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tutorial:beamformer [2018/10/21 15:05]
42.49.180.224 [Background]
tutorial:beamformer [2017/08/17 11:21] (current)
127.0.0.1 external edit
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 The brain is divided in a regular three dimensional grid and the source strength for each grid point is computed. The method applied in this example is termed Dynamical Imaging of Coherent Sources (DICS) and the estimates are calculated in the frequency domain (Gross ET al. 2001). Other beam-former methods rely on sources estimates calculated in the time domain, e.g. the Linearly Constrained Minimum Variance (LCMV) and Synthetic Aperture Magnetometry (SAM) methods (van Veen et al., 1997; Robinson and Cheyne, 1997). These methods produce a 3D spatial distribution of the power of the neuronal sources. This distribution is then overlaid on a structural image of the subject'​s brain. Furthermore,​ these distributions of source power can be subjected to statistical analysis. It is always ideal to contrast the activity of interest against some control/​baseline activity. Options for this will be discussed below, but it is best to keep this in mind when designing your experiment from the start, rather than struggle to find a suitable control/​baseline after data collection. The brain is divided in a regular three dimensional grid and the source strength for each grid point is computed. The method applied in this example is termed Dynamical Imaging of Coherent Sources (DICS) and the estimates are calculated in the frequency domain (Gross ET al. 2001). Other beam-former methods rely on sources estimates calculated in the time domain, e.g. the Linearly Constrained Minimum Variance (LCMV) and Synthetic Aperture Magnetometry (SAM) methods (van Veen et al., 1997; Robinson and Cheyne, 1997). These methods produce a 3D spatial distribution of the power of the neuronal sources. This distribution is then overlaid on a structural image of the subject'​s brain. Furthermore,​ these distributions of source power can be subjected to statistical analysis. It is always ideal to contrast the activity of interest against some control/​baseline activity. Options for this will be discussed below, but it is best to keep this in mind when designing your experiment from the start, rather than struggle to find a suitable control/​baseline after data collection.
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 ===== Procedure ===== ===== Procedure =====