spiketools.stats.trials.compare_pre_post_activity

spiketools.stats.trials.compare_pre_post_activity(trial_spikes, pre_window, post_window, avg_type='mean')

Compare pre & post activity, computing the average firing rates and a t-test comparison.

Parameters:

trial_spikeslist of 1d array

Spike times per trial, in seconds.

pre_window, post_windowlist of [float, float]

The pre and post event time window, in seconds, to compute firing rate across.

avg_type{‘mean’, ‘median’}

The type of averaging function to use.

Returns:

avg_pre, avg_postfloat

The average firing rates pre and post event.

t_val, p_valfloat

The t value and p statistic for a t-test comparing pre and post event firing.

Examples

Compute the average firing rates pre & post event as well as a t-test comparison:

>>> trial_spikes = [np.array([-0.3, -0.2, 0.4, 0.5, 0.6, 0.75]),
...                 np.array([-0.15, 0.45, 1.0, 1.2, 1.6]),
...                 np.array([-0.45, -0.12, -0.02, 0.32, 0.67, 0.89, 1.7])]
>>> pre_window, post_window = [-0.5, 0], [0, 2]
>>> compare_pre_post_activity(trial_spikes, pre_window, post_window, avg_type='mean')
(4.0, 2.0, 1.7320508075688774, 0.22540333075851657)