Models structure

DeNSE offers the chance to set different models for neuronal outgrowth. Models are structured in order to allow the user to enable or discard some specific properties and then set the relevant biological parameters or use the defaults. The table of parameters can be found at the end of this page, under the Parameters subsection.

What are models in DeNSE?

For now, models are mostly associated to growth cones. There are also branching models, but these are not yet covered in the documentation.

A full growth model is composed by a combination of three modules:

• an extension component, modeling the

Making a new growth model

To add a new model to DeNSE, you need to decide on two things:

• a name, for instance “great model”

• the type of feature it implements among:

  • deciding how much the growth cone will grow (extension)

  • setting the probability of going into each of the filopodial direction (steering)

  • selecting the actual direction in which the growth cone will go next (direction selection).

For this example, our “great model” will implement a new way of steering the growth cone.

Create the files

The C++ files containing the code for the new model must be placed in src/models. Since we’re creating a steering model, we will name them steering_great_model.hpp and steering_great_model.cpp (replace of course steering with extension or direction_select if your model deals with those instead).

Create the class

Inside these files, we will create the class GreatSteeringModel following the same structure as visible in the other files containing existing models. This means that our class:

• inherits from SteeringModel

• defines all the functions mentioned in steering_interface.hpp

Tell the simulator about the new model

Full growth models are automatically generated by combining all possible modules into a extention/steering/direction-selection triplets.

This is performed by the python file src/models/models_generator.py.

To add a new model the, you must:

1. include it in the associated methods list (here steering_methods) as ModelComponent(method="great-model", filename="steering_great_model.hpp", classname="GreatSteeringModel")

2. add an associated abbreviation in abbrev, for instance "great-model": "gm"

3. add steering_great_model.hpp and steering_great_model.cpp to the list of files in src/models/CMakeLists.txt

And that’s it, you’re done! Your new model is now available in DeNSE and should appear in the list returned by get_models().

Creating neurons and setting parameters

In order to simulate a system we need to initialize it, and, likely, we would like to set our own parameters to override the default described in previous section. Let’s assume we have 1 only neuron, how to manage many neurons and sets of parameters is described in another section.

Each neuron can be created with a different growth cone model, and in every moment these parameters can be overwritten, but it’s impossible to change the model, while is possible to turn off/on the neurite branching model (uniform, actin wave, van pelt) It’s possible to set the same parameters for dendrites and axon or to specify them, passing a dictionary with the respective name “axon_params” or “dendrite_params” to the create_neurons() function. This can also be done during the simulation with set_object_properties()

Parameters are set when kernel is initiated and the process is recursive. Each neuron is created with a StatusMap, which is a dictionary with all the non-default parameters, each neuron then set the parameters all its neurites, which set the parameters for all its growth cone. A similar process happen when status is set during the simulation.

The models of DeNSE are implemented in C++

class Neuron : public std::enable_shared_from_this<Neuron>

Implementation of the main container Neuron for the creation of neuronal networks.

class Neurite : public std::enable_shared_from_this<Neurite>

Neurite class,.

class growth::ActinWave : public std::enable_shared_from_this<ActinWave>

Public Functions

ActinWave(TNodePtr targetNode, double actin_content, NeuritePtr)

ActinWave is a single ActinWave element propagating in the neurite. ActinWave requires the ‘Neuron’ supports the AW models Each ‘ActinWave’, for each step can:

• propagate and keep walking up the neurite Branch

• reinforce a GrowthCone

Parameters

• NodePtr – Node is the Node leading the segment of neurite where AW is.

• double – DistanceToTarget is the distance to such a node.

class growth::Node : public growth::TopologicalNode

Public Functions

virtual void set_position(const BPoint&) final override

Set the position of the node.

Parameters

Point – xy: x and y of the node.

class growth::GrowthCone : public growth::TopologicalNode, public std::enable_shared_from_this<GrowthCone>

Subclassed by growth::GrowthConeModel< ElType, SteerMethod, DirSelMethod >

Public Functions

GrowthCone(const GrowthCone &copy)

Copy constructor for GrowthCone.

virtual void set_position(const BPoint &pos) final override

Set the position of the node.

