Extracting a recording from a plexon file

[AbhiSwamiUConn]

In my plexon file, there are 3 wideband channels per electrode, each with their own field potential and spikes. I am trying to return the timestamps and traces per spike.

• timestamps: 1 number per each spike occurrence per electrode channel (in seconds)

• traces: for each spike timestamp a trace is x numbers before and after the timestamp occurrence. If the trace duration is 1 ms before and 1 ms after spike occurrence and the number of points per ms of the recording is 10, then each timestamp spike occurrence will have a trace of 20 numbers (in voltage) which reflect the shape of the spike occurrence in 2 ms.

This is what I have done so far.

import spikeinterface as si
import spikeinterface.extractors as se
import spikeinterface.preprocessing as st
import spikeinterface.sorters as ss

'''Specify the path to your PLX file'''
plx_file = "plexon file here"

'''Load data using the PlexonIO extractor'''
plx_extractor = se.read_plexon(plx_file)

'''Select channels (SPKC01 and SPKC03)'''
channels = [1, 3]  # Assuming SPKC01 corresponds to channel 1, and SPKC03 corresponds to channel 3
plx_extractor_chs = "?"

'''Preprocess the data'''
recording = st.bandpass_filter(plx_extractor_chs, freq_min=300, freq_max=6000)
recording = st.common_reference(recording)

''' Spike detection and sorting using SpyKING CIRCUS 2'''
sorting = se.read_spykingcircus(recording)

''' Export the results to a text file'''
output_txt = 'output.txt'

'''Export spike times and cluster IDs'''
si.export_to_phy(recording, sorting, output_folder='C:/Users/Abhinav UConn User/Desktop/test/PLX/')

'''Export average templates with variability information'''
templates = st.postprocessing.get_unit_templates(recording, sorting)
variability = st.postprocessing.get_unit_template_variability(recording, sorting)

with open(output_txt, 'w') as f:
    f.write("Timestamps\tCluster_ID\tAverage_Template\tVariability\n")
    for unit_id in range(sorting.get_num_units()):
        timestamps = sorting.get_unit_spike_train(unit_id=unit_id)
        average_template = templates[unit_id]
        variability_score = variability[unit_id]
        f.write(f"{timestamps}\t{unit_id}\t{average_template}\t{variability_score}\n")

input()

[alejoe91]

HI,

Can you point us to the documentation you ar using to build your script?
Did you use ChatGPT? Some of the functions do not exist :)

[AbhiSwamiUConn]

No, there is not ai generated code here. When I started work on this script, I was given a template to work with by my professor, stating what he wanted it to accomplish. The functions that do not exist were a part of that template and do not exist in the spikeinterface api. I was wondering if there was any way to complete the code using the methods already available in that api.

[alejoe91]

We don't have a variability score, but definitely everything else can be accomplished.

Next week we're holding a tutorial on Tuesday. I think that is the best way for you to get used to the code base. Here's a registration link to participate to the live streaming:
https://forms.gle/Nj6py1C2tmM1g2Cb7