Damián Dellavale, PhD | Cross frequency couplings in brain recordings and at the organism level using imaging photoplethysmography

MindBrainBody Lecture

  • 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.
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