DescendingDrive__Pool#

class DescendingDrive__Pool(
n: int,
poisson_batch_size: int | None = None,
timestep__ms: Quantity__ms | None = None,
process_type: str = 'poisson',
shape: float = 3.0,
)[source]#

Bases: _Pool

Container for a population of descending drive neurons.

Manages a collection of DD cells that generate spike trains using either Poisson or Gamma point processes for cortical input to spinal circuits.

Parameters:

  • n (int) – Number of descending drive neurons to create.

  • poisson_batch_size (int, optional) – Batch size for exponential threshold generation algorithm (only used when process_type=”poisson”). Higher values improve statistical accuracy but increase computation. Typical values: 16-50. Required if process_type=”poisson”, ignored if process_type=”gamma”.

  • timestep__ms (float) – Time step for simulation (ms).

  • process_type (str, optional) – Type of point process: “poisson” or “gamma”, by default “poisson”. - “poisson”: Irregular firing (CV=1.0) - “gamma”: More regular firing with CV controlled by shape parameter

  • shape (float, optional) – Shape parameter for Gamma process (only used when process_type=”gamma”), by default 3.0. Controls spike regularity: - shape=1: Poisson-like (CV=1.0) - shape=2-5: Typical cortical neuron regularity (CV=0.45-0.71) - Higher values: More regular firing (CV=1/sqrt(shape))

Methods

__init__

get_initialization_data

Return sections and their initial voltages for NEURON simulation setup.
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