Tools   Select Another Resource Report Type

http://www.cogsci.ucsd.edu/index.php

This UCSD department, the first Cognitive Science Department in the world, provides a focus for the continued evolution of the discipline of cognitive science. Cognitive science is a diverse field unifying three broad categories: the brain, behavior and computation. It's the study of how people, animals and computers think, act and learn. In order to understand the mind/brain, cognitive science brings together the methods and discoveries from neuroscience, psychology, linguistics, anthropology, philosophy and computer science. The interdisciplinary aspects of cognitive science continue to flourish, and the participation of the broader cognitive science community on campus continues to be fundamental to cognitive science as practiced at UCSD. The interdisciplinary Ph.D. program continues to be offered as a degree option (in addition to the departmental Ph.D.), with participation by members of the Departments of Anthropology, Biology, Cognitive Science, Communication, Computer Science and Engineering, Linguistics, Music, Neuroscience, Philosophy, Psychiatry, Psychology, and Sociology. Cognitive Science is a relatively young field that focuses on conducting new research into the field or applying existing knowledge into new applications. This Department contains several research labs each specializing in different areas and the Department's faculty has also been published many times in various publications. Sponsors: This department is supported by the University of California at San Diego.

Proper citation: UCSD Cognitive Science: The Future of Cognitive Science (RRID:SCR_001926) Copy   

•   Source: SciCrunch Registry

http://nips.cc/

The Neural Information Processing Systems (NIPS) Foundation is a non-profit corporation whose purpose is to foster the exchange of research on neural information processing systems in their biological, technological, mathematical, and theoretical aspects. Neural information processing is a field which benefits from a combined view of biological, physical, mathematical, and computational sciences. The primary focus of the NIPS Foundation is the presentation of a continuing series of professional meetings known as the Neural Information Processing Systems Conference, held over the years at various locations in the United States and Canada.

Proper citation: NIPS - Neural Information Processing Systems Conference (RRID:SCR_001998) Copy   

•   Source: SciCrunch Registry

http://hendrix.ei.dtu.dk/software/mriwarp/mriwarp.html

Warping tool for intersubject registration of brain images consisting of C functions for Unix systems plus Matlab visualization utility functions. Apart from warping there are also (command line) functions for ANALYZE header information, mirroring, translation, subsampling. The package cannot only be used as a preprocessing step in function neuroimaging but also as a step in deformation-based morphometry.

Proper citation: MRIWarp (RRID:SCR_002072) Copy   

•   Source: SciCrunch Registry

http://sccn.ucsd.edu/

Computational neuroscience center that observes and models how functional activities in multiple brain areas interact dynamically to support human cognition, creativity and social interaction. Center research involves development computational methods and software, experimental methods and equipment, collection and analysis of human cognitive experiments, and collaborations to analyze data collected by other groups in such experiments. The Center has a 72-channel EEG recording system customized for use in the fMRI environment, and a very-high density Biosemi Active Two active-electrode EEG system, rapidly configurable either as a 256-channel system for a single subject or as two 136-channel systems for recording from two subjects simultaneously. In addition, UCSD now has a 306-channel MEG plus 128-channel EEG system (Neuromag/Elektra). Projects in the Center include studies of human cognitive processes including attention and memory, role of the anterior/posterior cingulate, time perception and emotional expression. Data acquisition includes high-density EEG, concurrent EEG and fMRI recording and analysis, and face video processing. Current analysis approaches include independent component and time-frequency analysis.

Proper citation: Swartz Center for Computational Neuroscience (RRID:SCR_001933) Copy   

