Network algorithmics and the emergence of information integration in cortical models

Consciousness: New Concepts and Neural Networks

The definition of consciousness remains a difficult issue that requires urgent understanding and resolution. Currently, consciousness research is an intensely focused area of neuroscience. However, to establish a greater understanding of the concept of consciousness, more detailed, intrinsic neurobiological research is needed. Additionally, an accurate assessment of the level of consciousness may strengthen our awareness of this concept and provide new ideas for patients undergoing clinical treatment of consciousness disorders. In addition, research efforts that help elucidate the concept of consciousness have important scientific and clinical significance. This review presents the latest progress in consciousness research and proposes our assumptions with regard to the network of consciousness.

Information-theoretic signatures of biodiversity in the barcoding gene

Analyzing the information content of DNA, though holding the promise to help quantify how the processes of evolution have led to information gain throughout the ages, has remained an elusive goal. Paradoxically, one of the main reasons for this has been precisely the great diversity of life on the planet: if on the one hand this diversity is a rich source of data for information-content analysis, on the other hand there is so much variation as to make the task unmanageable. During the past decade or so, however, succinct fragments of the COI mitochondrial gene, which is present in all animal phyla and in a few others, have been shown to be useful for species identification through DNA barcoding. A few million such fragments are now publicly available through the BOLD systems initiative, thus providing an unprecedented opportunity for relatively comprehensive information-theoretic analyses of DNA to be attempted. Here we show how a generalized form of total correlation can yield distinctive information-theoretic descriptors of the phyla represented in those fragments. In order to illustrate the potential of this analysis to provide new insight into the evolution of species, we performed principal component analysis on standardized versions of the said descriptors for 23 phyla. Surprisingly, we found that, though based solely on the species represented in the data, the first principal component correlates strongly with the natural logarithm of the number of all known living species for those phyla. The new descriptors thus constitute clear information-theoretic signatures of the processes whereby evolution has given rise to current biodiversity, which suggests their potential usefulness in further related studies.