Autocatalysis, information and coding

Autocatalytic self-construction in macromolecular systems requires the existence of a reflexive relationship between structural components and the functional operations they perform to synthesise themselves. The possibility of reflexivity depends on formal, semiotic features of the catalytic structure–function relationship, that is, the embedding of catalytic functions in the space of polymeric structures. Reflexivity is a semiotic property of some genetic sequences. Such sequences may serve as the basis for the evolution of coding as a result of autocatalytic self-organisation in a population of assignment catalysts. Autocatalytic selection is a mechanism whereby matter becomes differentiated in primitive biochemical systems. In the case of coding self-organisation, it corresponds to the creation of symbolic information. Prions are present-day entities whose replication through autocatalysis reflects aspects of biological semiotics less obvious than genetic coding.     

Neural correlations, population coding and computation

How the brain encodes information in population activity, and how it combines and manipulates that activity as it carries out computations, are questions that lie at the heart of systems neuroscience. During the past decade, with the advent of multi-electrode recording and improved theoretical models, these questions have begun to yield answers. However, a complete understanding of neuronal variability, and, in particular, how it affects population codes, is missing. This is because variability in the brain is typically correlated, and although the exact effects of these correlations are not known, it is known that they can be large. Here, we review studies that address the interaction between neuronal noise and population codes, and discuss their implications for population coding in general.     

Tuning curves, neuronal variability, and sensory coding

Tuning curves are widely used to characterize the responses of sensory neurons to external stimuli, but there is an ongoing debate as to their role in sensory processing. Commonly, it is assumed that a neuron's role is to encode the stimulus at the tuning curve peak, because high firing rates are the neuron's most distinct responses. In contrast, many theoretical and empirical studies have noted that nearby stimuli are most easily discriminated in high-slope regions of the tuning curve. Here, we demonstrate that both intuitions are correct, but that their relative importance depends on the experimental context and the level of variability in the neuronal response. Using three different information-based measures of encoding applied to experimentally measured sensory neurons, we show how the best-encoded stimulus can transition from high-slope to high-firing-rate regions of the tuning curve with increasing noise level. We further show that our results are consistent with recent experimental findings that correlate neuronal sensitivities with perception and behavior. This study illustrates the importance of the noise level in determining the encoding properties of sensory neurons and provides a unified framework for interpreting how the tuning curve and neuronal variability relate to the overall role of the neuron in sensory encoding.     

Olfactory coding in the insect brain: molecular receptive ranges, spatial and temporal coding

Odor information is coded in the insect brain in a sequence of steps, ranging from the receptor cells, via the neural network in the antennal lobe, to higher order brain centers, among which the mushroom bodies and the lateral horn are the most prominent. Across all of these processing steps, coding logic is combinatorial, in the sense that information is represented as patterns of activity across a population of neurons, rather than in individual neurons. Because different neurons are located in different places, such a coding logic is often termed spatial, and can be visualized with optical imaging techniques. We employ in vivo calcium imaging in order to record odor‐evoked activity patterns in olfactory receptor neurons, different populations of local neurons in the antennal lobes, projection neurons linking antennal lobes to the mushroom bodies, and the intrinsic cells of the mushroom bodies themselves, the Kenyon cells. These studies confirm the combinatorial nature of coding at all of these stages. However, the transmission of odor‐evoked activity patterns from projection neuron dendrites via their axon terminals onto Kenyon cells is accompanied by a progressive sparsening of the population code. Activity patterns also show characteristic temporal properties. While a part of the temporal response properties reflect the physical sequence of odor filaments, another part is generated by local neuron networks. In honeybees, γ‐aminobutyric acid (GABA)‐ergic and histaminergic neurons both contribute inhibitory networks to the antennal lobe. Interestingly, temporal properties differ markedly in different brain areas. In particular, in the antennal lobe odor‐evoked activity develops over slow time courses, while responses in Kenyon cells are phasic and transient. The termination of an odor stimulus is reflected by a decrease in activity within most glomeruli of the antennal lobe and an off‐response in some glomeruli, while in the mushroom bodies about half of the odor‐activated Kenyon cells also exhibit off‐responses.     

