Zobrazeno 1 - 10
of 1 367
pro vyhledávání: '"FitzGerald, James"'
Parkinson's Disease (PD) diagnosis remains challenging. This study applies Convolutional Kolmogorov-Arnold Networks (ConvKANs), integrating learnable spline-based activation functions into convolutional layers, for PD classification using structural
Externí odkaz:
http://arxiv.org/abs/2407.17380
Discriminating between Parkinson's Disease (PD) and Progressive Supranuclear Palsy (PSP) is difficult due to overlapping symptoms, especially early on. Saccades (rapid conjugate eye movements between fixation points) are affected by both diseases but
Externí odkaz:
http://arxiv.org/abs/2407.16063
Theoretical neuroscientists often try to understand how the structure of a neural network relates to its function by focusing on structural features that would either follow from optimization or occur consistently across possible implementations. Bot
Externí odkaz:
http://arxiv.org/abs/2310.20309
Publikováno v:
A Handbook of Contemporary Group Work Practice : Promoting Resilience and Empowerment in a Complex World, 2024.
Externí odkaz:
https://doi.org/10.1093/oso/9780197657928.003.0012
Autor:
Deer, Timothy R., Russo, Marc, Grider, Jay S., Sayed, Dawood, Lamer, Tim J., Dickerson, David M., Hagedorn, Jonathan M., Petersen, Erika A., Fishman, Michael A., FitzGerald, James, Baranidharan, Ganesan, De Ridder, Dirk, Chakravarthy, Krishnan V., Al-Kaisy, Adnan, Hunter, Corey W., Buchser, Eric, Chapman, Kenneth, Gilligan, Chris, Hayek, Salim M., Thomson, Simon, Strand, Natalie, Jameson, Jessica, Simopoulos, Thomas T., Yang, Ajax, De Coster, Olivier, Cremaschi, Fabián, Christo, Paul J., Varshney, Vishal, Bojanic, Stana, Levy, Robert M.
Publikováno v:
In Neuromodulation: Technology at the Neural Interface August 2024 27(6):951-976
Autor:
Yeh, Chien-Hung, Xu, Yifan, Shi, Wenbin, Fitzgerald, James J., Green, Alexander L., Fischer, Petra, Tan, Huiling, Oswal, Ashwini
Publikováno v:
In Brain Stimulation May-June 2024 17(3):501-509
Autor:
Fitzgerald, James, Wong-Lin, KongFatt
Spiking neural networks (SNNs) communicate through the all-or-none spiking activity of neurons. However, fitting the large number of SNN model parameters to observed neural activity patterns, for example, in biological experiments, remains a challeng
Externí odkaz:
http://arxiv.org/abs/2105.06824
Autor:
Manfield, James, Thomas, Sheena, Bogdanovic, Marko, Sarangmat, Nagaraja, Antoniades, Charalambos, Green, Alexander L., FitzGerald, James J.
Publikováno v:
In Neuromodulation: Technology at the Neural Interface April 2024 27(3):557-564