VR post sorting
Specific parameters need to be set for the vr analysis environment.
- stop_threshold this is the value in which the animals speed has to drop below for a stop to be extracted (<0.7 cm/second)
- movement_channel this is the pin on the DAQ which has the movement of the animal along the track : prm.set_movement_channel('100_ADC2.continuous')
- first_trial_channel this is the first pin on the DAQ which has the trial type information : prm.set_first_trial_channel('100_ADC4.continuous')
- second_trial_channel this is the first pin on the DAQ which has the trial type information : prm.set_second_trial_channel('100_ADC5.continuous')
The spatial data frame contains processed data describing the position of the animal in the virtual reality. The columns are organized as follows:
processed_position_data (name of the df in the main code)
- time_ms : arrays of time in seconds, synchronized with the ephys data
- position_cm : arrays of x coordinates of position of animal in virtual track in cm, synchronized with the ephys data
- trial_number : arrays of the current trial number, synchronized with the ephys data
- trial_type : arrays of the current trial type (beaconed, non beaconed, probe), synchronized with the ephys data
- velocity : instant velocity of animal (cm/s), synchronized with the ephys data
- speed : speed of animal averaged over 200 ms (cm/s), synchronized with the ephys data
- stops : whether an animal has stopped (0/1 : no/yes), synchronized with the ephys data
- filtered_stops : stops within 1 cm of each other are removed
- stop_times : array of times which the animal has stopped
spatial_firing (this is the name of the df in the main code)
[every row is cluster] [column is a different analysis]
- session_id : name of main recording folder (example: M5_2018-03-06_15-34-44_of)
- cluster_id : id of cluster within session (1 - number of clusters)
- tetrode : id of tetrode within session (1 - 4)
- primary_channel : channel where the event was detected on (1 - 4)
- firing_times : array of all firing event times that belong to cluster from the vr (in sampling points)
- x_position_cm : array of position in cm corresponding with firing event times
- trial_numbers : array of trial numbers corresponding with firing event times
- trial_types : array of trial types corresponding with firing event times
- number_of_spikes : total number of spikes during session
- mean_firing_rate :
- isolation :
- noise_overlap :
- peak_snr :
- random_snippets :
- speed_per_200ms : array of speed corresponding with firing event times
- beaconed_position_cm : array of position in cm corresponding with firing event times in beaconed trials
- beaconed_trial_number : array of trial number corresponding with firing event times in beaconed trials
- nonbeaconed_position_cm : array of position in cm corresponding with firing event times in non beaconed trials
- nonbeaconed_trial_number : array of trial number corresponding with firing event times in non beaconed trials
- probe_position_cm : array of x position cm corresponding with firing event times in non beaconed trials
- probe_trial_number :
- avg_spike_per_bin_b :
- avg_spike_per_bin_nb :
- avg_spike_per_bin_p :
- b_spike_number :
- nb_spike_number :
plots per cluster (curated)
(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.
(2) 2 autocorrelograms - the first shows time between -10 and 10 milliseconds, the second shows between -250 and 250.
(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.
(4) Spike rasters
(5) Spike rate vs location
(6) Stop raster
