WE3.PA1.11
QUANTIFYING SIGNAL-TO-NOISE RATIO IN NEURAL LATENT TRAJECTORIES VIA FISHER INFORMATION
Hyungju Jeon, Il Memming Park, Champalimaud Foundation, Portugal
Session:
WE3.PA1: Electroencephalogram Signal Processing Poster
Track:
BISA - Biomedical Image & Signal Analytics
Location:
Poster Area 1
Presentation Time:
Wed, 28 Aug, 16:10 - 17:50 France Time (UTC +1)
Session Chair:
Borbala Hunyadi, Delft University of Technology
Presentation
Discussion
Resources
No resources available.
Session WE3.PA1
WE3.PA1.1: Cross-site generalization using attention layer for epileptic seizure detection
Tala ABDALLAH, Université d' Angers, France; Nisrine Jrad, Université Catholique de l'Ouest, France; Fahed Abdallah, Université de Lorraine, France; Anne Humeau-Heurtier, Université d'Angers, France; Eliane El Howayek, Patrick Van Bogaert, Centre Hospitalier Universitaire Angers, France
WE3.PA1.2: Exploring Network Topology-Based Methods to Differentiate Healthy and Alzheimer's Cohorts: An EEG-Based Study
Prerna Singh, Tapan Gandhi, Lalan Kumar, IIT Delhi, India
WE3.PA1.3: Early Prediction of Electrographic Seizures in Neonatal Hypoxic-ischemic Encephalopathy Based on Amplitude-integrated EEG and Clinical Data
Tamara Skoric, University of Novi Sad, Serbia; Marija Djermanovic, Institute for Child and Youth Health Care of Vojvodina, Serbia; Jovana Kljajic, Slobodan Spasojevic, University of Novi Sad, Serbia; John M. O’ Toole, CergenX Ltd, Ireland
WE3.PA1.4: Machine learning models trained in a low-dimensional latent space for epileptogenic zone (EZ) localization
Sheng H. Wang, Helsinki University, Finland; Morgane Marzulli, Université Paris Cité, France; Gabriele Arnulfo, Lino Nobili, University of Genoa, Italy; Satu Palva, Helsinki University, Finland; J Matias Palva, Aalto University, Finland; Philippe Ciuciu, CEA/NeuroSpin, France
WE3.PA1.5: FUNCTIONAL NEURAL ACTIVITY MAPPING USING SPIKING NEURAL NETWORKS AND EEG SIGNALS: A PROOF OF CONCEPT STUDY
Dario Milea, Vincenzo Catrambone, Gaetano Valenza, University of Pisa, Italy
WE3.PA1.6: Assessing Neural Patterns of Anxiety Using Deep Learning: An EEG Study
Hamidreza Ghonchi, Tom Foulsham, Saideh Ferdowsi, University of Essex, United Kingdom
WE3.PA1.7: SOS-MUSIC, a subspace approach for EEG source imaging promoting sparsity of active sources
Carla Joud, Laurent Albera, Isabelle Merlet, University of Rennes, France; Julie Coloigner, INRIA IRISA Rennes, France
WE3.PA1.8: Memory Encoding Relation with Alzheimer's Severity: Excitation-to-Inhibition Insights
Shivani Ranjan, Harshal Shende, Amit Kumar, Indian Institute of Technology Delhi, India; Robin Badal, Pramod Yadav, All India Institute of Ayurveda, India; Lalan Kumar, India Institute of Technology Delhi, India
WE3.PA1.9: Introducing the modularity graph: an application to brain functional networks
Tiziana Cattai, Camilla Caporali, Sapienza university of Rome, Italy; Marie-Constance Corsi, Sorbonne Université, Institut du Cerveau – Paris Brain Institute -ICM, CNRS, France; Stefania Colonnese, Sapienza university of Rome, France
WE3.PA1.10: An Automatic Riemannian Artifact Rejection Method for P300-based BCIs
Davoud Hajhassani, University Grenoble Alpes, CNRS, France; Jérémie Mattout, Lyon Neuroscience Research Center, INSERM, France; Marco Congedo, University Grenoble Alpes, CNRS, France
WE3.PA1.11: QUANTIFYING SIGNAL-TO-NOISE RATIO IN NEURAL LATENT TRAJECTORIES VIA FISHER INFORMATION
Hyungju Jeon, Il Memming Park, Champalimaud Foundation, Portugal
WE3.PA1.12: Unsupervised Adaptive Deep Learning Method For BCI Motor Imagery Decoding
Yassine El Ouahidi, Giulia Lioi, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon, IMT Atlantique, France