This work, which was started in the early 1970s, was inspired by social interaction analysis based on direct observation and careful coding of behaviors according to a list of behavioral (mostly ethological) categories, especially the ethological work of N. Tinbergen, K. Lorenz, and K. von Frisch, for which they shared a Nobel Prize in 1973 in Medicine or Physiology but also H. Montagner’s ethological analyses of interactions in social insects and children. S. Duncan’s psychological and linguistic research on turn-taking in human interactions provided great inspiration, and so did Chomsky’s work on syntactic structure and Skinner’s probabilistic real-time functional analysis and their consequent debate. A hypothesis concerning numerous kinds of temporal and spatial natural and especially biological structures, the T-pattern is a hierarchical self-similar fractal-like structure that recurs with significant translational symmetry on a single discrete dimension, initially real time. It also points to profound self-similarity across many levels of biological spatio-temporal organization, as it seems characteristic of molecular structures such as genes and a multitude of recurrent motives on DNA and its 3D generalization corresponding to (3D) folded proteins. Developed initially to facilitate empirical analysis, the T-pattern and its detection algorithms were first presented in AI (Magnusson, 1981) and Applied Statistics (Magnusson, 1983) through THEME (3 k Fortran IV) software using an evolution algorithm. It is now over 300 k lines of code, runs under Windows, and, more recently, uses parallel processing for increased speed. This has allowed abundant detection of hidden structure in numerous kinds of biological phenomena at highly varied scales, from human behavior at timescales of days (Hirschenhauser et al., 2002; Hirschenhauser and Frigerio, 2005) to interactions of many individual neurons simultaneously registered at a temporal resolution of 10^–6 s in neuronal networks in rat brains to ongoing work on T-patterns in DNA molecules at a spatial nano-scale. T-pattern detection and analysis (TPA) thus mix qualitative and quantitative analyses, as T-patterns themselves are artificial categories composed of recurring coding categories with special real-scale statistical relations between their instances. After their detection, T-patterns are thus analyzed much as are other behavioral categories.

Nausea and vomiting are common symptoms in patients with many diseases, including cancer and its treatments. Although the neurological basis of vomiting is reasonably well known, an understanding of the physiology of nausea is lacking. The primary barrier to mechanistic research on the nausea system is the lack of an animal model. Indeed investigating the effects of anti-nausea drugs in pre-clinical models is difficult because the primary readout is often emesis. It is known that animals show a behavioral profile of sickness, associated with reduced feeding and movement, and possibly these general measures are signs of nausea. Studies attempting to relate the occurrence of additional behaviors to emesis have produced mixed results. Here we applied a statistical method, temporal pattern (t-pattern) analysis, to determine patterns of behavior associated with emesis. Musk shrews were injected with the chemotherapy agent cisplatin (a gold standard in emesis research) to induce acute (24 h) emesis. Emesis and other behaviors were coded and tracked from video files. T-pattern analysis revealed hundreds of non-random patterns of behavior associated with emesis, including sniffing, changes in body contraction, and locomotion. There was little evidence that locomotion was inhibited by the occurrence of emesis. Eating, drinking, and other larger body movements including rearing, grooming, and body rotation, were significantly less common in emesis-related behavioral patterns in real versus randomized data. These results lend preliminary evidence for the expression of emesis-related behavioral patterns, including reduced ingestive behavior, grooming, and exploratory behaviors. In summary, this statistical approach to behavioral analysis in a pre-clinical emesis research model could be used to assess the more global effects and limitations of drugs used to control nausea and its potential correlates, including reduced feeding and activity levels.

This project started in the 1970's inspired by biological behavior research (Morris, 1967; Tinbergen, 1965) including that of N. Tinbergen, K. Lorenz and K. von Frisch, for which they shared a Nobel Prize in 1973 in Medicine or Physiology, the first for ethological research. Further inspiration came from research on social insects and children (Montagner, 1971, 2012), interactions in human adults (Duncan & Fiske, 1977), probabilistic real-time analysis of behavior (Skinner, 1969) and linguistic analysis (Chomsky, 1957). There was not yet talk of self-similarity or nano scale agents. Adequate computational pattern discovery required models, algorithms and software, which has led to the definition of the scale independent T-pattern and related pattern types making up the T-system and the creation of the only available dedicated special purpose T-pattern and T-system pattern detection algorithms and software, THEME™. Theme has already allowed the detection of T-patterns in many different research areas from human to neuronal interactions at time scales from days to 10^-6 s and finally spatial T-patterns and T-strings in textual and molecular strings. Similarity of temporal and spatial patterning from human to neuronal interactions to giant purely informational physical strings, DNA and texts, seems to exist and biologically extremely recent self-similarity between each human mass-society and the protein mass-societies of the cells making up each of its typically >10⁴ individuals. Giant T-patterned text strings, T-strings, as external memory have in a biological eye blink allowed the development of modern mass-societies with their science and technology allowing the discovery of this biologically sudden advent of unique self-similarity and thus a bio-mathematical continuum between nano and human scales, which may change views on modern human mass-societies and their modern lifestyle and issues.