Parameters

Point – xy: x and y of the node.

class growth::Branch

The Branch class is responsible for storing the spatial points representing the neurite in space. Each Branch instance is associated to a unique TopologicalNode and thus stores the continuous set of points that defines its trajectory over time.

Public Functions

Branch(const BPoint &origin)

Create a branch with initial position and if necesary an initial length.

Branch()

default constructor

double module_from_points(const BPoint&)

Get the module of length between the point and the last in the array.

Parameters

BPoint& –

void set_first_point(const BPoint &xy, double distanceToSoma)

set first element of Branch container

Parameters

• xy – the points where the branch starts

• distanceToSoma – the distance from soma at branch start.

void resize_tail(stype new_size)

resize the head of the branch: first point invariate

Parameters

id_x – the length of the new branch container

BranchPtr resize_head(stype id_x) const

Create a new branch from tail of this Branch: tail invariate.

Parameters

id_x – the number of elements to delete from the begin of the container

Returns

void retract()

Remove one point from the container.

void append_branch(BranchPtr appended_branch)

Append a Branch to existing one.

Parameters

appended_branch – Branch to add after the last element of the existing Branch

BPoint get_last_xy() const

return the last xy

PointArray at(stype idx) const

Return a BPoint object from the ‘idx’ element of the Branch

Parameters

Defines

BRANCHING_PROBA_DEFAULT

NEURITE_DIAMETER

SOMA_RADIUS

THINNING_RATIO

MIN_DIAMETER

DIAMETER_RATIO_AVG

DIAM_RATIO_STD

DIAMETER_ETA_EXP

POLA_STRENGTH

AXON_POLA_WEIGHT

MAX_GC_NUM

MAX_ARBOR_LENGTH

DURATION_RETRACTION

FILOPODIA_MIN_NUM

FILOPODIA_FINGER_LENGTH

FILOPODIA_SUBSTRATE_AFINITY

FILOPODIA_WALL_AFFINITY

MAX_SENSING_ANGLE

ONE_DEGREE

PROBA_RETRACTION

PROBA_DOWN_MOVE

PERSISTENCE_LENGTH

SCALE_UP_MOVE

SENSING_ANGLE

SPEED_RATIO_RETRACTION

SPEED_GROWTH_CONE

WALL_AFNTY_DECAY_CST

DEFAULT_POINTS_PER_CIRCLE

MIN_FILOPODIA_FINGER_LENGTH

SRF_AVOIDANCE_FACTOR

SRF_AVOIDANCE_SCALE

SRF_RIGIDITY_FACTOR

SRF_SOMATROPIC_FACTOR

SRF_SOMATROPIC_SCALE

USE_CRITICAL

CRITICAL_USE_RATIO

CRITICAL_LEAKAGE

CRITICAL_CORRELATION

CRITICAL_VARIANCE

CRITICAL_WEIGHT_DIAMETER

CRITICAL_WEIGHT_CENTRIFUGAL

CRITICAL_ELONGATION_FACTOR

CRITICAL_ELONGATION_TH

CRITICAL_RETRACTION_FACTOR

CRITICAL_RETRACTION_TH

CRITICAL_BRANCHING_TH

CRITICAL_BRANCHING_PROBA

CRITICAL_AVAILABLE

CRITICAL_GEN_VAR

CRITICAL_GENERATED

CRITICAL_GEN_TAU

CRITICAL_DEL_TAU

CRITICAL_GEN_CORR

CRITICAL_SLOPE

CRITICAL_GC_SUPPORT

GC_SPLIT_ANGLE_MEAN

GC_SPLIT_ANGLE_STD

USE_VAN_PELT

VP_B

VP_E

VP_S

VP_T

DIAM_FRAC_LB

LATERAL_BRANCHING_ANGLE_MEAN

LATERAL_BRANCHING_ANGLE_STD

UNIFORM_BRANCHING_RATE

USE_ACTIN_WAVES

ACTIN_CONTENT

ACTIN_CONTENT_TAU

ACTIN_WAVE_SPEED

AW_GENERATION_STEP

DEFAULT_MAX_RESOL

MAX_MAX_SYN_DIST

namespace growth

namespace names

Variables

const std::string description

const std::string growth_cone_model

const std::string num_neurites

const std::string soma_radius

const std::string has_axon

const std::string axon_polarization_weight

const std::string neurite_angles

const std::string polarization_strength

const std::string random_rotation_angles

const std::string neurite_names

const std::string max_gc_number

const std::string max_arbor_length

const std::string active

const std::string initial_diameter

const std::string axon_angle

const std::string initial_branch_lenght

const std::string branching_proba_default

const std::string neurite_type

const std::string taper_rate

const std::string diameter_ratio_avg

const std::string diameter_ratio_std

const std::string diameter_eta_exp

