The BESA Webinars enable you to learn about topics directly related to your work, conveniently from your work place – no travel required!
New features in BESA Research 7.1
This webinar will focus on the new features added in the recent major release of BESA Research. In particular, the following topics will be covered:
– Boundary element and finite element modelling
– Confidence limits of source modelling
– Multi-slice view of source images
– Combining MEG and EEG in source imaging
– Improvements in SESAME
– Atlas-based source montages and (beamformer) virtual sensor montages
– And also other improvements
Use M/EEG beamformers and virtual sensors to set the focus on the brain activity you are interested in
M/EEG brain connectivity is an important and exciting topic. However, it often seems difficult to separate the activity of interest from other phenomena like volume conduction, and surface signals are often spread over a wide area, making it difficult to interpret what the underlying neural generators are, and how they interact with each other.
M/EEG beamforming is a source analysis technique with the desirable feature of contrasting the activity of the brain region of interest with the surrounding activity. However, as in all inverse methods, it is not guaranteed to give you the correct solution for your data – -this depends largely on the data, and to some extent on the method parameters.
This webinar will explain how to transform your M/EEG signals into source space, and show what insights can be gained using connectivity analysis in source space.
This webinar will explore some of the underlying concepts, and show the use of beamforming in source imaging, and also as a tool to provide virtual sensors inside the brain for exploring raw data.
Date: 7th May 2020, 3 p.m. CEST (GMT+2). Registration closed.
Date: 12th May 2020, 3 p.m. CEST (GMT+2). Registration closed.
Analyzing joint fMRI-EEG recordings – pitfalls and how to overcome them
What is Bayesian M/EEG Source Analysis, and why should I care (and not be afraid)?
Joint recordings of fMRI and EEG have the huge potential of marrying two worlds that are usually quite separated: The superior spatial resolution of fMRI, and the unmatched temporal resolution of EEG. Also both techniques measure two different phenomena – blood oxygenation changes and electrical activity – combining them gives unprecedented insight into brain activity. However, recording EEG in the magnet also means introducing large artifacts into the EEG.
Bayesian source analysis methods for M/EEG are becoming increasingly popular. But what is actually Bayesian source analysis, how can it be applied, and what are benefits and pitfalls of this approach?
In this webinar, we will explain what these artifacts are, and even better, how you can get rid of them easly to reconstruct the original EEG signal. Finally, we will give you some tips on interpreting the data.
This webinar will shed some light on these questions and show a demonstration of applying Bayesian source analysis in real life.
Date: 14th May 2020, 3 p.m. CEST (GMT+2). Registration closed.
Date: 19th May 2020, 3 p.m. CEST (GMT+2). Registration closed.
Watch on Youtube:
New features in BESA Research 7.0 on Thursday, 6th December 2018, at two different time slots:
9:00 a.m. CET (GMT+1)
3:00 p.m. CET (GMT+1)
Duration: 1 hour
The webinar will cover the following topics:
Bayesian Source Imaging with SESAME
Simultaneous EEG / fMRI recordings
Watch this webinar on Youtube:
New features in BESA Research 6.1 on 1st December 2016, 3:30 p.m. CET (GMT+1). Duration: 1 hourThis webinar will focus on the new features added in the recent major release of BESA Research. In particular, the following topics will be covered:
Cortical imaging methods
Age-appropriate template head models for EEG
Source montages for Default Mode Network analysis
Watch this webinar on Youtube:
AN(C)OVA and Correlation: BESA Statistics 2.0 on 6th December 2016, 3:30 p.m. CET (GMT+1). Duration: 1 hourThis webinar will focus on the new features added in the recent major release of BESA Statistics. In particular, the following topics will be covered:
Introduction into nonparametric cluster statistics
One-factor ANOVA with or without co-variate of no interest