Analysing animal path trajectories in terms of individual behavioral acts

T.V. Mukhina1, A.O. Lukashev2, K.V. Anokhin2 and S.O. Bachurin1

1Neurochemistry Laboratory, Institute of Physiologically Active Compounds, Chernogolovka, Moscow, Russian Federation
2Anokhin Institute of Normal Physiology, Moscow, Russian Federation

 

Standard approaches to the analysis of movement trajectories with video-tracking systems (e.g. EthoVision [1]), using such measurements as track length or time in zones of interest, provide useful information about animal behavior in tests like the open field or Morris water maze. However, such cumulative characteristics are related only indirectly to the complex organization of an animal’s motivated behavior and learning. On the other hand, coding systems (e.g. The Observer [2]) are able to supply data on the units and structure of behavior, but lack detailed spatial information. The objective of the present study, therefore, was to develop an approach for isolating and analyzing individual acts within the behavioral continuum, using path trajectories from BVision video-tracking software [3].

To perform such an analysis, we first divide a continuous movement trajectory into individual behavioral acts, each of which is defined as a component of the behavioral continuum from the result of one goal-directed activity to another [4]. The points of separation between behavioral acts are chosen as points of minimal activity, i.e. the moments of drastic decrease in speed of movement [5]. Functional affiliation of these acts is achieved using a coding system, and the ensuing pattern is analyzed to reveal the structure of exploratory behavior or performance strategies within different learning tasks. In this way, the behavioral trajectory of an animal in an experimental session can be described, making it possible to find differences in behavior between different groups of animals, or to study the evolution of behavioral patterns of animals within the same group. We have developed corresponding software for the functional analysis of rat and mouse path trajectories.

References

  1. Noldus, L.P.; Spink, A.J.; Tegelenbosch, R.A. (2001). EthoVision: a versatile video tracking system for automation of behavioral experiments. Behavior Research Methods, Instruments & Computers, 33, 398-414.
  2. Noldus, L.P.J.J.; Trienes, R.J.H.; Hendriksen, A.H.M.; Jansen, H.; Jansen, R.G. (2000). The Observer Video-Pro: new software for the collection, management and presentation of time-structured data from videotapes and digital media files. Behavior Research Methods, Instruments & Computers, 32, 197-206.
  3. Mukhina, T.V.; Bachurin, S.O.; Lermontova, N.N.; Zefirov, N.S. (2001). Versatile computerized system for tracking and analysis of water maze tests. Behavior Research Methods, Instruments & Computers, 33, 371-380.
  4. Anokhin, P.K. (1968). The functional system as a unit of organism integrative activity. Pp. 376-403 in: Mesarovic, M.D., ed. Systems Theory and Biology. New York: Springer Verlag.
  5. Drai, I.; Benjamini, Y.; Golani, I. (2000). Statistical discrimination of natural modes of motion in rat exploratory behavior. Journal of Neuroscience Methods, 96, 119-131.

Paper presented at Measuring Behavior 2002 , 4th International Conference on Methods and Techniques in Behavioral Research, 27-30 August 2002, Amsterdam, The Netherlands

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