Evolution and development of complex computational systems using the paradigm of metabolic computing in Epigenetic Tracking

Epigenetic Tracking (ET) is an Artificial Embryology system which allows for the evolution and development of large complex structures built from artificial cells. In terms of the number of cells, the complexity of the bodies generated with ET is comparable with the complexity of biological organisms. We have previously used ET to simulate the growth of multicellular bodies with arbitrary 3-dimensional shapes which perform computation using the paradigm of "metabolic computing". In this paper we investigate the memory capacity of such computational structures and analyse the trade-off between shape and computation. We now plan to build on these foundations to create a biologically-inspired model in which the encoding of the phenotype is efficient (in terms of the compactness of the genome) and evolvable in tasks involving non-trivial computation, robust to damage and capable of self-maintenance and self-repair.Comment: In Proceedings Wivace 2013, arXiv:1309.712

Evolving small spiking neural networks to work as state machines for temporal pattern recognition

Peer reviewe

Robust Very Small Spiking Neural Networks Evolved with Noise to Recognize Temporal Patterns

© 2018 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. https://creativecommons.org/licenses/by/4.0/To understand how biological and bio-inspired complex computational networks can function in the presence of noise and damage, we have evolved very small spiking neural networks in the presence of noise on the membrane potential. The networks were built with adaptive exponential integrate and fire neurons. The simple but not trivial task we evolved the networks for consisted of recognizing a short temporal pattern in the activity of the network inputs. This task can be described in abstract terms as finding a specific subsequence of symbols (“ABC”) in a continuous sequence of symbols (“..ABCCCAAABCAC..”). We show that networks with three interneurons and one output neuron can solve this task in the presence of biologically plausible levels of noise. We describe how such a network works by mapping its activity onto the state of a finite state transducer—an abstract model of computation on continuous time series. We demonstrate that the networks evolved with noise are much more robust than networks evolved without noise to the modification of neuronal parameters and variation of the properties of the input. We also show that the networks evolved with noise are denser and have stronger connections than the networks evolved without noise. Finally, we demonstrate the emergence of memory in the evolved networks—sustained spiking of some neurons maintained thanks to the presence of self-excitatory loops

Autapses enable temporal pattern recognition in spiking neural networks

© 2023 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Most sensory stimuli are temporal in structure. How action potentials encode the information incoming from sensory stimuli remains one of the central research questions in neuroscience. Although there is evidence that the precise timing of spikes represents information in spiking neuronal networks, information processing in spiking networks is still not fully understood. One feasible way to understand the working mechanism of a spiking network is to associate the structural connectivity of the network with the corresponding functional behaviour. This work demonstrates the structure-function mapping of spiking networks evolved (or handcrafted) for a temporal pattern recognition task. The task is to recognise a specific order of the input signals so that the Output neurone of the network spikes only for the correct placement and remains silent for all others. The minimal networks obtained for this task revealed the twofold importance of autapses in recognition; first, autapses simplify the switching among different network states. Second, autapses enable a network to maintain a network state, a form of memory. To show that the recognition task is accomplished by transitions between network states, we map the network states of a functional spiking neural network (SNN) onto the states of a finite-state transducer (FST, a formal model of computation that generates output symbols, here: spikes or no spikes at specific times, in response to input, here: a series of input signals). Finally, based on our understanding, we define rules for constructing the topology of a network handcrafted for recognising a subsequence of signals (pattern) in a particular order. The analysis of minimal networks recognising patterns of different lengths (two to six) revealed a positive correlation between the pattern length and the number of autaptic connections in the network. Furthermore, in agreement with the behaviour of neurones in the network, we were able to associate specific functional roles of locking, switching, and accepting to neurones

Topology testing of phylogenies using least squares methods

BACKGROUND: The least squares (LS) method for constructing confidence sets of trees is closely related to LS tree building methods, in which the goodness of fit of the distances measured on the tree (patristic distances) to the observed distances between taxa is the criterion used for selecting the best topology. The generalized LS (GLS) method for topology testing is often frustrated by the computational difficulties in calculating the covariance matrix and its inverse, which in practice requires approximations. The weighted LS (WLS) allows for a more efficient albeit approximate calculation of the test statistic by ignoring the covariances between the distances. RESULTS: The goal of this paper is to assess the applicability of the LS approach for constructing confidence sets of trees. We show that the approximations inherent to the WLS method did not affect negatively the accuracy and reliability of the test both in the analysis of biological sequences and DNA-DNA hybridization data (for which character-based testing methods cannot be used). On the other hand, we report several problems for the GLS method, at least for the available implementation. For many data sets of biological sequences, the GLS statistic could not be calculated. For some data sets for which it could, the GLS method included all the possible trees in the confidence set despite a strong phylogenetic signal in the data. Finally, contrary to WLS, for simulated sequences GLS showed undercoverage (frequent non-inclusion of the true tree in the confidence set). CONCLUSION: The WLS method provides a computationally efficient approximation to the GLS useful especially in exploratory analyses of confidence sets of trees, when assessing the phylogenetic signal in the data, and when other methods are not available

16S rDNA pyrosequencing analysis of bacterial community in heavy metals polluted soils

