Biomedical subjects

Janet Wiles

Publications and source records attributed to Janet Wiles.

7 recordsLinked to original sources

PubMed2006

Potential role for adult neurogenesis in the encoding of time in new memories.

The dentate gyrus in the hippocampus is one of two brain regions with lifelong neurogenesis in mammals. Despite an increasing amount of information about the characteristics of the newborn granule cells, the specific contribution of their robust generation to memory formation by the hippocampus remains unclear. We describe here a possible role that this population of young granule cells may have in the formation of temporal associations in memory. Neurogenesis is a continuous process; the newborn population is only composed of the same cells for a short period of time. As time passes, the young neurons mature or die and others are born, gradually changing the identity of this young population. We discuss the possibility that one cognitive impact of this gradually changing population on hippocampal memory formation is the formation of the temporal clusters of long-term episodic memories seen in some human psychological studies.

Animals↗

PubMed2006

Hyperspace geography: visualizing fitness landscapes beyond 4D.

Human perception is finely tuned to extract structure about the 4D world of time and space as well as properties such as color and texture. Developing intuitions about spatial structure beyond 4D requires exploiting other perceptual and cognitive abilities. One of the most natural ways to explore complex spaces is for a user to actively navigate through them, using local explorations and global summaries to develop intuitions about structure, and then testing the developing ideas by further exploration. This article provides a brief overview of a technique for visualizing surfaces defined over moderate-dimensional binary spaces, by recursively unfolding them onto a 2D hypergraph. We briefly summarize the uses of a freely available Web-based visualization tool, Hyperspace Graph Paper (HSGP), for exploring fitness landscapes and search algorithms in evolutionary computation. HSGP provides a way for a user to actively explore a landscape, from simple tasks such as mapping the neighborhood structure of different points, to seeing global properties such as the size and distribution of basins of attraction or how different search algorithms interact with landscape structure. It has been most useful for exploring recursive and repetitive landscapes, and its strength is that it allows intuitions to be developed through active navigation by the user, and exploits the visual system's ability to detect pattern and texture. The technique is most effective when applied to continuous functions over Boolean variables using 4 to 16 dimensions.

Algorithms↗

PubMed2005

A gene network model for developing cell lineages.

Biological development is a remarkably complex process. A single cell, in an appropriate environment, contains sufficient information to generate a variety of differentiated cell types, whose spatial and temporal dynamics interact to form detailed morphological patterns. While several different physical and chemical processes play an important role in the development of an organism, the locus of control is the cell's gene regulatory network. We designed a dynamic recurrent gene network (DRGN) model and evaluated its ability to control the developmental trajectories of cells during embryogenesis. Three tasks were developed to evaluate the model, inspired by cell lineage specification in C. elegans, describing the variation in gene activity required for early cell diversification, combinatorial control of cell lineages, and cell lineage termination. Three corresponding sets of simulations compared performance on the tasks for different gene network sizes, demonstrating the ability of DRGNs to perform the tasks with minimal external input. The model and task definition represent a new means of linking the fundamental properties of genetic networks with the topology of the cell lineages whose development they control.

Animals↗

PubMed2003

Mapping the royal road and other hierarchical functions.

In this paper we present a technique for visualising hierarchical and symmetric, multi-modal fitness functions that have been investigated in the evolutionary computation literature. The focus of this technique is on landscapes in moderate-dimensional, binary spaces (i.e., fitness functions defined over [0,1](n), for n < or = 16). The visualisation approach involves an unfolding of the hyperspace into a two-dimensional graph, whose layout represents the topology of the space using a recursive relationship, and whose shading defines the shape of the cost surface defined on the space. Using this technique we present case-study explorations of three fitness functions: royal road, hierarchical-if-and-only-if (H-IFF), and hierarchically decomposable functions (HDF). The visualisation approach provides an insight into the properties of these functions, particularly with respect to the size and shape of the basins of attraction around each of the local optima.

