BB&D Research Day 2025 – Javed & Weber
Developing a Rigorous Method for Detecting Power-Law Scaling and Critical Dynamics in fMRI Brain Signals
E. A. Javed, BC Children’s Hospital Research Institute; A. M. Weber, BC Children’s Hospital Research Institute
Presentation Info
Event: Brain, Behaviour & Development Theme Research Day
Institution: BC Children’s Hospital Research Institute
Location: Vancouver, BC
Date: Monday, November 24, 2025
Presentation Type: Poster Presentation
Abstract
The “Critical Brain Theory” suggests the brain evolved to operate in a critical state, balanced between order and disorder. Critical systems show scale-invariance and long-range temporal correlations. Accurately measuring these scale-free dynamics can deepen our understanding of brain function and health.
This project aimed to create a Python-based signal-processing tool to (1) test for power-law distributions (scale-invariance), (2) classify signals as fractional Gaussian noise (fGn) or fractional Brownian motion (fBm), and (3) estimate the Hurst exponent (H), which quantifies long-range temporal correlations.
Simulated time series with known H values were used to benchmark and validate estimation and preprocessing methods. Power spectral density (PSD) analysis and log-log regression extracted scaling exponents, while Monte Carlo testing validated power-law fits and robustness. Preliminary results show that “Bridge Window Detrend” preprocessing combined with PSD-based slope estimation most accurately classified fGn versus fBm and estimated H.
Future work will apply this pipeline to voxel-wise fMRI data to investigate scale-free behaviour in spontaneous brain activity and assess how preprocessing affects power-law detection and reproducibility.