Demetris Kennes

Contents Aims Method(The Model) Genetic Component Cellular Component Evolution Test and results Conclusion Questions?

Aims There 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 Component Genes are responsible for developing proteins during genetic transcription Special 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

Evolution Several 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 Results Five 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

Conclusion Initial step in the study of critical periods The model was deliberately straightforward and so suffers from numerous limitations The model is completely deterministic The size of the perturbation window is extremely large The study must be broadened to other developmental processes It has provided evidence of a correlation among critical periods and developmental rate of change It is a first step to the goal of a general technique for calculating critical periods in developmental systems

QUESTIONS ?