const std::string affinity_axon_self

const std::string affinity_axon_dendrite_same_neuron

const std::string affinity_axon_soma_same_neuron

const std::string affinity_axon_axon_other_neuron

const std::string affinity_axon_dendrite_other_neuron

const std::string affinity_axon_soma_other_neuron

const std::string affinity_dendrite_self

const std::string affinity_dendrite_axon_same_neuron

const std::string affinity_dendrite_dendrite_same_neuron

const std::string affinity_dendrite_soma_same_neuron

const std::string affinity_dendrite_axon_other_neuron

const std::string affinity_dendrite_dendrite_other_neuron

const std::string affinity_dendrite_soma_other_neuron

const std::string duration_retraction

const std::string filopodia_min_number

const std::string filopodia_finger_length

const std::string filopodia_wall_affinity

const std::string max_sensing_angle

const std::string proba_down_move

const std::string proba_retraction

const std::string scale_up_move

const std::string sensing_angle

const std::string speed_ratio_retraction

const std::string substrate_affinity

const std::string points_per_circle

const std::string persistence_length

const std::string rigidity_factor

const std::string speed_decay_factor

const std::string speed_growth_cone

const std::string speed_variance

const std::string memory_dist_cut

const std::string memory_dist_exp

const std::string memory_influence

const std::string somatropic_factor

const std::string somatropic_scale

const std::string somatropic_mode

const std::string self_avoidance_factor

const std::string self_avoidance_scale

const std::string noise_amplitude

const std::string critical_pull

const std::string resource

const std::string use_critical_resource

const std::string res_use_ratio

const std::string res_leakage

const std::string res_correlation

const std::string res_variance

const std::string res_weight_diameter

const std::string res_weight_centrifugal

const std::string res_elongation_factor

const std::string res_elongation_threshold

const std::string res_retraction_factor

const std::string res_retraction_threshold

const std::string res_branching_threshold

const std::string res_branching_proba

const std::string res_neurite_available

const std::string res_neurite_variance

const std::string res_neurite_generated

const std::string res_neurite_generated_tau

const std::string res_neurite_delivery_tau

const std::string res_increase_slope

const std::string res_typical_gc_support

const std::string gc_split_angle_mean

const std::string gc_split_angle_std

const std::string use_van_pelt

const std::string B

const std::string E

const std::string S

const std::string T

const std::string diameter_fraction_lb

const std::string flpl_branching_rate

const std::string lateral_branching_angle_mean

const std::string lateral_branching_angle_std

const std::string min_branching_distance

const std::string use_flpl_branching

const std::string use_uniform_branching

const std::string uniform_branching_rate

const std::string use_uniform_split

const std::string uniform_split_rate

const std::string use_actin_waves

const std::string actin_content

const std::string actin_content_tau

const std::string actin_wave_speed

const std::string actin_freq

const std::string event_type

const std::string interval

const std::string level

const std::string observable

const std::string observables

const std::string record_to

const std::string restrict_to

const std::string targets

const signed char lateral_branching

const signed char gc_splitting

const signed char gc_deletion

const std::string num_growth_cones

const std::string interactions

const std::string max_allowed_resolution

const std::string max_synaptic_distance

const std::string print_time

const std::string resolution