Published June 8, 2014
| Version v1
Publication
Electro-Metabolic Coupling Investigated with Jitter Invariant Dictionary Learning
Contributors
Others:
- Computational Imaging of the Central Nervous System (ATHENA) ; Centre Inria d'Université Côte d'Azur (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- Laboratoire Traitement et Communication de l'Information (LTCI) ; Télécom ParisTech-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)
- Institut de Neurosciences des Systèmes (INS) ; Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)
- Doctoral grant of the region Provence-Alpes-Cote d'Azur
- ANR-09-EMER-0002,CO-ADAPT,Coadaptation Cerveau Ordinateur pour de meilleures interfaces(2009)
Description
This work aims at establishing a relationship between neurophysiological and hemodynamic activity in an animal model of epilepsy. For the analysis, we propose a novel algorithm that is suited to learn meaningful representations of the multimodal datasets. As a result, we are able to learn a hemodynamic response and discover spike synchronization with hemodynamic activity.
Abstract
International audienceAdditional details
Identifiers
- URL
- https://inria.hal.science/hal-01094674
- URN
- urn:oai:HAL:hal-01094674v1
Origin repository
- Origin repository
- UNICA