Gating in Neuronal Networks and the Neuronal Replicator Hypothesis
The above pages discuss progress in models of neuronal gating and the neuronal replicator hypothesis. One of the aims is to understand how chemical symbol systems (similar but distinct from physical symbol systems) can be implemented in neuronal networks. We propose that the brain is a fluid automaton in which patterns of activation interact with other patterns of activation in a manner that is NOT constrained to particular neuronal connections. One application of this is a system capable of natural selection of neuronal units of selection.
Chaos in cellular dynamics: An adapative advantage?
Recent experiments have sparked my interest in some findings (download paper here) showing that there is chaos in the replication period of a chemoton model. What are the various ways in which cells can exhibit chaos, and why might this be a useful thing for the cell? See here.
Network Motifs as Adaptations for Evolvability in Bacteria
I am forming and testing the hypothesis that network motifs in bacteria may be adaptations for evolvability. See notes here. Some bioinformatics resources can be found here. I consider the evolvability properties of gene regulatory networks using a logic gate model here.
Liquid State Machines in Real Neural Networks
Work in Collaboration with Peter Passaro at Sussex. Work In Progress.
Complexity Economics
Download a Mac OS X version of the Santa Fe Artifiicial Stock Market here. I am investigating whether
Ecosystem Selection Mini-Workshop
A group of us held a workshop on 16th October, 2006 at Birmingham University on ecosystem selection. Click above for the abstracts and details. Can ecosystems act as units of selection? Some experiments give inconclusive results, and some models suggest limited heredity is possible. So what?
Proposal for an MSc Mini-Project (University of Birmingham): Computational Models of the Origin of Life.
Click above for details on this project on modeling the first cells, the minimal units of life.
Dynamical Systems Analysis of Autocatalytic Chemical Ecologies
The above pages contain examples of using dynamical systems analysis to understand some re-cycling chemical ecologies. In particular to calculate the dynamic stability of co-existence of replicators with different growth and decay rates.
The Evolution of Metabolism
Recent Marie Curie extensions of my papers on chemical evolution by natural selection are discussed in the above link.
See this page for work in progress on a model of the evolution of metabolism. The main issue here is how chemical 'evolution' actually works, in the absence of micro-mutation. What is a chemical individual? What allows some chemical systems to succesfully continue to maximize their production of entropy, i.e. to maximize the extent to which they can absorb energy and dissipiate it as heat?
June 2006. More recent models involving the concept of MEP (Maximization of Entropy Production Principle) are discussed here.
July 2006. A spatial metabolism simulator is available for download here.
Download a Spatial Network Simulator Backbone (for Mac OS X)
You can download this very simple skeleton program that simulates using Eular integration, a network of agents on a grid, with diffusion of agents between grid squares. The code is in C++ and works with Cocoa on Mac OS X. It is intended to form a sort of template that you can use to write more complex simulations. One can adapt the code to model ecosystems, metabolism or replicators on surfaces, or any dynamic network process on a 2D surface.
Artificial Ecosystem Selection Experiments Using Pond-Water.
In a fit of wanting to do some real experiments with real organisms, I ordered several hundred test-tubes, an assorted set of flasks, and a pH meter on the 28th July 2006. My intention, inspired by Alex Penn's work, to evolve an ecosystem of pond organisms capable of attaining a desired pH. See here for my notes on this experiment. It is also a good excuse to look down a microscope and learn about a real biological ecosystem!
In Silico Evolution of Cell Signaling Networks
I am currently working on a post-doc for the ESIGNET project on the evolution of cell signaling networks. This is a difficult project, looking at the principles underlying the organization of cell signaling networks in cells. What sorts of computations if any are carried out by single cells? How complex need the computations of a single cell be after all?! Click on the title for details.
Landmark Learning in Bees
The first piece of work I did on the EASY (Evolutionary and Adaptive Systems) MSc at Sussex. It was great fun, and it exposed me to a new world of possibilities. Fernando, C. Neural Mechanisms for Single-Episode Landmark Learning in Artificial Bees. (2002) COGS, Sussex University. Download pdf.zip
A Evolutionary Robotic Model of Classical and Instrumental Conditioning.
