Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Tobias Kühn

Showing results (1-10 of 6) with videos related to

Pageof 1
Sort By:
Physical Review. E|January 20, 2024
Information content in continuous attractor neural networks is preserved in the presence of moderate disordered background connectivityTobias Kühn, Rémi Monasson
Plos Computational Biology|June 13, 2017
Locking of correlated neural activity to ongoing oscillationsTobias Kühn, Moritz Helias
Physical Review Letters|October 22, 2021
Large-Deviation Approach to Random Recurrent Neuronal Networks: Parameter Inference and Fluctuation-Induced TransitionsAlexander van Meegen, Tobias Kühn, Moritz Helias
Physical Review Letters|May 6, 2022
Gell-Mann-Low Criticality in Neural NetworksLorenzo Tiberi, Jonas Stapmanns, Tobias Kühn, et al.
Physical Review. E|June 16, 2022
Erratum: Self-consistent formulations for stochastic nonlinear neuronal dynamics [Phys. Rev. E 101, 042124 (2020)]Jonas Stapmanns, Tobias Kühn, David Dahmen, et al.
Physical Review. E|May 20, 2020
Self-consistent formulations for stochastic nonlinear neuronal dynamicsJonas Stapmanns, Tobias Kühn, David Dahmen, et al.
Pageof 1

Showing results (1-10 of 6) with videos related to

Sort By:
Pageof 1
Physical Review. E|January 20, 2024
Information content in continuous attractor neural networks is preserved in the presence of moderate disordered background connectivityTobias Kühn, Rémi Monasson
Plos Computational Biology|June 13, 2017
Locking of correlated neural activity to ongoing oscillationsTobias Kühn, Moritz Helias
Physical Review Letters|October 22, 2021
Large-Deviation Approach to Random Recurrent Neuronal Networks: Parameter Inference and Fluctuation-Induced TransitionsAlexander van Meegen, Tobias Kühn, Moritz Helias
Physical Review Letters|May 6, 2022
Gell-Mann-Low Criticality in Neural NetworksLorenzo Tiberi, Jonas Stapmanns, Tobias Kühn, et al.
Physical Review. E|June 16, 2022
Erratum: Self-consistent formulations for stochastic nonlinear neuronal dynamics [Phys. Rev. E 101, 042124 (2020)]Jonas Stapmanns, Tobias Kühn, David Dahmen, et al.
Physical Review. E|May 20, 2020
Self-consistent formulations for stochastic nonlinear neuronal dynamicsJonas Stapmanns, Tobias Kühn, David Dahmen, et al.
Pageof 1