Identifying prototypical components in behaviour using clustering algorithms

PLoS ONE

Volumn 5, Issue 2, 2010, Pages

  Braun, Elke ^a   Geurten, Bart ^a   Egelhaaf, Martin ^a  

^a BIELEFELD UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; BEHAVIORAL SCIENCE; CALLIPHORA VICINA; DATA BASE; FLIGHT; FLY; GAZE; HEAD; NONHUMAN; ROTATION; ANIMAL; ANIMAL BEHAVIOR; BIOLOGICAL MODEL; CLUSTER ANALYSIS; FLYING; MOVEMENT (PHYSIOLOGY); PHYSIOLOGY;

ANIMALIA; CALLIPHORIDAE;

ALGORITHMS; ANIMALS; BEHAVIOR, ANIMAL; CLUSTER ANALYSIS; DIPTERA; FLIGHT, ANIMAL; MODELS, BIOLOGICAL; MOVEMENT;

EID: 77949631223     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0009361     Document Type: Article

References (46)

1. Stephens GJ, Johnson-Kerner B, Bialek W, Ryu WS (2008) Dimensionality and dynamics in the behavior of c. elegans. PLoS Comput Biol 4: e1000028.
2. Kern R, van Hateren J, Michaelis C, Lindemann JP, Egelhaaf M (2005) Function of a fly motion-sensitive neuron matches eye movements during free flight. PLoS Biology 3: e171.
3. Sokolowski MB (2001) Drosophila: Genetics meets behaviour. Nature Reviews Genetics 2: 879-890.
4. Bucan M, Abel T (2002) The mouse: genetics meets behaviour. Nature Reviews Genetics 3: 114-123.
5. Fentress JC, Stilwell FP (1973) Grammar of a movement sequence in inbred mice. Nature 244: 52-53.
6. Ghahramani Z (2000) Building blocks of movement. Nature 407: 682-683.
7. Schack T (2004) The cognitive architecture of complex movement. International Journal of Sport and Exercise Psychology 2: 403-438.
8. Del Vecchio D, Murray RM, Perona P (2003) Decomposition of human motion into dynamics-based primitives with application to drawing tasks. Automatica 39: 2085-2098.
9. Fussnecker BL, Smith BH, Mustard JA (2006) Octopamine and tyramine influence the behavioral profile of locomotor activity in the honey bee (apis mellifera). Journal of Insect Physiology 52: 1083-1092.
10. Martin P, Bateson P (2002) Measuring behaviour. Cambridge: Cambridge Univ. Press. XVI.
11. Lehner PN (1998) Handbook of ethological methods. Cambridge: Cambridge Univ. Press. XIX.
12. Baek JH, Cosman P, Feng Z, Silver J, Schafer WR (2002) Using machine vision to analyze and classify c. elegans behavioral phenotypes quantitatively. J Neurosci Methods 118: 9-21.
13. Hoshi K, Shingai R (2006) Computer-driven automatic identification of locomotion states in caenorhabditis elegans. J Neurosci Methods 157: 355-363.
14. Suster M, Karunanithi S, Atwood H, Sokolowski M (2004) Turning behaviour in drosophila larvae: a role for the small scribbler transcript. Genes, Brain and Behaviour 3: 273-286.
15. Osborne K, Robichon A, Burgess E, Butland S, Shaw R, et al. (1997) Natural behavior polymorphism due to a cgmp-dependent protein kinase of drosophila. Science 277: 834-836.
16. Saraswati S, Fox LE, Soll DR, Wu CF Tyramine and octopamine have opposite effects on the locomotion of drosophila larvae. Journal of Neurobiology 58.
17. Panuccio A, Bicego M, Murino V (2002) A hidden markov model-based approach to sequential data clustering. Springer Verlag, volume 2396 of Lecture Notes In Computer Science. pp 734-742.
18. Fod A, Mataric MJ, Jenkins OC (2002) Automated derivation of primitives for movement classification. Autonomous Robots 12: 39-54.
19. Pomplun M, Mataric MJ (2001) A segmentation algorithm for the comparison of human limb trajectories. Technical Report IRIS-02-410, Institute for Robotics and Intelligent Systems, School of Engineering, University of Southern California.
20. Galata A, Johnson N, Hogg D (2001) Learning variable length markov models of behaviour. Computer Vision and Image Understanding 81: 398-413.
21. Niemann H (1990) Pattern analysis and understanding Springer series in information sciences; 4. Springer. XIV.
22. Fukunaga K (1990) Introduction to statistical pattern recognition. San DiegoCalif. [u.a.]: Acad. Press. XIII.
23. Duda RO, Hart PE, Stork DG (2001) Pattern classification. New York [u.a.]: Wiley. XX.
24. Geng W, Cosman P, Baek JH, Berry CC, Schafer WR (2003) Quantitative classification and natural clustering of caenorhabditis elegans behavioral phenotypes. Genetics 165: 1117-1126.
25. Thurau C, Bauckhage C, Sagerer G (2004) Synthesizing movements for computer game characters. In: DAGM-Symposium Springer, volume 3175 of Lecture Notes in Computer Science. pp 179-186.
26. Schilstra C, van Hateren J (1998) Using miniature sensor coils for simultaneous measurement of orientation and position of small, fast-moving animals. J Neurosci Methods 83: 125-131.
27. Schilstra C, van Hateren J (1999) Blowfly flight and optic flow. i. thorax kinematics and flight dynamics. JExpBiol 202: 1481-1490.
28. Everitt BS, Landau S, Leese M (2001) Cluster analysis. London: Arnold [u.a.]. VIII.
29. Jambu M, Lebeaux MO (1983) Cluster analysis and data analysis. Amsterdam [u.a.]: North-Holland. XXIV.
30. Härdle W, Simar L (2003) Applied multivariate statistical analysis. Berlin [u.a.]: Springer.
31. Jain AK, Dubes RC (1988) Algorithms for clustering data. Englewood Cliffs, NJ: Prentice Hall. XIV.
32. Kanungo T, Mount DM, Netanyahu NS, Piatko CD, Silverman R, et al. (2002) An efficient k-means clustering algorithm: Analysis and implementation. IEEE Trans Pattern Anal Mach Intell 24: 881-892.
33. Levine E, Domany E (2001) Resampling method for unsupervised estimation of cluster validity. Neural Computation 13: 2573-2593.
34. Dudoit S, Fridlyand J (2002) A prediction-based resampling method for estimating the number of clusters in a dataset. Genome Biology 3: research0036.1-0036.21.
35. Smyth P (2000) Model selection for probalistic clustering using cross-validation likelihood. Statistics and Computing 10: 63-72.
36. Ben-Hur A, Elisseeff A, Guyon I (2002) A stability based method for discovering structure in clustered data. Pacific Symposium on Biocomputing. pp 6-17.
37. Lange T, Roth V, Braun ML, Buhmann JM (2004) Stability-based validation of clustering solutions. Neural Comput 16: 1299-1323.
38. West DB (2001) Introduction to graph theory. Upper Saddle RiverNJ: Prentice Hall. XIX.
39. Milligan G, Cooper M (1985) An examination of procedures for determining the number of clusters in a data set. Psychometrika 50: 159-179.
40. Halkidi M, Batistakis Y, Vazirgiannis M (2001) On clustering validation techniques. Journal of Intelligent Information Systems 17: 107-145.
41. Coggins JM, Jain AK (1985) A spatial filtering approach to texture analysis. Patt Recogn Lett 3: 195-203.
42. van Hateren J, Schilstra C (1999) Blowfly flight and optic flow. ii. head movements during flight. JExpBiol 202: 1491-1500.
43. Böddeker N, Egelhaaf M (2005) A single control system for smooth and saccade-like pursuit in blowflies. J Exp Biol 208: 1563-1572.
44. Lindemann JP, Kern R, Michaelis C, Meyer P, Hateren JHv, et al. (2003) Flimax, a novel stimulus device for panoramic and highspeed presentation of behaviourally generated optic flow. Vision research 43: 779-791.
45. Bobick AF, Ivanov YA (1998) Action recognition using probabilistic parsing. In: In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. pp 196-202.
46. Flash T, Hochner B (2005) Motor primitives in vertebrates and invertebrates. Curr Opin Neurobiol 15: 660-666.