meanap.pipeline.burst_detection

Functions

burst_detect_isin(spike_times, n, isin_th)	Detect bursts using Bakkum's ISI_N method.
burst_detect_network(spike_times_dict, fs[, ...])	Network burst detection combining all active channels.
get_isin_threshold(spike_times[, n])	Calculate the automatic ISIn threshold using Bakkum's method.
single_channel_burst_detection(...[, ...])	Per-channel burst detection matching singleChannelBurstDetection.m.

meanap.pipeline.burst_detection.burst_detect_isin(spike_times, n, isin_th)

Detect bursts using Bakkum’s ISI_N method.

Returns:

dict with T_start, T_end, S (size in spikes) SpikeBurstNumber: 1D array assigning each spike to a burst (-1 if not in burst)

Return type:

Burst

Parameters:

• spike_times (ndarray)

• n (int)

• isin_th (float)

meanap.pipeline.burst_detection.burst_detect_network(spike_times_dict, fs, min_spikes=10, min_channels=3, isin_th_param='automatic')

Network burst detection combining all active channels.

Parameters:

• spike_times_dict (dict[int, ndarray])

• fs (float)

• min_spikes (int)

• min_channels (int)

• isin_th_param (str | float)

Return type:

tuple[list[dict], ndarray, list[ndarray], dict]

meanap.pipeline.burst_detection.get_isin_threshold(spike_times, n=10)

Calculate the automatic ISIn threshold using Bakkum’s method.

spike_times: 1D array of spike times in seconds. n: The number of spikes to consider for ISI_N. Returns the threshold in seconds.

Parameters:

• spike_times (ndarray)

• n (int)

Return type:

float

meanap.pipeline.burst_detection.single_channel_burst_detection(spike_times_dict, n_channels, fs, min_spikes=5, isi_threshold='automatic', recording_duration_s=0.0)

Per-channel burst detection matching singleChannelBurstDetection.m.

Parameters:

• spike_times_dict (dict[int, ndarray])

• n_channels (int)

• fs (float)

• min_spikes (int)

• isi_threshold (str | float)

• recording_duration_s (float)

Return type:

dict