Sailing in rough waters: Examining volatility of fMRI noise.

ABSTRACT:

Background

The assumption that functional magnetic resonance imaging (fMRI) noise has constant volatility has recently been challenged by studies examining heteroscedasticity arising from head motion and physiological noise. The present study builds on this work using latest methods from the field of financial mathematics to model fMRI noise volatility.

Methods

Multi-echo phantom and human fMRI scans were used and realised volatility was estimated. The Hurst parameter H ∈ (0,1), which governs the roughness/irregularity of realised volatility time series, was estimated. Calibration of H was performed pathwise, using well-established neural network calibration tools.

Results

In all experiments the volatility calibrated to values within the rough case, H < 0.5, and on av

SUBMITTER: Leppanen J 

PROVIDER: S-EPMC7992030 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature