Discovering hidden temporal patterns in behavior and interaction : t-pattern detection and analysis with theme[TM]
著者
書誌事項
Discovering hidden temporal patterns in behavior and interaction : t-pattern detection and analysis with theme[TM]
(Neuromethods, 111)(Springer protocols)
Humana Press, c2016
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注記
On t.p. "[TM]" is superscript
Includes bibliographical references and index
内容説明・目次
内容説明
Discovering hidden recurring patterns in observable behavioral processes is an important issue frequently faced by numerous advanced students and researchers across many research areas, including psychology, biology, sports, robotics, media, finance, and medicine. As generally, themany powerful methods included in statistical software packages were not developed for this kind of analysis, discovering such patterns has proven a particularly difficult task, due to a lack of a) adequate formalized models of the kinds of patterns to look for, b) corresponding detection algorithms and c) their implementation in available software. The research described in this book is based on the application of such pattern types, algorithms and software developed from the late seventies to the present in the context of research in collaboration with human and animal behavioral research teams at internationally leading universities in the US and Europe, thus testing the usefulness and validity of the pattern types, algorithms and software in numerous research areas. With the (scale independent statistical hierarchical and fractal-like) T-Pattern at its heart, a set of proposed pattern types, called the T-System, forms the basis for the search algorithms implemented as the software THEME (TM) (vs. 6), which is easily available in free educational and full commercial versions.
目次
- Introduction. Magnusson M.S., et al.
- Preface. Anguera M. T.
Part 1 - Human Behavior1. Time and Self-similar Structure in Behavior and Interactions: From Sequences to Symmetry and Fractals. Magnusson M.S.
2. Interactive Deception In Group Decision-Making: New Insights From Communication Pattern Analysis. Burgoon J., et al.
3. Imposing Cognitive Load To Detect Prepared Lies: A T-Pattern Approach. Zurloni V., et al.
4. Paraverbal Communicative Teaching T-patterns using SOCIN and SOPROX observational systems. Castaner M., et al.
5. The Self-Organization of Self-Injurious Behavior as Revealed Through Temporal Pattern Analyses. Kemp A., et al.
6. Detecting and Characterizing Patterns of Behavioral Symptoms of Dementia. Woods D.L., et al.
7. Typical errors and behavioral sequences in judo techniques: knowledge of performance and the analysis of T-patterns in relation to teaching and learning the Ouchi-gari throw. Prieto I., et al.
8. Qualitative differences in men's and women's facial movements in an experimental situation. Racca A., et al.
9. Understanding Film Art: Moments Of Impact And Patterns Of Reactions. Suckfull M. and Unz D
10. Immersive Dynamics: Presence Experiences And Patterns Of Attention. M. Brill et al.
11. Accessing Individual Style Th
roug
h Proposed Use Of Theme Associates. Quaeghebeur L. and McNeill D.
Part 2 - Animal and Neuronal Behavior (Non-Human Behavior)12. Application Of T-Pattern Analysis In The Study Of Rodent Behavior: Methodological And Experimental Highlights. Casarrubea M. et al
13. Using Hidden Behavioral Patterns To Study Nausea In A Preclinical Model. Horn C. and Magnusson M.S.
14. Informative Value Of Vocalizations During Multimodal Interactions In Red-Capped Mangabeys. Baraud I., et al.
15. Identification And Description Of Behaviours And Domination Patterns In Captive Vervet Monkeys (Cercophitecus Aethiops Pygerythrus) During Feeding Time. Ortiz G., et al.
16. Tidal Location Of Atlantic Cod In Icelandic Waters And Identification Of Vertical And Horizontal Movement Patterns In Cod Behavior. Jonsson G. et al.
17. Complex Spike Patterns in Olfactory Bulb Neuronal Networks. Nicol A. et al.
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