•   Source: SciCrunch Registry

http://www.pc.rhul.ac.uk/staff/J.Larsson/software.html

Set of programs and Tk/Tcl scripts, with a GUI wrapper, for extracting the inner and outer cortical surfaces from a T1-weighted MR image of the human brain. It is based on the TFI C++ library and is written for a Unix-based environment (specifically 64-bit and 32-bit versions of Ubuntu). As a courtesy to Apple users a version for Apple/X11 is maintained but the OS X version will always lag the Linux version; also, because some of the third-party libraries SurfRelax relies on may not be supported in or compatible with future versions of OS X, there is no guarantee that the OS X version will be supported indefinitely. Although in principle SurfRelax could be run under Windows (using Cygwin), because of the difficulties of maintaining multiple platforms and the limited support libraries available under Cygwin, there will no longer be support for SurfRelax on this platform. The surfaces are guaranteed to be topologically equivalent to a sphere, thereby obviating the need for handle removal. SurfRelax requires no user intervention, although minor manual editing is recommended for optimal results (normally less than 10 minutes per hemisphere). SurfRelax has several properties that compare favorably with other software packages for surface reconstruction: * Free software - The binaries (written in C++ and Tcl/Tk) are in the public domain. The source code will be released once legacy code issues have been resolved (i.e. replacing with GPL code). * Uses standard public file formats: Analyze file format (SPM/FSL-compatible) for volumes and OOGL OFF binary format for surfaces (see www.geomview.org (http://www.geomview.org/docs/html/geomview_26.html#OOGLRef)) * Combines advantages of volumetric and surface-based methods for surface generation * Correct topology of output surface guaranteed * Requires little or no user intervention - no need for manual handle removal * Relatively robust to noise - multi-scale method compensates for partial volume effects and intensity inhomogeneities * Relatively fast (an entire brain is segmented, extracted and unfolded in less than 2 hours of CPU time) * Powerful editing and visualization tools for volumes and surfaces * Readily extendable - for instance for use with monkey brains or children's brains * Can be used to visualize functional data from SPM or FSL * Includes tools for integration with Stanford's VISTASOFT tools for FMRI data analysis (white.stanford.edu)

Proper citation: SurfRelax (RRID:SCR_002139) Copy   

•   Source: SciCrunch Registry

http://www.incf.org/

Independent international facilitator catalyzing and coordinating global development of neuroinformatics aiming to advance data reuse and reproducibility in global brain research. Integrates and analyzes diverse data across scales, techniques, and species to understand brain function and positively impact the health and well being of society.

Proper citation: International Neuroinformatics Coordinating Facility (RRID:SCR_002282) Copy   

•   Source: SciCrunch Registry

http://www.bioon.com/bioline/neurosci/course/index.htm

An illustrated guide to the essential basics of clinical neuroscience created in conjunction with the first-year course for medical students.
Topics covered:
* Coronal and horizontal sections
* Basic visual pathway
* Basic somatosensory pathway
* Basic motor pathway
* Eye and retina
* Central visual pathways
* Auditory and vestibular systems
* Somatosensory pathways from the body
* Somatosensory pathways from the face
* Spinal motor structures
* Brainstem nuclei of cranial nerves
* Basal ganglia and cerebellum
* Hypothalamus and autonomic nervous system
* Medial temporal lobe and memory
* Sleep and language
* Where is...?

Proper citation: Washington University School of Medicine Neuroscience Tutorial (RRID:SCR_002271) Copy   

•   Source: SciCrunch Registry

http://connectomes.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 28,2025. Project mapping whole mouse brain connectivity using serial block face scanning electron microscopy (SBF-SEM) with a specially-designed whole-brain microtome (WBM). With any luck, the whole mouse brain will be mapped ultrastructurally in the near term, which will then open the door to more serious problems; reliable automated segmentation and circuit reconstruction. These will undoubtedly require advances in machine learning methods and their application. Connectomics Software and a Multiresolution Image Viewer (MIV) is also available.

Proper citation: Connectomes.org (RRID:SCR_002243) Copy   

•   Source: SciCrunch Registry

http://www.kumc.edu/instruction/medicine/anatomy/histoweb/nervous/nervous.htm

Histology atlas of different parts of the nervous system that corresponds with the laboratory exercises of the Cell & Tissue Biology course of the School of Medicine of the University of Kansas. Succinct explanations of the tissues to guide the first-year medical student in the use of their microscope is provided and subsequently serves as a permanent histology resource for all medical students and physicians. Sections of the brain that are included are: * Spinal Cord * Central Canal * White Matter * Gray Matter * Dorsal Root Ganglion * Cerebellum * Cerebrum * Astrocytes * Nerve * Node of Ranvier * Pacinian Corpuscle

