MorphologyDistance

MorphologyDistance#

class braintools.conn.MorphologyDistance(sigma, decay_function='gaussian', compartment_mapping=None, morphology_positions=None, weight=None, delay=None, **kwargs)#

Distance-dependent connectivity based on detailed morphology.

This pattern uses the actual morphological structure of neurons to determine connection probabilities and strengths based on distances between specific compartments.

Parameters:

  • sigma (float | Quantity) – Characteristic distance scale for connectivity.

  • decay_function (str) – Distance decay function (‘gaussian’, ‘exponential’, ‘linear’).

  • compartment_mapping (Dict) – Mapping of which compartments can connect to which.

  • morphology_positions (Dict | None) – Detailed positions of compartments for each neuron.

  • weight (Initialization | float | int | ndarray | Array | Quantity | None) – Weight initialization.

  • delay (Initialization | float | int | ndarray | Array | Quantity | None) – Delay initialization.

Examples

>>> import brainunit as u
>>> morph_dist = MorphologyDistance(
...     sigma=50 * u.um,
...     decay_function='gaussian',
...     compartment_mapping={AXON: [BASAL_DENDRITE, APICAL_DENDRITE]}
... )
generate(pre_size, post_size, pre_positions=None, post_positions=None, **kwargs)[source]#

Generate morphology-based distance-dependent connections.

Return type:

ConnectionResult