Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Peter Duggins"'
Autor:
Peter Duggins, Chris Eliasmith
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 9, p e1010461 (2022)
Improving biological plausibility and functional capacity are two important goals for brain models that connect low-level neural details to high-level behavioral phenomena. We develop a method called "oracle-supervised Neural Engineering Framework" (
Externí odkaz:
https://doaj.org/article/8ae9e078c3f4469db61568099ce425c7
Autor:
Dustin Anderson, Arie Kapulkin, Moses Z. R. Misplon, Walter Lynn, Bibek Pokharel, Arjendu K. Pattanayak, Peter Duggins, Kevin Hallman
Publikováno v:
Scientific Reports, Vol 8, Iss 1, Pp 1-10 (2018)
Scientific Reports
Scientific Reports
We study the largest Lyapunov exponents λ and dynamical complexity for an open quantum driven double-well oscillator, mapping its dependence on coupling to the environment Γ as well as effective Planck’s constant β2. We show that in general λ i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f0104c0de27f3ffc96e18ff6a01888c
http://link.springer.com/article/10.1038/s41598-018-20507-w
http://link.springer.com/article/10.1038/s41598-018-20507-w
Publikováno v:
Topics in Cognitive Science. 9:117-134
We use a spiking neural network model of working memory (WM) capable of performing the spatial delayed response task (DRT) to investigate two drugs that affect WM: guanfacine (GFC) and phenylephrine (PHE). In this model, the loss of information over
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::184ab03cd5c00c4a6894eef0f4f92674
https://doi.org/10.1111/tops.12247
https://doi.org/10.1111/tops.12247
Autor:
Peter Duggins
Agent-based models are versatile tools for studying how societal opinion change, including political polarization and cultural diffusion, emerges from individual behavior. This study expands agents' psychological realism using empirically-motivated r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91540a3cfb210052c3db327efba7267d
