Presentation 2021-10-28
Neural Mechanisms of Prepulse Inhibition in Drosophila Larvae
Kotaro Furuya, Yuki Katsumata, Masayuki Ishibashi, Takako Morimoto, Toru Aonishi,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Prepulse inhibition (PPI) is a phenomenon in which the startle response to stimuli is suppressed by preceding stimuli. In this work, we investigated neural mechanisms underlying PPI in Drosophila larvae using numerical simulation. We confirmed that the neural circuit model of Drosophila larvae proposed by Jovanic et al. can reproduce several experimental results including PPI using the same model and parameters by adjusting the parameters heuristically determined by them. By examining the activity of each neuron during PPI in our model, we identified the neurons contributing to PPI and suggested its neural circuit mechanisms.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Prepulse Inhibition / Drosophila larvae / Neural circuit model / Computational model
Paper # NC2021-18
Date of Issue 2021-10-21 (NC)

Conference Information
Committee MBE / NC
Conference Date 2021/10/28(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Ryuhei Okuno(Setsunan Univ.) / Rieko Osu(Waseda Univ.)
Vice Chair Junichi Hori(Niigata Univ.) / Hiroshi Yamakawa(Univ of Tokyo)
Secretary Junichi Hori(Osaka Electro-Communication Univ) / Hiroshi Yamakawa(ATR)
Assistant Jun Akazawa(Meiji Univ. of Integrative Medicine) / Emi Yuda(Tohoku Univ) / Nobuhiko Wagatsuma(Toho Univ.) / Tomoki Kurikawa(KMU)

Paper Information
Registration To Technical Committee on ME and Bio Cybernetics / Technical Committee on Neurocomputing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Neural Mechanisms of Prepulse Inhibition in Drosophila Larvae
Sub Title (in English)
Keyword(1) Prepulse Inhibition
Keyword(2) Drosophila larvae
Keyword(3) Neural circuit model
Keyword(4) Computational model
1st Author's Name Kotaro Furuya
1st Author's Affiliation Tokyo Institute of Technology(Tokyo Tech)
2nd Author's Name Yuki Katsumata
2nd Author's Affiliation Tokyo Institute of Technology(Tokyo Tech)
3rd Author's Name Masayuki Ishibashi
3rd Author's Affiliation Tokyo Institute of Technology(Tokyo Tech)
4th Author's Name Takako Morimoto
4th Author's Affiliation Tokyo University of Pharmacy and Life Science(TUPLS)
5th Author's Name Toru Aonishi
5th Author's Affiliation Tokyo Institute of Technology(Tokyo Tech)
Date 2021-10-28
Paper # NC2021-18
Volume (vol) vol.121
Number (no) NC-223
Page pp.pp.1-6(NC),
#Pages 6
Date of Issue 2021-10-21 (NC)