DendriticTree

class braintools.conn.DendriticTree(tree_structure, branch_targeting, distance_dependence=True, weight=None, delay=None, **kwargs)

Dendritic tree connectivity patterns with branch-specific targeting.

This models realistic dendritic connectivity considering the branching structure of dendritic trees and branch-specific connection rules.

Parameters:

• tree_structure (Dict) – Description of dendritic tree structure.

• branch_targeting (Dict) – Rules for targeting specific branches (e.g., {‘proximal’: 0.8, ‘distal’: 0.2}).

• distance_dependence (bool) – Whether to include distance dependence within the tree.

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

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

Examples

>>> tree_structure = {
...     'basal': {'n_branches': 5, 'branch_length': 200 * u.um},
...     'apical': {'n_branches': 1, 'branch_length': 600 * u.um}
... }
>>> dend_tree = DendriticTree(
...     tree_structure=tree_structure,
...     branch_targeting={'proximal': 0.8, 'distal': 0.2}
... )

generate(pre_size, post_size, pre_positions=None, post_positions=None, **kwargs)

Generate dendritic tree connections.

Return type:

ConnectionResult