Prebuilt measures

NeuroSTR includes a huge library of prebuilt measures some new, others already presented in the scientific literature or implemented in existing neuroanatomy tools.

Prebuilt measures are organized in the same way as Selectors, by their input element type: all measure functions that take either a single node or a node set as input fall into the Node category. You can find more details about each measure by clicking on their name.

You might notice (and it seems odd) that there are very few Neurite and Neuron measures, but it is on purpose. Since we can use Selectors and Aggregators along with measures to create new measures, we focus on defining "low level" measures, that can be use to create "high level measures". Check the Create a measure to see a simple example of this.

Node Measures

Branch Measures

Neurite Measures

Neuron Measures

Generic Measures

L-measure Measures

L-measure comparison

Node measures

X, Y, Z components

Function: node_x, node_y, node_z = [](const Node& n) -> float

Description: Returns the x, y, z component of the given Node position.

Output: Real number.

Radius, diameter

Function: node_radius,node_diameter = [](const Node& n) -> float

Description: Returns the radius/diameter of the given Node.

Output: Real number.

Details: The Hillman taper rate defined as the ratio of the difference between first and last node diameters and the first node diameter. If the branch's root exists, it is taken as the first node. If we assume non-decreasing diameters, the hillman taper rate should be non-negative. Note that it will throw an exception for a Branch with no nodes.

Centrifugal order

Function: node_order = [](const Node& n) -> int

Description: Returns the centrifugal order of the Branch that the Node belongs to.

Output: Integer. Centrifugal order

Details: See Branch order

Distance to parent

Function: node_length_to_parent,node_length_to_parent_border = [](const Node& n) -> float

Description: Returns the euclidean distance between the given Node and its parent. the border variant subtract the radius of both nodes to the distance.

Output: Real Number.

Details: Please note that the border variant might return negative values if the sum of radius is greater than the distance

Distance to root

Function: node_distance_to_root = [](const Node& n) -> float

Description: Computes the euclidean distance between the given Node and the root of the Neurite that the node belongs to.

Output: Non negative real Number.

Details: If the Neurite doesn't have a root node, the distance is computed to its first Node

Distance to soma

Function: node_distance_to_soma = [](const Node& n) -> float

Description: Computes the euclidean distance between the given Node and the closest [Soma] point in the neuron.

Output: Non negative real Number.

Details: If the Neuron doesn't have a [Soma], the the method returns the distance between the given node and the point (0,0,0).

Path length to root

Function: node_path_to_root = [](const Node& n) -> float

Description: Computes the length of the path from the given Node to the root of the Neurite that the node belongs to.

Output: Non negative real Number.

Compartment volume

Function: node_volume = [](const Node& n) -> float

Description: Computes the volume of the truncated cone from the given Node to its parent.

Output: Non negative real Number.

Details: The aforementioned cone has the radius of the parent at one end and the radius of the given Node at the other. If the parent of the given Node cannot be determined, it returns 0.

Compartment surface

Function: node_compartment_surface = [](const Node& n) -> float

Description: Computes the surface of the truncated open cone from the given Node to its parent.

Output: Non negative real Number.

Details: The aforementioned cone has the radius of the parent at one end and the radius of the given Node at the other. If the parent of the given Node cannot be determined, it returns 0.

Compartment section area

Function: node_compartment_section_area = [](const Node& n) -> float

Description: Computes section area as the area of the circle with radius the average of the given Node and its parent radius.

Output: Non negative real Number.

Details: If the parent of the given Node cannot be determined, the circle radius is just the given node radius.

Local Hillman taper rate

Function: node_segment_taper_rate_hillman = [](const Node& n) -> float

Description: Computes the Hillman taper rate between the given Node and its parent

Output: Non negative real Number.

Details: If the parent of the given Node cannot be determined, the taper rate is 0. The Hillman taper rate is given by: (parent.radius-node.radius)/parent.radius

Local Burker taper rate

Function: node_segment_taper_rate_burker = [](const Node& n) -> float

Description: Computes the Burker taper rate between the given Node and its parent

Output: Non negative real Number.

