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Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional

Chen Qiao1, Bin Gao1, Yuechen Liu1

  • 1School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, PR China.

Medical Image Analysis
|September 8, 2023
PubMed
Summary

This study introduces an explainable deep learning method for neuroimaging analysis. The approach reveals how brain networks mature, becoming more organized and efficient with age, with distinct changes in processing regions.

Keywords:
Deep learning with explainabilityDynamic functional connectivityFeature back-selectionJoint feature selection

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Area of Science:

  • Neuroimaging
  • Developmental Neuroscience
  • Machine Learning

Background:

  • Deep learning models in medicine often prioritize accuracy over explainability.
  • Understanding brain development and disorders requires interpretable neuroimaging analysis.
  • Explainability is crucial for identifying biomarkers in brain development.

Purpose of the Study:

  • To propose an explainable deep learning approach for neuroimaging.
  • To elucidate information transmission mechanisms within deep networks.
  • To analyze dynamic brain functional connectivity during development.

Main Methods:

  • Developed an explainable deep learning framework.
  • Employed a joint feature selection strategy.
  • Integrated shallow-layer explainable models and sparse learning.
  • Applied the approach to functional magnetic resonance imaging (fMRI) data from a brain development study.

Main Results:

  • Identified age-related differences in functional brain networks.
  • Demonstrated a transition from undifferentiated to specialized brain structures.
  • Showed increased information processing efficiency with age.
  • Detected distinct developmental patterns in functional connectivity (FC).

Conclusions:

  • The proposed method enhances the interpretability of deep learning in neuroimaging.
  • Brain network organization and efficiency evolve significantly during development.
  • Specific brain regions show altered functional connectivity patterns during maturation.