Parameters and distributions

This page describes the format of the expected parameters and distributions used by NeuroTS.

Parameters

Schema

TMD parameters

The parameters used to synthesize new cells
type	object
properties
apical_dendrite	Specific parameters for apicals
	oneOf	Empty object
		Neurite
axon	Specific parameters for axons
	oneOf	Empty object
		Neurite
basal_dendrite	Specific parameters for basals
	oneOf	Empty object
		Neurite
diameter_params	Parameters used to generate the diameters
	type	object
	oneOf	properties
		method	The method used to synthesize the diameters
			type	string
			enum	external, default, uniform
		additionalProperties	True
		properties
		method	The method used to synthesize the diameters
			type	string
			not	enum	external, default, uniform
		additionalProperties	False
grow_types	Select which tree types will be generated
	type	array
	items	type	string
		enum	basal_dendrite, apical_dendrite, axon
pia_direction	Pia direction
	Point
origin	Defines the center of the soma, from which the growth starts
	Point

Empty object

An object without any property
type	object
additionalProperties	False

Null object

A null object
type	null

Neurite

The properties of a neurite
type	object
properties
apical_distance	The apical distance (NEVER USED)
	type	number
bias	The branches that are major inherit a bias towards the target orientation of the tree. Bias defines the weight. If bias = 0 the growth is isotropic, and if bias = 1 it goes straight along orientation.
	type	number
	maximum	1
	minimum	0
bias_length	The branches that are major inherit a bias towards the target orientation of the tree. Bias_length defines which branches are major and therefore will have a bias. Only branches of size greater than (bias_length * barcode length) are biased.
	type	number
	minimum	0
branching_method	Defines the method that will be used for the bifurcation angles
	type	string
growth_method	Defines the method that will be used for the growth
	type	string
	enum	tmd, tmd_gradient, tmd_apical, axon_trunk, trunk
major_termination_length	Termination length of major branches, to use mostly for main axon to connect to long-range axon
	type	number
	minimum	0
has_apical_tuft	Select True if the tree is an apical and is expected to have a tuft
	type	boolean
metric	Defines the metric for the growth (only path distance is currently available)
	type	string
modify	A modification function to be applied to a TMD (barcode) before synthesis starts
	oneOf	type	object
		Null object
num_seg	Number of segments (used when an alternative to TMD, basic growth algorithm is chosen)
	type	integer
	minimum	0
orientation	Defines the target orientation of a tree, as it emanates from the soma
	anyOf	Null object
		type	array
		items	The orientation vector
			Point
		type	object
		properties
		mode	The orientation mode to use
			type	string
		values	oneOf	Null object
				type	object
				properties
				orientations	type	array
					items	The orientation vector
						Point
				additionalProperties	False
				type	object
				properties
				primary_orientation	The primary orientation vector
					Point
				additionalProperties	False
				type	object
				properties
				additionalProperties	False
				direction	type	object
					properties
					additionalProperties	False
					mean	oneOf	type	number
							maximum	3.1416
							minimum	0
							type	array
							items	type	number
								maximum	3.1416
								minimum	0
					std	oneOf	type	number
							minimum	0
							type	array
							items	type	number
								minimum	0
				additionalProperties	False
				type	object
				properties
				form	Form of the 3d angle fit
					type	string
				params	type	array
					items	The fit parameters
				additionalProperties	False
		additionalProperties	False
radius	[Deprecated] Defines the radius of the tree. If default diameter is chosen, diameter will be constant. If external diametrization is used, the radius value is not important
	type	number
	minimum	0
randomness	Controls the percentage of randomness within a section of a neuron. 0.0: the path is straight, 1.0: the path is a random walk. Randomness + targeting + history should be normalized to 1.
	type	number
	maximum	1
	minimum	0
step_size	Defines the distribution from which the step size is sampled
	type	object
	properties
	norm	The normal distribution used
		type	object
		properties
		mean	The mean of the distribution
			type	number
			minimum	0
		std	The std of the distribution
			type	number
			minimum	0
		additionalProperties	False
	additionalProperties	False
targeting	Controls the percentage of targeting (complementary to the randomness). 1.0: the path is straight, 0.0: the path is a random walk. Randomness + targeting + history should be normalized to 1.
	type	number
	maximum	1
	minimum	0
tree_type	Defines the tree index that will be written to the file
	type	integer
trunk_absolute_orientation	Orientation of trunks emerging from the soma (on x-y plane).
	type	boolean
additionalProperties	False

