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https://www.amazon.com/How-Brain-Works-Mark-Dubin/dp/0632044411

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Is the Brain (Like) a Computer is an e-book written by Prof. Mark Dubin. It consists of the following: Introduction. Why do we consider the relationship of brains and computers and what does this have to do with consciousness? What's a Brain Made Of? A thought experiment. Test Drive a Turing Machine. A theoretical approach. Interim Summary. Many of the main pages have links to additional information. When you click on one of those links a NEW page will open ON TOP of the page you are clicking from. This convention is adopted so that you can look at the additional information and then easily return to the main page you got there from.

Proper citation: Is the Brain (Like) a Computer (RRID:SCR_008809) Copy   

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http://healthybrain.umn.edu/

Research forum portal to address brain status by acquiring comprehensive, multimodal data from healthy humans across the lifespan to characterize brain status, assess its change over time, and associate composite descriptors of brain status. Specifically, the measurements are acquired noninvasively by existing neuroimaging technologies (structural MRI, functional MRI, magnetic resonance spectroscopy, diffusion MRI, and magnetoencephalography); in addition, genetic, cognitive, language, and lifestyle data are acquired. Goals: * Derive the Brain Health Index- An integrative assessment of brain status derived from multimodal measurements of brain structure, function, and chemistry. * Continue acquiring data to construct the first-ever databank on brain, cognitive, language and genetic measurements for healthy people across the lifespan. * Provide a novel and unique dataset by which to: characterize brain status, assess its change over time, and associate it with genetic makeup, cognitive function, and language abilities. * Forecast future brain health and disease based on current measurements and guide physicians towards new interventions and evaluate interventions as they develop. * Extend to siblings and other family members to further assess the genetic influences and inheritability.

Proper citation: HBP: Healthy Brain Project (RRID:SCR_013137) Copy   

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https://github.com/NOCIONS/letswave6/wiki/Download-and-setup

Open source electroencephalogram (EEG) signal processing toolbox to process and visualise EEG/MEG data and other neurophysiological signals.

Proper citation: Letswave (RRID:SCR_016414) Copy   

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http://brainliner.jp

Portal and tools for sharing and editing neurophysiological and behavioral data for brain-machine interface research. Users can search for existing data or login with their Google, Facebook, or Twitter account and upload new data. Their main focus is on supporting brain-machine interface research, so we encourage users to not just provide recordings of brain activity data, but also information about stimuli, etc., so that statistical relationships can be found between stimuli and/or subject behavior and brain activity. The Matlab tools are for writing, reading, and converting Neuroshare files, the common file format. A free, open source desktop tool for editing neurophysiological data for brain-machine interface research is also available: https://github.com/ATR-DNI/BrainLiner Since data formats aren''''t standardized between programs and researchers, data and analysis programs for data cannot be easily shared. Neuroshare was selected as the common file format. Neuroshare can contain several types of neurophysiological data because of its high flexibility, including analog time-series data and neuronal spike timing. Some applications have plug-ins or libraries available that can read Neuroshare format files, thus making Neuroshare somewhat readily usable. Neuroshare can contain several types of neurophysiological data, but there were no easy tools to convert data into the Neuroshare format, so they made and are providing a Neuroshare Converter Library and Simple Converter using the library. In future work they will make and provide many more useful tools for data sharing. Shared experiments include: EMG signal, Takemiya Exp, Reconstruct (Visual image reconstruction from human brain activity using a combination of multi-scale local image decoders), SPIKE data, Speech Imagery Dataset (Single-trial classification of vowel speech imagery using common spatial patterns), Functional Multineuron Calcium Imaging (fMCI), Rock-paper-scissors (The data was obtained from subject while he make finger-form of rock/paper/scissors). They also have a page at https://www.facebook.com/brainliner where you can contact us

Proper citation: BrainLiner (RRID:SCR_004951) Copy   

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http://www.med.umkc.edu/psychiatry/nbtb/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 31, 2016. The UMKC Neuroscience Brain Tissue Bank and Research Laboratory has been established to obtain, process, and distribute human brain tissue to qualified scientists and clinicians dedicated to neuroscience research. No other living organ approaches the human brain in complexity or capacity. Healthy, it astounds and inspires miracles. Diseased, it confounds and diminishes hope. The use of human brain tissue for research will provide insight into the anatomical and neurochemical aspects of diseased and non-diseased brains. While animal models are helpful and necessary in understanding disease, certain disorders can be more efficiently studied using human brain tissue. Also, modern research techniques are often best applied to human tissue. We also need samples of brain tissue that have not been affected by disease. They help us to compare a 'normal' brain with a diseased one. Also, we have a critical need for brain donations from relatives who have genetically inherited disorders. Tissue preparation consists of fresh quick-frozen tissue blocks or coronal slices (nitrogen vapor frozen; custom dissection of specific anatomic regions) or formalin-fixed coronal slices (custom dissection of specific anatomic regions).