Details: If the parent of the given Node cannot be determined, the taper rate is 0. The Burker taper rate is given by: (parent.radius-node.radius)/distance(parent,node)

Non axis aligned minimum box volume

Function: box_volume = [](const const_node_iterator& b, const const_node_iterator& e) -> double

Description: Computes the minimum box volume for the given Node set. The box is not restricted to be axis-aligned.

Output: Non negative real Number.

Details: The box volume is computed by applying a PCA over the position of the nodes, and then computing the axis-aligned box volume on the rotated positions.

Vector to parent

Function: node_parent_vector = [](const Node& n) -> point_type

Description: Computes the vector from the given Node to its parent.

Output: 3D Vector

Details: If the parent of the given Node cannot be determined, the method returns the null vector.

Local bifurcation angle

Function: node_local_bifurcation_angle = [](const Node& n) -> float

Description: If the given node is a bifurcation, it returns the local bifurcation angle.

Output: Angle in radians [0,pi)

Details: If the node is not a bifurcation node it returns 0. See Branch local bifurcation angle

Local elongation angle

Function: node_local_elongation_angle = [](const Node& n) -> float

Description: If the given Node is an elongation, i.e. it only has one descendant, returns the oriented angle between the vector form the parent to the given Node and the vector from the Node to its descendant.

Output: Angle in radians

Details: If the node is not an elongation node it returns 0. The reference vector for 3D angle orientation is the Neuron up vector (by default it is the (0,0,1) vector)

Local orientation

Function: node_local_orientation = [](const Node& n) -> std::pair<float, float>

Description: It computes the values of azimuth and elevation for the given Node using the orthonormal basis span by the vector from the parent and the neuron up vector as reference.

Output: Pair of angles in radians (-pi,pi). Azimuth and elevation

In terminal branch

Function: node_in_terminal_segment = [](const Node& n) -> bool

Description: Returns true if the Branch that the node belongs to is a terminal branch

Output: Boolean value. True if the node's branch is terminal.

Distance to closest segment

Function: segment_distance_to_closest = [](const Node& n) -> bool

Description: Returns the minimum distance between the segment [parent,node] to any other segment in the neuron.

Output: Non negative value. If the parent of the given Node cannot be determined, the method returns the highest value representable in a float.

Distance to closest segment

Function: segment_distance_to_closest = [](const Node& n) -> bool

Description: Returns the minimum distance between the segment [parent,node] to any other segment in the neuron.

Output: Non negative value. If the parent of the given Node cannot be determined, the method returns the highest value representable in a float.

Fractal dimension

Function: node_set_fractal_dim = [](const const_node_iterator& b, const const_node_iterator& e) -> float

Description: Computes the fractal dimension of the given set of nodes (assuming that they are a sequence).

Output: Fractal dimension, real value between 1 (straight line) and 2 (random walk)

Details: See L-measure fractal dimension documentation.

Branch measures

Hillman taper rate

Function: taper_rate_hillman = [](const Branch& b) -> float

Description: Computes the Hillman taper rate for the given Branch

Output: real number. Hillman taper rate.

Details: The Hillman taper rate defined as the ratio of the difference between first and last node diameters and the first node diameter. If the branch's root exists, it is taken as the first node. If we assume non-decreasing diameters, the hillman taper rate should be non-negative. Note that it will throw an exception for a Branch with no nodes.

(first.diameter - last.diameter) / first.diameter

Burker taper rate

Function: taper_rate_burker = [](const Branch& b) -> float

Description: Computes the Burker taper rate for the given Branch

Output: real number. Burker taper rate.

Details: The Burker taper rate defined as the ratio of the difference between the first and last node diameters and the euclidean distance between these two same nodes. If the branch's root exists, it is taken as the first node. If we assume non-decreasing diameters, the hillman taper rate should be non-negative. Note that it will throw an exception for a Branch with no nodes.

(first.diameter - last.diameter) / distance(first,last)

Tortuosity

Function: tortuosity = [](const Branch& b) -> float

Description: Computes the branch tortuosity value.

Output: Non-negative real number. Greater or equal than 1.

