Demetris Kennes

ContentsAimsMethod(The Model)Genetic ComponentCellular ComponentEvolutionTest and resultsConclusionQuestions?

AimsThere are two important aims:

To show that critical periods actually occur as complex dynamical systems that are mostly used in simulations of natural development

To give an extension on the positive output

Method(The Model)

Models the early stages of embryonic development

Models the development of cellular structures and cell differentiation

The Model is divided in two important components:

The genetic component

The cellular component

The genetic component - Simulates genetic expression and regulation

by use of a Genetic Regulatory Network - Artificial record factors and proteins are

synthesized, that excite and inhibit genes in the network.

The cellular component - Simulates numerous cell functions that make

it feasible to grow cellular structures collected from cells of other types

- These functions are controlled by particular proteins formed by the Genetic Regulatory Network.

Genetic ComponentGenes are responsible for developing

proteins during genetic transcriptionSpecial molecules (ribosome) decode genetic

set of laws into strings of amino acids which fold into proteins

The essential mechanism by which genes work together with one another

The synthesis of a transcription factor by one gene can affect the expression of all other genes in the genome.

Cellular Component

Cell division

Cell death

Cell Spindle and Cell Orbit

Cell signaling

Cell division: - When a cell is divided it makes a copy of itself and

places the copy one and a half radius lengths away from its centre position in the way of its mitotic spindle

- The daughter cell’s genome is initialized with the value of its mother cell.

- Inherits the mitotic spindle orientation from its mother

- This function takes 10 time steps to complete

Cell death: - The cell is removed from the universe freeing up a

location for another cell to divide into. - This function takes 5 time steps to complete.

Cell Spindle and Cell Orbit: - The cell’s mitotic spindle points to one of

twelve positions on the cell’s surface - The twelve positions are the corners of three

mutually orthogonal squares centred at the cell’s centre

- Cells that perform different functions, or the same functions at different frequencies, suitable to dissimilar dynamics in genetic regulation are considered to be different cell types

- In this model, various cell types are represented by the attention of morphogens that a cell is producing

Cell Signalling: - Principal mechanism that cells differentiate

and organize themselves into sub populations - Cells use concentration gradients of

morphogens proteins that can spread through cell membranes and encourage signal responses in other cells

- Provides spatial information to cell populations

- In this model cells can produce three morphogens

- Morphogen diffusion is simulated by using a 3D Gaussian function centred at the position of the cell

EvolutionSeveral populations are developed via the

identical fitness function, every population with a different number of genes

The fittest individuals from these populations were detached after 500 generations and used in experiments

Every individual in the population was run for 300 time-steps before its fitness was measured

Simple 3D shapes are placed in the virtual universe and passing on target cell types to them, most structures could be more precise.

The target structure was a set of 5 spheres with a gradated target type, from blue in the centre, to strong green on the outer layer

The algorithm works as follows:

1. Create an initial random population of genomes. 2. Run each individual for a fixed number of time

steps. 3. Compute all individual fitness based on a fitness

function. 4. Create a small sub-population (the elite

population) of the fittest individuals. 5. For each non-elite individual, select a random

elite and infect the non-elite with it. 6. Mutate the infected individual. 7. Repeat from step 2 for a fixed number of

generations.

Tests and ResultsFive genomes were developed, with a genome

size ranging from 13 to 17 genes All created organisms with separate layers of

cells approximately match with those specified in the fitness function

Statistically meaningful peaks do not exist in neither rate of change nor cross correlation.

The cross-correlation reveals an important correlation involving periods of sensitivity and the developmental profile

None of these peaks in rate of change are significant except a less strict threshold of one standard deviation

Explain that developmental models, do indeed exhibit critical periods.

It has provided facts of correlation between critical periods and developmental rate of change

3 of 5 organisms display critical periods around the 150th time step

There is a period of time during which the perturbation has an effect on the outcome of development

The presence of these critical periods is consistent with the working hypothesis of this paper

The cross-correlation shows significant peaks, with a lag within the window of the perturbation

Evolution has more parameters to tune for genomes, more generations are needed to form the process

Critical periods are the product of the evolutionary process on systems

ConclusionInitial step in the study of critical periods The model was deliberately straightforward and so

suffers from numerous limitationsThe model is completely deterministicThe size of the perturbation window is extremely

largeThe study must be broadened to other

developmental processesIt has provided evidence of a correlation among

critical periods and developmental rate of changeIt is a first step to the goal of a general technique

for calculating critical periods in developmental systems

QUESTIONS ?