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Related Concept Videos

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Related Experiment Video

Updated: May 27, 2026

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
10:06

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

Surface-based analysis methods for high-resolution functional magnetic resonance imaging.

Rez Khan1, Qin Zhang, Shayan Darayan

  • 1Imaging Research Center, 3925B West Braker Lane, Austin TX, 78757 USA.

Graphical Models
|November 30, 2011
PubMed
Summary
This summary is machine-generated.

High-resolution functional magnetic resonance imaging (fMRI) offers deeper brain insights. New surface-based methods analyze fMRI depth profiles, improving brain activity studies.

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Last Updated: May 27, 2026

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
10:06

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

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
  • Human Brain Activity Analysis

Background:

  • Functional magnetic resonance imaging (fMRI) is widely used for brain studies.
  • Standard fMRI resolution averages cortical thickness, limiting detailed analysis.
  • High-resolution fMRI (<1.5-mm sampling) requires new analytical approaches to capture depth variations.

Purpose of the Study:

  • To develop surface-based methods for analyzing high-resolution fMRI data.
  • To enable depth analysis of functional activity within the cerebral cortex.
  • To improve the contrast-to-noise ratio in high-resolution fMRI studies.

Main Methods:

  • Utilizing white-matter segmentations and deformable-surface algorithms.
  • Creating smooth surface representations of the gray-white interface and pial membrane.
  • Calculating vertex positions and normals for precise depth measurements.

Main Results:

  • Developed methods to exploit high-resolution fMRI for depth analysis.
  • Enabled averaging schemes that enhance contrast-to-noise ratio.
  • Facilitated direct analysis of functional activity depth profiles in the brain.

Conclusions:

  • Surface-based methods are effective for high-resolution fMRI depth analysis.
  • These techniques allow for a more detailed understanding of brain activity variations.
  • The approach enhances the utility of advanced fMRI for neuroscience research.