title: Evolvable neuronal paths: a novel basis for information and search in the brain.
abstract: We propose a previously unrecognized kind of informational entity in the brain that is capable of acting as the basis for unlimited hereditary variation in neuronal networks. This unit is a path of activity through a network of neurons, analogous to a path taken through a hidden Markov model. To prove in principle the capabilities of this new kind of informational substrate, we show how a population of paths can be used as the hereditary material for a neuronally implemented genetic algorithm, (the swiss-army knife of black-box optimization techniques) which we have proposed elsewhere could operate at somatic timescales in the brain. We compare this to the same genetic algorithm that uses a standard 'genetic' informational substrate, i.e. non-overlapping discrete genotypes, on a range of optimization problems. A path evolution algorithm (PEA) is defined as any algorithm that implements natural selection of paths in a network substrate. A PEA is a previously unrecognized type of natural selection that is well suited for implementation by biological neuronal networks with structural plasticity. The important similarities and differences between a standard genetic algorithm and a PEA are considered. Whilst most experiments are conducted on an abstract network model, at the conclusion of the paper a slightly more realistic neuronal implementation of a PEA is outlined based on Izhikevich spiking neurons. Finally, experimental predictions are made for the identification of such informational paths in the brain.
authors: Department of Informatics, University of Sussex, Brighton, United Kingdom. ctf20@sussex.ac.uk
authors: Chrisantha
authors: C
authors: Fernando
authors: Vera
authors: V
authors: Vasas
authors: Eörs
authors: E
authors: Szathmáry
authors: Phil
authors: P
authors: Husbands
mesh_terms: D000465:Algorithms; D000483:Alleles; D005075:Biological Evolution; D001921:Brain / Q000502:physiology*; D056426:Genetic Loci / Q000235:genetics; D015810:Linkage Disequilibrium / Q000235:genetics; D008568:Memory / Q000502:physiology; D009154:Mutation / Q000235:genetics; D009415:Nerve Net / Q000502:physiology*; D009473:Neuronal Plasticity / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D010641:Phenotype; D012641:Selection, Genetic