Damián Dellavale, PhD | Cross frequency couplings in brain recordings and at the organism level using imaging photoplethysmography
MindBrainBody Lecture
- Date: Jan 10, 2022
- Time: 02:30 PM - 03:30 PM (Local Time Germany)
- Speaker: Damián Dellavale, PhD
- Institut de Neurosciences des Systèmes INS - INSERM U1106 | Aix-Marseille Université - Faculté de Médecine
- Room: Zoom Meeting
- Host: Department of Neurology
Cross Frequency Coupling (CFC) patterns have been proposed as biomarkers
characterizing physiological and pathological brain states like those
observed in Parkinson's disease (PD) and epilepsy. The basic mechanistic
interpretation behind CFC is that independent oscillatory dynamics interact
hierarchically. However, the interpretation of these CFC patterns remains
challenging since harmonic spectral correlations characterizing repetitive
non-sinusoidal waveform constituting the recorded neural activity can act
as a confounding factor. Moreover, CFC is a rather ubiquitous phenomenon
that has been also observed at the organism level. In particular, autonomic
dysfunctions are observed even in the long prodromal phase of PD such as
cardiovascular dysfunctions elicited by the early sympathetic denervation
of the heart muscle. This evidence suggests that significant changes in the
interaction among the neural, cardiac and respiratory rhythms, i.e.
multimodal CFC, can be expected in the parkinsonian state. However, how
these early autonomic dysfunctions occurring in PD patients affect
physiological phenomena like the respiratory sinus arrhythmia (RSA) remains
largely unexplored. Addressing these open questions is important since it
could pave the way to identify prodromal biomarkers of PD based on
multimodal CFC, aimed to improve the early clinical diagnosis and
treatments, and to better understand pathophysiology and progression of the
disease. In this talk I will present some results from the analysis of
invasive brain recordings in epileptic patients to introduce the signal
processing tools developed to help the interpretation of CFC by efficiently
quantifying the degree of harmonicity between the frequency bands
associated to the emergence of CFC patterns. In addition, I will briefly
describe the hardware platform and data analysis tools for the non-invasive
characterization of CFC at the organism level using imaging
photoplethysmography (iPPG). As a proof of concept of the proposed methods,
I will also present preliminary results showing Phase-Frequency and
Phase-Amplitude CFC patterns observed in the iPPG signal obtained from
healthy subjects at rest.