Proper citation: HistoWeb: Nervous System (RRID:SCR_002369) Copy   

•   Source: SciCrunch Registry

http://irc.cchmc.org/software/pedbrain.php

Brain imaging data collected from a large population of normal, healthy children that have been used to construct pediatric brain templates, which can be used within statistical parametric mapping for spatial normalization, tissue segmentation and visualization of imaging study results. The data has been processed and compiled in various ways to accommodate a wide range of possible research approaches. The templates are made available free of charge to all interested parties for research purposes only. When processing imaging data from children, it is important to take into account the fact that the pediatric brain differs significantly from the adult brain. Therefore, optimized processing requires appropriate reference data be used because adult reference data will introduce a systematic bias into the results. We have shown that, in the in the case of spatial normalization, the amount of non-linear deformation is dramatically less when a pediatric template is used (left, see also HBM 2002; 17:48-60). We could also show that tissue composition is substantially different between adults and children, and more so the younger the children are (right, see also MRM 2003; 50:749-757). We thus believe that the use of pediatric reference data might be more appropriate.

Proper citation: CCHMC Pediatric Brain Templates (RRID:SCR_003276) Copy   

•   Source: SciCrunch Registry

http://www.macbrain.org/

Portal on how the experiences of early childhood are incorporated into the structures of the developing brain, and how, in turn, those changes in the structures of the brain influence behavior. The network explores how knowledge of brain development can guide us in understanding of behavioral development and vice versa. It focuses specifically on sensitive periods and neural plasticity, the reciprocal phenomena whereby (a) the brain is negatively affected if certain experiences fail to occur within a certain time period, and (b) the brain is altered by experience at virtually any point in the life span. Here we consider not only how the structure of experience is incorporated into the structure of the brain, but also how this knowledge can influence the decisions we make about intervening in the lives of children. Research and other projects conducted by the Network fall into four broad categories: * Effects of early experience on brain development * New methods for studying brain-behavior relations * Comparative studies of early brain-behavioral development * Impact on public policy: Educating educators and the media RESOURCES NimStim Face Stimulus Set The Research Network on Early Experience and Brain Development has developed a battery of 646 facial expression stimuli for use in its own and other studies of face and emotion recognition. Images include the following expressions, displayed by a variety of models of various genders and races: fearful, happy, sad, angry, surprised, calm, neutral, disgusted. They are making these stimuli available to the public free of charge with registration and acceptance of the terms and conditions to use the stimulus set.

Proper citation: Research Network in Early Experience and Brain Development (RRID:SCR_003271) Copy   

•   Source: SciCrunch Registry

http://genome.ucsc.edu/cgi-bin/hgVisiGene

Virtual microscope for viewing in situ images that show where a gene is used in an organism, sometimes down to cellular resolution. The user can examine cell-by-cell as well as tissue-by-tissue expression patterns. Users can retrieve images that meet specific search criteria, then interactively zoom and scroll across the collection. Image set contributions are welcome. The following image collections are currently available for browsing: * High-quality high-resolution images of eight-week-old male mouse sagittal brain slices with reverse-complemented mRNA hybridization probes from the Allen Brain Atlas, courtesy of the Allen Institute for Brain Science * Mouse in situ images from the Jackson Lab Gene Expression Database (GXD) at MGI * Transcription factors in mouse embryos from the Mahoney Center for Neuro-Oncology * Mouse head and brain in situ images from NCBI''''s Gene Expression Nervous System Atlas (GENSAT) database * Xenopus laevis in situ images from the National Institute for Basic Biology (NIBB) XDB project