Details: The tortuosity value is defined as the ratio of the total length of the branch and the euclidean distance between the first and the last nodes. If the branch's root exists, it is taken as the first node.

branch.length / distance(first,last)

Node count

Function: branch_size = [](const Branch &b) -> int

Description: Returns the number of nodes in the Branch.

Output: Non-negative integer

Details: This returns the number of nodes that are part of the Branch excluding the root. In our data model, the branch's root node belongs to the parent branch (or to the soma) and not to the branch itself.

Branch index

Function: branch_index = [](const Branch &b) -> unsigned int

Description: Returns the index of the given branch as daughter of the parent branch.

Output: Non-negative integer

Details: This returns 0 for the first branch, 1 for the second and so on. If the Neurite has been sorted, the first and last branches are ordered by they azimuth, in other words the rightmost and leftmost branches correspond to the first and last position respectively.

Centrifugal order

Function: branch_order = [](const Branch &b) -> int

Description: Returns the centrifugal order of the given Branch

Output: Non-negative integer

Details: Branch orders counts the number of bifurcations in the path from the given Branch to the root of the Neurite. That is, the root Branch has a centrifugal order of 0, it's daughters have a centrifugal order of 1, and so on.

Child diameter ratio

Function: child_diam_ratio = [](const Branch& b) -> float

Description: Returns the child-diameter ratio of the daughters of the given Branch], the ratio of the daughter branches first node's diameters.

Output: Real number

Details: If the number of descendants of the given Branch is not equal to 2, the measure always return 0.

branch.child[0].first.diameter / branch.child[1].first.diameter

Parent-Child diameter ratio

Function: parent_child_diam_ratio = [](const Branch& b) -> std::pair<float,float>

Description: Returns the ratio between the diameter of the last node of the given branch and the first nodes of the daughter branches.

Output: Real number pair

Details: If the number of descendants of the given Branch is not equal to 2, the measure always return the pair (0,0).

(branch.child[0].first.diameter/branch.last.diameter, branch.child[1].first.diameter/branch.last.diameter)

Partition asymmetry

Function: partition_asymmetry = [](const Branch& b) -> float

Description: The partition asymmetry first computes the number of terminal points in the left/right subtrees, n1 and n2 respectively. Then computes the following quantity as the partition asymmetry value:

|n1-n2| / (n1 + n2 - 2)|

Output: Non negative real number

Details: If the number of descendants of the given Branch is not equal to 2, the measure always returns -1.

Rall's power fit

Factory function: auto rall_power_fit_factory(float min = 0 , float max = 5)

Function: (const Branch &b) -> float

Description: Computes the best value for the parameter r in the range [min,max] that minimizes the following quantity:

(branch.diameter^r - branch.child[0].diameter^r - branch.child[1].diameter^r)^2

Output: Real number - best fit value

Details: If the number of descendants of the given Branch is not equal to 2, the measure always returns -1.

Pk measure

Factory function: auto pk_factory(float r)

Function: (const Branch &b) -> float

Description: Given the parameter r, computes the quantity:

(branch.child[0].diameter^r - branch.child[1].diameter^r)/branch.diameter^r

Output: Real number

Details: If the number of descendants of the given Branch is not equal to 2, the measure always returns -1.

Note: pk_fit_factory(float min = 0 , float max = 5) just applies this same measure where r is computed using Rall's power fit.

Hillman threshold

Function: hillman_threshold = [](const Branch &b) -> float

Description: Computes the Hillman threshold value for the given Branch bifurcation. The Hillman threshold is the weighted sum of parent and daugther diameters (0.5,0.25,0.25). Hillman threshold only applies to pre-terminal branches (i.e to terminal bifurcation nodes).

0.25*(branch.child[0].diameter + branch.child[1].diameter) + 0.5*branch.diameter

Output: Real number

Details: If the number of descendants of the given Branch is not equal to 2 or it is not a pre-terminal branch the measure returns -1.

Local bifurcation angle

Function: local_bifurcation_angle = [](const Branch &b) -> float

Description: Computes the bifurcation amplitude, measured as the shortest planar angle between the vectors from the bifurcation node (the last node of the given branch) to the first nodes of the daughter branches.

