HesTheMan

Thanks for the suggestion. I just tried recording = se.NeuralynxRecordingExtractor(nldirectory,stream_id='0',strict_gap_mode=False) with the identical results. Additional suggestions are greatly appreciated.

I tried sorting = se.read_neuralynx_sorting(nldirectory,32000,stream_id='0',strict_gap_mode=False) and get the error line 25, in sorting = se.read_neuralynx_sorting(nldirectory,32000,stream_id='0',strict_gap_mode=False) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ TypeError: NeuralynxSortingExtractor.__init__() got an unexpected keyword argument 'strict_gap_mode'

I am using spikeinterface version 0.101 and neo version 0.13.3 >>> si.__version__ '0.101.0' >>>neo.__version__ '0.13.3' Here is what I see when I use neo and strict_gap_mode=true >>> reader NeuralynxRawIO: C:\Users\The...

[NeuralynxSpikeInteface.zip](https://github.com/user-attachments/files/17074078/NeuralynxSpikeInteface.zip) Here is a recording of one of the channels

Thanks for taking the time to look at the data. The ncs files were created as the signals were being processed to extract spikes. Maybe that is the reason for...

I just mean the equipment is recording raw continuous data but at the same time it is extracting spikes. Just trying to find a reason why there are so many...

I agree. I am the technical person. I will do some more recordings and work with Neuralynx to improve the configuration settings. When I plot the extracted spikes and the...

OK to close. Thank you very much for your help. My take away is the Neuralynx recordings I have been trying to analyze have gaps in the continuous data and...

There are indeed duplicates in the input data. I was trying to combine known spikes with a background recording. The known spikes are all identical snippets. They occur every 100ms.

neo==0.13.1