Soil contamination with heavy metals is a widespread problem, especially prominent on grounds lying in the vicinity of mines, smelters, and other industrial facilities. Many such areas are located in Southern Poland; they are polluted mainly with Pb, Zn, Cd, or Cu, and locally also with Cr. As for now, little is known about most bacterial species thriving in such soils and even less about a core bacterial community—a set of taxa common to polluted soils. Therefore, we wanted to answer the question if such a set could be found in samples differing physicochemically and phytosociologically. To answer the question, we analyzed bacterial communities in three soil samples contaminated with Pb and Zn and two contaminated with Cr and lower levels of Pb and Zn. The communities were assessed with 16S rRNA gene fragments pyrosequencing. It was found that the samples differed significantly and Zn decreased both diversity and species richness at species and family levels, while plant species richness did not correlate with bacterial diversity. In spite of the differences between the samples, they shared many operational taxonomic units (OTUs) and it was possible to delineate the core microbiome of our sample set. The core set of OTUs comprised members of such taxa as Sphingomonas, Candidatus Solibacter, or Flexibacter showing that particular genera might be shared among sites ~40 km distant

Low virus to prokaryote ratios in the cold: benthic viruses and prokaryotes in a subpolar marine ecosystem (Hornsund, Svalbard)

The density and spatial distribution of benthic viruses and prokaryotes in relation to biotic and abioticfactors were investigated in sediment cores collected in Hornsund, a permanently cold fjord on the West coast of Svalbard,Norway. The cores were obtained from the mouth of the fjord to the central basin, along a longitudinal transect. Theresults of our analyses showed lower densities of viruses (0.2 × 108 to 5.4 × 108 virus-like particles/g) and lower virus-toprokaryoteratios (0.2-0.6, with the exception of the uppermost layer in the central basin, where the ratio was about 1.2)at the study site than generally found in the temperate areas, despite the relatively high organic matter content in subpolarsediments. Variations in benthic viral and prokaryote abundances along gradients of particle sedimentation rates, phytopigmentconcentrations, and macrobenthic species composition together suggested the influence of particle sedimentationand macrobenthic bioturbation on the abundance and spatial distribution of prokaryotes and viruses in cold habitats. [IntMicrobiol 2013; 16(1):45-52

Metal and antibiotic resistance of bacteria isolated from the Baltic Sea

The resistance of 49 strains of bacteria isolated from surface Baltic Sea waters to 11 antibiotics was analyzedand the resistance of selected strains to three metal ions (Ni2+, Mn2+, Zn2+) was tested. Most isolates belonged to Gammaproteobacteria (78 %), while Alphaproteobacteria (8 %), Actinobacteria (10 %), and Bacteroidetes (4 %) were lessabundant. Even though previous reports suggested relationships between resistance and the presence of plasmids or the abilityto produce pigments, no compelling evidence for such relationships was obtained for the strains isolated in this work. In particular, strains resistant to multiple antibiotics did not carry plasmids more frequently than sensitive strains. A relationbetween resistance and the four aminoglycosides tested (gentamycin, kanamycin, neomycin, and streptomycin), but not tospectinomycin, was demonstrated. This observation is of interest given that spectinomycin is not always classified as anaminoglycoside because it lacks a traditional sugar moiety. Statistical analysis indicated relationships between resistance tosome antibiotics (ampicillin and erythromycin, chloramphenicol and erythromycin, chloramphenicol and tetracycline, erythromycinand tetracycline), suggesting the linkage of resistance genes for antibiotics belonging to different classes. The effectsof NiSO4, ZnCl2 and MnCl2 on various media suggested that the composition of Marine Broth might result in low concentrationsof Mn2+ due to chemical interactions that potentially lead to precipitation. [Int Microbiol 2012; 15(3):131-139

Biodiversity of bacteriophages: morphological and biological properties of a large group of phages isolated from urban sewage

A large scale analysis presented in this article focuses on biological and physiological variety of bacteriophages. A collection of 83 bacteriophages, isolated from urban sewage and able to propagate in cells of different bacterial hosts, has been obtained (60 infecting Escherichia coli, 10 infecting Pseudomonas aeruginosa, 4 infecting Salmonella enterica, 3 infecting Staphylococcus sciuri, and 6 infecting Enterococcus faecalis). High biological diversity of the collection is indicated by its characteristics, both morphological (electron microscopic analyses) and biological (host range, plaque size and morphology, growth at various temperatures, thermal inactivation, sensitivity to low and high pH, sensitivity to osmotic stress, survivability upon treatment with organic solvents and detergents), and further supported by hierarchical cluster analysis. By the end of the research no larger collection of phages from a single environmental source investigated by these means had been found. The finding was confirmed by whole genome analysis of 7 selected bacteriophages. Moreover, particular bacteriophages revealed unusual biological features, like the ability to form plaques at low temperature (4 °C), resist high temperature (62 °C or 95 °C) or survive in the presence of an organic solvents (ethanol, acetone, DMSO, chloroform) or detergent (SDS, CTAB, sarkosyl) making them potentially interesting in the context of biotechnological applications

Evolutionary design of soft-bodied animats with decentralized control

We show how a biologically inspired model of multicellular development combined with a simulated evolutionary process can be used to design the morphologies and controllers of soft-bodied virtual animats. An animat’s morphology is the result of a developmental process that starts from a single cell and goes through many cell divisions, during which cells interact via simple physical rules. Every cell contains the same genome, which encodes a gene regulatory network (GRN) controlling its behavior. After the developmental stage, locomotion emerges from the coordinated activity of the GRNs across the virtual robot body. Since cells act autonomously, the behavior of the animat is generated in a truly decentralized fashion. The movement of the animat is produced by the contraction and expansion of parts of the body, caused by the cells, and is simulated using a physics engine. Our system makes possible the evolution and development of animats that can run, swim, and actively navigate toward a target in a virtual environment