Proper citation: UMKC Neuroscience Brain Tissue Bank and Research Laboratory (RRID:SCR_005148) Copy   

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http://www.tnp.pitt.edu/pages/donationfrm_mb.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 19,2024. Brain tissue donation is a valuable contribution to mental health research. It enables scientists to investigate how the normal brain works, and how the brain is disturbed when it is affected by schizophrenia, depression, bipolar (manic depressive) disease or other related disorders. The Department of Psychiatry at the University of Pittsburgh has established a brain tissue bank to which brain tissue can be donated at no expense. The gift of brain tissue enables scientists to conduct research designed to understand causes, to develop new treatments, and ultimately to find cures for diseases that affect the brain. Brain tissue donation is a gift that makes it possible for researchers to study various types of mental disorders. Donations of brain tissue from individuals without these disorders are also needed to establish comparisons with brain samples from individuals who have these disorders. Any legally competent adult or guardian may indicate during life their interest in donating brain tissue after death. Next-of-kin either of healthy individuals or of those with psychiatric disorders may give consent to donate brain tissue following the death of a loved one. Brain tissue is removed during autopsy at a morgue or hospital and is transported to the University of Pittsburgh Medical Center for examination and study.

Proper citation: University of Pittsburgh Brain Tissue Donation Program (RRID:SCR_005028) Copy   

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https://adrc.mc.duke.edu/index.php/research/brain-bank

A research repository of human brains with neurological disorders and normal controls, recruited through the Autopsy and Brain Donation Program coordinator. The Kathleen Price Bryan Brain Bank contains brains from patients with Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis, Huntington's disease, Muscular Dystrophy, and other neurological and dementing disorders. The brain tissue is subjected to a detailed neuropathological evaluation and then stored as fixed and frozen hemispheres, paraffin blocks and histological slides. After receipt of an IRB approved request, tissue is supplied to investigators at Duke University, major medical centers and pharmaceutical companies across the United States and worldwide.

Proper citation: Duke University Kathleen Price Bryan Brain Bank (RRID:SCR_005022) Copy   

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http://glioblastoma.alleninstitute.org/

Platform for exploring the anatomic and genetic basis of glioblastoma at the cellular and molecular levels that includes two interactive databases linked together by de-identified tumor specimen numbers to facilitate comparisons across data modalities: * The open public image database, here, providing in situ hybridization data mapping gene expression across the anatomic structures inherent in glioblastoma, as well as associated histological data suitable for neuropathological examination * A companion database (Ivy GAP Clinical and Genomic Database) offering detailed clinical, genomic, and expression array data sets that are designed to elucidate the pathways involved in glioblastoma development and progression. This database requires registration for access. The hope is that researchers all over the world will mine these data and identify trends, correlations, and interesting leads for further studies with significant translational and clinical outcomes. The Ivy Glioblastoma Atlas Project is a collaborative partnership between the Ben and Catherine Ivy Foundation, the Allen Institute for Brain Science and the Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment.

Proper citation: Ivy Glioblastoma Atlas Project (RRID:SCR_005044) Copy   

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http://en.wikibooks.org/wiki/MINC/Atlases