Proper citation: VisiGene Image Browser (RRID:SCR_003341) Copy   

•   Source: SciCrunch Registry

http://braintrap.inf.ed.ac.uk/braintrap/

This database contains information on protein expression in the Drosophila melanogaster brain. It consists of a collection of 3D confocal datasets taken from EYFP expressing protein trap Drosophila lines from the Cambridge Protein Trap project. Currently there are 884 brain scans from 535 protein trap lines in the database. Drosophila protein trap strains were generated by the St Johnston Lab and the Russell Lab at the University of Cambridge, UK. The piggyBac insertion method was used to insert constructs containing splice acceptor and donor sites, StrepII and FLAG affinity purification tags, and an EYFP exon (Venus). Brain images were acquired by Seymour Knowles-Barley, in the Armstrong Lab at the University of Edinburgh. Whole brain mounts were imaged by confocal microscopy, with a background immunohistochemical label added to aid the identification of brain structures. Additional immunohistochemical labeling of the EYFP protein using an anti-GFP antibody was also used in most cases. The trapped protein signal (EYFP / anti-GFP), background signal (NC82 label), and the merged signal can be viewed on the website by using the corresponding channel buttons. In all images the trapped protein / EYFP signal appears green and the background / NC82 channel appears magenta. Original .lsm image files are also available for download.

Proper citation: BrainTrap: Fly Brain Protein Trap Database (RRID:SCR_003398) Copy   

•   Source: SciCrunch Registry

http://www.pediatricmri.nih.gov/

Data sets of clinical / behavioral and image data are available for download by qualified researchers from a seven year, multi-site, longitudinal study using magnetic resonance technologies to study brain maturation in healthy, typically-developing infants, children, and adolescents and to correlate brain development with cognitive and behavioral development. The information obtained in this study is expected to provide essential data for understanding the course of normal brain development as a basis for understanding atypical brain development associated with a variety of developmental, neurological, and neuropsychiatric disorders affecting children and adults. This study enrolled over 500 children, ranging from infancy to young adulthood. The goal was to study each participant at least three times over the course of the project at one of six Pediatric Centers across the United States. Brain MR and clinical/behavioral data have been compiled and analyzed at a Data Coordinating Center and Clinical Coordinating Center. Additionally, MR spectroscopy and DTI data are being analyzed. The study was organized around two objectives corresponding to two age ranges at the time of enrollment, each with its own protocols. * Objective 1 enrolled children ages 4 years, 6 months through 18 years (total N = 433). This sample was recruited across the six Pediatric Study Centers using community based sampling to reflect the demographics of the United States in terms of income, race, and ethnicity. The subjects were studied with both imaging and clinical/behavioral measures at two year intervals for three time points. * Objective 2 enrolled newborns, infants, toddlers, and preschoolers from birth through 4 years, 5 months, who were studied three or more times at two Pediatric Study Centers at intervals ranging from three months for the youngest subjects to one year as the children approach the Objective 1 age range. Both imaging and clinical/behavioral measures were collected at each time point. Participant recruitment used community based sampling that included hospital venues (e.g., maternity wards and nurseries, satellite physician offices, and well-child clinics), community organizations (e.g., day-care centers, schools, and churches), and siblings of children participating in other research at the Pediatric Study Centers. At timepoint 1, of those enrolled, 114 children had T1 scans that passed quality control checks. Staged data release plan: The first data release included structural MR images and clinical/behavioral data from the first assessments, Visit 1, for Objective 1. A second data release included structural MRI and clinical/behavioral data from the second visit for Objective 1. A third data release included structural MRI data for both Objective 1 and 2 and all time points, as well as preliminary spectroscopy data. A fourth data release added cortical thickness, gyrification and cortical surface data. Yet to be released are longitudinally registered anatomic MRI data and diffusion tensor data. A collaborative effort among the participating centers and NIH resulted in age-appropriate MR protocols and clinical/behavioral batteries of instruments. A summary of this protocol is available as a Protocol release document. Details of the project, such as study design, rationale, recruitment, instrument battery, MRI acquisition details, and quality controls can be found in the study protocol. Also available are the MRI procedure manual and Clinical/Behavioral procedure manuals for Objective 1 and Objective 2.

Proper citation: NIH MRI Study of Normal Brain Development (RRID:SCR_003394) Copy   

•   Source: SciCrunch Registry

http://www.ispa.pt/ui/uie/ibbg/TilapiaBrainAtlas/index.html

Digital three-dimensional MRI atlas of the Mozambique tilapia brain, supported by Nissl staining. Images were viewed and analyzed in all orientations (transverse, sagittal, and horizontal) and manually labelled to reveal structures in the olfactory bulb, telencephalon, diencephalon, optic tectum, and cerebellum. The MRI atlas data (16-bit int) and delineation data (8-bit int) are provided in Raw data (file_name.raw), Amira format (file_name.am) and in Analyze format (file_name.img and file_name.hdr).

