Usage

Running the code

The project provides two command line tools: one to run the simulations and another to evaluate them. The commands can be run directly from the command line, without needing to import any Python modules.

Running simulation

To run a simulation, use this command:

poetry run py_simulate [options]

After running the simulation, the resulting data is saved in the output/<model_name> folder, and the generated plots are saved in the plots/<model_name> folder.

Running evaluation

To run the evaluation, use this command:

poetry run py_evaluate

After running the evaluation, the resulting plots are saved in the plots folder.

Arguments ([options])

By default, the commands use parameters from the following configuration file: configs/model_params.yml.

You can modify this YAML file to change the default parameters. Alternatively, you can provide the following arguments to the commands. They will override the default parameters.

arg name	type (+ options)	default	help
--n	int	1	number of simulations to run
--model_name	str	"Simulated macro EEG model"	name of the model
--nodes	str (a list of labels separated by semicolon)	"frontal lobe; parietal lobe; occiptal lobe; temporal lobe; thalamus"	brain areas where the nodes are placed (according to Julich brain labels)
--relay_station	str (a label or "none")	"none"	brain area to use as a relay station (according to Julich brain labels or ‘none’)
--custom_connectivity	bool	True	whether to use custom connectivity (from connectivity_weights.csv) or not
--sample_rate	int	1000	sample rate
--t_lags	int	300	lagged time in ms
--t_secs	int	500	simulation time in seconds
--t_burnit	int	10	number of seconds to delete to ensure model convergence
--noise_color	str	"white"	color of the noise (‘white’ or ‘pink’)
--std_noise	float	1950	scalar standard deviation of the noise (effectively controls the scale of the output)
--dist_shape	float	-0.25	shape param for the lag distribution.
--dist_scale	float	0.09	scale param for the lag distributions
--dist_location	float	0.25	location param for the lag distributions
--dist_trunc_percent	float	0.0	tail truncation percentile for the lag distributions

As you can see from the --custom_connectivity argument, you can specify a custom connectivity weights matrix in the configs/connectivity_weights.csv file. Use either a symmetrical of an upper triangular matrix (it will be converted to symmetrical). The diagonal values are ignored.