A linear average model atlas produced by the International Consortium for Brain Mapping (ICBM) project. A set of full- brain volumetric images from a normative population specifically for the purposes of generating a model were collected by the Montreal Neurological Institute (MNI), UCLA, and University of Texas Health Science Center at San Antonio Research Imaging Center (RIC). 152 new subjects were scanned using T1, T2 and PD sequences using a specific protocol. These images were acquired at a higher resolution than the original average 305 data and exhibit improved contrast due predominately to advances in imaging technology. Each individual was linearly registered to the average 305 and a new model was formed. In total, three models were created at the MNI, the ICBM152_T1, ICBM152_T2 and ICBM152_PD from 152 normal subjects. This resulting model is now known as the ICBM152 (although the model itself has not been published). One advantage of this model is that it exhibits better contrast and better definition of the top of the brain and the bottom of the cerebellum due to the increased coverage during acquisition. The entirely automatic analysis pipeline of this data also included grey/white matter segmentation via spatial priors. The averaged results of these segmentations formed the first MNI parametric maps of grey and white matter. The maps were never made publicly available in isolation but have formed parts of other packages for some time including SPM, FSL AIR and as models of grey matter for EEG source location in VARETTA and BRAINWAVE. Again, as these models are an approximation of Talairach space, there are differences in varying areas, to continue our use of origin shift as an example, the ICBM models are approximately 152: +3.5mm in Z and +-co-ordinate -3.5mm and 2.0mm in Y as compared to the original Talairach origin. In addition to the standard analysis performed on the ICBM data, 64 of the subjects data were segmented using model based segmentation. 64 of the original 305 were manually outlined and a resulting parametric VOI atlas built. The native data from these acquisitions was 256x256 with 1mm slices. The final image resolution of this data was 181x217x181 with 1mm isotropic voxels. Refer to the ICBM152 NonLinear if you are fitting an individual to model and do not care about left/right comparisons. A short history of the various atlases that have been produced at the BIC (McConnell Brain Imaging Center, Montreal Neurological Institute) is provided.

Proper citation: MINC/Atlases (RRID:SCR_005281) Copy   

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http://www.neurosci.ucsd.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 31, 2016. The Laboratory of Experimental Neuropathology is engaged in the study of neurodegenerative disease, including Alzheimer's, Parkinson's, and the dementia of HIV encephalitis. It contains a large bank of materials available to fellow investigators including images, publications, and lab safety. Fellow Investigators and Collaborators may request materials from the brain bank. Technologies employed by the laboratory include immunocytochemistry, neurochemistry, molecular genetics, transgenic models of disease, and imaging by scanning laser confocal microscopy.

Proper citation: UCSD Experimental Neuropath Laboratory (RRID:SCR_004906) Copy   

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http://www.bri.ucla.edu

Portal touching on all aspects of neuroscience from molecules to the mind, from the laboratory bench to the patient's bedside. Members study the normal structure and workings of the nervous system, its development, its cognitive functions, its derangement by disease and injury, and the means of its repair and protection. Projects span traditional disciplinary boundaries, as do graduate and postdoctoral training programs. Its major achievement has been to foster and improve multidisciplinary collaborations which has increasingly permitted the identification of pathogenic mechanisms and the formulation of new therapeutic approaches.

Proper citation: Brain Research Institute (RRID:SCR_004988) Copy   

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http://211.73.64.34/NNG

Neuron Navigator (NNG) integrates a 3D neuron image database into an easy-to-use visual interface. Via a flexible and user-friendly interface, NNG is designed to help researchers analyze and observe the connectivity within the neural maze and discover possible pathways. With NNG''s 3D neuron image database, researchers can perform volumetric searches using the location of neural terminals, or the occupation of neuron volumes within the 3D brain space. Also, the presence of the neurons under a combination of spatial restrictions can be shown as well. NNG is a result of a multi-discipline collaboration between neuroscientists and computer scientists, and NNG has now been implemented on a coordinated brain space for the Drosophila (fruit fly) brain. Account is required.

Proper citation: Neuron Navigator (RRID:SCR_005063) Copy   

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http://brainethics.org/

There are a lot of fine blogs out there covering the avalance of current neuroscience research. With this blog Thomas Rams��y & Martin Skov want to highlight the many consequences of this growing understanding of the human brain. We are especially interested in two types of consequences: Tinkering with the brain and What is it like to be a human being? * Tinkering with the brain: First and foremost, with an understanding of how the brain works comes the possibility of tinkering with it. We already use billions of dollars every year on psychopharmocologia trying to treat depression, schizophrenia, obsessive-compulsive disorder and other mental diseases. But should we also use our knowledge of the brain to treat undesirable mental traits such as pedophilia or sociopathy? And what about enhancing normal brains? Clearly, evolution hasn''t endowed us with the most efficient brain imaginable. Shouldn''t we do something about its many shortcomings? * What is it like to be a human being?: Secondly, our view of human behavior is sure to change with our improved understanding of the human brain. Our knowledge of core human faculties such as language, social reasoning, aesthetics, and economics is already being challenged by modern neuroscience, yielding multiple hard questions. Do we have a free will? Is the mind innate or plastic? If people are not responsible for their actions (since all actions are caused by blind molecular processes) does our legal system still make sense? In short, will modern neuroscience come to completely redefine human nature? We try to discuss contemporary research literature, not just news reports. Although we will occasionally also target popular science reports, since we believe they play an important role in dissemining lessons from the lab. And in the future we plan to also post interviews with interesting researchers, as well as link to our own publications in journals and books. Additionally, the latest and most important books in the multidisciplinary field of neuroscience, cognition, psychology, ethics and economics are presented.

