hnn_core.jones_2009_model¶

hnn_core.jones_2009_model(params=None, add_drives_from_params=False, legacy_mode=False, mesh_shape=(10, 10))[source]¶

Instantiate the network model described in Jones et al. J. of Neurophys. 2009 [1]

Parameters:

paramsstr | dict | None: The path to the parameter file for constructing the network. If None, parameters loaded from default.json Default: None
add_drives_from_paramsbool: If True, add drives as defined in the params-dict. NB this is mainly for backward-compatibility with HNN GUI, and will be deprecated in a future release. Default: False
legacy_modebool: Set to False by default. Enables matching HNN GUI output when drives are added suitably. Will be deprecated in a future release.
mesh_shapetuple of int (default: (10, 10)): Defines the (n_x, n_y) shape of the grid of pyramidal cells.

Returns:

netInstance of Network object: Network object used to store

Notes

The network is composed of a square grid of pyramidal cells, arranged in two layers (L5 and L2). The default in-plane separation of the grid points is 1.0 um, and the layer separation 1307.4 um. These can be adjusted after the net is created using the set_cell_positions-method. An all-to-all connectivity pattern is applied between cells. Inhibitory basket cells are present at a 1:3-ratio.

References

[1]

Jones, Stephanie R., et al. “Quantitative Analysis and Biophysically Realistic Neural Modeling of the MEG Mu Rhythm: Rhythmogenesis and Modulation of Sensory-Evoked Responses.” Journal of Neurophysiology 102, 3554–3572 (2009).