pharmacology Guide * Glossary of Brain Injury Terms * Brain Injury Research Articles * Common Brain Injury Assessment Tools / Rating Scale * Certified Continuing Education Courses * Links to Resource Sites

Proper citation: Centre for Neuro Skills (RRID:SCR_006106) Copy   

•   Source: SciCrunch Registry

http://www.alz.washington.edu/

A clinical research, neuropathological research and collaborative research database that uses data collected from 29 NIA-funded Alzheimer's Disease Centers (ADCs). The database consists of several datasets, and searches may be done on the entire database or on individual datasets. Any researcher, whether affiliated with an ADC or not, may request a data file for analysis or aggregate data tables. Requested aggregate data tables are produced and returned as soon as the queue allows (usually within 1-3 days depending on the complexity).

Proper citation: National Alzheimer's Coordinating Center (RRID:SCR_007327) Copy   

•   Source: SciCrunch Registry

http://www.thomaskoenig.ch/Lester/ibaspm.htm

The aim of this work is to present a toolbox for structure segmentation of structural MRI images. All programs were developed in MATLAB based on a widely used fMRI, MRI software package, SPM99, SPM2, SPM5 (Wellcome Department of Cognitive Neurology, London, UK). Other previous works have developed a similar strategy for obtaining the segmentation of individual MRI image into different anatomical structures using a standardized Atlas. Have to be mentioned the one introduced by Montreal Neurological Institute (MNI) that merges the information coming from ANIMAL (algorithm that deforms one image (nonlinear registration) to match previously labelled) and INSECT (Cerebral Tissue Classification) programs for obtaining a suitable gross cortical structure segmentation (Collins et al, 1999). Here both, nonlinear registration and gray matter segmentation processes have been performed through SPM99, SPM2, SPM5 subroutines. Three principal elements for the labeling process are used: gray matter segmentation, normalization transform matrix (that maps voxels from individual space to standardized one) and MaxPro MNI Atlas. All three are combined to yield a good performance in segmenting gross cortical structures. The programs here can be used in general for any standardized Atlas and any MRI image modality. System Requirements: 1. The IBASPM graphical user interface (GUI) runs only under MATLAB 7.0 or higher. The non-graphical version runs under MATLAB 6.5 or higher. 2. Statistical Parametrical Mapping Software SPM2, SPM5 Main Functions: * Atlasing: Main function ( This file contains spm_select script from SPM5 toolbox and uigetdir script from MATLAB 7.0 ). * Auto_Labeling : Computes individual atlas. * Create_SPAMs : Constructs Statistical Probability Anatomy Maps (SPAMs). * Create_MaxProb : Creates Maximum Probability Atlas (MaxPro) using the SPAMs previously computed. * All_Brain_Vol : Computes whole brain volume masking the brain using the segmentation files (if the segmentation files does not exist it segments). * Struct_Vol : Computes the volume for different structures based on individual Atlas previously obtained by the atlasing process. * Vols_Stats : Computes mean and standard deviation for each structure in a group of individual atlases.

Proper citation: IBASPM: Individual Brain Atlases using Statistical Parametric Mapping Software (RRID:SCR_007110) Copy   

•   Source: SciCrunch Registry

https://www.upf.edu/web/ntsa/downloads/-/asset_publisher/xvT6E4pczrBw/content/2001-indications-of-nonlinear-deterministic-and-finite-dimensional-structures-in-time-series-of-brain-electrical-activity-dependence-on-recording-regi?p_r_p_assetEntryId=229569389&_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw_type=content&_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw_urlTitle=2001-indications-of-nonlinear-deterministic-and-finite-dimensional-structures-in-time-series-of-brain-electrical-activity-dependence-on-recording-regi&_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw_redirect=https%3A%2F%2Fwww.upf.edu%3A443%2Fweb%2Fntsa%2Fdownloads%3Fp_p_id%3Dcom_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw%26p_p_lifecycle%3D0%26p_p_state%3Dnormal%26p_p_mode%3Dview%26p_r_p_assetEntryId%3D229569389%26_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw_cur%3D0%26p_r_p_resetCur%3Dfalse#229569389

Five data sets containing quasi-stationary, artifact-free EEG signals both in normal subjects and epileptic patients were put in the web by Ralph Andrzejak from the Epilepsy center in Bonn, Germany. Each data set contains 100 single channel EEG segments of 23.6 sec duration.

