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data_and_figures
talks/serts
tests
README
bliss_random_no3rule_halfITI_halfTO.sce
code_responses.m
get_andrei_index.m
get_average_go_nogo_bias.m
get_lick_rate_during_stim.m
get_multisession_data.m
lick_rate_stim_script.m
lucas_discrim_airpuff_4contrast.sce
motivated_time.m
plot_andrei_index.m
plot_expected_lick_curve.m
plot_lick_curve.m
plot_lick_rate_across_session.m
plot_lick_rate_during_stim.m
plot_lick_rate_per_block.m
plot_longitudinal_performance.m
plot_nogo_FA_by_contrast.m
plot_old_v_new_lick_curves.m
plot_old_v_new_performance.m
plot_old_v_new_weights.m
read_logfile.m
save_data.m
window_lick_rates.m

README

How to do stuff:

* Save today's data locally
  1) save_data(subject 1, rig #, subject 2, rig #, etc.)

* Save past day's data locally
  1) save_data(subject 1, rig #, etc., date)
  
* Plot lick rate across session
  1) plot_lick_rate_across_session(subject, test_date)
     A) [words codes times] = read_logfile(logfile)
     B) W = window_lick_rates(times, words)

* Plot average d' by contrast across all sessions, all animals
  1) plot_old_v_new_performance('d')
     A) [words codes times] = read_logfile(logfile)
     B) W = window_lick_rates(times, words)
     C) [words codes times] = motivated_time(W, words, codes, times)
     D) responses = code_responses(words, codes)

* Plot hit rate minus FA rate across all sessions, all animals
  1) plot_old_v_new_performance('h')

* Plot percent of trials with licks by signed contrast
  1) plot_old_v_new_lick_curves
     A) [words codes times] = read_logfile(logfile)
     B) W = window_lick_rates(times, words)
     C) [words codes times] = motivated_time(W, words, codes, times)
     D) responses = code_responses(words, codes)

* Plot GLM weights in two figures, one for contrast and the other for the rest
  1) plot_old_v_new_weights
     A) [words codes times] = read_logfile(logfile)
     B) W = window_lick_rates(times, words)
     C) [words codes times] = motivated_time(W, words, codes, times)
     D) responses = code_responses(words, codes)
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