BlechCTA

Scripts used for Christina's Ph.D. thesis on neural mechanisms underlying learned and non-learned gaping. Order of operations:

Initial set-up:

Run each session recording through Pytau, Blech_EMG_Classifier, and BlechClust packages before running this package.
Run create_tau_dict.py # combines tau, spike trains, and num cps from cp model into dictionary
Run combine_classifier_files.py # puts all Blech EMG Classifier segments files into one dataframe
Run initialize_dataframe.py # Adds important metrics to dataframe

Behavior-only analyses:

Run extract_emg_from_transition.py # calculates frequency of each behavior across trials, plots, and saves artifacts for each session
Run extract_emg_from_transition_aggregate.py # plots frequency of each behavior across trials, averages across all sessions

Name		Name	Last commit message	Last commit date
Latest commit History 20 Commits
LFP_analyses		LFP_analyses
Bottle_Test_Plot.py		Bottle_Test_Plot.py
README.md		README.md
combine_classifier_files.py		combine_classifier_files.py
cp_gape_duration_correlation.py		cp_gape_duration_correlation.py
cp_sudden_change_sigmoid_fit.py		cp_sudden_change_sigmoid_fit.py
cp_sudden_change_sigmoid_fit_final.py		cp_sudden_change_sigmoid_fit_final.py
cp_timing_around_state_change.py		cp_timing_around_state_change.py
create_tau_dict.py		create_tau_dict.py
extract_emg_from_transition.py		extract_emg_from_transition.py
extract_emg_from_transition_agg_one_test_day.py		extract_emg_from_transition_agg_one_test_day.py
extract_emg_from_transition_aggregate.py		extract_emg_from_transition_aggregate.py
gape_bout_duration_single_test_day.py		gape_bout_duration_single_test_day.py
gape_metrics_cta_vs_ctrl.py		gape_metrics_cta_vs_ctrl.py
gaping_around_CS_plots.py		gaping_around_CS_plots.py
neural_behavior_correlations_aggregate.py		neural_behavior_correlations_aggregate.py
pal_taste_analyses.py		pal_taste_analyses.py
qhcl_cp_times.py		qhcl_cp_times.py

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