Proper citation: EEG time series Data Sets (RRID:SCR_001579) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/

Biomedical technology resource center specializing in novel approaches and tools for neuroimaging. It develops novel strategies to investigate brain structure and function in their full multidimensional complexity. There is a rapidly growing need for brain models comprehensive enough to represent brain structure and function as they change across time in large populations, in different disease states, across imaging modalities, across age and sex, and even across species. International networks of collaborators are provided with a diverse array of tools to create, analyze, visualize, and interact with models of the brain. A major focus of these collaborations is to develop four-dimensional brain models that track and analyze complex patterns of dynamically changing brain structure in development and disease, expanding investigations of brain structure-function relations to four dimensions.

Proper citation: Laboratory of Neuro Imaging (RRID:SCR_001922) Copy   

•   Source: SciCrunch Registry

http://www.fmri.org

THIS RESOURCE IS NO LONGER IN SERVICE, documented on 7/28/13. Core facility of Columbia Neuroscience with the goal of establishing a collaborative and multi-investigator neuroimaging environment that is focused on the investigation of the neurocircuitry of the brain that underlies cognition, perception and action, and also the development of clinical applications that enhance the goals of personalized medicine. Within this environment the specific current research interests of the Hirsch group include several related directions of investigation. The first is conscious and subconscious neural processes that mediate emotion and cognition in healthy individuals and in patients with psychiatric disorders. This direction also includes neurocircuitry that is characteristic of disorders of consciousness such as minimally conscious or vegetative states, self and visual awareness, and attention. Neurocircuitry of other complex cognitive processes such as decisions, inductive and deductive reasoning, language, truthfulness and top-down influences of expectation, reward, and regulation on early visual and mid-level perceptual and emotional systems. On-going projects targeted for clinical applications include benefits for neurosurgery such as the development of task batteries to map the cortical locations of essential functions such as language, motor, sensation, memory, emotion and sensory functions including visions, audition and the chemical senses. Computational innovations for labeling correspondence between brain structure and specific functional regions are under development to achieve the highest interpretive precision. Current projects include integration of EEG and fMRI techniques to localize seizuregenic cortex in relation to eloquent and functioning cortex for neurosurgical planning; integration of TMS and fMRI to discriminate essential and associative language-sensitive cortical areas; and integration of VEP, EEG and fMRI to inform assessments of visual disease secondary to stroke or neural degeneration. Projects intended to refine and enhance diagnosis of psychiatric disorders such as anxiety, depression, and eating disorders include development of specialized paradigms to target dysfunctional neurocircuitry such as emotional systems (amygdala and basal ganglia) and control and regulatory systems (cingulate and pre-frontal cortex). Comparison of before-treatment images with after-treatment images to inform models of both treatment and disease and investigation of the hypothesis that individual genetic and functional differences have predictive value for treatment options and outcome are currently underway. The lab has pioneered techniques for functional mapping of single patients, and operates an active clinical service for mapping individuals for neurosurgical planning, assessments of the neurocircuitry that underlie acquired or inherited disabilities and the mechanisms of neuroplasticity that restore lost functions are actively investigated using both groups and single subject studies. :

Proper citation: fMRI Research Center at Columbia (RRID:SCR_002658) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/pro/BeijingShortTR.html