Algorithms↗

PubMedDate not supplied

Towards more biological mutation operators in gene regulation studies.

Genetic regulation is often viewed as a complex system whose properties emerge from the interaction of regulatory genes. One major paradigm for studying the complex dynamics of gene regulation uses directed graphs to explore structure, behaviour and evolvability. Mutation operators used in such studies typically involve the insertion and deletion of nodes, and the insertion, deletion and rewiring of links at the network level. These network-level mutational operators are sufficient to allow the statistical analysis of network structure, but impose limitations on the way networks are evolved. There are a wide variety of mutations in DNA sequences that have yet to be analysed for their network-level effects. By modelling an artificial genome at the level of nucleotide sequences and mapping it to a regulatory network, biologically grounded mutation operators can be mapped to network-level mutations. This paper analyses five such sequence level mutations (single-point mutation, transposition, inversion, deletion and gene duplication) for their effects at the network level. Using analytic and simulation techniques, we show that it is rarely the case that nodes and links are cleanly added or deleted, with even the simplest point mutation causing a wide variety of network-level modifications. As expected, the vast majority of simple (single-point) mutations are neutral, resulting in a neutral plateau from which a range of functional behaviours can be reached. By analysing the effects of sequence-level mutations at the network level of gene regulation, we aim to stimulate more careful consideration of mutation operators in gene regulation models than has previously been given.

Algorithms↗

PubMedDate not supplied

Effective affective user interface design in games.

It is proposed that games, which are designed to generate positive affect, are most successful when they facilitate flow (Csikszentmihalyi 1992). Flow is a state of concentration, deep enjoyment, and total absorption in an activity. The study of games, and a resulting understanding of flow in games can inform the design of non-leisure software for positive affect. The paper considers the ways in which computer games contravene Nielsen's guidelines for heuristic evaluation (Nielsen and Molich 1990) and how these contraventions impact on flow. The paper also explores the implications for research that stem from the differences between games played on a personal computer and games played on a dedicated console. This research takes important initial steps towards defining how flow in computer games can inform affective design.

Affect↗

PubMedDate not supplied

Transient phenomena in learning and evolution: genetic assimilation and genetic redistribution.

Deacon has recently proposed that complexes of genes can be integrated into functional groups as a result of environmental changes that mask and unmask selection pressures. For example, many animals endogenously synthesize ascorbic acid (vitamin C), but anthropoid primates have only a nonfunctional version of the crucial gene for this pathway. It is hypothesized that the loss of functionality occurred in the evolutionary past when a diet rich in vitamin C masked the effect of the gene, and its loss effectively trapped the animals in a fruit-eating lifestyle. As a result, the complex of abilities that support this lifestyle were evolutionarily bound together, forming a multilocus complex. In this study we use evolutionary computation simulations to explore the thesis that masking and unmasking can transfer dependence from one set of genes to many sets, and thereby integrate the whole complex of genes. We used a framework based on Hinton and Nowlan's 1987 simulation of the Baldwin effect. Additional gene complexes and an environmental parameter were added to their basic model, and the fitness function extended. The simulation clearly demonstrates that the genetic redistribution effect can occur in silico, showing an initial advantage of endogenously synthesized vitamin C, followed by transfer of the fitness contribution to the complex of genes that together allow the acquisition of vitamin C from the environment. As is well known in the modeling community, the Baldwin effect only occurs in simulations when the population of agents is ''poised on the brink'' of discovering the genetically specified solution. Similarly, the redistribution effect occurs in simulations under specific initial conditions: too little vitamin C in the environment, and its synthesis it is never fully masked; too much vitamin C, and the abilities required to acquire it are not tightly integrated. The Baldwin effect has been hypothesized as a potential mechanism for developing language-specific adaptations like innate universal grammar and other highly modular capacities. We conclude with a discussion of the relevance of genetic assimilation and genetic redistribution to the evolution of language and other cognitive adaptations.

Biological Evolution↗