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Output figures Python

klaragerlei edited this page Oct 22, 2018 · 6 revisions

The figures generated depend on the data available.

Figures will be generated for each cluster identified that passes curation.

For all data types, Python will plot:

(1) Waveforms - 50 example waveforms from the cluster are plotted (grey) for each channel on the tetrode on which the event was detected, with an average waveform overlaid (red). The x axis represents number of data samples (30k/sec), and the y axis shows change in voltage in mV. m5_2018-03-06_15-34-44_of_4_waveforms (2) 2 autocorrelograms - the first shows time between -10 and 10 milliseconds, the second shows between -250 and 250. m5_2018-03-06_15-34-44_of_4_autocorrelogram_10ms m5_2018-03-06_15-34-44_of_4_autocorrelogram_250ms (3) Spike histograms - plots number of spikes against sampling points in units of 1e7, and firing rate against speed of the animal in cm/s. m5_2018-03-06_15-34-44_of_4_spike_histogram m5_2018-03-06_15-34-44_of_4_speed_histogram

For open field data, uses Bonsai tracking data to plot:

(1) Trajectory of animal (grey) with spikes overlaid (red dots). m5_2018-03-06_15-34-44_of_6 0_spikes_on_trajectory (2) Firing rate map - shows firing rate as colour within pixels, and displays maximum firing rate. m5_2018-03-06_15-34-44_of_rate_map_6 0 (3) Heat map of animal's coverage of environment. heatmap (4) Head direction - firing rate against direction of head in degrees. Also displays maximum firing rate, preferred head direction, and head direction score. m5_2018-03-06_15-34-44_of_hd_polar_6 0 (5) Head direction with trajectory - shows head direction (-180 to 180 degrees) as colour of spikes on trajectory plot. m5_2018-03-06_15-34-44_of_hd_map_6 0

m5_2018-03-06_15-34-44_of_rate_map_autocorrelogram_5

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