Dataset of resting state fMRI scans obtained using two different TR's in healthy college-aged volunteers. Specifically, for each participant, data is being obtained with a short TR (0.4 seconds) and a long TR (2.0 seconds). In addition this dataset contains a 64-direction DTI scan for every participant. The following data are released for every participant: * 8-minute resting-state fMRI scan (TR = 2 seconds, # repetitions = 240) * 8-minute resting-state fMRI scans (TR = 0.4 seconds, # repetitions = 1200) * MPRAGE anatomical scan, defaced to protect patient confidentiality * 64-direction diffusion tensor imaging scan (2mm isotropic) * Demographic information

Proper citation: Beijing: Short TR Study (RRID:SCR_003502) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/pro/Quiron-Valencia.html

Resting state datasets, including an anatomical as well as a resting state fMRI scan, collected from a community sample in Valencia, Spain. The first release includes data for 45 participants. Participants were instructed to keep their eyes open during the resting state scan, no visual stimulus was presented. The following data are released for every participant: * Scanner Type: Philips Achieva 3T-TX * One high-resolution T1-weighted mprage, defaced to protect patient confidentiality * At least one 6-minute resting state fMRI scan (R-fMRI), eyes open, no visual stimulus presented * Demographic Information

Proper citation: Quiron-Valencia Sample (RRID:SCR_003538) Copy   

•   Source: SciCrunch Registry

http://www.linked-neuron-data.org/

Neuroscience data and knowledge from multiple scales and multiple data sources that has been extracted, linked, and organized to support comprehensive understanding of the brain. The core is the CAS Brain Knowledge base, a very large scale brain knowledge base based on automatic knowledge extraction and integration from various data and knowledge sources. The LND platform provides services for neuron data and knowledge extraction, representation, integration, visualization, semantic search and reasoning over the linked neuron data. Currently, LND extracts and integrates semantic data and knowledge from the following resources: PubMed, INCF-CUMBO, Allen Reference Atlas, NIF, NeuroLex, MeSH, DBPedia/Wikipedia, etc.

Proper citation: Linked Neuron Data (RRID:SCR_003658) Copy   

•   Source: SciCrunch Registry

http://www.cs.tau.ac.il/~shlomito/tissue-net/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. Network visualizations in which the expression and predicted flux data are projected over the global human network. These network visualizations are accessible through the supplemental website using the publicly available Cytoscape software (Cline, Smoot et al. 2007). Since many high degree nodes exist in the network, special layouts are required to produce network visualizations that are readily interpretable. To this end we produced network visualizations in which hub nodes are repeated multiple times and hence layouts with a small number of edge crossings can be generated. Contains entries for brain compartments and brain pathways.

Proper citation: Network-based Prediction of Human Tissue-specific Metabolism (RRID:SCR_007392) Copy   

•   Source: SciCrunch Registry

http://nac.spl.harvard.edu/

Biomedical Technology Resource Center that develops image processing and analysis techniques for basic and clinical neurosciences. The NAC research approach emphasizes both specific core technologies and collaborative application projects. The core activity of the center is the development of algorithms and techniques for postprocessing of imaging data. New segmentation techniques aid identification of brain structures and disease. Registration methods are used for relating image data to specific patient anatomy or one set of images to another. Visualization tools allow the display of complex anatomical and quantitative information. High-performance computing hardware and associated software techniques further accelerate algorithms and methods. Digital anatomy atlases are developed for the support of both interactive and algorithmic computational tools. Although the emphasis of the NAC is on the dissemination of concepts and techniques, specific elements of the core software technologies have been made available to outside researchers or the community at large. The NAC's core technologies serve the following major collaborative projects: Alzheimer's disease and the aging brain, morphometric measures in schizophrenia and schizotypal disorder, quantitative analysis of multiple sclerosis, and interactive image-based planning and guidance in neurosurgery. One or more NAC researchers have been designated as responsible for each of the core technologies and the collaborative projects.

Proper citation: Neuroimage Analysis Center (RRID:SCR_008998) Copy   

•   Source: SciCrunch Registry