Structural and functional interplay in anxiety related classification: a graph signal processing approach

Giovanna Orrù (1) , Pierre Maurel (1) , Julie Coloigner (1)

1 Empenn - Neuroimagerie: méthodes et applications

Anxiety disorders are one of the most common mental health conditions with a high rate of everyday life disability. Connectivity is steadily gaining relevance to increase our knowledge of psychiatric diseases. Graph signal processing (GSP) is a new framework to integrate structural connectivity and brain function. We propose here a graph-based analysis using GSP metrics and classification procedure, to identify anxiety biomarkers. Results suggest that the joint consideration of structure-function features improves their discriminatory accuracy, and our understanding of the pathophysiology of anxiety.

Mots clés: functional and structural connectivity; neuropsychological biomarkers; graph signal processing

Domaines: Imagerie médicale; Traitement du signal et de l'image [eess.SP]

Giovanna Orrù, Pierre Maurel, Julie Coloigner. Structural and functional interplay in anxiety related classification: a graph signal processing approach. ISBI 2021 - IEEE International Symposium on Biomedical Imaging, Apr 2021, Nice, France. pp.1-4. ⟨hal-03450470⟩