Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Kristofer Bouchard"'
Publikováno v:
Frontiers in Neuroinformatics, Vol 16 (2022)
Single neuron models are fundamental for computational modeling of the brain's neuronal networks, and understanding how ion channel dynamics mediate neural function. A challenge in defining such models is determining biophysically realistic channel d
Externí odkaz:
https://doaj.org/article/434ebc5e707f41d88d3d4c980f86890c
Autor:
Sugeerth Murugesan, Kristofer Bouchard, Edward Chang, Max Dougherty, Bernd Hamann, Gunther H. Weber
Publikováno v:
BMC Bioinformatics, Vol 18, Iss S6, Pp 1-15 (2017)
Abstract Background There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurologic
Externí odkaz:
https://doaj.org/article/7e947c30d7ac4b0fa75f07c066eb85fe
Autor:
Oliver Ruebel, Max Dougherty, Mr. Prabhat, Peter Denes, David Conant, Edward Chang, Kristofer Bouchard
Publikováno v:
Frontiers in Neuroinformatics, Vol 10 (2016)
Neuroscience continues to experience a tremendous growth in data; in terms of the volume and variety of data, the velocity at which data is acquired, and in turn the veracity of data. These challenges are a serious impediment to sharing of data, anal
Externí odkaz:
https://doaj.org/article/e9776bdd505f4d9d8a05e057a057cfb2
Publikováno v:
2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS).
Autor:
Ankit Kumar, Kristofer Bouchard
Publikováno v:
AI and Optical Data Sciences III.
Autor:
Hector G Martin, Tijana Radivojevic, Jeremy Zucker, Kristofer Bouchard, Jess Sustarich, Sean Peisert, Dan Arnold, Nathan Hillson, Gyorgy Babnigg, Jose M Marti, Christopher J Mungall, Gregg T Beckham, Lucas Waldburger, James Carothers, ShivShankar Sundaram, Deb Agarwal, Blake A Simmons, Tyler Backman, Deepanwita Banerjee, Deepti Tanjore, Lavanya Ramakrishnan, Anup Singh
Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d88b4c62549eefa41c2f13ac906510a
Sparse regression is frequently employed in diverse scientific settings as a feature selection method. A pervasive aspect of scientific data that hampers both feature selection and estimation is the presence of strong correlations between predictive
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd5ab07986905177716d1d25d8d0e5cd
Publikováno v:
Journal of Vacuum Science & Technology B. 39:063001
Neural optoelectrodes can read and manipulate large numbers of neurons in vivo. However, state-of-the-art devices rely on either standard microfabrication materials (i.e., silicon and silicon nitride), which result in high scalability and throughput
Autor:
Christopher Holdgraf, Stefan Appelhoff, Stephan Bickel, Kristofer Bouchard, Sasha D'Ambrosio, Olivier David, Orrin Devinsky, Ben Dichter, adeen flinker, Brett Foster, Krzysztof Jacek Gorgolewski, Iris I.A. Groen, David Groppe, Aysegul Gunduz, Liberty S Hamilton, Christopher John Honey, Mainak Jas, Robert Knight, Jean-Philippe Lachaux, Jonathan Lau, Brian N. Lundstrom, Christopher Lee-Messer, Kai Miller, Jeffrey G. Ojemann, Robert Oostenveld, Giovanni Piantoni, Natalia Petridou, Andrea Pigorini, Nader Pouratian, Nick ramsey, Arjen Stolk, Nicole C. Swann, Francois Tadel, Bradley Voytek, Brian Arie Wandell, Jonathan Winawer, Lyuba Zehl, Dora Hermes
Intracranial electroencephalography (iEEG) data offer a unique combination of high spatial and temporal resolution measures of the living human brain. However, data collection is limited to highly specialized clinical environments. To improve interna
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::845e8f0baed1e6570efb9579956bffcc
https://osf.io/preprints/lissa/r7vc2
https://osf.io/preprints/lissa/r7vc2