Output: Real number. Angle in radians [0,pi]

Details: If the number of descendants of the given Branch is not equal to 2 it returns -1. NAN values might appear if null segments are present.

Remote bifurcation angle

Function: remote_bifurcation_angle = [](const Branch &b) -> float

Description: Computes the bifurcation amplitude, measured as the shortest planar angle between the vectors from the bifurcation node (the last node of the given branch) to the last nodes of the daughter branches.

Output: Real number. Angle in radians [0,pi]

Details: If the number of descendants of the given Branch is not equal to 2 it returns -1. NAN values might appear if null segments are present.

Local tilt angle

Function: local_tilt_angle = [](const Branch &b) -> float

Description: Computes the tilt angle at the last node bifurcation point. Tilt angle is the smallest angle between the branch director vector and the vectors form the bifurcation point to the first node of the daughter branches.

Output: Real number. Angle in radians [0,pi]

Details: If the number of descendants of the given Branch is not equal to 2 it returns -1. NAN values might appear if null segments are present.

Remote tilt angle

Function: remote_tilt_angle = [](const Branch &b) -> float

Description: Computes the tilt angle at the last node bifurcation point. Tilt angle is the smallest angle between the branch director vector and the vectors form the bifurcation point to the last node of the daughter branches.

Output: Real number. Angle in radians [0,pi]

Details: If the number of descendants of the given Branch is not equal to 2 it returns -1. NAN values might appear if null segments are present.

Local plane vector

Function: local_plane_vector = [](const Branch &b) -> point_type

Description: Computes the normal vector to the plane defined by the vectors from the root to the first node of the daughter branches.

Output: Plane normal vector

Details: If the branch don't have a sibling branch, it returns the null vector.

Remote plane vector

Function: remote_plane_vector = [](const Branch &b) -> point_type

Description: Computes the normal vector to the plane defined by the vectors from the branch root and the last node of the daughter branches.

Output: Plane normal vector

Details: If the branch don't have a sibling branch, it returns the null vector.

Local torque angle

Function: local_plane_vector = [](const Branch &b) -> point_type

Description: Computes the angle between the branch local plane vector and the daughter branches plane vector.

Output: Angle in radians [0,pi)]

Details: If the number of daughter branches is not equal to 2, returns -1. NAN values might appear if the tree is malformed. See Local plane vector function.

Remote torque angle

Function: local_plane_vector = [](const Branch &b) -> point_type

Description: Computes the angle between the branch local plane vector and the daughter branches plane vector.

Output: Angle in radians [0,pi)]

Details: If the number of daughter branches is not equal to 2, returns -1. NAN values might appear if the tree is malformed. See Local plane vector function.

Length

Function: branch_length = [](const Branch &b) -> float

Description: Computes the branch total length.

Output: Non negative real number - branch length.

Intersects

Factory: branch_intersects_factory(bool ignore_radius = false)

Function: (const Branch &b ) -> std::string

Description: Checks if the given Branch intersects with any other Branch in the Neuron, and returns its id in that case. If ignore_radius flag is set to true, the radius of each compartment is taken into account when checking intersections.

Output: Id of the intersecting branch + "@ Neurite: id". An empty string otherwise.

Details: The function pre-checks the possible intersection by checking the bounding box of each pair of [Branches]. If the boxes intersect, then computes the branch-branch distance (that is, the segment-segment distance for each pair of segments).

Vertex type

Function: vertex_type = [](const Branch& b) -> float

Description: Returns the bifurcation type. There are three possible values: 2: (primary bifurcation) ends in two terminals; 1: (secondary bifurcation) one terminal and one bifurcating child; 0 (tertiary bifurcation) two bifurcating children.

Output: An integer: 0, 1, or 2.

Neurite measures

Root is soma

Function: root_is_soma

Description: Returns true if the Neurite is attached to the soma

Output: Boolean flag. True if the Neurite root is a soma point (or it is inside the soma)

Details: root_is_soma measure just calls the Neurite.root_is_soma() member function which checks if the root branch of the neurite has a root node.

