biology

Neurophysiological Biomarker Toolbox

Neurophysiological Biomarker Toolbox is a biology topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Neurophysiological Biomarker Toolbox rather than just read about it. In short: The Neurophysiological Biomarker Toolbox (NBT) is an open source MATLAB toolbox for the computation and integration of neurophysiological biomarkers (e.g., biomarkers based on EEG or MEG recordings). The NBT toolbox has so far been used in seven peer-reviewed research articles, and has a broad user base of more than 1000 users.

Key takeaways

Neurophysiological Biomarker Toolbox belongs to biology; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Neurophysiological Biomarker Toolbox to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Neurophysiological Biomarker Toolbox from memory before moving on to harder problems.

Reference excerpt

The Neurophysiological Biomarker Toolbox (NBT) is an open source MATLAB toolbox for the computation and integration of neurophysiological biomarkers (e.g., biomarkers based on EEG or MEG recordings). The NBT toolbox has so far been used in seven peer-reviewed research articles, and has a broad user base of more than 1000 users. The NBT toolbox provides unique features for analysis of resting-state EEG or MEG recordings. NBT offers a pipeline from data storage to statistics including artifact rejection, signal visualization, biomarker computation, statistical testing, and biomarker databasing. NBT allows for easy implementation of new biomarkers, and incorporates an online wiki (the NBTwiki) that aims at facilitating collaboration among NBT users including extensive help and tutorials. The standardised way of data storage and analysis that NBT proposes allow different research projects to merge, compare, or share their data and biomarker algorithms.

Features Neuronal oscillations are generated at many spatial and temporal scales of neuronal organization, and thought to provide a network-level mechanism for the coordination of spatio-temporally distributed spiking activity. For an adequate understanding of quantitative changes in neurophysiological signals, such as electroencephalography (EEG) or magnetoencephalography (MEG), as a consequence of disease, experimental manipulations, or genetic variability there is a need to apply multiple biomarker algorithms. The aim of the NBT toolbox is to make biomarker research easier at all levels. From having raw data, cleaning it, calculating biomarkers, to performing advanced statistics. The NBT toolbox includes biomarkers, such as:

Standard spectral biomarkers Phase locking value Detrended fluctuation analysis The toolbox has a standard template for how biomarkers should be implemented, which makes it relatively easy to implement new biomarkers. Originally the toolbox was aimed at biomarkers based on EEG or MEG signals, recently however the toolbox has moved towards supporting almost any type of biomarker data. The biomarker data and associated meta information is stored in a Matlab-based database; the NBT elements database. The NBT toolbox works as a plugin to the open-source Matlab toolbox EEGLAB. Commercial EEG analysis mainly targeting large clinical research studies or clinical trials are provided as an service to NBT toolbox by NBT Analytics.

History The development of the NBT toolbox was started in 2008 by Simon-Shlomo Poil and Klaus Linkenkaer-Hansen from the VU University Amsterdam, the Netherlands. Later the developer team was joined by Rick Jansen, Richard Hardstone, Sonja Simpraga, and Giuseppina Schiavone. The toolbox has also received contributions from many other people. The toolbox and its associated tutorial website has served as a major part of courses at the VU University Amsterdam; such as, the Human Neurophysiology course (with on average 100 students each year), and the advanced human neurophysiology. The first public release of the toolbox was made (release candidate R1) on the 18th April 2012. As of March 2014, the toolbox has been downloaded more than 1200 times. The most recent public version of the NBT toolbox is 5.0.2-alpha (released 13 November 2014).

Scientific publications using the NBT toolbox Poil et al., Age dependent electroencephalographic changes in Attention Deficit/Hyperactivity Disorder (ADHD), Clinical Neurophysiology, 2014 Poil et al., Integrative EEG biomarkers predict progression to Alzheimer's disease at the MCI stage, Frontiers in Aging Neuroscience, 2013 Diaz et al., The Amsterdam Resting-State Questionnaire reveals multiple phenotypes of resting-state cognition, Frontiers in Human Neuroscience, 2013 O'Gorman et al., Coupling Between Resting Cerebral Perfusion and EEG, Brain Topography, 2012 Hardstone et al., Detrended fluctuation analysis: A scale-free view on neuronal oscillations, Frontiers in Fractal Physiology, 2012

Worked examples

Example 1 — a first encounter with Neurophysiological Biomarker Toolbox

Start with the simplest possible case. Write down what Neurophysiological Biomarker Toolbox claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In biology, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Neurophysiological Biomarker Toolbox before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Neurophysiological Biomarker Toolbox ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Neurophysiological Biomarker Toolbox

In research: Neurophysiological Biomarker Toolbox appears in biology research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Neurophysiological Biomarker Toolbox in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Neurophysiological Biomarker Toolbox is common in secondary-school and first-year university syllabi. It links to neighbouring topics Electroencephalography, Free data analysis software, Free statistical software, so understanding it makes those chapters shorter.
In everyday life: Look for Neurophysiological Biomarker Toolbox outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Neurophysiological Biomarker Toolbox in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Neurophysiological Biomarker Toolbox means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Neurophysiological Biomarker Toolbox out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Neurophysiological Biomarker Toolbox in simple terms?

Why does Neurophysiological Biomarker Toolbox matter?

Because it connects several biology ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Neurophysiological Biomarker Toolbox?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Neurophysiological Biomarker Toolbox.