Proper citation: BrainEthics (RRID:SCR_005530) Copy   

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http://neurolex.org/wiki/Main_Page

A freely editable semantic wiki for community-based curation of the terms used in Neuroscience. Entries are curated and eventually incorporated into the formal NIFSTD ontology. NeuroLex also includes a Resource branch for community members to freely add neuroscience relevant resources that do not become part of NIFSTD ontology but rather make up the NIF Registry. As part of the NIF, we provide a simple search interface to many different sources of neuroscience information and data. To make this search more effective, we are constructing ontologies to help organize neuroscience concepts into category hierarchies, e.g., neuron is a cell. These categories provide the means to perform more effective searches and also to organize and understand the information that is returned. But an important adjunct to this activity is to clearly define all of the terms that we use to describe our data, e.g., anatomical terms, techniques, organism names. Because wikis provide an easy interface for communities to contribute their knowledge, we started the NeuroLex.

Proper citation: NeuroLex (RRID:SCR_005402) Copy   

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http://fcon_1000.projects.nitrc.org/

Collection of resting state fMRI (R-fMRI) datasets from sites around world. It demonstrates open sharing of R-fMRI data and aims to emphasize aggregation and sharing of well-phenotyped datasets.

Proper citation: 1000 Functional Connectomes Project (RRID:SCR_005361) Copy   

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http://www.med.harvard.edu/AANLIB/

An atlas of normal and abnormal brain images intended as an introduction to basic neuroanatomy, with emphasis on the pathoanatomy of several leading central nervous system diseases that integrates clinical information with magnetic resonance (MR), x-ray computed tomography (CT), and nuclear medicine images. A range of brain abnormalities are presented including examples of certain brain disease presented with various combinations of image type and imaging frequency. Submissions of concise, exemplary, clinically driven examples of neuroimaging are welcome.

Proper citation: Whole Brain Atlas (RRID:SCR_005390) Copy   

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http://science.education.nih.gov/home2.nsf/feature/index.htm

The NIH Office of Science Education (OSE) coordinates science education activities at the NIH and develops and sponsors science education projects in house. These programs serve elementary, secondary, and college students and teachers and the public. Activities * Develop curriculum supplements and other educational materials related to medicine and research through collaborations with scientific experts at NIH * Maintain a website as a central source of information about NIH science education resources * Establish national model programs in public science education, such as the NIH Mini-Med School and Science in the Cinema * Promote science education reform as outlined in the National Science Education Standards and related guidelines The OSE was established in 1991 within the Office of Science Policy of the Office of the Director of the National Institutes of Health. The NIH is the world''s foremost biomedical research center and the U.S. federal government''s focal point for such research. It is one of the components of the Department of Health and Human Services (HHS). The Office of Science Education (OSE) plans, develops, and coordinates a comprehensive science education program to strengthen and enhance efforts of the NIH to attract young people to biomedical and behavioral science careers and to improve science literacy in both adults and children. The function of the Office is as follows: (1) develops, supports, and directs new program initiatives at all levels with special emphasis on targeting students in grades kindergarten to 16, their educators and parents, and the general public; (2) advises NIH leadership on science education issues; (3) examines and evaluates research and emerging trends in science education and literacy for policy making; (4) works closely with the NIH extramural, intramural, women''s health, laboratory animal research, and minority program offices on science education special issues and programs to ensure coordination of NIH efforts; (5) works with NIH institutes, centers, and divisions to enhance communication of science education activities; and (6) works cooperatively with other public- and private-sector organizations to develop and coordinate activities.

