The Neurophysiological Biomarker Toolbox (NBT)



Basic features in NBT

Introduction

NBT is an open source Matlab toolbox for the computation and integration of neurophysiological biomarkers. NBT offers a pipeline from data storage to statistics including artefact rejection, signal visualization, biomarker computation, and statistical testing. NBT allows for easy implementation of new biomarkers. You can read about the NBT processing flow here. See List of NBT terms with explanations of nomenclature.

The NBT GUI

The NBT consists of a collection of Matlab scripts, that can be used by typing code in the Matlab command line, or by using the NBT GUI (graphical user interface). The main functions of NBT are accessible through the GUI. When using the GUI the equivalent command line code is displayed, which shows which function are used by the GUI. Also, NBT files can be imported and exported from EEGlab (another Matlab toolbox for EEG data) via the GUI.

From raw signal to NBT

The main focus of NBT is EEG/MEG signals. But any type of signals can be analysed in NBT. The import function of NBT supports .txt files, .mat files, .set and .raw files. See Importing data into NBT format for a tutorial about importing signals into NBT format. NBT provides you with a standard form of organizing your data. This starts with the file name convention, and the storage of the data in three separate files per subject per condition: one file contains the signals, one file contains information about the recording, and one file contains the analysis results.

Cleaning signals

If you are analysing, e.g., EEG data (which is the main focus of NBT) you need to remove artifacts from your signals. NBT has been developed using high-density EEG signal and has a wide-collection of tools to handle the cleaning process of these complex signals, see the tutorials How to remove bad channels and transient artifacts and ICA - Independent Component Analysis. For non EEG data, see the tutorial Artifact rejection: how to remove noisy channels and intervals from your signals. Artifacts are stored in the Info file, and omitted in further analysis.

Calculating biomarkers

Several biomarkers are implemented in NBT. If the biomarker you are interested in is not yet implemented, you can use a template script in order to adapt to the NBT format, see Implementing new biomarkers.

Biomarker statistics

NBTelements

In order to use biomarker from other sources and to database your biomarkers; NBT uses NBTelements. NBTelements is a Matlab database organizing data in a search tree structure. NBTelements allows you to query data with complex definitions.

tutorial/nbt_processing_flow.txt · Last modified: 2013/11/03 10:12 by Simon-Shlomo Poil
The NBTwiki platform - version 2.8 - 9 May 2013
Copyright (C) 2008-2015