Damián Dellavale, PhD | Cross frequency couplings in brain recordings and at the organism level using imaging photoplethysmography
- Datum: 10.01.2022
- Uhrzeit: 14:30 - 15:30
- Vortragende(r): Damián Dellavale, PhD
- Institut de Neurosciences des Systèmes INS - INSERM U1106 | Aix-Marseille Université - Faculté de Médecine
- Raum: Zoom Meeting
- Gastgeber: Abteilung Neurologie
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.