Evolving synaptic plasticity with an evolutionary cellular development model.

Since synaptic plasticity is regarded as a potential mechanism for memory formation and learning, there is growing interest in the study of its underlying mechanisms. Recently several evolutionary models of cellular development have been presented, but none have been shown to be able to evolve a range of biological synaptic plasticity regimes. In this paper we present a biologically plausible evolutionary cellular development model and test its ability to evolve different biological synaptic plasticity regimes. The core of the model is a genomic and proteomic regulation network which controls cells and their neurites in a 2D environment. The model has previously been shown to successfully evolve behaving organisms, enable gene related phenomena, and produce biological neural mechanisms such as temporal representations. Several experiments are described in which the model evolves different synaptic plasticity regimes using a direct fitness function. Other experiments examine the ability of the model to evolve simple plasticity regimes in a task -based fitness function environment. These results suggest that such evolutionary cellular development models have the potential to be used as a research tool for investigating the evolutionary aspects of synaptic plasticity and at the same time can serve as the basis for novel artificial computational systems.

Inevitable evolutionary temporal elements in neural processing: a study based on evolutionary simulations.

Recent studies have suggested that some neural computational mechanisms are based on the fine temporal structure of spiking activity. However, less effort has been devoted to investigating the evolutionary aspects of such mechanisms. In this paper we explore the issue of temporal neural computation from an evolutionary point of view, using a genetic simulation of the evolutionary development of neural systems. We evolve neural systems in an environment with selective pressure based on mate finding, and examine the temporal aspects of the evolved systems. In repeating evolutionary sessions, there was a significant increase during evolution in the mutual information between the evolved agent's temporal neural representation and the external environment. In ten different simulated evolutionary sessions, there was an increased effect of time-related neural ablations on the agents' fitness. These results suggest that in some fitness landscapes the emergence of temporal elements in neural computation is almost inevitable. Future research using similar evolutionary simulations may shed new light on various biological mechanisms.

Examining emergence of functional gene clustering in a simulated evolution.

Recent research suggests that rather than being random, gene order may be coupled with gene functionality. These findings may be explained by mechanisms that require physical proximity such as co-expression and co-regulation. Alternatively, they may be due to evolutionary-dynamics forces, as expressed in genetic drift or linkage disequilibrium. This paper proposes a biologically plausible model for evolutionary development. Using the model, which includes natural selection and the development of gene networks and cellular organisms, the co-evolution of recombination rate and gene functionality is examined. The results presented here are compatible with previous biological findings showing that functionally related genes are clustered. These results imply that evolutionary pressure in a complex environment is sufficient for the emergence of gene order that is coupled with functionality. They shed further light on the mechanisms that may cause such gene clusters.