Mathematics and Computer Science
Research Tools

Monitoring and Classifying Complex Social Interactions (No. T4-1571)

Lead Researcher: Prof. Tali Kimchi


A novel social behavior monitoring system automatically tracks the precise location of each animal at excellent temporal resolution. This innovative technology provides simultaneous identification of complex social and individual behaviors via an integration of RFID and video surveillance.
There is a rapidly growing interest in detecting the molecular substrates of social behavior. This interest is driven by the vast implications of such understanding in both research and the pharmaceutical industry, since some prevalent pathological conditions are mainly characterized by a behavioral deficit or abnormality.
It is extremely challenging to quantify social behavior in a reliable manner. Existing methods struggle to find a balance between objectively quantifying behavior on one hand while enabling a natural, stress-free behavioral estimation on the other hand. Currently, researchers work in a strictly controlled and constrained environment that is estranged and stressful to the animals. The outcome is a highly contaminated measurement of natural behavior. This difficultly becomes increasingly complex when more than one animal is involved as often applied in social behavioral studies.


  • Rigorous characterization of social organizational deficiencies and evaluation of their severity in animal and human models (for example in autism).

  • An optimized system for estimating the efficacy of clinical treatments.
  • Advantages

  • Long-term tracking of unlimited number of simultaneously studied animals.

  • Machine based, hence objective and automated quantification of behavior.

  • Excellent spatiotemporal resolution in semi natural environment

  • Flexible- the number, size and distribution of the RFID antennas can be adjusted with different enclosure dimensions.

  • Can be applied from Individual behavioral profile or pairs interactions up to collective social organization of groups.

  • Systematic analysis and classification of basic locomotion up to more complex social
  • Technology's Essence

    Researchers at the Weizmann institute developed a method for tightly controlled monitoring of social behavior in a semi-natural environment. They used integrated and synchronized chip reporting and continuous video postage to precisely locate each individual animal. Using this automated monitoring which provides an exceptional temporal resolution they achieved correct identification of numerous basic individual behaviors as well as complex social behaviors. Such complex behavioral profiles set the basis for subsequent analysis which reveals the formation of a social hierarchy.