Single-subject manual independent component analysis and resting state fMRI connectivity outcomes in patients with juvenile absence epilepsy

Magn Reson Imaging. 2020 Feb:66:42-49. doi: 10.1016/j.mri.2019.11.012. Epub 2019 Nov 14.

Abstract

The quality of fMRI data impacts functional connectivity measures and consequently, the decisions that clinicians and researchers make regarding functional connectivity interpretation. The present study used resting state fMRI to investigate resting state network connectivity in a sample of patients with Juvenile Absence Epilepsy. Single-subject manual independent component analysis was used in two levels, whereby all noise components were removed, and cerebrospinal fluid pulsation components only were isolated and removed. Improved temporal signal to noise ratios and functional connectivity metrics were observed in each of the cleaning levels for both epilepsy and control cohorts. Results showed full, single-subject manual independent component analysis reduced the number of functional connectivity correlations and increased the strength of these correlations. Similar effects were also observed for the cerebrospinal fluid pulsation only cleaned data relative to the uncleaned, and fully cleaned data. Single-subject manual independent component analysis coupled with short TR multiband acquisition can significantly improve the validity of findings derived from fMRI data sets.

Keywords: Epilepsy; Functional MRI; ICA; Independent component analysis; Juvenile absence epilepsy; Multiband; Resting state; fMRI.

MeSH terms

  • Adolescent
  • Brain / diagnostic imaging*
  • Brain / physiology*
  • Brain / physiopathology
  • Brain Mapping / methods*
  • Epilepsy, Absence / diagnosis*
  • Epilepsy, Absence / physiopathology*
  • Female
  • Humans
  • Magnetic Resonance Imaging / methods*
  • Male
  • Neural Pathways / physiopathology
  • Signal-To-Noise Ratio