Data and code for Crombie et al. "Spiking activity in the visual thalamus is coupled to pupil dynamics across temporal scales"
To generate figures from already processed data, copy the *.pkl
data files out of data/original_cooked/
and data/original_raw
into data/
and then run the corresponding cells in the figures_*.ipynp
Jupyter notebooks. Note that notebook cells should be run in order to avoid variable name conflicts. Figures will by default be stored in the figures/
folder, which also contains sub-folder
Note : Because many of the analyses involve randomization (e.g. comparison to random permutations of the data), the original figures may only be exactly reproduced by using the data files from the original_cooked
folder.
Data for this project is stored as "pickled" Pandas DataFrame objects. The "raw" data, including pupil_*.pkl
, spikes_*.pkl
, ball_*.pkl
, and trials_*.pkl
, are minimally-processed data to be used in further analyses.
To re-generate the processed ("cooked") data, run the corresponding *.py
file with the desired arguments. The positional argument e_name
specifies the experiment name, and is required for all scripts. It can be one of
Note : Spontaneous and sparse noise experiments are generally analyzed together, but the analysis scripts need to be run separately for each experiment type.
Other arguments may include:
Spike type : --spk_type -s
Time ranges : --tranges -t