Computational Brain Science and Complex Networks with Matlab (SPM)

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Lecturer
Wakita Ken  Akama Hiroyuki
Place
Mon3-4(GSIC隨ｬ1螳溽ｿ貞ｮ､ GSIC Computer Room1)
Credits
Lecture0  Exercise2  Experiment0
Code
65067
Syllabus updated
2014/5/25
Lecture notes updated
2014/3/18
Semester
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 introduce the basics of MATLAB programming by using GSIC Educational System and Tsubame Grid Cluster to provide necessary knowledge about the computation of social networks as complex networks and neuro-imaging data 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 basic approaches of graph analysis and brain analysis using MATLAB.

Plan of lecture

April, 7th Course Introduction and guidance
April, 14th Introduction to social network analysis
April, 21th Getting started with MATLAB
April, 28th Social network analysis with MATLAB
May, 7th (Wed.) Small world phenomenon
May, 12th Scale-free networks
May, 26th Multi dimensional array in MATLAB
June, 2nd Simulation and visualization in MATLAB
June, 9th Brain imaging technology and MATLAB
June, 16th Basics of fMRI data analysis
June, 23rd Introduction to MATLAB(SPM)(1):Preprocessing of fMRI data
June, 30th Introduction to MATLAB(SPM)(2):Single subject analysis
July, 7th Introduction to MATLAB(SPM)(3):Group analysis and other topics
July, 14th Advanced topics: Multi-voxel pattern analysis

Textbook and reference

No textbook is required.

Related and/or prerequisite courses

Everybody is welcome

Evaluation

Attendance and reports