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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
The hindbrain, located at the base of the brain, plays a vital role in regulating automatic processes that sustain life. It includes the medulla oblongata, which is essential for...
Brain Imaging01:14

Brain Imaging

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.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).
Anatomy of the Brain: Major Regions01:20

Anatomy of the Brain: Major Regions

The brain is the most complex organ in the human body. It consists of four main parts: the cerebrum, diencephalon, cerebellum, and brainstem.
The cerebrum is the largest section of the brain and divides into left and right hemispheres, separated by a deep fissure. The cerebral outer layer of grey matter — the cerebral cortex — comprises elevations called gyri and shallow groves called sulci. The inner portion of white matter includes long nerve fibers known as axons, which connect various areas...

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Related Experiment Video

Updated: Jun 3, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
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Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

A framework on surface-based connectivity quantification for the human brain.

Hao Huang1, Jerry L Prince, Virendra Mishra

  • 1Advanced Imaging Research Center, University of Texas Southwestern Medical Center, United States. hao.huang@utsouthwestern.edu

Journal of Neuroscience Methods
|March 15, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel framework for quantifying human brain cortical connectivity using MRI and tractography. The method reveals connectivity signatures, aiding in the detection of abnormalities in conditions like schizophrenia.

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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

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Related Experiment Videos

Last Updated: Jun 3, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
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Published on: October 13, 2023

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol
10:14

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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Medical Image Analysis

Background:

  • Quantifying brain cortical connectivity is crucial for understanding brain function and diseases.
  • Current methods face challenges in representing complex cortical surface structures.

Purpose of the Study:

  • To present a framework for quantifying connectivity between arbitrary surface patches in the human brain cortex.
  • To enable detailed analysis of brain connectivity patterns for clinical applications.

Main Methods:

  • Utilized structural MRI for cortical surface segmentation and labeling.
  • Employed diffusion tensor imaging (DTI) tractography for connection mapping.
  • Applied nonlinear inter-subject registration to a template space for population analysis.
  • Defined connectivity intensity and proportion metrics for quantifying connections.

Main Results:

  • Developed population connectivity metrics (average intensity, average proportion) in a template space.
  • Derived connectivity profiles and histograms for specific cortical regions of interest.
  • Applied the framework to schizophrenia patients and controls, identifying distinct connectivity signatures and abnormalities.

Conclusions:

  • The proposed framework effectively quantifies cortical connectivity using advanced neuroimaging techniques.
  • This method aids in identifying and characterizing brain connectivity abnormalities relevant to neurological and psychiatric disorders.
  • The derived metrics offer valuable insights into brain function and disease mechanisms.