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# swissknife | ||
Multiple tools to: | ||
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- post-process neural data recorded in singing/anesthetized with the Intan RHD2000 system using both Intan and OpenEphys software. | ||
- convert it to the Klusta-team's Kwik format. | ||
- sort spikes using klusta/kilosort/mountainsort, or simply detect supra-threshold events. | ||
- align the neural data with the stimuli played/bouts detected | ||
- fit parameters and create synthetic vocalizations by integrating the Mindlin model for the vocal organ of the zebra finch. | ||
- Use a FFNN/LSTM/Linear decoder to produce synthetic vocalizations driven by neural activity. | ||
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(Documentation and splitting into more reasonably sized, stand-alone packages is in progress). |
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author_email='[email protected]', | ||
license='MIT', | ||
packages=['swissknife'], | ||
requires=['numpy', 'scipy', 'matplotlib'], | ||
install_requires=['numpy', | ||
'pandas>=0.23', | ||
'more_itertools', | ||
'peakutils>=1.3', | ||
'scipy', | ||
'matplotlib', | ||
'librosa', | ||
'tqdm', | ||
'joblib', | ||
'h5py', | ||
'yml'], | ||
zip_safe=False) |
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