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A system monitoring social interactions in rodents

Technology Number: 

1593

Principal Investigator

Prof.
Alon
Chen

Department: 

Neurobiology

Patent Status: 

Pending
Summary 

The study of social behavior in groups of mice may have crucial implications for understanding the social aspects of different disorders. 
To be executed correctly, group studies require the ability to track individual’s behavior within the group structure. The main challenge of current research tools is to allow individuals identification while maintaining sufficient resolution for accurate tracking.
The present technology provides a system that utilizes fluorescent fur dyes to differentially mark and track individuals within a group. Using a sensitive color camera and a newly designed tracking algorithm, behavior of groups may be recorded and analyzed with high temporal and spatial resolution.   
The technology further offers a method for characterizing the group’s interactions using the maximum entropy model.

 

Applications


 


Advantages


  • High spatial and temporal resolution – enabled by sensitive color video tracking.
  • Enables high detailed analysis of individual behavior within the group.
  • Suitable for community study of groups - limited only by available fur dyes.
  • Compatible with long-term analysis.
  • Simple, cost effective.
  • Minimal suffering and improved animal welfare.

  • Technology's Essence


    The present technology takes advantage of the fact that mice are nocturnal (active at night) animals, to mark their fur with different fluorescent dyes. Under ultraviolet light, the mice can be accurately and automatically tracked, over a number of days. As the mice are allowed to move freely in an interesting arena for exploration containing ramps, nest boxes and barriers (Figure 1), their trajectory and behavior are recorded using a sensitive color camera.
    The system further includes an image processing module which analyses the recorded images, calculates a spatiotemporal model and the nature of social interactions between individuals.
    Combining detailed behavioral and genetic analysis ate the level of individuals, in association with group analysis, may enable the identification of genetic and neuronal correlates of complex social interactions.