ATR – DNi

• About
• Research
  • Reading ‘what you see’: Reconstruction of visual images using brain activity patterns
  • Prediction of Motor Commands from Interior Central Sulcus Cortical EEG (ECoG) with Extremely High Accuracy
  • Real-Time Control of a Prosthetic Hand using Human Electrocorticograms
• Publications
• Members
  • Yukiyasu Kamitani (Department Head)
• DNi in the News
• BrainLiner
  • BrainLiner Web Quick Start Guide
  • How to read our data format
• Downloads
  • fMRI Data Set for Visual Image Reconstruction
  • Tools for Brain-Behavior Data Sharing
  • Brain Decoder Toolbox
  • iConfer
  • Brainliner Desktop
• Links

Brainliner Desktop

We provide tools for synchronizing brain activity data with behavioral information.

You can download our software and documentation from this page.

If you want to access our source and developer information, please visit our GitHub project page.

Introduction

Researchers all around the world are studying the

relationship between brain activity and behavior information. However,

it is often difficult to synchronize these different types of data in order to study the relationship between stimuli and response.

Thus we are creating the “BrainLiner” desktop application and sharing it as

an open source project.

Our program uses the NetBeans Platform API as to allow pluggable modules to easily be developed. We also use GitHub to host our open-source project, in order to facilitate social-networking for developers to contribute to our project.

For developer information, please visit our GitHub project page.

Your cooperation will be much appreciated!

History

2011.09.02 Released BrainLiner Desktop BETA (ver 0.9) for Mac OS X Snow Leopard.

2011.09.08 Fixed Bugs. It works for Mac OS X Lion.

Download

• BrainLiner Desktop BETA (ver 0.9) [download][ONLY for Mac OS X]

Documents

• User Manual[download]

Copyright

This software conforms to CC BY (Creative Commons Attrivution license).

See creative commons [http://creativecommons.org/licenses/by/3.0/]

Acknowledgement

This work was supported by the Strategic Research Program for Brain

Sciences(SRPBS) from MEXT, Japan [http://brainprogram.mext.go.jp/].

Also, ‘Multineuronal Research Resource’ Project Group of the research

grant program by MEXT, ‘Integrative Brain,’ collaborated with us.