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This function sets the structure of a network object, defining its layers, columns, neuron types, and local connectivity parameters. It also generates local nodes based on the specified structure.

Usage

set.network.structure(
  network,
  neuron_types = c("principal"),
  layer_names = c("layer"),
  n_layers = 1,
  n_columns = 1,
  patch_depth = 1,
  layer_height = 180,
  column_diameter = 120,
  segment_length = 20,
  layer_separation_factor = 2.5,
  column_separation_factor = 2.5,
  patch_separation_factor = 2.5,
  neurons_per_node = 10,
  local_synaptic_conductance = 1e-10,
  synaptic_neighborhood = 10
)

Arguments

network

Network object to configure.

neuron_types

Character vector giving types of neurons in the network. Known types can be accessed using print.known.celltypes(). Default is "principal", which will assign the most common neuron type for each layer, as defined in principal.neurons().

layer_names

Character vector giving names of layers in the network, ordered deepest to most superficial, e.g. c("L6", "L5", "L4", "L3", "L2", "L1").

n_layers

Integer giving number of layers in the network.

n_columns

Integer giving number of columns in the network.

patch_depth

Integer giving the number of "patches" (n_layers x n_columns sheets) in the network.

layer_height

Numeric giving height of each layer (in units specified at network creation, default unit is microns, default value is 180.0).

column_diameter

Numeric giving diameter of each column (in units specified at network creation, default unit is microns, default value is 120.0).

segment_length

Numeric giving expected length of each segment in the axonal and dendritic processes of each neuron (in units specified at network creation, default unit is microns, default value is 20.0).

layer_separation_factor

Numeric giving mean distance between layers as a fraction of layer height (default: 2.5).

column_separation_factor

Numeric giving mean distance between columns as a fraction of column diameter (default: 2.5).

patch_separation_factor

Numeric giving mean distance between network patches as a fraction of column diameter (default: 2.5).

neurons_per_node

Matrix giving number of neurons of each type per node in each layer; dimensions must match n_layers (rows) and length of neuron_types (columns).

local_synaptic_conductance

List (one entry per layer) of matrices giving synaptic conductance in millisiemens for local connections by cell-type; each matrix must have dimensions matching length of neuron_types (rows and columns).

synaptic_neighborhood

Numeric giving the radius (in microns) within which an axon node will trigger a synapse when near a dendrite node (default: 10.0).

neuron_type_valences

Numeric vector giving valences of each neuron type, e.g. c(1, -1) for excitatory and inhibitory neurons.

neuron_type_temporal_modulation

Numeric matrix giving temporal modulation time components (for modulation time in the unit_time of the network) for each neuron type: bias, step size, and count cutoff (rows as neuron types, columns as components). Will example a single value or a vector of length three.

Value

The updated network object with the specified structure and local nodes generated.