Outdated egg!
This is an egg for CHICKEN 4, the unsupported old release. You're almost certainly looking for the CHICKEN 5 version of this egg, if it exists.
If it does not exist, there may be equivalent functionality provided by another egg; have a look at the egg index. Otherwise, please consider porting this egg to the current version of CHICKEN.
picnic
An implementation of a description language for models of geometric neural connectivity.
TOC »
Usage
picnic [options...] [input files ...]
Documentation
The main idea of Picnic is to combine experimental data on cell morphology and synthetic cell geometry. Cell geometry is described as sets of 3D points and can be one of the following:
- Neurolucida data
- cylinders described by start point, end point, diameter
- Synthetic geometry
- points along a line, polynomial curve, or angular displacement
Cell placement can be defined by rectangular grids, regular tilings (e.g. bricks or hexagons), random point distributions. Connectivity currently is simply projections based on Euclidean distances between cell objects.
Layers
In Picnic terminology, a layer describes the placement of cell objects in 3D space. The placement is determined by a set of points, which can be generated by one of the following methods:
- sampling from typical distributions such as uniform or exponential
- point coordinates loaded from a file
- Regular grid defined by spacing in x, y and z direction
- Regular 2D tiling, such as hexagons or bricks with a given side length. In this case, position x and y coordinates are determined by the center point of each generated tile, and the z coordinate is set to zero.
A layer is defined by a point set described by one of the methods above, and one or more cell objects that are to be placed at positions determined by the point set. If there are less cell objects than there are points in the point set, then the cell objects are copied until an object is placed at each point.
Cell objects
A cell object consists of a bounding box and a set of connection points. The connection points can be loaded from a Neurolucida file, or can be sampled from the trajectory of a parametric curve.
The set of points that belong to a cell object can be further divided into compartments, e.g. dendrites and axon, which can be later used when specifying connectivity.
In addition, random perturbations can be applied to the points of a cell or one of its compartments.
Projections
Once layers are defined with the different cell types, connectivity is specified in Picnic as projections between layers.
The single type of projection currently supported by Picnic is based on Euclidean distances between the points of the different cell object. Given a maximum distance, Picnic can determine all cell points in two layers that are close enough to be considered connected.
Model description language
The following constructs comprise the model description language:
INPUT {ID} | {ID} [AS {LOCAL-ID}] [FROM {NAMESPACE}] ...Declares one or several imported quantities. If the optional AS parameter is given, then the quantity is imported as {LOCAL-ID}. If the optional FROM parameter is given, then the quantity is imported from namespace {NAMESPACE}.
OUTPUT {ID}Declares that an existing quantity be exported.
CONST {ID} = {EXPR}Declares a constant quantity (its value will be computed at declaration time).
FUN {ID} ( {ARG-ID} ... ) {EXPR}Declares a function (a parameterized expression with no free variables).
{ID} = {EXPR}Declares an assigned quantity (an expression that can refer to other quantities in the system).
PROCESS ( {ID} ) = (GENERATOR {F}) (npts {N})Declares a process quantity. {F} is the generating function that returns the parametric curves for this process.
COMPONENT ( TYPE {ID} ) ( NAME {ID} ) {ELEMENTS} )Declares a system component (a quantity that can contain other quantities).
Examples
picnic-model
GL
config PFlength
config PFlengthSlope ;; how much the PF length decreases with depth
;; PFs deeper in the molecular layer tend to be shorter
;; (Pichitpornchai et al, 1994)
config MLdepth
config PCLdepth
config numAxonGolgi ;; GoC axonal dimensions
config GoC_Axon_Xmin
config GoC_Axon_Xmax
config GoC_Axon_Ymin
config GoC_Axon_Ymax
config GoC_Axon_Zmin
config GoC_Axon_Zmax
config GoC_nDendML ;; GoC # of apical dendrites
config GoC_nDendGL ;; GoC # of basolateral dendrites
config GoC_Ad_nseg ;; GoC apical dendrites number of segments
config GoC_Ad_nsegpts ;; GoC apical dendrites number of points per segment
config GoC_Bd_nseg
config GoC_Bd_nsegpts
config GoC_PhysApicalDendH
config GoC_PhysApicalDendR
config GoC_Atheta_min
config GoC_Atheta_max
config GoC_Atheta_stdev config GoC_PhysBasolateralDendH
config GoC_PhysBasolateralDendR
config GoC_Btheta_min
config GoC_Btheta_max
config GoC_Btheta_stdev
config AAtoGoCzone
config PFtoGoCzone
config GoCtoGoCzone
config GoCtoGoCgapzone
config GoCxrange
config GoCyrange
const xExtent = GoCxrange
const yExtent = GoCyrange
component (type local-cell-forest) (name GC)
component (type layout) (name GCTcoordinates)
s = (PointsFromFile ("GCTcoordinates1.dat"))
