Computational Brain Science and Complex Networks with Matlab (SPM)

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Wakita Ken  Akama Hiroyuki 
Mon3-4(GSIC Computer Room 1)  
Lecture0  Exercise2  Experiment0
Syllabus updated
Lecture notes updated
Spring Semester

Outline of lecture

Mathematica is a highly ingenious, extremely precise and among others user-friendly programming language. From the standpoint of the human economic science, it is the most suitable for 1) complicated symbolic computation including vast amounts of terms, 2) analytical or numerical solutions of equations, differential equations or minimization calculation, 3) accurate and aesthetic visualization of graphs or figures. In this class, we provide practices using GSIC Educational System and Tsubame Grid Cluster to learn how to manipulate "Mathematica", which is necessary for the calculation of economics or cognitive psychology such as solution to equations, linear algebra (list, vector and matrix manipulation), statistics (Descriptive statistics, Regression, Anova), graphs and complex network, and simulation of complex systems.

Purpose of lecture

We provide trainings for 窶廴atlab窶 and 窶彜PM窶 by using GSIC Educational System and Tsubame Grid Cluster to increase necessary knowledge for the analysis of brain image obtained by functional magnetic resonance imaging (fMRI). The SPM (statistical parametric mapping) is a software package to analyze human brain activities and it is employed in many fMRI studies. In this lecture, students will learn the theoretical background of the SPM and practical usage as well as how to use the Matlab that is required to run the SPM.

Plan of lecture

1.(13.Apr) Procedures to Get Tsubame Account and Introduction to Tsubame Literacy
2.(20.Apr) X11 Desktop Environment; Downloading and Uploading Data; Basic UNIX Commands (1)
3.(27.Apr) Use of a File-synchronization Tool Unison; Basic UNIX Commands (2)
4.(11.May) Basic Operation of Matlab
5.(18.May) Batch Processing and Script-M file
6.(25.May) Working with Data Matrix by Matlab
7.(1.Jun) Hands on SPM (I) : Instalation of SPM and Basic Usage
8.(8.Jun) The priciples behind SPM (Statistical Parametric Mapping) for brain imaging I
9.(15.Jun) Hands on SPM (II) : Preprocessing
10.(22.Jun) Preprocesssing of Brain images by SPM
11.(29.Jun) Hands on SPM (III) : Statistical Analysis
12.(6.Jul) Data and Model Specification on SPM
13.(13.Jul) Hands on SPM (IV) : Groupl Analysis
14.(24.Jul) The priciples behind SPM (Statistical Parametric Mapping) for brain imaging II
15.(27.Jul) Self-learning for Reviewal

Textbook and reference

No textbook is required.

Related and/or prerequisite courses

Everybody is welcome


Attendance and reports

Comments from lecturer

This lecture will be held from April the 13th on every Monday, 15:00~16:30 (Time Slots: 7-8) at the 1st Practical Room of Global Scientific Information and Computing Center (GSIC) (3rd floor). The access information can be found at the following URLs.
This course is strongly supported by Prof. Yasunori Kotani and Prof. Yoshimi Ohgami, specialists of the neurophysiology and assistant professors of the Graduate School of Decision Science and Technology.
No special knowledge on the brain is required.
For the more detailed information on the course, please refer to and feel free to send an email to Prof. Akama ( or Prof.Kotani (
The credit of this course can be used to complete the International Human Economic Science Special Course which will start in April, 2009.

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