neurite_type

Type of neurite
type	string
enum	basal_dendrite, apical_dendrite, axon

Point

A point with 3 coordinates
type	array
maxItems	3
minItems	3

Example

 1{"apical_dendrite": {"branching_method": "directional",
 2            "growth_method": "tmd",
 3            "has_apical_tuft": true,
 4            "metric": "path_distances",
 5            "modify": null,
 6            "orientation": {"mode": "use_predefined", "values": {"orientations": [[0.0, 1.0, 0.0]]}},
 7            "randomness": 0.32,
 8            "targeting": 0.24,
 9            "tree_type": 4,
10            "step_size": {"norm":{"mean":1.0, "std":0.2}}},
11"axon": {},
12"basal_dendrite": {"branching_method": "bio_oriented",
13          "growth_method": "tmd",
14          "metric": "path_distances",
15          "modify": null,
16          "orientation": {"mode": "sample_pairwise_angles", "values": null},
17          "randomness": 0.32,
18          "targeting": 0.24,
19          "tree_type": 3,
20          "step_size": {"norm":{"mean":1.0, "std":0.2}}},
21"grow_types": ["basal_dendrite", "apical_dendrite"],
22"origin": [0.0,
23           0.0,
24           0.0],
25"diameter_params": {"method": "uniform",
26                    "basal_dendrite": 0.6,
27                    "apical_dendrite": 0.6,
28                    "axon": 0.6}}

Distributions

Schema

TMD distributions

type	object
properties
apical_dendrite	Specific distributions for apicals
	oneOf	Empty distribution
		Neurite distribution
axon	Specific distributions for axons
	oneOf	Empty distribution
		Neurite distribution
basal_dendrite	Specific distributions for basals
	Neurite distribution
diameter	The diameter specifications
	type	object
	additionalProperties	True
	oneOf	properties
		method	type	string
			enum	external
		additionalProperties	True
		properties
		method	type	string
			enum	default
		apical_dendrite	type	array
			items	type	number
		basal_dendrite	type	array
			items	type	number
		axon	type	array
			items	type	number
		additionalProperties	False
		properties
		apical	Neurite diameter distribution
		axon	Neurite diameter distribution
		basal	Neurite diameter distribution
		method	type	string
			not	enum	external, default
		apical_dendrite	Neurite diameter distribution
		basal_dendrite	Neurite diameter distribution
		additionalProperties	False
soma	Specific distributions for the somas
	type	object
	properties
	size	The distribution of soma sizes
		type	object
		properties
		norm	type	object
			properties
			mean	The mean of the distribution
				type	number
			std	The std of the distribution
				type	number
			additionalProperties	False
		additionalProperties	False
	additionalProperties	False
additionalProperties	False

Data distribution

A distribution based on data bins and weights
type	object
properties
data	The data used for the distribution
	type	object
	properties
	bins	The bins
		type	array
		items	type	number
	weights	The weights
		type	array
		items	type	number
	additionalProperties	False
additionalProperties	False

Empty distribution

An object without any property
type	object
additionalProperties	False

Neurite diameter distribution

The diameter distributions of a type of neurite
type	object
properties
Rall_ratio	type	number
siblings_ratio	type	number
taper	type	array
	items	type	number
term	type	array
	items	type	number
trunk	type	array
	items	type	number
trunk_taper	type	array
	items	type	number
additionalProperties	False

Neurite distribution

The distributions of a type of neurite
type	object
properties
filtration_metric	type	string
num_trees	The data distribution used for the number of trees to synthesize
	Data distribution
min_bar_length	The minimum bar length, used for checking input parameters consistency
	type	number
	minimum	0
persistence_diagram	The persistence diagram
	type	array
	items	type	array
		items	type	array
			items	type	number
trunk	oneOf	No trunk distribution provided
		type	null
		The distributions used to synthesize the trunk using orientation deviation
		type	object
		properties
		absolute_elevation_deviation	The data distribution used for the absolute elevation deviation
			Data distribution
		azimuth	The uniform distribution used for the azimuth
			type	object
			properties
			uniform	The properties of the uniform distribution
				type	object
				properties
				max	type	number
				min	type	number
				additionalProperties	False
			additionalProperties	False
		orientation_deviation	The data distribution used for the orientation deviation
			Data distribution
		pia_3d_angles	The data distribution used for the 3d angles wrt pia direction
			Data distribution
		apical_3d_angles	The data distribution used for the 3d angles wrt apical direction
			Data distribution
		additionalProperties	False
additionalProperties	False

