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Program at a Glance (tentative)

 

AINI2018 Program at a glance
   1st workshop day (December 21, 2018)     2nd workshop day (December 22, 2018)

 9:00  Reception Desk Open

 9:30  Opening Remarks

 9:40  Keynote Lecture 1

10:20 Keynote Lecture 2

11:00 Break

11:20 Organized Session 1

12:30 Lunch Break

13:00 Poster Session

15:00 Organized Session 2

16:10 Break

16:30 Organized Session 3

17:40 Break

18:00 Social Gathering  (Hirosawa Club)

20:30 Breakup

 9:00  Reception Desk Open

 9:30  Keynote Lecture 3

10:10 Keynote Lecture 4

10:50 Break

11:10 Organized Session 4

12:10 Closing Remarks

12:20 Break

13:30 Tutorial Courses

16:30 Closing of Tutorial Courses

 

 

Keynote Lectures

  • Elissa J. CHESLER (The Jackson Laboratory, CA)
  • Kozo KAIBUCHI (Nagoya University, JP)
  • Norio KOBAYASHI (RIKEN ISC, JP)
    'Novel trends of research data utilisation through an open science approach'
  • Benigno URIA (Google DeepMind, UK)
    'Vector-based Navigation using Grid-like Representations in Artificial Agents'

Organized Sessions

Large Scale Mouse Brain Data

 Organized by Tsuyoshi MIYAKAWA, Akira SATO

  • Tsuyoshi MIYAKAWA (Fujita Health University)
  • Akira SATO  (Tokyo University of Science)
  • Hiroshi MASUYA  (RIKEN BRC)

Neuroinformatics for Drug Discovery

 Organized by Junichiro YOSHIMOTO and Yoshiyuki ASAI

  • Junichiro YOSHIMOTO  (Nara Institute of Science and Technolgy)
  • Yoshiyuki ASAI  (Yamaguchi University)
  • TBA

Challenges in Data Analysis for Innovation in Neuroscience

Organized by Shinji KAKEI, Alexander WOODWARD and Yoshinobu KANO

  • Shinji KAKEI  (Tokyo Metropolitan Institute of Medical Science)
  • Alexander WOODWARD  (RIKEN CBS)
  • Yoshinobu KANO  (Shizuoka University)
  • Panel Discussion

Neuroinformatics Infrastructure and Platforms in INCF Japan Node (tentative)

Organized by Yoko YAMAGUCHI

  • Taishin NOMURA  (Osaka University)  "Opening of OpenNeuro Repository"
  • Yuko OKAMURA-OHO (Jissen Woman's University)   "Data integration in ViBrism  Database"
  • Shinobu MASAKI (Brain Activity Imaging Center, ATR Promotions, Inc.)
  • Yoko YAMAGUCHI (RIKEN) "Neuroinformatics Infrastructure in INCF Japan Node"

Tutorial Courses

Description of EEG Data in a Standard Format based on NIX/odML schemes

Lecturer: Hiroaki WAGATSUMA (Kyusyu Institute of Technology)

Overview: This tutorial will give a short lecture for the standardization of multi-time scale (different sampling rate) timeseries obtained in the simltaneous recording, which is expected to add annotations to data epoches by usuing with meta-data descriptions. Participants exprience and learn
 i) the procedure of the data conversion of the human EEG data (.mat) and Eye-Tracking data (.json) to a single package of the standard format based on NIX (.nix) with given annotations on odML,
ii) programming to extract a specific target data of interest (NIX data access method) and visualize it in plot,
iii)  data analysis of the target data, generation of a new meta data label depending on the interest and re-embed the new metadata into the NIX format data.

The data and sample codes will be provided in the session. MATLAB (nix-mx) and Java (nix-java) are also available in the system; however we are using the python software tools in the tutorial.

A limit in the number of participants:  possibly 20 (30 as maximum)

Requirements of participants:

  • Experience of the use of linux or mac and python programming.

(windows PC is acceptable under the following condition.)

  • Participants are recommended to install "nixio" (as follows) in their own laptops if the PC are unix or mac (the instration will be done for 5-10mins), while if it is windows, the setting of python environment, installations and the software dependency check is taking time a lot. Therefore, if it is windows, participants must complete to install "nixio" in their windows PCs by themselves according to the installation manual in the web (*).

The simplest way to install NIXPY is from PyPI using pip, like  

pip install nixio           #python2
pip3 install nixio         #python3

(*) Neuroscience information exchange format - NIX:
-data model for storing fully annotated datasets
https://github.com/G-Node/nix/wiki
http://g-node.github.io/nix/
http://g-node.github.io/nixpy/tutorial.html

References: 

NIX-odML Global Workshop & Hackathon 2017 in Japan (with References more in the site) https://dynamicbrain.neuroinf.jp/modules/hackathon/nix-odml2017_eng.html
https://www.neuroinf.jp/fmanager/view/3592/Wagatsuma.pdf
 

Creating the insect brain

Lecturers: Hidetoshi IKENO (University of Hyogo) and  Tomoki KAZAWA (The University of Tokyo)

Overview: This tutorial will give basic skills for the image processing using the confocal image data for constructing a standard brain map of small insect brain. Its applications will be also presented. We are using several software tools for the image processing and visualization.

A limit in the number of participants: 10

Requirements of participants: 

  • Their notebook PC needed on the day.

Note: The tutorial will be conducted in Japanese and used a Japanese text book “昆虫の脳をつくる”.  We will prepare materials based on the book for the day.

References:

  • 神崎亮平(編)『昆虫の脳をつくる』朝倉書店,2018 (in Japanese)

Introduction of Collaborative Large-Scale Modeling for High-Performance Computing

Lectures: Keiichiro INAGAKI (Chubu University), Takayuki KANNON (Kanazawa University) and Yoshihiro OKUMURA (RIKEN CBS)

Overview: This tutorial will give a short lecture for collaborative large-scale modeling and a hands-on using computer cluster. In the lecture, we/participants parallelize the several program code for brain system, connecting them using neuroinformatics tools, and simulate as one large-scale model in the computer cluster.

A limit in the number of participants:  We expect 5-8 participants. If we have received more applications that expected, we will select the participants based on background and experience.

Requirements of participants:

  • Participants must have laptop with installing ssh to log onto our computer cluster.
  • Experience of the use of linux and c/c++ programming.

Note: Part of lecture might be performed in Japanese.

References:

  • T. Kannon, K. Inagaki, N.L. Kamiji, K. Makimura, S. Usui, PLATO: Data-oriented approach to collaborative large-scale brain system modeling, Neural Networks, vol.24, 9, pp.918-926, 2011.
 

 

 

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