This capsule is designed to postprocess ephys data for the AIND pipeline.
This capsule first removes redundant/duplicate units (sharing >90% of the spikes). Then, it computes sparse waveforms and then in computes several additional postprocessing data, including:
In addition, quality metrics are also computed here. Postprocessed data are used downstream for spike sorting curation and visualization.
The data/ folder must include the output of the aind-ephys-preprocessing and the aind-ephys-spikesort-pykilosort/aind-ephys-spikesort-kilosort25capsules, including the preprocessed_{recording_name} and spikesorted_{recording_name} folders.
The code/run script takes the follwing arguments:
--n-jobs N_JOBS Number of jobs to use for parallel processing.
Default is -1 (all available cores). It can also be a float between 0 and 1 to use a fraction of available cores
--params-file PARAMS_FILE
Optional json file with parameters
--params-str PARAMS_STR
Optional json string with parameters
A full list of parameters used for postprocessing and quality metrics calculation can be found in the code/params.json:
{
"job_kwargs": {
"chunk_duration": "1s",
"progress_bar": false
},
"sparsity": {
"method": "radius",
"radius_um": 100
},
"postprocessing": {
"duplicate_threshold": 0.9,
"waveforms_deduplicate": {
"ms_before": 0.5,
"ms_after": 1.5,
"max_spikes_per_unit": 100,
"return_scaled": false,
"dtype": null,
"sparse": false,
"precompute_template": ["average"],
"use_relative_path": true
},
"waveforms": {
"ms_before": 3.0,
"ms_after": 4.0,
"max_spikes_per_unit": 500,
"return_scaled": true,
"dtype": null,
"precompute_template": ["average", "std"],
"use_relative_path": true
},
"spike_amplitudes": {
"peak_sign": "neg",
"return_scaled": true,
"outputs": "concatenated"
},
"similarity": {
"method": "cosine_similarity"
},
"correlograms": {
"window_ms": 50.0,
"bin_ms": 1.0
},
"isis": {
"window_ms": 100.0,
"bin_ms": 5.0
},
"unit_locations": {
"method": "monopolar_triangulation"
},
"spike_locations": {
"method": "grid_convolution"
},
"template_metrics": {
"upsampling_factor": 10,
"sparsity": null,
"include_multi_channel_metrics": true
},
"principal_components": {
"n_components": 5,
"mode": "by_channel_local",
"whiten": true
}
},
"quality_metrics_names": [
"num_spikes",
"firing_rate",
"presence_ratio",
"snr",
"isi_violation",
"rp_violation",
"sliding_rp_violation",
"amplitude_cutoff",
"amplitude_median",
"amplitude_cv",
"synchrony",
"firing_range",
"drift",
"isolation_distance",
"l_ratio",
"d_prime",
"nearest_neighbor",
"silhouette"
],
"quality_metrics": {
"presence_ratio": {
"bin_duration_s": 60
},
"snr": {
"peak_sign": "neg",
"peak_mode": "extremum",
"random_chunk_kwargs_dict": null
},
"isi_violation": {
"isi_threshold_ms": 1.5,
"min_isi_ms": 0
},
"rp_violation": {
"refractory_period_ms": 1,
"censored_period_ms": 0.0
},
"sliding_rp_violation": {
"bin_size_ms": 0.25,
"window_size_s": 1,
"exclude_ref_period_below_ms": 0.5,
"max_ref_period_ms": 10,
"contamination_values": null
},
"amplitude_cutoff": {
"peak_sign": "neg",
"num_histogram_bins": 100,
"histogram_smoothing_value": 3,
"amplitudes_bins_min_ratio": 5
},
"amplitude_median": {
"peak_sign": "neg"
},
"amplitude_cv": {
"average_num_spikes_per_bin": 50,
"percentiles": [5, 95],
"min_num_bins": 10,
"amplitude_extension": "spike_amplitudes"
},
"firing_range": {
"bin_size_s": 5,
"percentiles": [5, 95]
},
"synchrony": {
"synchrony_sizes": [2, 4, 8]
},
"nearest_neighbor": {
"max_spikes": 10000,
"n_neighbors": 4
},
"nn_isolation": {
"max_spikes": 10000,
"min_spikes": 10,
"n_neighbors": 4,
"n_components": 10,
"radius_um": 100
},
"nn_noise_overlap": {
"max_spikes": 10000,
"min_spikes": 10,
"n_neighbors": 4,
"n_components": 10,
"radius_um": 100
},
"silhouette": {
"method": ["simplified"]
}
}
}The output of this capsule is the following:
results/postprocessed_{recording_name} folder, containing the postprocessed data (as a WaveformExtractor folder)results/postprocessed-sorting_{recording_name} folder, containing the spike sorted data, saved by SpikeInterface, after de-duplicationresults/data_process_postprocessing_{recording_name}.json file, a JSON file containing a DataProcess object from the aind-data-schema package.