Neuron measures

Neuron has soma

Function: has_soma

Description: Returns true if the neuron has at least one soma node.

Output: Boolean flag. True if the [Soma] is defined in the Neuron

Details: has_soma measure just calls the Neuron.has_soma() member function which checks if the number of soma points in the neuron is greater than 0.

Neurite count

Function: neuron_neurite_count

Description: Returns the number of Neurites in the Neuron.

Output: Non-negative integer value. The number of Neurites (of any type) in the Neuron.

Neurite type count

Function: neuron_type_counter (factory method)

Parameters: type - NeuriteType - Neurite type.

Description: Returns the number of Neurites in the Neuron of certain type.

Instances:

  • neuron_dendrite_counter Counts the number of dendrites in the Neuron
  • neuron_axon_counter Counts the number of axons in the Neuron
  • neuron_apical_counter Counts the number of apical dendrites in the Neuron

Output: Non-negative integer value. The number of Neurites of type type in the Neuron.

Soma surface area

Function: soma_surface

Description: Returns the [Soma] surface area under spherical shape assumption.

Output: Non-negative real value. The computed soma surface area.

Details: If there are several soma points, the computed area is the surface of the sphere centered at the soma barycenter with radius the average distance from the barycenter to the external border of the sphere. Otherwise, for a sigle-point [Soma], the sphere surface area is computed.

L-measure measures

Soma surface

Function: soma_surface

Description: Computes the soma surface area under spherical shape assumption.

Output: Non-negative real number. Soma surface area. Zero if the neuron don't have soma points.

Details: If there are several soma points, the computed area is the surface of the sphere centered at the soma barycenter with radius the average distance from the barycenter to the external border of the sphere. See soma_surface measure.

Number of stems

Function: n_stems

Description: Returns the number of stems (what we call neurites) in the neuron.

Output: Non-negative integer. Number of stems/neurites.

Details: See neuron_neurite_count measure.

Number of bifurcations

Function: n_bifs

Description: Returns the number of bifurcation points in the neuron.

Output: Non-negative integer. Number of bifurcations.

Number of branches

Function: n_branch

Description: Counts the number of branches in the neuron.

Output: Non-negative integer. Number of branches.

Number of terminal tips

Function: n_tips

Description: Counts the number of terminal tips in the neuron.

Output: Non-negative integer. Terminal tips count.

Width, Height and Depth

Function: width, height, depth

Description: Computes the neuron range length for the x,y and z axis respectively.

Output: Non-negative real number.

Diameter

Function: diameter

Description: Computes the Summary statistics for the Node diameter value.

Output: Diameter Summary stats (sum, max, min, median, mean and sd).

Details: See Node diameter measure.

Diameter power

Function: diameter_pow

Description: Computes the Summary statistics for the Node diameter value power to 1.5.

Output: Diameter power Summary stats (sum, max, min, median, mean and sd).

Details: See Node diameter pow measure.

Length

Function: length

Description: Computes the Summary statistics for compartment lengths.

Output: Compartment length Summary stats (sum, max, min, median, mean and sd).

Details: See Node length to parent measure.

Branch length

Function: branch_pathlength

Description: Computes the Summary statistics for branch lengths.

Output: Branch length Summary stats (sum, max, min, median, mean and sd).

Details: See Branch length measure.

Surface

Function: surface

Description: Computes the Summary statistics for compartment surface area.

Output: Compartment surface Summary stats (sum, max, min, median, mean and sd).

Details: See Node compartment surface measure.

Branch surface

Function: branch_surface

Description: Computes the Summary statistics for branch surface area.

Output: Branch surface area Summary stats (sum, max, min, median, mean and sd).

Details: Branch surface is computed as the sum of compartment surfaces. See Node compartment surface measure.

Compartment section area

Function: section_area

Description: Computes the Summary statistics for compartment section area.

Output: Compartment section area Summary stats (sum, max, min, median, mean and sd).

Details: See Node compartment section area measure.

Compartment volume

Function: volume

Description: Computes the Summary statistics for compartment volume.

Output: Compartment volume Summary stats (sum, max, min, median, mean and sd).

Details: See Node compartment volume measure.

