Statistical Learning Methods for Neuroimaging Data Analysis with Applications

Annu Rev Biomed Data Sci. 2023 Aug 10:6:73-104. doi: 10.1146/annurev-biodatasci-020722-100353. Epub 2023 Apr 26.

Abstract

The aim of this review is to provide a comprehensive survey of statistical challenges in neuroimaging data analysis, from neuroimaging techniques to large-scale neuroimaging studies and statistical learning methods. We briefly review eight popular neuroimaging techniques and their potential applications in neuroscience research and clinical translation. We delineate four themes of neuroimaging data and review major image processing analysis methods for processing neuroimaging data at the individual level. We briefly review four large-scale neuroimaging-related studies and a consortium on imaging genomics and discuss four themes of neuroimaging data analysis at the population level. We review nine major population-based statistical analysis methods and their associated statistical challenges and present recent progress in statistical methodology to address these challenges.

Keywords: causal pathway; heterogeneity; image processing analysis; neuroimaging techniques; population-based statistical analysis; study design.

Publication types

  • Review
  • Research Support, N.I.H., Extramural

MeSH terms

  • Image Processing, Computer-Assisted
  • Imaging Genomics
  • Learning
  • Neuroimaging* / methods
  • Neurosciences*