The selectivity of canary HVC neurons for the Bird's Own Song: rate coding, temporal coding, or both?

The neuronal selectivity observed in the avian song system for the Bird's Own Song progressively emerged as an extraordinary fruitful model to investigate the neural code underlying the recognition of complex stimuli and the occurrence of learned behaviors. In adult zebra finch, neurons from the HVC (used as a proper name) show very selective auditory responses, firing more to presentation of the Bird's Own Song (BOS) than to reverse BOS or other conspecific songs. However, as adult zebra finches always produce the same stereotyped song, the presence of such highly selective neurons in birds with larger repertoire still remains an open question. Data presented here show that neurons selective for the BOS can be found in adult canary, a seasonal breeding bird which display a large repertoire. More precisely, we found that a large proportion of neurons (29/36) exhibits higher responses to presentation of the forward than to the reverse BOS, and that 22% of the cells were identified as selective on the basis of the d' value. For a cell that was extensively studied, we evaluated to what extent temporal stimulus-related structure predicts the acoustic stimulus using linear or non-linear artificial neural networks (ANN). These analyses indicated that the temporal structure contained in spike trains characterizes more accurately the stimulus than the firing rate. The limitations of applying ANN analyses to electrophysiological data are discussed and potential solutions to increase the confidence in these analysis are proposed.     

Eco-evolutionary dynamics,coding structure and the information threshold

Background  

The amount of information that can be maintained in an evolutionary system of replicators is limited by genome length, the number of errors during replication (mutation rate) and various external factors that influence the selection pressure. To date, this phenomenon, known as the information threshold, has been studied (both genotypically and phenotypically) in a constant environment and with respect to maintenance (as opposed to accumulation) of information. Here we take a broader perspective on this problem by studying the accumulation of information in an ecosystem, given an evolvable coding structure. Moreover, our setup allows for individual based as well as ecosystem based solutions. That is, all functions can be performed by individual replicators, or complementing functions can be performed by different replicators. In this setup, where both the ecosystem and the individual genomes can evolve their structure, we study how populations cope with high mutation rates and accordingly how the information threshold might be alleviated.     

MSW, a yeast gene coding for mitochondrial tryptophanyl-tRNA synthetase

E569 and E606 are noncomplementing pet mutants of Saccharomyces cerevisiae. Both strains are defective in mitochondrial protein synthesis and as a result exhibit a pleiotropic deficiency in respiratory components that are translated on mitochondrial ribosomes. The wild type gene MSW capable of complementing the protein synthesis defect has been cloned by transformation of one of the mutants with a genomic library of wild type yeast nuclear DNA. The cloned gene has been sequenced and shown to code for a protein with a molecular weight of 42,414 which is 37 and 39% identical to the tryptophanyl-tRNA synthetases of Escherichia coli and Bacillus stearothermophilus, respectively. A strain containing an insertion in the chromosomal copy of MSW was constructed by in situ gene replacement. This mutant fails to charge mitochondrial tryptophanyl-tRNA providing further evidence that MSW is the structural gene for mitochondrial tryptophanyl tRNA synthetase. The existence of another gene coding for the cytoplasmic tryptophanyl-tRNA synthetase is inferred from the observation that mutations in MSW are not lethal but only result in a respiratory deficiency.     

Theory of degenerate coding and informational parameters of protein coding genes

The theory of degenerate coding is presented in a way enabling further application to molecular biology. There are two kinds of redundancy of a degenerate code. The first is due to the excess in codon length and the second to the code degeneracy. If the code is asymmetrically degenerate, the second kind of redundancy can be profitable for control of error rate. This control can be performed just by selective synonymous codon usage. Utilisation of the genetic code is partially influenced by this theoretical possibility. In particular the degree of error protectivity is well correlated with deviation from equiprobability in synonymous codon usage. The biological significance of this fact is discussed.     

The DNA sequence of Bombyx mori fibroin gene including the 5' flanking, mRNA coding, entire intervening and fibroin protein coding regions.

