Classification based on Neural Connectivity Analysis in a Motor Imaginary Task

Haruo Mizutani; I Giannopulu

Classification based on Neural Connectivity Analysis in a Motor Imaginary Task

Haruo Mizutani, I Giannopulu

Faculty of Society & Design

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

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Abstract

This study aims at developing a classification
method based on the neural connectivity by human EEG
dataset. An experimental result of four class classification
on a motor imagery task indicates that our novel analytical
method has a good performance and yields a crossvalidation accuracy of 53.5%.

Original language	English
Title of host publication	The Proceedings of the 28th Annual Conference of the Japanese Neural Network Society
Subtitle of host publication	第 28 回日本神経回路学会全国大会講演論文集
Publisher	Okinawa Institute of Science and Technology
Chapter	P2-6
Pages	122-123
Number of pages	2
Publication status	Published - Oct 2018
Event	The 28th Annual Conference of the Japanese Neural Network Society - Okinawa Institute of Science and Technology (OIST)., Okinawa, Japan Duration: 24 Oct 2018 → 27 Oct 2018 Conference number: 28th http://jnns.org/conference/2018/index.html

Conference

Conference	The 28th Annual Conference of the Japanese Neural Network Society
Abbreviated title	JNNS2018
Country/Territory	Japan
City	Okinawa
Period	24/10/18 → 27/10/18
Other	The 28th Annual Conference of the Japanese Neural Network Society (JNNS2018) will be held from October 24th to 27th at Okinawa Institute of Science and Technology (OIST). JNNS2018 aims to provide a forum for scientists, engineers, educators, and students to discuss the latest progress and future challenges in the field of neural information processing. This year, JNNS aims to make the conference international with all the presentations in English and world-renowned keynote lecturers, Dr. Shun-ich Amari (RIKEN Center for Brain Science) and Dr. Maneesh Sahani (Gatsby Computational Neuroscience Unit, UCL). Travel support will be provided for selected student presenters.
Internet address	http://jnns.org/conference/2018/index.html

Access to Document

JNNS 2018 posterFinal published version, 1.11 MBLicence: Free to read

http://jnns.org/conference/2018/JNNS2018_Proceedings/JNNS2018_Proceedings.pdfLicence: Free to read

Cite this

Mizutani, H., & Giannopulu, I. (2018). Classification based on Neural Connectivity Analysis in a Motor Imaginary Task. In The Proceedings of the 28th Annual Conference of the Japanese Neural Network Society: 第 28 回日本神経回路学会全国大会講演論文集 (pp. 122-123). Okinawa Institute of Science and Technology . http://jnns.org/conference/2018/JNNS2018_Proceedings/JNNS2018_Proceedings.pdf

@inproceedings{e6aa4ca5b19c4fca887dfeccc2efac8f,

title = "Classification based on Neural Connectivity Analysis in a Motor Imaginary Task",

abstract = "This study aims at developing a classificationmethod based on the neural connectivity by human EEGdataset. An experimental result of four class classificationon a motor imagery task indicates that our novel analyticalmethod has a good performance and yields a crossvalidation accuracy of 53.5%.",

author = "Haruo Mizutani and I Giannopulu",

year = "2018",

month = oct,

language = "English",

pages = "122--123",

booktitle = "The Proceedings of the 28th Annual Conference of the Japanese Neural Network Society",

publisher = "Okinawa Institute of Science and Technology ",

note = "The 28th Annual Conference of the Japanese Neural Network Society, JNNS2018 ; Conference date: 24-10-2018 Through 27-10-2018",

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}

Mizutani, H & Giannopulu, I 2018, Classification based on Neural Connectivity Analysis in a Motor Imaginary Task. in The Proceedings of the 28th Annual Conference of the Japanese Neural Network Society: 第 28 回日本神経回路学会全国大会講演論文集. Okinawa Institute of Science and Technology , pp. 122-123, The 28th Annual Conference of the Japanese Neural Network Society, Okinawa, Japan, 24/10/18. <http://jnns.org/conference/2018/JNNS2018_Proceedings/JNNS2018_Proceedings.pdf>

Classification based on Neural Connectivity Analysis in a Motor Imaginary Task. / Mizutani, Haruo; Giannopulu, I.
The Proceedings of the 28th Annual Conference of the Japanese Neural Network Society: 第 28 回日本神経回路学会全国大会講演論文集. Okinawa Institute of Science and Technology , 2018. p. 122-123.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

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AB - This study aims at developing a classificationmethod based on the neural connectivity by human EEGdataset. An experimental result of four class classificationon a motor imagery task indicates that our novel analyticalmethod has a good performance and yields a crossvalidation accuracy of 53.5%.

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BT - The Proceedings of the 28th Annual Conference of the Japanese Neural Network Society

PB - Okinawa Institute of Science and Technology

T2 - The 28th Annual Conference of the Japanese Neural Network Society

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