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Related Concept Videos

Organization of the Brain01:30

Organization of the Brain

The brain is an integral component of the nervous system and serves as the center for processing sensory inputs, making decisions, and directing bodily actions. This complex organ is organized into three primary sections: the hindbrain, midbrain, and forebrain, each responsible for a range of vital functions.
Hindbrain
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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
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Neuroplasticity01:01

Neuroplasticity

Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.

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3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol
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Published on: May 12, 2019

Neuroinformatics: from bioinformatics to databasing the brain.

Thomas M Morse1

  • 1Department of Neurobiology, Yale University School of Medicine, 336 Cedar Street, New Haven, CT 06510, USA. tom.morse@yale.edu

Bioinformatics and Biology Insights
|October 9, 2009
PubMed
Summary
This summary is machine-generated.

Neuroinformatics integrates diverse brain data and tools for understanding neurological function and disorders. It bridges traditional bioinformatics with complex, multi-scale neuroscience data challenges.

Keywords:
betweencomparisondifferenceoverlapsimilarityunderstand

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Area of Science:

  • Neuroscience
  • Bioinformatics
  • Computational Biology

Background:

  • Neuroinformatics aims to build web-accessible databases and software tools for neuroscience research.
  • Understanding the nervous system requires integrating diverse data types, from gene sequences to brain imaging and clinical data.
  • Challenges arise from the wide range of spatial scales and data types in neuroinformatics.

Purpose of the Study:

  • To review neuroinformatics and clarify its relationship with traditional and modern bioinformatics.
  • To highlight the complexities and scope of neuroinformatics in neuroscience research.

Main Methods:

  • Review of existing neuroinformatics databases and software tools.
  • Comparison of neuroinformatics data types and scales with traditional bioinformatics.
  • Discussion of challenges in integrating multi-modal neuroscience data.

Main Results:

  • Neuroinformatics encompasses a broad spectrum of neuroscience data, including genomics, atlases, imaging (PET, fMRI, EEG, MEG), electrophysiology, and clinical data.
  • Building comprehensive neuroinformatics resources is complex due to the heterogeneity of data and spatial scales.
  • Neuroinformatics extends traditional bioinformatics by incorporating a wider array of biological and clinical data.

Conclusions:

  • Neuroinformatics is crucial for advancing our understanding of the nervous system and neurological disorders.
  • Effective neuroinformatics requires innovative solutions to manage and analyze diverse, multi-scale datasets.
  • The field is rapidly evolving, integrating traditional bioinformatics with new data types and analytical approaches.