Zobrazeno 1 - 10
of 107
pro vyhledávání: '"Kenneth Kreutz-Delgado"'
Publikováno v:
IEEE Access, Vol 9, Pp 147967-147984 (2021)
State-of-the-art deep learning solutions for image upsampling are currently trained using either resize or sub-pixel convolution to learn kernels that generate high fidelity images with minimal artifacts. However, performing inference with these lear
Externí odkaz:
https://doaj.org/article/6918181698ef4588b0398f020c59e7d9
Autor:
Ramón Martínez-Cancino, Arnaud Delorme, Dung Truong, Fiorenzo Artoni, Kenneth Kreutz-Delgado, Subhashini Sivagnanam, Kenneth Yoshimoto, Amitava Majumdar, Scott Makeig
Publikováno v:
NeuroImage, Vol 224, Iss , Pp 116778- (2021)
EEGLAB signal processing environment is currently the leading open-source software for processing electroencephalographic (EEG) data. The Neuroscience Gateway (NSG, nsgportal.org) is a web and API-based portal allowing users to easily run a variety o
Externí odkaz:
https://doaj.org/article/d9e41c8a1d4d4cfea04ef3c226009818
ICLabel: An automated electroencephalographic independent component classifier, dataset, and website
Publikováno v:
Neuroimage
The electroencephalogram (EEG) provides a non-invasive, minimally restrictive, and relatively low cost measure of mesoscale brain dynamics with high temporal resolution. Although signals recorded in parallel by multiple, near-adjacent EEG scalp elect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ccc6b37bc474a26aaa0da89101ad31f
https://doi.org/10.1016/j.neuroimage.2019.05.026
https://doi.org/10.1016/j.neuroimage.2019.05.026
Autor:
Kenneth Yoshimoto, Ramón Martínez-Cancino, Dung Truong, Scott Makeig, Fiorenzo Artoni, Amitava Majumdar, Kenneth Kreutz-Delgado, Subhashini Sivagnanam, Arnaud Delorme
Publikováno v:
NeuroImage
NeuroImage, Elsevier, 2021, 224, pp.116778. ⟨10.1016/j.neuroimage.2020.116778⟩
Neuroimage
NeuroImage, Vol 224, Iss, Pp 116778-(2021)
NeuroImage, Elsevier, 2021, 224, pp.116778. ⟨10.1016/j.neuroimage.2020.116778⟩
Neuroimage
NeuroImage, Vol 224, Iss, Pp 116778-(2021)
EEGLAB signal processing environment is currently the leading open-source software for processing electroencephalographic (EEG) data. The Neuroscience Gateway (NSG, nsgportal.org) is a web and API-based portal allowing users to easily run a variety o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f52442e939f2cd9d776e5e29ae0b2a1d
https://hal.archives-ouvertes.fr/hal-03426074/file/1-s2.0-S1053811920302652-main.pdf
https://hal.archives-ouvertes.fr/hal-03426074/file/1-s2.0-S1053811920302652-main.pdf
Publikováno v:
Neural Comput
Electromagnetic source imaging (ESI) and independent component analysis (ICA) are two popular and apparently dissimilar frameworks for M/EEG analysis. This letter shows that the two frameworks can be linked by choosing biologically inspired source sp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dfa9ccc22500fba29a47782399a5fe0b
https://pubmed.ncbi.nlm.nih.gov/34412115
https://pubmed.ncbi.nlm.nih.gov/34412115
Publikováno v:
BIBE
Phase-Amplitude Coupling (PAC) in electrophysiological signals refers to the transient interplay of activities in different frequency ranges, wherein phase in a low-frequency band and amplitude in a high-frequency band are in some way dependent. PAC
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9583b720c441a62740c560fe8820c92e
https://doi.org/10.1109/bibe50027.2020.00070
https://doi.org/10.1109/bibe50027.2020.00070
Autor:
Ramón Martínez-Cancino, Kenneth Kreutz-Delgado, Roberto C. Sotero, Scott Makeig, Arnaud Delorme, Johanna Wagner
Publikováno v:
Entropy
Entropy, MDPI, 2020, 22 (11), pp.1262. ⟨10.3390/e22111262⟩
Entropy (Basel, Switzerland), vol 22, iss 11
Volume 22
Issue 11
Entropy, MDPI, 2020, 22 (11), pp.1262. ⟨10.3390/e22111262⟩
Entropy (Basel, Switzerland), vol 22, iss 11
Volume 22
Issue 11
International audience; Modulation of the amplitude of high-frequency cortical field activity locked to changes in the phase of a slower brain rhythm is known as phase-amplitude coupling (PAC). The study of this phenomenon has been gaining traction i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2df7d98167dc451f7ac38e2610767e6b
https://hal.archives-ouvertes.fr/hal-03426073/file/entropy-22-01262.pdf
https://hal.archives-ouvertes.fr/hal-03426073/file/entropy-22-01262.pdf
Publikováno v:
NeuroImage. 150:99-111
To map cortical representations of the body, we recently developed a wearable technology for automatic tactile stimulation in human functional magnetic resonance imaging (fMRI) experiments. In a two-condition block design experiment, air puffs were d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e464125b644c2894e66c6b476887c2c
https://doi.org/10.1016/j.neuroimage.2017.02.024
https://doi.org/10.1016/j.neuroimage.2017.02.024
Publikováno v:
ACSSC
Stochastic-sampling-based Generative Neural Networks, such as Restricted Boltzmann Machines and Generative Adversarial Networks, are now used for applications such as denoising, image occlusion removal, pattern completion, and motion synthesis. In sc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6e4771af803ceda55d1cf60c861fee8d
http://arxiv.org/abs/1910.12454
http://arxiv.org/abs/1910.12454
Publikováno v:
Data in Brief, Vol 25, Iss, Pp-(2019)
The ICLabel dataset is comprised of training and test sets of a set of spatiotemporal features of electroencephalographic (EEG) independent components (IC). The ICLabel training set feature sets were computed for over 200,000 EEG ICs from more than 6
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed87d9b2f3712ba9b2464ef6d995cf09
https://escholarship.org/uc/item/75z1f15w
https://escholarship.org/uc/item/75z1f15w