■通常使用条件冻结或抑制操作性反应来评估对威胁相关线索的防御性反应。然而,大鼠表现出广泛的行为,并根据威胁和上下文的即时性改变其防御行为。这项研究旨在系统地量化响应威胁相关线索而触发的防御行为,并评估是否可以使用DeepLabCut与SimBA一起准确识别它们。
■我们使用听觉恐惧条件范式评估了对恐惧的行为反应。使用EthovisionXT对由威胁相关线索触发的可观察行为进行手动评分。随后,我们研究了地西泮(0、0.3或1mg/kg)的作用,在恐惧记忆测试之前腹膜内给药,评估其对这些行为的抗焦虑作用。然后,我们使用一系列机器学习模型开发了DeepLabCut+SimBA用于道德分析的工作流程。通过将其输出分数与手动注释的分数进行比较来评估由该管道生成的行为分类的准确性。
■我们的研究结果表明,除了条件抑制和冻结,大鼠表现出高度的风险评估行为,包括嗅探,饲养,自由空气搅拌,头部扫描。我们观察到地西泮剂量依赖性地减轻了两性的这些风险评估行为,表明我们的读数有很好的预测有效性。有足够的训练数据(大约>30,000帧包含此类行为),DeepLabCut+SimBA工作流程产生了高准确性和合理的可转移性,可以在不同的实验条件下对表现良好的行为进行分类。我们还发现,在开发DeepLabCut+SimBA工作流程时,建议在训练和评估数据集之间保持相同的条件,以实现最高的准确性。
■我们的研究结果表明,行为学分析可用于评估恐惧学习。随着DeepLabCut和SimBA的应用,这种方法为解码雄性和雌性大鼠的持续防御行为提供了一种替代方法,用于进一步研究与恐惧相关的神经生物学基础.
UNASSIGNED: Defensive responses to threat-associated cues are commonly evaluated using conditioned freezing or suppression of operant responding. However, rats display a broad range of behaviors and shift their defensive behaviors based on immediacy of threats and context. This study aimed to systematically quantify the defensive behaviors that are triggered in response to threat-associated cues and assess whether they can accurately be identified using DeepLabCut in conjunction with SimBA.
UNASSIGNED: We evaluated behavioral responses to fear using the auditory fear conditioning paradigm. Observable behaviors triggered by threat-associated cues were manually scored using Ethovision XT. Subsequently, we investigated the effects of diazepam (0, 0.3, or 1 mg/kg), administered intraperitoneally before fear memory testing, to assess its anxiolytic impact on these behaviors. We then developed a DeepLabCut + SimBA workflow for ethological analysis employing a series of machine learning models. The accuracy of behavior classifications generated by this pipeline was evaluated by comparing its output scores to the manually annotated scores.
UNASSIGNED: Our findings show that, besides conditioned suppression and freezing, rats exhibit heightened risk assessment behaviors, including sniffing, rearing, free-air whisking, and head scanning. We observed that diazepam dose-dependently mitigates these risk-assessment behaviors in both sexes, suggesting a good predictive validity of our readouts. With adequate amount of training data (approximately > 30,000 frames containing such behavior), DeepLabCut + SimBA workflow yields high accuracy with a reasonable transferability to classify well-represented behaviors in a different experimental condition. We also found that maintaining the same condition between training and evaluation data sets is recommended while developing DeepLabCut + SimBA workflow to achieve the highest accuracy.
UNASSIGNED: Our findings suggest that an ethological analysis can be used to assess fear learning. With the application of DeepLabCut and SimBA, this approach provides an alternative method to decode ongoing defensive behaviors in both male and female rats for further investigation of fear-related neurobiological underpinnings.