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Related Concept Videos

Brain Imaging01:14

Brain Imaging

212
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...
212

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High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
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Principles of intensive human neuroimaging.

Eline R Kupers1, Tomas Knapen2, Elisha P Merriam3

  • 1Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA; Department of Psychology, Stanford University, Stanford, CA, USA.

Trends in Neurosciences
|October 25, 2024
PubMed
Summary
This summary is machine-generated.

Intensive functional magnetic resonance imaging (fMRI) offers a new deep fMRI approach for detailed brain function analysis. This method focuses on extensive cognitive sampling to support computational modeling and single voxel investigations.

Keywords:
big databrain imagingcognitiondata qualitydeep fMRIfunctional MRI

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Neuroimaging

Background:

  • Large, shared functional magnetic resonance imaging (fMRI) datasets are crucial in human neuroscience.
  • Current approaches include 'wide' fMRI (many individuals, less data) and 'deep' fMRI (few individuals, more data).

Purpose of the Study:

  • Introduce and define 'intensive' fMRI as an emerging deep fMRI strategy.
  • Highlight its potential for advanced computational modeling and single-voxel brain function analysis.
  • Discuss principles, trade-offs, and practical considerations for this approach.

Main Methods:

  • Focus on extensive sampling of cognitive phenomena.
  • Emphasize careful experimental design for a rich hypothesis space.
  • Incorporate optimization of data quality and strategic curation of public resources.

Main Results:

  • Intensive fMRI enables detailed investigation of brain function at the single voxel level.
  • This approach supports robust computational modeling of cognitive processes.
  • It necessitates more than just increased data collection, requiring strategic design and curation.

Conclusions:

  • Intensive fMRI represents a significant advancement within deep fMRI methodologies.
  • It provides a powerful framework for exploring complex cognitive phenomena and neural mechanisms.
  • Maximizing community impact through curated resources is essential for the success of intensive fMRI.