Sequence analysis of the cloned genomic fibroin gene and cDNA containing the sequence complementary to fibroin mRNA has been carried out for the regions covering the 5′ flanking, mRNA coding, entire intervening sequence and its borders, and fibroin coding sequences. The sequences determined on the gene extend from nucleotide ?552 to +1497 (assigning +1 to the cap locus); sequence analysis of the cDNA has confirmed our previous mapping of the cap locus (Tsujimoto and Suzuki, 1979). Comparison of the nucleotide sequence of the genomic gene with that of cDNA has confirmed the existence of an intervening sequence 970 bases long. The sequence comparison also pinpointed the 5′ coding-intervening junction at +64?66 and the 3′ intervening-coding junction at +1034?1036. Both the 5′ and 3′ junctions of the fibroin gene (insect) share homologous segments of about 10 nucleotides each with the published sequences of β-globin (mammal), immunoglobulin (mammal) and ovalbumin (avian) genes. A long inverted repeat sequence (17 of 23 base match) has been found next to the junctions within the intervening sequence of the fibroin gene. The repetitious sequence that codes for the Gly-Ala peptide characteristic of fibroin protein begins at position +1448. The characteristics of the N terminal portion of fibroin protein (or its precursor) are discussed, as are the features of the 5′ flanking sequence of the gene and the mRNA sequence (with special attention to the putative promoter sequence for the gene), the possible secondary structure and a sequence complementary to the 3′ end of 18S ribosomal RNA at the 5′ proximal region of fibroin mRNA.     

Tissue allograft coding and traceability in USM Tissue Bank,Malaysia

In Malaysia, tissue banking activities began in Universiti Sains Malaysia (USM) Tissue Bank in early 1990s. Since then a few other bone banks have been set up in other government hospitals and institutions. However, these banks are not governed by the national authority. In addition there is no requirement set by the national regulatory authority on coding and traceability for donated human tissues for transplantation. Hence, USM Tissue Bank has taken the initiatives to adopt a system that enables the traceability of tissues between the donor, the processed tissue and the recipient based on other international standards for tissue banks. The traceability trail has been effective and the bank is certified compliance to the international standard ISO 9001:2008.     

Rare coding sequence changes are consistent with Ecdysozoa, not Coelomata

There is growing interest in the use of alternative, more slowly-evolving RGCs (rare genomic changes). Recently, Rogozin and coauthors (Rogozin et al. 2007) proposed a novel phylogenetic method employing rare amino acid changes, RGC-CAMs (rare genomic changes-conserved amino acids-multiple substitutions). They applied their method to 694 sets of eukaryotic orthologs in order to distinguish the relationship between nematodes, arthropods and deuterostomes. They concluded that such rare amino acid changes were consistent with the Coelomata hypothesis, which groups arthropods and deuterostomes to the exclusion of nematodes. Here we use newly available genomic sequences from Nematostella vectensis, a basal metazoan, and from Brugia malayi, an additional nematode. We show that the apparent support for Coelomata is likely to be the result of the rapid rate of evolution leading to Caenorhabditis nematodes. Including the additional species paints a very different picture, with 13 remaining characters consistent with Ecdysozoa versus only 1 consistent with Coelomata.     

Analysis,classification, and coding of multielectrode spike trains with hidden Markov models

It is shown that hidden Markov models (HMMs) are a powerful tool in the analysis of multielectrode data. This is demonstrated for a 30-electrode measurement of neuronal spike activity in the monkey's visual cortex during the application of different visual stimuli. HMMs with optimized parameters code the information contained in the spatiotemporal discharge patterns as a probabilistic function of a Markov process and thus provide abstract dynamical models of the pattern-generating process. We compare HMMs obtained from vector-quantized data with models in which parametrized output processes such as multivariate Poisson or binomial distributions are assumed. In the latter cases the visual stimuli are recognized at rates of more than 90% from the neuronal spike patterns. An analysis of the models obtained reveals important aspects of the coding of information in the brain. For example, we identify relevant time scales and characterize the degree and nature of the spatiotemporal variations on these scales.