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Bug 3105 - implement NAI / unit-noise gain MV beamformer; orientation not properly optimized when NAI manually calculated as in tutorial
| Status | ASSIGNED |
| Reported | 2016-04-06 18:40:00 +0200 |
| Modified | 2016-04-07 16:14:06 +0200 |
| Product: | FieldTrip |
| Component: | inverse |
| Version: | unspecified |
| Hardware: | All |
| Operating System: | All |
| Importance: | P5 major |
| Assigned to: | Sarang Dalal |
| URL: | |
| Tags: | |
| Depends on: | |
| Blocks: | |
| See also: |
Sarang Dalal - 2016-04-06 18:40:35 +0200
For beamforming time series, it is desirable to implement the unit-noise gain minimum-variance (aka Borgiotti-Kaplan) beamformer and the related neural activity index. The major reason this should happen directly in the beamformer code is that when the optimal orientation is calculated, any such "weight normalization" should be taken into account. (See equation 4.47 in the Sekihara & Nagarajan 2008 book.) This is not feasible to recalculate after the weights are already obtained, but can make a surprisingly dramatic improvement in the source reconstruction quality.
Sarang Dalal - 2016-04-06 19:02:59 +0200
I think I have resolved this with Pull #133 :-) https://github.com/fieldtrip/fieldtrip/pull/133
Sarang Dalal - 2016-04-06 19:06:20 +0200
Note: I have tested this with vector lead fields with orientation optimization, i.e., a scalar beamformer. A vector beamformer may require a "trace" operation on the denominator for both NAI and UNG.
Robert Oostenveld - 2016-04-06 20:24:32 +0200
thanks, I just I merged your PR Are you planning to look into the trace for vector BFs?