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Sulcal pits and patterns in developing human brains.

Kiho Im1, P Ellen Grant2

  • 1Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA 02215, USA; Division of Newborn Medicine, Boston Children's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA.

Neuroimage
|March 31, 2018
PubMed
Summary
This summary is machine-generated.

Early human brain sulcal patterns, identified using graph analysis, show genetic influence and aid in detecting developmental abnormalities. This research offers insights into brain development and function.

Keywords:
Early cortical foldingFetal brainSulcal patternSulcal pit

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Area of Science:

  • Neuroscience
  • Developmental Biology
  • Medical Imaging

Background:

  • Early sulcal folds are hypothesized to have stronger genetic control and influence brain organization.
  • Sulcal pits and patterns are crucial anatomical features linked to human brain function.
  • Recent observations show early sulcal folding in healthy and abnormal fetal brains.

Purpose of the Study:

  • To investigate the genetic control and functional significance of early sulcal folding patterns.
  • To assess the utility of graph-based analysis in detecting subtle fetal brain abnormalities.
  • To explore the potential of early sulcal patterns in predicting neurodevelopmental outcomes.

Main Methods:

  • Utilized graph-based quantitative sulcal pattern analysis.
  • Analyzed sulcal pit distribution and topological patterning.
  • Examined early sulcal folding in fetal brains, including those with abnormalities.

Main Results:

  • Graph-based analysis demonstrated high sensitivity in detecting subtle cortical growth abnormalities in early fetal stages.
  • This method is more effective than traditional measures like gyrification index and curvature for early detection.
  • Early sulcal folding patterns are effective in characterizing genetically influenced cortical development.

Conclusions:

  • Early sulcal folding patterns are significant indicators of brain development and genetic influence.
  • Quantitative sulcal pattern analysis is a sensitive tool for early detection of fetal brain abnormalities.
  • Future research will focus on longitudinal studies to map spatio-temporal dynamics and predict outcomes.