My MSc thesis was on an evolutionary robotic model of classical and instrumental conditioning in T-maze tasks. It can be downloaded here. Fernando, C. A Situated and Embodied Model of Classical and Instrumental Conditioning. MSc Thesis (2003) Download pdf.zip
Neural Networks.
I am interested in learning and pattern recognition using neural networks. See the liquid state machine talks below (The Liquid Brain) for some research on this topic. Some notes on LSMs in MEAs here.
Misc. Talks.
Natural Selection in the Brain. Fellows Seminar Collegium Budapest March 2009. Download here.
Keynote talk given at Mathematics, Computation and Biology Meeting Hewlett Packard Laboratories, Bristol. Is there a Neurome? Download here. 2008
Three Kinds of Learning. Fellows Seminar (Marie Curie Fellowship) Collegium Budapest 6th June 2008.Download here.
Hebbian Learning in Gene Networks. SISSA, Trento, Italy. 14th December 2007. Download here.
ESIGNET 2 year report. Evolvability and Cross-talk in Cellular Networks. Download ppt here.
Revision notes for Molecular Computaton Series, Birmingham, 2007
Lecture 5 for Molecular Computation Series: Nature Inspired Molecular Engineering. April 2007. Download ppt here, and jpegs here. This is a more relaxed lecture introducing some concepts such as development and differentiation, molecular machines, and the potential liquid state properties of E.Coli gene regulatory networks, in the absence of metabolic and environmental mediated feedback loops. Download Ben Jone's talk on liquid state machines in E.Coli here.
Lecture 4 for Molecular Computation Series: Chemotaxis by E.Coli (Part 1). University of Birmingham, March 2007. Download ppt. Download supplementary material here (same as below). Download lecture as jpegs here. (An animation ppt that actually explains what is happening here. Chemotaxis by E.Coli (Part 2). I re-wrote the lecture containing a clearer explanation of the chemotaxis mechanism, and you can download it here. Also, you can download the mathematica model I made of chemotaxis here.
Lecture 3 for Molecular Computation Series: Computation by Cell Signaling Networks. University of Birmingham March 2007. Download ppt. Download mathematica (cellerator) file of Bistable Switch here. Download supplementary material here. Download lecture as a jpegs here
Lecture 1 and 2 for Molecular Computation Series: Self-Replication. Implementation of the Evolutionary Algorithm, University of Birmingham. March 2007. Download ppt Download the supplementary material here . Download lecture as jpegs here.
Hebbian Learning in Gene Networks. Download talks for CSB, ESIGNET, and GECCO. 18thMonthReport
The Origin of Life: The Chicken and Egg Tree. Talk for Darwin Day Monday 12th February 2007. Download ppt.
Introduction to Evolution (for Computer Scientists). 2nd Year Undergraduate Computer Science. November 2006. Download ppt.
Introduction to Genetic Algorithms. 2nd Year Undergraduate Computer Science. November 2006. Download ppt.
Michaelis-Menten Kinetics, October 2006. Download ppt.
Chemical Evolution by Natural Selection, Ecosystem Selection Workshop, University of Birmingham, October, 2006. Download ppt.
From the Proliferating MIcrosphere to the Chemoton. San Sebastian Workshop, September 2006. Download ppt.
The Chemical Evolution of Metabolism. San Sebastian Workshop, September 2006. Download ppt.
Artificial Selection for Maximization of Steady State Energy Flux in an Artificial Chemistry. Dublin ESIGNET Workshop, August 2006. Download ppt.
The Origin of Recycling. Autonomy workshop. Alife X Bloomington, Indiana, 2006. Download ppt. View in html
The Black Art of Evolution. Fellows Seminar. Collegium Budapest 2005. Download ppt.
Non-Enzymatic Template Replication. Biols Seminar, Collegium Budapest. (2005) Download ppt.
Stochastic Template Models (Early Attempts). A talk given in Crete for the COST D27 Meeting for Prebiotic Chemistry (2004). Download ppt.
A Souffle of Life, a Mars Bar of Tar. Talk given at Alergic 2004. University of Sussex. Download ppt. (10MB).
Introduction to the Chemoton. Talk given at Units of Life Reading Group, University of Sussex 2004. Download ppt.
The Liquid Brain. Talk given at ECAL 2003 Dortmund. (Winner of best paper). Download ppt.