Branch Volume

Function: branch_volume

Description: Computes the Summary statistics for branch compartment volume.

Output: Branch volume Summary stats (sum, max, min, median, mean and sd).

Details: Branch volume is computed as the sum of compartment surfaces. See Node compartment volume measure.

Distance to root

Function: euc_distance

Description: Computes the Summary statistics for the euclidean distance of each Node to the Neurite root.

Output: Distance Summary stats (sum, max, min, median, mean and sd).

Details: See Node root distance measure.

Path length to root

Function: path_distance

Description: Computes the Summary statistics for the path distance of each Node to the Neurite root.

Output: Distance Summary stats (sum, max, min, median, mean and sd).

Details: See Node path distance measure.

Branch centrifugal order

Function: branch_order

Description: Computes the Summary statistics for the branch centrifugal order of each Branch in the neuron.

Output: Centrifugal order Summary stats (sum, max, min, median, mean and sd).

Details: See Branch centrifugal order measure.

Node Terminal degree

Function: terminal_degree

Description: Computes the Summary statistics for the terminal degree centrifugal order of each Node in the neuron. The terminal degree is the number of terminal tips in the subtree of the given Node.

Output: Terminal degree Summary stats (sum, max, min, median, mean and sd).

Branch Terminal degree

Function: branch_terminal_degree

Description: Computes the Summary statistics for the terminal degree centrifugal order of each Branch in the neuron. The terminal degree is the number of terminal tips in the subtree of the given Branch.

Output: Terminal degree Summary stats (sum, max, min, median, mean and sd).

Taper 1: Burker taper rate

Function: taper_1

Description: Computes the Summary statistics for the branch Burker taper rate Branch in the neuron for every Branch in the Neuron.

Output: Taper rate Summary stats (sum, max, min, median, mean and sd).

Details: See Burker taper rate measure.

Taper 2: Hillman taper rate

Function: taper_2

Description: Computes the Summary statistics for the branch Hillman taper rate Branch in the neuron for every Branch in the Neuron.

Output: Taper rate Summary stats (sum, max, min, median, mean and sd).

Details: See Hillman taper rate measure.

Contraction

Function: contraction

Description: Computes the Summary statistics for the Branch contraction, i.e. its tortuosity for every Branch in the Neuron.

Output: Contraction Summary stats (sum, max, min, median, mean and sd).

Details: See Tortuosity measure.

Fragmentation

Function: fragmentation

Description: Computes the Summary statistics for the Branch fragmentation, i.e. its number of nodes for every Branch in the Neuron.

Output: Fragmentation Summary stats (sum, max, min, median, mean and sd).

Details: See Branch size measure.

Daughter ratio

Function: daughter_ratio

Description: Computes the Summary statistics for the Branch daughter ratio, i.e. the ratio of the diameters of its daughter branches for every non-terminal Branch in the Neuron.

Output: Daughter ratio Summary stats (sum, max, min, median, mean and sd).

Details: See Child diameter ratio measure.

Partition asymmetry

Function: partition_asymmetry

Description: Computes the Summary statistics for the Branch partition asymmetry value, i.e. the ratio between the number of terminals in the left-subtree and the right-subtree , for every non-terminal Branch in the Neuron.

Output: Partition asymmetry Summary stats (sum, max, min, median, mean and sd).

Details: See Partition asymmetry measure.

Rall's power

Function: rall_power

Description: Computes the Summary statistics for the Rall's power fitted value for every non-terminal Branch in the Neuron.

Output: Rall's power fitted value Summary stats (sum, max, min, median, mean and sd).

Details: See Rall's power fit measure.

Pk fitted value

Function: pk

Description: Computes the Summary statistics for the Pk with factor given by the fitted value returned by the Rall's power fit measure for every non-terminal Branch in the Neuron.

Output: Pk value Summary stats (sum, max, min, median, mean and sd).

Details: See Rall's power fit and Pk factory measures.

Pk classic and squared

Function: pk_classic, pk2

Description: Computes the Summary statistics for the Pk with factors 1.5 and 2 respectively for every non-terminal Branch in the Neuron.

