Neuroscience Center (HiLIFE, U of Helsinki) seminar

Speaker: Philippe Ciuciu (CEA/NeuroSpin & Inria Parietal) Position: CEA Research Director
Title: Functional connectivity in the human brain assessed from fractal dynamics of MEG data
Host: Matias Palva

The seminar will be streamed via Zoom

Meeting ID: 674 3141 0576
Passcode: 338869

Abstract:  The analysis of human brain functional networks is normally achieved by computing functional connectivity indices reflecting phase coupling and interactions between remote brain regions. In magneto and electroencephalography (M/EEG), the most frequently used functional connectivity indices, Imaginary Coherence (ICOH) and weighted Phase Lag indices (WPLI), are constructed using Fourier-based cross-spectral estimation applied to specific fast and band-limited oscillatory regimes (α, β and γ frequency bands). Recently, infraslow (< 2Hz) arrhythmic or scale-free (or fractal) dynamics, whose hallmark is a 1/f power spectrum in this frequency range, was recognized as playing a leading role in spontaneous brain activity. In this talk, I will present new tools to assess functional connectivity for scale-free dynamics – or fractal connectivity. Notably, I will extend the ICOH and WPLI indices by designing appropriate estimators that rely on complex-valued wavelet (w) representations, namely w-ICOH and w-WPLI respectively. Then I will show how these new indices, assessed on MEG recordings collected on 36 individuals both at rest and during a visual motion discrimination task, demonstrate a gain in statistical sensitivity, compared to their Fourier counterparts ICOH and WPLI, in capturing relevant functional interactions in the infraslow regime and modulations from rest to task. Notably, I will show how the consistent overall increase in functional connectivity that w-WPLI captures from rest to task correlates with a change in temporal dynamics (i.e. decrease of self-similarity) as well as with improved performance in task completion. This suggests that w-WPLI is the sole index able to capture brain plasticity in the infraslow scale-free regime.