SEE locomotor behavior test discriminates C57BL/6J and DBA/2J mouse inbred strains across laboratories and protocol conditions.

Kafkafi, Neri; Lipkind, Dina; Benjamini, Yoav; Mayo, Cheryl L.; Elmer, Gregory I.; Golani, Ilan

doi:10.1037/0735-7044.117.3.464

Cited by 77 publications

(70 citation statements)

References 52 publications

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“…EthoVision was used to calculate the total distance traveled as well as the time spent and the number of entries into the center square area (20 × 20 cm). SEE (Software for the Exploration of Exploration; Kafkafi et al, 2003) was used to smooth path shape and calculate specific measures of locomotor behavior. SEE uses the distribution of speed peaks to parse the locomotor data slow local movements (so-called lingering episodes) and progression segments.…”

Section: Open Field Testmentioning

confidence: 99%

Ubiquitin ligase TRIM3 controls hippocampal plasticity and learning by regulating synaptic γ-actin levels

Schreiber¹,

Végh²,

Dawitz³

et al. 2015

J Exp Med

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Section: Open Field Testmentioning

confidence: 99%

Ubiquitin ligase TRIM3 controls hippocampal plasticity and learning by regulating synaptic γ-actin levels

Schreiber¹,

Végh²,

Dawitz³

et al. 2015

J Exp Med

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“…Open-field tests were conducted during the light phase of the cycle using the standard procedure in SEE (Software for the Exploration of Exploration; see Drai and Golani, 2001;Kafkafi et al, 2003a;. Briefly, each animal was injected once and immediately introduced to a 2.50 m diameter circular open-field arena for 60 min while its location was tracked using Noldus EthoVision video-tracking system at a rate of 30 Hz and the highest video resolution (480 Â 640 pixel).…”

Section: Drugs Animals and Experimental Proceduresmentioning

confidence: 99%

A Data Mining Approach to In Vivo Classification of Psychopharmacological Drugs

Kafkafi

Yekutieli

Elmer

2008

Neuropsychopharmacol

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Data mining is a powerful bioinformatics strategy that has been successfully applied in vitro to screen for gene-expression profiles predicting toxicological or carcinogenic response ('class predictors'). In this report we used a data mining algorithm named Pattern Array (PA) in vivo to analyze mouse open-field behavior and characterize the psychopharmacological effects of three drug classesFpsychomotor stimulant, opioid, and psychotomimetic. PA represents rodent movement with B100 000 complex patterns, defined as multiple combinations of several ethologically relevant variables, and mines them for those that maximize any effect of interest, such as the difference between drug classes. We show that PA can discover behavioral predictors of all three drug classes, thus developing a reliable drug-classification scheme in small group sizes. The discovered predictors showed orderly dose dependency despite being explicitly mined only for class differences, with the high doses scoring 4-10 standard deviations from the vehicle group. Furthermore, these predictors correctly classified in a dose-dependent manner four 'unknown' drugs (ie that were not used in the training process), and scored a mixture of a psychomotor stimulant and an opioid as being intermediate between these two classes. The isolated behaviors were highly heritable (h 2 450%) and replicable as determined in 10 inbred strains across three laboratories. PA can in principle be applied for mining behaviors predicting additional properties, such as within-class differences between drugs and within-drug dose-response, all of which can be measured automatically in a single session per animal in an open-field arena, suggesting a high potential as a tool in psychotherapeutic drug discovery.

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“…This approach, however, was not applied to locomotor patterns of arbitrary morphology and did not address pattern temporal structure, a fundamental limitation of simple Markov models. Algorithms that identify individual bouts of locomotor activity have also been reported (Drai et al 2000;Drai and Golani 2001;Golani et al 1999;Kafkafi et al 2003), but these techniques are not readily adaptable to the quantification of route-tracing stereotypies. Finally, in a novel use of ergodic theory, Paulus and colleagues demonstrated that both metric and topological entropy parameters could describe increased home-cage stereotypical locomotor behavior after psychostimulant treatment (Paulus et al 1990(Paulus et al , 1999Paulus and Geyer 1991).…”

Section: Introductionmentioning

confidence: 99%

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

Bonasera

Schenk

Luxenberg³

et al. 2007

Psychopharmacology

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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 damphetamine 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-patternderived route-tracing stereotypy score. Compared to scores derived by manual observation, these tpattern-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-patternanalysis is a versatile and robust pattern detection and quantification algorithm that complements currently available observational phenotyping methods.

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SEE locomotor behavior test discriminates C57BL/6J and DBA/2J mouse inbred strains across laboratories and protocol conditions.

Cited by 77 publications

References 52 publications

Ubiquitin ligase TRIM3 controls hippocampal plasticity and learning by regulating synaptic γ-actin levels

Ubiquitin ligase TRIM3 controls hippocampal plasticity and learning by regulating synaptic γ-actin levels

A Data Mining Approach to In Vivo Classification of Psychopharmacological Drugs

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

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