Neuroscience 2023 Washington DC
Scientists from around the world will congregate at Neuroscience 2023 to discover new ideas, share their research, and experience the best the field has to offer.
Dates: Saturday, November 11–Wednesday, November 15
Location: Walter E. Washington Convention Center in Washington, D.C.
Sfn 2023 MEG EEG ERP BESA wiki
SfN 2023 MEG EEG ERP Source Analysis BESA
Many options for review and pre-processing
Several artifact correction algorithms
Dedicated ERP module
Visualization of results
Handling of paradigms, events, and conditions
Batch scripts for automated processing
ERP displays and tools
Sfn 2023 MEG EEG ERP Source analysis features
Large amount of source reconstruction methods:
discrete
distributed
beamformer
surface-based
Bayesian
time-domain and time-frequency domain
Sfn 2023 MEG EEG ERP BESA EEG and MEG formats
MEG and EEG can now be combined into a single data set for simultaneous source modeling of the two modalities. This is available for many source analysis and source imaging methods.
Sfn 2023 MEG EEG ERP BESA Connectivity
Time-Frequency Analysis
Complex Demodulation
Wavelet Analysis (Morlet or Mexican Hat)
Multitaper
Batch processing of all subject data
Grand Average and individual average review
Connectivity Analysis
Averaging over time and / or frequency ranges matrix
Connectome view using combined time-frequency averages
Circular Connectome view for one-glance overview of connectivity
Directly compare conditions, and connectivity methods
ASCII data result export and input support for MATLAB
Sfn 2023 MEG EEG ERP BESA Interoperability with other software
Matlab interface to directly send data to Matlab
Export of data to ASCII and EDF format
All export formats open and described
Matlab scripts are provided to exchange data between Matlab and BESA Research
Sfn 2023 MEG EEG-fMRI Simultaneous
Correct your fMRI artifacts directly in the BESA Research review window
Choose between three proven methods for correction with few mouse clicks
Read your fMRI data directly into BESA Research
Seed sources from fMRI and directly see activation patterns on millisecond scale
Sfn 2023 MEG EEG Cortical LORETA and CLARA
Use the individual cortex as source space for LORETA and CLARA analysis. BESA Research truly computes the solution on the individual cortex, which is superior to other approaches which simply project the source solution onto the cortex.
Spectral analysis of a segment of EEG can be understood as taking a sinusoidal wave (over all cycles contained in the marked block) and shift the wave along the recorded (and filtered) signal. At every latency (or phase shift) we multiply both wave and signal and obtain an output signal of a certain magnitude.
Sfn 2023 EEG individual head FEM generation
In an optional step the individual (FEM) head model can be generated based on the segmentation results (see Wolters et al. 2007) and surface meshes of the 4 tissue layers (skin, scalp, CSF and brain) are extracted. The individual FEM head models can be used for EEG or MEG source analysis.
Sfn 2023 EEG BESA Simulator free software
Simulate both EEG and MEG data
See maps resulting from a dipole anywhere within the head
Add any number of dipoles to a model
Generate independent waveforms for each dipole (source waveforms)
See the surface data resulting from the model as reference-free, average reference, Laplacian (CSD) reference, or using any electrode / sensor as reference
Place a cursor anywhere in the time interval and visualize the scalp activity at that time point
Specify the parameters of the spherical head model
Sfn 2023 EEG Bayesian Source Imaging
SESAME
Cortical LORETA
Cortical CLARA
Minimum Norm
Age-appropriate template head models
Volume imaging using Bayesian methods
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