Deriving LFP signals from Raw signals

Author: Konstantinos Nasiotis

The toolbox features a convenient signal converter that produces local field potential time series from raw signals. The converter jointly processes the recorded raw data and the events generated by the spike sorter. The fast-sampled raw signals are downsampled to a new sampling rate (1000 Hz), with an anti-aliasing bandpass filter (e.g., [0.5, 150] Hz) applied. The event latencies are also adjusted to the new sampling rate before both the new event file and the LFP time series are automatically featured in the Brainstorm database as new data files.

Everything needed for the electrophysiology analysis will be incorporated into a single .bst file (Brainstorm binary file format), located in the brainstorm_db folder.

In order to get the LFP from the raw file after spike sorting, users need to drag and drop the link to raw file into the processing box, and then click Run->Electrophysiology->Convert Raw to LFP.

Note: Following the spike sorting steps is not needed in order to Derive the LFP from the RAW signal. Users can go straight to this step if needed.

Once the conversion function is selected, a new window appears with the following options:

1. Despike LFP: Apply Bayesian Spike Removal (See next section).
2. Parallel Processing: Activate the parallel toolbox and run processes in parallel. Greatly improves the speed of the process (requires Matlab’s parallel toolbox).

3. Memory to use for demultiplexing: There is a demultiplexing process that separates the electrodes into separate files in the background. The larger the RAM selected is, the faster this process will be performed. Make sure a high portion of the Computer’s RAM is selected. Demultiplexing should have already been performed on the spike-sorting step. In case the temp folder emptied (Brainstorm restarted), or users went straight to LFP conversion, only then demultiplexing would be performed again.