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Linking Brain Structure, Activity, and Cognitive Function through Computation.

eNeuro | 2022

Understanding the human brain is a "Grand Challenge" for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by principles and theories of brain function, are instrumental for linking brain structure and function. An example of a resource enabling such an integrated approach to neuroscientific discovery is the BigBrain, which spatially anchors tissue models and data across different scales and ensures that multiscale models are supported by the data, making the bridge to both basic neuroscience and medicine. Research at the intersection of neuroscience, computing and robotics has the potential to advance neuro-inspired technologies by taking advantage of a growing body of insights into perception, plasticity and learning. To render data, tools and methods, theories, basic principles and concepts interoperable, the Human Brain Project (HBP) has launched EBRAINS, a digital neuroscience research infrastructure, which brings together a transdisciplinary community of researchers united by the quest to understand the brain, with fascinating insights and perspectives for societal benefits.

Pubmed ID: 35217544 RIS Download

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This is a list of tools and resources that we have found mentioned in this publication.


MGH-USC Human Connectome Project (tool)

RRID:SCR_003490

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.

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EBRAINS (tool)

RRID:SCR_019260

Research infrastructure for the EU Human Brain Project. Provides digital tools and services which can be used to address challenges in brain research and brain inspired technology development. Digital research infrastructure, created by EU-funded Human Brain Project, that gathers extensive range of data and tools for brain-related research. EBRAINS will capitalize on the work performed by the Human Brain Project teams in digital neuroscience, brain medicine, and brain-inspired technology.You can share your neuroscience data, models and software.

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BigBrain (tool)

RRID:SCR_001593

Ultrahigh resolution 3D human brain model at nearly cellular resolution of 20 micrometers, based on reconstruction of histological sections. Provides considerable neuroanatomical insight into human brain, thereby allowing extraction of microscopic data for modeling and simulation. Enables testing of hypotheses on optimal path lengths between interconnected cortical regions or on spatial organization of genetic patterning, redefining traditional neuroanatomy maps such as those of Brodmann and von Economo.

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