Published December 3, 2013
| Version v1
Conference paper
Inference of functional connectivity in Neurosciences via Hawkes processes
Contributors
Others:
- Laboratoire Jean Alexandre Dieudonné (LJAD) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
- CEntre de REcherches en MAthématiques de la DEcision (CEREMADE) ; Université Paris Dauphine-PSL ; Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)
- Laboratoire Jean Alexandre Dieudonné (JAD) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)
Description
We use Hawkes processes as models for spike trains analysis. A new Lasso method designed for general multivariate counting processes enables us to estimate the functional connectivity graph between the different recorded neurons.
Abstract
International audienceAdditional details
Identifiers
- URL
- https://hal.science/hal-00866823
- URN
- urn:oai:HAL:hal-00866823v1
Origin repository
- Origin repository
- UNICA