Sahar Allouch

Bâtiment 22, Campus de Beaulieu, Université de Rennes 1 · 35042 Rennes, France · (+33) 6 56 67 56 68 · saharallouch@gmail.com

Ph.D. student at the University of Rennes 1 and the Lebanese University (thesis defense will take place on the 14th of December 2022).

Research Experience

Analytical variability in electroencephalography-based functional brain networks estimation

Ph.D. thesis

The objective of the thesis is to call into question the analytical variability in the EEG source connectivity pipeline. Mainly, we focused on three key factors in the analysis: the number of EEG electrodes, source reconstruction algorithms, and functional connectivity measures. [manuscript]

October 2019 - Present

Graph-theory based method to identify pathological networks involved in alzheimer's disease

Master's thesis

The main objective of this project was to identify differences in EEG-based cortical netowrks in alzheimer's disease patients and healthy controls that correlate with the cognitive impairment level of each group. Alterations in dynamic functional brain networks were investigated during a picture naming and button press tasks. [manuscript, slides]

March 2019 - July 2019

Education

University of Rennes 1 - Lebanese University

Ph.D.
Signal, Image, Vision - Biomedical Engineering
October 2019 - Present

Lebanese University, Faculty of Engineering

Master of Research
Technology of communication, medical and industrial systems

GPA: 83.53/100. Rank: 2

September 2018 - July 2019

Lebanese University, Faculty of Engineering

Engineering Diploma
Electrical and Electronic Engineering

GPA: 82.47/100

September 2014 - July 2019

Skills

Programming Languages
Workflow
  • EEG signal pre-processing
  • EEG source reconstruction
  • Functional connectivity

Publications

  • Allouch, S., Kabbara, A., Duprez, J., Paban, V., Khalil, M., Modolo J., and Hassan, M. “Effect of analytical variability in estimating EEG-based functional connectivity.” (in preparation)
  • Allouch, S., Kabbara, A., Duprez, J., Khalil, M., Modolo J., and Hassan, M. “Effect of Channel Density, Inverse Solutions and Connectivity Measures on EEG Resting-State Networks: A Simulation Study.” bioRxiv, June 2, 2022. https://doi.org/10.1101/2022.06.01.494301. Submitted to NeuroImage
  • Allouch, S., Yochum M., Kabbara, A., Duprez J., Khalil, M., Wendling F., Hassan M., and Modolo,J. “Mean-Field Modeling of Brain-Scale Dynamics for the Evaluation of EEG Source-Space Networks.” Brain Topography, July 9, 2021. https://doi.org/10.1007/s10548-021-00859-9.

Conferences

  • EMBC 2022. Glasgow, Scotland (July 11-15, 2022). Methods Used to Estimate EEG Source-Space Networks: A Comparative Simulation-Based Study. [poster]
  • ICABME 2021. Werdanyeh, Lebanon (October 7-8, 2021). COALIA: a ground-truth for the evaluation of the EEG source connectivity. https://doi.org/10.1109/ICABME53305.2021.9604833. [slides]
  • OHBM 2021. Online (June 21-25, 2021). Mean-field modeling of brain-scale dynamics for the evaluation of EEG source-space networks. [poster, slides]

Scholarships and Awards

  • Doctoral scholorship delivered by the Agence Universitaire de la Francophonie, the National Center for Scientific Research in Lebbanon and the Lebanese University (Rank: 2)
  • First prize at the 11th Annual Conference for Engineering and Architecture Graduates in North Lebanon (Category: Biomedical Engineering) [poster, slides]