Proper citation: NIH Office of Science Education (RRID:SCR_005603) Copy   

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http://www.nimh.nih.gov/educational-resources/brain-basics/brain-basics.shtml

Brain Basics provides information on how the brain works, how mental illnesses are disorders of the brain, and ongoing research that helps us better understand and treat disorders. Mental disorders are common. You may have a friend, colleague, or relative with a mental disorder, or perhaps you have experienced one yourself at some point. Such disorders include depression, anxiety disorders, bipolar disorder, attention deficit hyperactivity disorder (ADHD), and many others. Some people who develop a mental illness may recover completely; others may have repeated episodes of illness with relatively stable periods in between. Still others live with symptoms of mental illness every day. They can be moderate, or serious and cause severe disability. Through research, we know that mental disorders are brain disorders. Evidence shows that they can be related to changes in the anatomy, physiology, and chemistry of the nervous system. When the brain cannot effectively coordinate the billions of cells in the body, the results can affect many aspects of life. Scientists are continually learning more about how the brain grows and works in healthy people, and how normal brain development and function can go awry, leading to mental illnesses. Brain Basics will introduce you to some of this science, such as: * How the brain develops * How genes and the environment affect the brain * The basic structure of the brain * How different parts of the brain communicate and work with each other * How changes in the brain can lead to mental disorders, such as depression.

Proper citation: Brain Basics (RRID:SCR_005606) Copy   

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http://fcon_1000.projects.nitrc.org/indi/adhd200/index.html#

A grassroots initiative dedicated to accelerating the scientific community''''s understanding of the neural basis of ADHD through the implementation of open data-sharing and discovery-based science. They believe that a community-wide effort focused on advancing functional and structural imaging examinations of the developing brain will accelerate the rate at which neuroscience can inform clinical practice. The ADHD-200 Global Competition invited participants to develop diagnostic classification tools for ADHD diagnosis based on functional and structural magnetic resonance imaging (MRI) of the brain. Applying their tools, participants provided diagnostic labels for previously unlabeled datasets. The competition assessed diagnostic accuracy of each submission and invited research papers describing novel, neuroscientific ideas related to ADHD diagnosis. Twenty-one international teams, from a mix of disciplines, including statistics, mathematics, and computer science, submitted diagnostic labels, with some trying their hand at imaging analysis and psychiatric diagnosis for the first time. The data for the competition was provided by the ADHD-200 Consortium. Consortium members from institutions around the world provided de-identified, HIPAA compliant imaging datasets from almost 800 children with and without ADHD. A phenotypic file including all of the test set subjects and their diagnostic codes can be downloaded. Winner is presented. The ADHD-200 consortium included: * Brown University, Providence, RI, USA (Brown) * The Kennedy Krieger Institute, Baltimore, MD, USA (KKI) * The Donders Institute, Nijmegen, The Netherlands (NeuroImage) * New York University Medical Center, New York, NY, USA (NYU) * Oregon Health and Science University, Portland, OR, USA (OHSU) * Peking University, Beijing, P.R.China (Peking 1-3) * The University of Pittsburgh, Pittsburgh, PA, USA (Pittsburgh) * Washington University in St. Louis, St. Louis, MO, USA (WashU)

Proper citation: ADHD-200 Sample (RRID:SCR_005358) Copy   

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http://cbrain.mcgill.ca/

A flexible software platform for distributed processing, analysis, exchange and visualization of brain imaging data. The expected result is a middleware platform that will render the processing environment (hardware, operating systems, storage servers, etc...) transparent to a remote user. Interaction with a standard web browser allows application of complex algorithm pipelines to large datasets stored at remote locations using a mixture of network available resources such as small clusters, neuroimaging tools and databases as well as Compute Canada's High Performance Computing Centers (HPC). Though the focus of CBRAIN is providing tools for use by brain imaging researchers, the platform is generalizable to other imaging domains, such as radiology, surgical planning and heart imaging, with profound consequences for Canadian medical research. CBRAIN expanded its concept to include international partners in the US, Germany and Korea. As of December 2010, GBRAIN has made significant progress with the original three partners and has developed new partners in Singapore, China, India, and Latin America. CBRAIN is currently deployed on 6 Compute Canada HPC clusters, one German HPC cluster and 3 clusters local to McGill University Campus, totaling more than 80,000 potential CPU cores.

Proper citation: CBRAIN (RRID:SCR_005513) Copy   

•   Source: SciCrunch Registry