Output: Pk value Summary stats (sum, max, min, median, mean and sd).

Details: See Pk factory measure.

Local bifurcation amplitude

Function: bif_ampl_local

Description: Computes the Summary statistics for the bifurcation angle computed w.r.t. the firs node in the daughter branches for every non-terminal Branch in the Neuron.

Output: Bifurcation amplitude (angle in radians) Summary stats (sum, max, min, median, mean and sd).

Details: See Local bifurcation angle measure.

Remote bifurcation amplitude

Function: bif_ampl_remote

Description: Computes the Summary statistics for the bifurcation angle computed w.r.t. the last nodes in the daughter branches for every non-terminal Branch in the Neuron.

Output: Bifurcation amplitude (angle in radians) Summary stats (sum, max, min, median, mean and sd).

Details: See Remote bifurcation angle measure.

Local bifurcation tilt

Function: bif_tilt_local

Description: Computes the Summary statistics for the bifurcation tilt angle computed w.r.t. the first nodes in the daughter branches for every non-terminal Branch in the Neuron.

Output: Tilt angle in radians Summary stats (sum, max, min, median, mean and sd).

Details: See Local tilt angle measure.

Remote bifurcation tilt

Function: bif_tilt_remote

Description: Computes the Summary statistics for the bifurcation tilt angle computed w.r.t. the last nodes in the daughter branches for every non-terminal Branch in the Neuron.

Output: Bifurcation tilt angle in radians Summary stats (sum, max, min, median, mean and sd).

Details: See Remote tilt angle measure.

Local bifurcation torque

Function: bif_torque_local

Description: Computes the Summary statistics for the bifurcation torque angle computed w.r.t. the first nodes in the daughter branches for every non-terminal Branch in the Neuron.

Output: Torque angle in radians Summary stats (sum, max, min, median, mean and sd).

Details: See Local torque angle measure.

Remote bifurcation tilt

Function: bif_torque_remote

Description: Computes the Summary statistics for the bifurcation torque angle computed w.r.t. the last nodes in the daughter branches for every non-terminal Branch in the Neuron.

Output: Bifurcation torque angle in radians Summary stats (sum, max, min, median, mean and sd).

Details: See Remote torque angle measure.

Terminal bifurcation diameter

Function: last_parent_diam

Description: Computes the Summary statistics for the diameter of every terminal bifurcation (see Terminal bifurcation selector) Node in the Neuron.

Output: Node diameter Summary stats (sum, max, min, median, mean and sd).

Hillman threshold

Function: hillman_threshold

Description: Computes the Summary statistics for the Hillman threshold value (see Hillman threshold measure) for every pre-terminal Branch in the Neuron.

Output: Hillman threshold value Summary stats (sum, max, min, median, mean and sd).

Details: See Hillman threshold measure.

Fractal dimension

Function: fractal_dim

Description: Computes the Summary statistics for the Fractal dimension of every Branch in the Neuron.

Output: Fractal dimension Summary stats (sum, max, min, median, mean and sd).

Details: See Fractal dimension measure.

L-measure comparison

This compares 17 L-Measure analyses to the corresponding ones computed with NeuroSTR. The table shows the mean absolute difference and correlation across on 219 interneurons (the names correspond to the L-Measure ones). Measures with an absolute correlation < 0.90 are marked as different.

For most of the measures, NeuroSTR produces identical or very similar results as L-Measure. Differing measures include fractal dimension, and torque and tilt angles. As far as tilt angles, the definition used by NeuroSTR seems to differ form the one used by L-Measure, as NeuroSTR produces significantly smaller tilt angles than L-Measure. PathDistance_min, for example, differs because L-Measure seems to be computing the distance to soma centroid, and not to the point of insertion.