Example

  1{
  2    "apical_dendrite": {
  3        "filtration_metric": "path_distances",
  4        "min_bar_length": 1.0,
  5        "num_trees": {
  6            "data": {
  7                "bins": [
  8                    1
  9                ],
 10                "weights": [
 11                    1
 12                ]
 13            }
 14        },
 15        "persistence_diagram": [
 16            [
 17                [
 18                    290,
 19                    95,
 20                    0,
 21                    0,
 22                    1.0471975511965976,
 23                    0
 24                ],
 25                [
 26                    150,
 27                    100,
 28                    0,
 29                    0,
 30                    1.0471975511965976,
 31                    0
 32                ],
 33                [
 34                    170,
 35                    50,
 36                    0,
 37                    0,
 38                    1.0471975511965976,
 39                    0
 40                ],
 41                [
 42                    145,
 43                    29,
 44                    0,
 45                    0,
 46                    1.0471975511965976,
 47                    0
 48                ],
 49                [
 50                    300,
 51                    0,
 52                    NaN,
 53                    NaN,
 54                    NaN,
 55                    NaN
 56                ]
 57            ]
 58        ],
 59        "trunk": {
 60            "azimuth": {
 61                "uniform": {
 62                    "max": 0.0,
 63                    "min": 3.141592653589793
 64                }
 65            },
 66            "orientation_deviation": {
 67                "data": {
 68                    "bins": [
 69                        0.016666666666666663
 70                    ],
 71                    "weights": [
 72                        1
 73                    ]
 74                }
 75            },
 76            "absolute_elevation_deviation": {
 77                "data": {
 78                    "bins": [
 79                        0
 80                    ],
 81                    "weights": [
 82                        1
 83                    ]
 84                }
 85            }
 86        }
 87    },
 88    "axon": {},
 89    "basal_dendrite": {
 90        "filtration_metric": "path_distances",
 91        "min_bar_length": 1.0,
 92        "num_trees": {
 93            "data": {
 94                "bins": [
 95                    4
 96                ],
 97                "weights": [
 98                    1
 99                ]
100            }
101        },
102        "persistence_diagram": [
103            [
104                [
105                    224.08653783450782,
106                    10.891041859252676,
107                    0.06392198549840433,
108                    -0.27205559604985874,
109                    -0.5365480370168811,
110                    0.8312206407245757
111                ],
112                [
113                    196.61363089528587,
114                    2.674821865134806,
115                    -0.5220708314792457,
116                    -0.7471831099566546,
117                    3.6071418547490937,
118                    0.589636578046099
119                ],
120                [
121                    265.9921913001744,
122                    0,
123                    NaN,
124                    NaN,
125                    NaN,
126                    NaN
127                ]
128            ]
129        ],
130        "trunk": {
131            "azimuth": {
132                "uniform": {
133                    "max": 0.0,
134                    "min": 3.141592653589793
135                }
136            },
137            "orientation_deviation": {
138                "data": {
139                    "bins": [
140                        0.09586683335089932,
141                        0.39001954178950027,
142                        1.174426764292436,
143                        1.566630375543904,
144                        2.9393430149240416
145                    ],
146                    "weights": [
147                        4,
148                        3,
149                        1,
150                        1,
151                        2
152                    ]
153                }
154            },
155            "absolute_elevation_deviation": {
156                "data": {
157                    "bins": [
158                        0
159                    ],
160                    "weights": [
161                        1
162                    ]
163                }
164            }
165        }
166    },
167    "soma": {
168        "size": {
169            "norm": {
170                "mean": 9.024144162609812,
171                "std": 3.5462697985669935
172            }
173        }
174    },
175    "diameter": {
176        "method": "uniform"
177    }
178}