Description
Date depot: 2 avril 2019
Titre: - Development of network features for brain-computer interfaces
Directeur de thèse:
Fabrizio DE VICO FALLANI (ICM)
Domaine scientifique: Sciences et technologies de l'information et de la communication
Thématique CNRS : Non defini
Resumé:
Brain-computer interfaces (BCIs) are increasingly explored for control and communication, as well as for treatment of neurological disorders, particularly via the ability of subjects to voluntary modulate their brain activity through mental imagery (MI) [1].
Despite this technique has gained a wide territory in the last years, the community is still facing a critical issue in terms of performance as measured by the correct classification of the user’s intent [2]. While much of the efforts to solve this problem have focused on the classification block of the BCI, the research of alternative features has been poorly explored and rather crude univariate measurements, such as the signal band power of single brain areas, have been used so far [3].
However, the brain is not just a collection of isolated pieces working independently, but it rather consists of a distributed complex network that integrates information across differently specialized regions [4]. It turns out that examining the signal of one specific region – while neglecting its interactions with other regions – oversimplifies the real phenomenon and one must instead obtain an understanding of the system’s collective behavior to fully capture the brain functioning. This project aims to extract new features from brain connectivity networks derived from functional neuroimaging data during BCI-related tasks.References
[1] M. Hamedi, S.-H. Salleh, and A. M. Noor, “Electroencephalographic Motor Imagery Brain Connectivity Analysis for BCI: A Review,” Neural Computation, vol. 28, no. 6, pp. 999–1041, May 2016.
[2] M. C. Thompson, “Critiquing the Concept of BCI Illiteracy,” Sci Eng Ethics, pp. 1–17, Aug. 2018.
[3] L. Bougrain, M. Clerc, and F. Lotte, Brain-Computer Interfaces 1: Methods and Perspectives. John Wiley & Sons, 2016.
[4] F. De Vico Fallani, J. Richiardi, M. Chavez, and S. Achard, “Graph analysis of functional brain networks: practical issues in translational neuroscience,” Phil. Trans. R. Soc. B, vol. 369, no. 1653, p. 20130521, Oct. 2014.
Doctorant.e: Gonzalez Astudillo Juliana