abs difference correlation different
Partition_asymmetry_min 0.000000e+00 X
Partition_asymmetry_avg 2.071100e-03 0.996100276045597
Partition_asymmetry_std 7.656900e-03 0.907571434440884
Partition_asymmetry_max 0.000000e+00 X
Partition_asymmetry_sum 1.200151e+00 0.999083527492007
PathDistance_min 2.229969e+01 X
PathDistance_avg 2.001725e+01 0.991257984928102
PathDistance_std 6.976029e-01 0.999907974623442
PathDistance_max 2.230283e+01 0.998855843934241
PathDistance_sum 2.816866e+05 0.99922990822852
Fractal_Dim_min 3.160400e-03 0.0206401479615145 X
Fractal_Dim_avg 1.236650e-02 0.410283477603493 X
Fractal_Dim_std 1.034990e-02 0.785722143517184 X
Fractal_Dim_max 1.070795e-01 0.581901774924155 X
Fractal_Dim_sum 3.844008e+01 0.979548213398901
Branch_pathlength_min 5.446470e-01 0.708340638736405 X
Branch_pathlength_avg 2.324426e-01 0.999865047347315
Branch_pathlength_std 6.052271e-01 0.999786069805852
Branch_pathlength_max 2.728793e-01 0.999998964420045
Branch_pathlength_sum 6.211538e+01 0.999984856890684
Contraction_min 1.197640e-02 0.977796130877257
Contraction_avg 1.021690e-02 0.97321722383137
Contraction_std 4.501100e-03 0.986251109426759
Contraction_max 4.993800e-03 0.477191281053891 X
Contraction_sum 3.084918e+00 0.999757237623208
EucDistance_min 1.349360e+00 0.988231220230445
EucDistance_avg 1.823260e+00 0.999863574895347
EucDistance_std 7.403589e-01 0.999898926332369
EucDistance_max 1.728592e+00 0.999977217689101
EucDistance_sum 6.910249e+04 0.99979683332156
Length_min 7.839590e-02 0.8273460933385 X
Length_avg 2.148606e-01 0.998762273938329
Length_std 9.202530e-02 0.993449609351132
Length_max 9.703300e-03 0.999994727485554
Length_sum 6.369182e+01 0.999984572724984
Branch_Order_min 0.000000e+00 X
Branch_Order_avg 4.141417e-01 0.97069802899676
Branch_Order_std 2.137369e-01 0.986986520821249
Branch_Order_max 1.050228e-01 0.998969212978679
Branch_Order_sum 7.898101e+04 0.673317766087749 X
Bif_torque_remote_min 1.680708e+00 0.635288359081423 X
Bif_torque_remote_avg 4.272049e+01 0.0404260940147207 X
Bif_torque_remote_std 2.587815e+01 0.108875636009112 X
Bif_torque_remote_max 8.639793e+01 0.218415684125337 X
Bif_torque_remote_sum 6.806988e+03 0.987680908722341
Bif_ampl_remote_min 6.683836e-01 0.948920995214031
Bif_ampl_remote_avg 1.783731e+00 0.989652715694246
Bif_ampl_remote_std 1.164879e+00 0.9882689021774
Bif_ampl_remote_max 2.317163e+00 0.890147511797299 X
Bif_ampl_remote_sum 2.761723e+02 0.998837863523185
Bif_tilt_remote_min 1.949893e+01 0.134134833363253 X
Bif_tilt_remote_avg 8.376762e+01 -0.473003077459945 X
Bif_tilt_remote_std 1.209846e+01 0.390476990326114 X
Bif_tilt_remote_max 7.490481e+01 -0.0163546264278658 X
Bif_tilt_remote_sum 1.336028e+04 0.926173733334739
Bif_torque_local_min 5.472301e+00 -0.0414314037376772 X
Bif_torque_local_avg 5.194249e+01 0.0278312934989923 X
Bif_torque_local_std 2.301028e+01 0.0592057638788328 X
Bif_torque_local_max 8.810073e+01 0.0752406964607671 X
Bif_torque_local_sum 8.028468e+03 0.00506177323461263 X
Bif_tilt_local_min 1.237795e+02 -0.0473856576332252 X
Bif_tilt_local_avg 1.422379e+02 -0.185367299328921 X
Bif_tilt_local_std 1.475418e+01 0.111155845900793 X
Bif_tilt_local_max 7.678624e+01 X
Bif_tilt_local_sum 1.611524e+04 0.955729654829031
N_bifs_sum 1.574247e+02 0.999960965731527