Quantifying behavior to understand the brain

Pereira, Talmo; Shaevitz, Joshua W.; Murthy, Mala

doi:10.1038/s41593-020-00734-z

Cited by 211 publications

(167 citation statements)

References 125 publications

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“…and not always present across experiments. Assessing divergent defensive strategies in male and female rats may require machine learning-based behavioral scoring methods (Mathis et al, 2018;Pereira et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…We do report here that female rats frequently show increased freezing during SCS habituation and conditioning, although the effects were small and not always present across experiments. Assessing divergent defensive strategies in male and female rats may require machine learning-based behavioral scoring methods (Mathis et al, 2018; Pereira et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

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Behavioral and brain mechanisms mediating conditioned flight behavior in rats

Totty

Warren

Huddleston

et al. 2021

Preprint

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Environmental contexts and associative learning can inform animals of potential threats, though it is currently unknown how contexts bias defensive transitions. Here we investigated context-dependent flight responses in the Pavlovian serial-compound stimulus (SCS) paradigm. We show here that SCS-evoked flight behavior in male and female rats is dependent on contextual fear. Flight was reduced in the conditioning context after context extinction and could be evoked in a different shock-associated context. Although flight was exclusive to white noise stimuli, it was nonetheless associative insofar as rats that received an equal number of unpaired USs did not show flight-like behavior. Finally, we found that inactivation of either the central nucleus of the amygdala (CeA) or bed nucleus of the stria terminalis (BNST) attenuated both contextual fear and flight responses. This work demonstrates that contextual fear summates with cued and innate fear to drive a high fear state and freeze-to-flight transitions.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Behavioral and brain mechanisms mediating conditioned flight behavior in rats

Totty

Warren

Huddleston

et al. 2021

Preprint

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“…These details can now be extracted efficiently using modern computational methods. Recent advances in automated tracking open the possibility of deep behavioral phenotyping consisting of simultaneous tracking of body-centric joint and body part positions, x-y position in an arena, and task performance, thereby providing a multilevel view of behavior [3,7,15,34]. This allows the measurement of both movement and cognitive/social features from a single dataset [20,21].…”

Section: Introductionmentioning

confidence: 99%

Deep Behavioral Phenotyping of Mouse Autism Models using Open-Field Behavior

Klibaite¹,

Kislin

Verpeut

et al. 2021

Preprint

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Autism is noted for both its genotypic and phenotypic diversity. Repetitive action, resistance to environmental change, and motor disruptions vary from individual to individual. In animal models, conventional behavioral phenotyping captures such fine-scale variations incompletely. Here we use advances in computer vision and deep learning to develop a framework for characterizing mouse behavior on multiple time scales using a single popular behavioral assay, the open field test. We observed male and female C57BL/6J mice to develop a dynamic baseline of adaptive behavior over multiple days. We then examined two rodent models of autism, a cerebellum-specific model, L7-Tsc1, and a whole-brain knockout model, Cntnap2. Both Cntnap2 knockout and L7-Tsc1 mutants showed forelimb lag during gait. L7-Tsc1 mutants showed complex defects in multi-day adaptation, lacking the tendency of wild-type mice to spend progressively more time in corners of the arena. In L7-Tsc1 mutant mice, failure-to-adapt took the form of maintained ambling, turning, and locomotion, and an overall decrease in grooming. Adaptation in Cntnap2 knockout mice more broadly resembled that of wild-type. L7-Tsc1 mutant and Cntnap2 knockout mouse models showed different patterns of behavioral state occupancy. Our automated pipeline for deep phenotyping successfully captures model-specific deviations in adaptation and movement as well as differences in the detailed structure of behavioral dynamics.

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“…A major breakthrough in recent years has been the development of artificial intelligence and deep learning methods as promising solutions for improved scoring of behaviour expressed by animals in test situations [59][60][61][62][63]. Machine learning approaches bring enormous potential for automated, precise and unbiased scoring (notwithstanding the limitation that the (supervised) learning requires annotation of behaviours by a human) or the exploration and detection of novel behavioural sequences and patterns (unsupervised learning).…”

Section: P a G Ementioning

confidence: 99%

The Open Field Test

Võikar¹,

sC²

2021

Preprint

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The Open Field Test (OFT) is the most widely used method for observing the behaviour of mice and rats under laboratory conditions. It is used to evaluate the exploratory behaviour, general locomotor activity and emotionality of rats and mice. However, it has to be kept in mind that these behaviours are not independent, they interact and so a change in one will affect another. Despite being a seemingly simple test, several caveats need to be acknowledged when selecting the variables for analysis and interpreting the data with regard to the aforementioned domains. The observed behaviours can depend on a number of procedural, environmental and biological factors, which should be carefully considered when planning the experiment, as well as during the analysis and interpretation of the results. This review provides a critical overview of these factors, followed by some warnings and practical tips for conducting the OFT.

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Quantifying behavior to understand the brain

Cited by 211 publications

References 125 publications

Behavioral and brain mechanisms mediating conditioned flight behavior in rats

Behavioral and brain mechanisms mediating conditioned flight behavior in rats

Deep Behavioral Phenotyping of Mouse Autism Models using Open-Field Behavior

The Open Field Test

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