output s component (type pointset) (name GC)
s = (PointsFromFile ("GCcoordinates.dat"))
output s component (type pointset) (name GCT)
s = (PointsFromFile ("GCTcoordinates.dat"))
output s component (type section) (name AscendingAxons)
fun f (gid origin)
let ((dX 0) (dY 0) (dZ (neg (PCLdepth))))
LineSegment (origin dX dY dZ)
const n = 1
p (u) = (generator f) (npts 4)
output u n
component (type section) (name ParallelFibers)
component (type perturbation)
fun pf (gid origin init)
let ((period (randomUniform ((PFlength / 50.0) ~ (PFlength / 30.0) ~ init)))
(phase (randomUniform (0.0 ~ 10.0 ~ init))))
;; Harmonic (amplitude period phase npts)
Harmonic (0 5.0 period phase 50)
const n = 2
p (s) = (generator pf) (initial (randomInit (randomSeed ())))
output s n
component (type perturbation)
fun pf (gid origin init)
let ((period (randomUniform ((PFlength / 4.0) ~ (PFlength / 10.0) ~ init)))
(phase (randomUniform (0.0 ~ 10.0 ~ init))))
;; Harmonic (amplitude period phase npts)
Harmonic (1 0.5 period phase 50)
const n = 2
p (s) = (generator pf) (initial (randomInit (randomSeed ())))
output s n
fun f (gid origin)
let ((z (pointCoord (2 origin))) ;; depth of this PF
(dX (PFlengthSlope * (z - MLdepth) + (PFlength / 2))) (dY 0) (dZ 0))
LineSegment (origin dX dY dZ)
fun g (gid origin)
let ((z (pointCoord (2 origin))) ;; depth of this PF
(dX (PFlengthSlope * (z - MLdepth) + (PFlength / 2))) (dY 0) (dZ 0))
LineSegment (origin ~ (neg (dX)) ~ dY ~ dZ)
const n = 1
;; process u grows in the positive X direction
;; process v grows in the negative X direction
p (u) = (generator f) (sampler (polynomial 0.003 0.0085 0.0085 )) (npts 200)
p (v) = (generator g) (sampler (polynomial 0.003 0.0085 0.0085 )) (npts 200)
output u n v n
component (type cell-forest) (name GoC)
component (type layout) (name GolgiCoordinates)
s = (PointsFromFile ("GoCcoordinates.dat"))
output s
component (type section) (name BasolateralDendrites)
fun f (gid origin init)
let (
(thetaDeg (randomNormal (GoC_Btheta_min GoC_Btheta_stdev init)))
(theta ((PI / 180) * thetaDeg))
(dX (GoC_PhysBasolateralDendR * cos (theta)))
(dY (GoC_PhysBasolateralDendR * sin (theta)))
(dZ GoC_PhysBasolateralDendH)
)
LineSegment (origin dX dY dZ)
fun g (gid origin init)
let (
(thetaDeg (randomNormal (GoC_Btheta_max GoC_Btheta_stdev init)))
(theta ((PI / 180) * thetaDeg))
(dX (GoC_PhysBasolateralDendR * cos (theta)))
(dY (GoC_PhysBasolateralDendR * sin (theta)))
(dZ GoC_PhysBasolateralDendH)
)
LineSegment (origin dX dY dZ)
const n = 1
segp (u) = (generator f) (initial (randomInit (randomSeed ()))) (nsegs GoC_Bd_nseg) (nsegpts GoC_Bd_nsegpts)
segp (v) = (generator g) (initial (randomInit (randomSeed ()))) (nsegs GoC_Bd_nseg) (nsegpts GoC_Bd_nsegpts)
output u n v n component (type section) (name ApicalDendrites)
fun f (gid origin init)
let (
(thetaDeg (randomNormal (GoC_Atheta_min GoC_Atheta_stdev init)))
(theta ((PI / 180) * thetaDeg))
(dX (GoC_PhysApicalDendR * cos (theta)))
(dY (GoC_PhysApicalDendR * sin (theta)))
(dZ GoC_PhysApicalDendH)
)
LineSegment (origin dX dY dZ)
fun g (gid origin init)
let (
(thetaDeg (randomNormal (GoC_Atheta_max GoC_Atheta_stdev init)))
(theta ((PI / 180) * thetaDeg))
(dX (GoC_PhysApicalDendR * cos (theta)))
(dY (GoC_PhysApicalDendR * sin (theta)))
(dZ GoC_PhysApicalDendH)
)
LineSegment (origin dX dY dZ)
const n = 1
segp (u) = (generator f) (initial (randomInit (randomSeed ()))) (nsegs GoC_Ad_nseg) (nsegpts GoC_Ad_nsegpts)
segp (v) = (generator g) (initial (randomInit (randomSeed ()))) (nsegs GoC_Ad_nseg) (nsegpts GoC_Ad_nsegpts)
output u n v n component (type section) (name Axons)
const n = numAxonGolgi
fun f (gid origin init)
let (
(dX (randomUniform (GoC_Axon_Xmin GoC_Axon_Xmax init)))
(dY (randomUniform (GoC_Axon_Ymin GoC_Axon_Ymax init)))
(dZ (randomUniform (GoC_Axon_Zmin GoC_Axon_Zmax init)))
)
LineSegment (origin dX dY dZ)
p (u) = (generator f) (initial (randomInit (randomSeed ())))
output u n
component (type projection)
input (GC from cell-forests) (GoC from cell-forests)
r = PFtoGoCzone
set source = (section GC ParallelFibers)
set target = (section GoC ApicalDendrites)
PFtoGoC = (SegmentProjection (r source target))
output PFtoGoC
component (type projection)
input (GC from cell-forests) (GoC from cell-forests)
r = AAtoGoCzone
set source = (section GC AscendingAxons)
set target =
union
section GoC ApicalDendrites
section GoC BasolateralDendrites
AAtoGoC = (SegmentProjection (r source target))
output AAtoGoC
component (type projection)
input (GoC from cell-forests)
r = GoCtoGoCzone
set source = (section GoC Axons)
set target = (population GoC)
GoCtoGoC = (Projection (r source target))
output GoCtoGoC component (type projection)
input (GoC from cell-forests)
r = GoCtoGoCgapzone
set source = (population GoC)
set target = (population GoC)
GoCtoGoCgap = (Projection (r source target))
output GoCtoGoCgapAbout this egg
Author
Version history
- 1.0
- Initial release
License
Copyright 2012-2015 Ivan Raikov. This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. A full copy of the GPL license can be found at <http://www.gnu.org/licenses/>.