A novel method for automatic quantification of psychostimulant-evoked route-tracing stereotypy: Application to Mus musculus

Stephen J. Bonasera, A. Katrin Schenk, Evan J. Luxenberg, Laurence H. Tecott

Research output: Contribution to journalArticlepeer-review

36 Scopus citations


Rationale: Route-tracing stereotypy is a powerful behavioral correlate of striatal function that is difficult to quantify. Measurements of route-tracing stereotypy in an automated, high throughput, easily quantified, and replicable manner would facilitate functional studies of this central nervous system region. Objective: We examined how t-pattern sequential analysis (Magnusson Behav Res Meth Instrum Comput 32:93-110, 2000) can be used to quantify mouse route-tracing stereotypies. This method reveals patterns by testing whether particular sequences of defined states occur within a specific time interval at a probability greater than chance. Results: Mouse home-cage locomotor patterns were recorded after psychostimulant administration (GBR 12909, 0, 3, 10, and 30 mg/kg; d-amphetamine, 0, 2.5, 5, and 10 mg/kg). After treatment with GBR 12909, dose-dependent increases in the number of found patterns and overall pattern length and depth were observed. Similar findings were seen after treatment with d-amphetamine up to the dosage where focused stereotypies dominated behavioral response. For both psychostimulants, detected patterns displayed similar morphological features. Pattern sets containing a few frequently repeated patterns of greater length/depth accounted for a greater percentage of overall trial duration in a dose-dependant manner. This finding led to the development of a t-pattern-derived route-tracing stereotypy score. Compared to scores derived by manual observation, these t-pattern-derived route-tracing stereotypy scores yielded similar results with less within-group variability. These findings remained similar after reanalysis with removal of patterns unmatched after human scoring and after normalization of locomotor speeds at low and high ranges. Conclusions: T-pattern analysis is a versatile and robust pattern detection and quantification algorithm that complements currently available observational phenotyping methods.

Original languageEnglish (US)
Pages (from-to)591-602
Number of pages12
Issue number4
StatePublished - Mar 2008
Externally publishedYes


  • Behavioral pattern detection
  • Behavioral pattern differentiation
  • Behavioral phenotyping
  • GBR 12909 (vanoxerine)
  • Mouse
  • Sequential analysis
  • Stereotypy, route-tracing
  • T-pattern
  • d-amphetamine

ASJC Scopus subject areas

  • Pharmacology

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