Proper citation: Brain Atlas of the Mozambique Tilapia Oreochromis mossambicus (RRID:SCR_003501) Copy   

•   Source: SciCrunch Registry

http://www.humanconnectomeproject.org/

A multi-center project comprising two distinct consortia (Mass. Gen. Hosp. and USC; and Wash. U. and the U. of Minn.) seeking to map white matter fiber pathways in the human brain using leading edge neuroimaging methods, genomics, architectonics, mathematical approaches, informatics, and interactive visualization. The mapping of the complete structural and functional neural connections in vivo within and across individuals provides unparalleled compilation of neural data, an interface to graphically navigate this data and the opportunity to achieve conclusions about the living human brain. The HCP is being developed to employ advanced neuroimaging methods, and to construct an extensive informatics infrastructure to link these data and connectivity models to detailed phenomic and genomic data, building upon existing multidisciplinary and collaborative efforts currently underway. Working with other HCP partners based at Washington University in St. Louis they will provide rich data, essential imaging protocols, and sophisticated connectivity analysis tools for the neuroscience community. This project is working to achieve the following: 1) develop sophisticated tools to process high-angular diffusion (HARDI) and diffusion spectrum imaging (DSI) from normal individuals to provide the foundation for the detailed mapping of the human connectome; 2) optimize advanced high-field imaging technologies and neurocognitive tests to map the human connectome; 3) collect connectomic, behavioral, and genotype data using optimized methods in a representative sample of normal subjects; 4) design and deploy a robust, web-based informatics infrastructure, 5) develop and disseminate data acquisition and analysis, educational, and training outreach materials.

Proper citation: MGH-USC Human Connectome Project (RRID:SCR_003490) Copy   

•   Source: SciCrunch Registry

http://www.brainfacts.org/

A web portal that aggregates information and educational materials about the brain and brain diseases. Resources such as videos, key brain concepts, and hands-on activities may be used and shared with the public.

Proper citation: brainfacts.org (RRID:SCR_003514) Copy   

•   Source: SciCrunch Registry

http://pons.incf.org/

Program consisting of three Task Forces and one Working Group to promote data exchange and integration in the neurosciences by developing terminology standards and formal ontologies for neural structures. Closely linked to the Program on Digital Brain Atlasing, the Program aims to establish a structured lexicon for the translation and definition of terms describing neural structures at multiple levels of granularity. The three Task Forces and one Working Group involved in the PONS effort: * Structural lexicon * Neuron registry * Representation and deployment * KnowledgeSpace Working Group Structural lexicon, Neuron registry, Representation and deployment, and KnowledgeSpace Working Group.

Proper citation: Program on Ontologies of Neural Structures (RRID:SCR_003549) Copy   

•   Source: SciCrunch Registry

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

Dataset consisting of a community sample of individuals ranging in age from 18 to 60 years old with at least two 7.5-minute resting state fMRI scans. During the resting state scan participants were instructed to relax while keeping their eyes open. In part of the sample eye status was randomized between scans. The particular eye status for each scan is indicated in the phenotypic information. No visual stimulus was presented. A subset of participants completed the ICS and PANAS affective behavior scales. The following data are released for every participant: * Scanner Type: Siemens, 3T Trio Tim * 7.5-minute resting state fMRI scan (R-fMRI) * MPRAGE anatomical scan, defaced to protect patient confidentiality * Demographic information, inluding ICS and PANAS scores (included in the release file).

Proper citation: Neuro Bureau - Berlin Mind and Brain Sample (RRID:SCR_003537) Copy   

•   Source: SciCrunch Registry

http://www.incf.org/activities/our-programs/pons/cumbo

Ontology of formal definitions (i.e., machine processable) for the types of structures commonly described in neuroanatomy.

Proper citation: Common Upper Mammalian Brain Ontology (RRID:SCR_003629) Copy   

•   Source: SciCrunch Registry