SaLSa: a combinatory approach of semi-automatic labeling and long short-term memory to classify behavioral syllables
SaLSa: a combinatory approach of semi-automatic labeling and long short-term memory to classify behavioral syllables
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SaLSa：半自动标记和长短期记忆的组合方法对行为音节进行分类
DOI：
10.1101/2023.04.05.535796
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Sakata S
中科院分区：
文献类型：
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作者：
Sakata S
准确和定量地描述老鼠的行为是一个重要的领域。尽管机器学习的进步使得准确地跟踪它们的行为成为可能，但行为序列或音节的可靠分类仍然是一个挑战。在这项研究中，我们提出了一种新的机器学习方法，称为SaLSa（半自动标记和基于长短期记忆的分类的结合），用于对探索开放领域的小鼠的行为音节进行分类。这种方法包括两个主要步骤。首先，在对多个身体部位进行跟踪后，提取其自我中心坐标的时空特征；一个完全自动化的无监督过程识别行为音节的候选，然后使用图形用户界面（GUI）手动标记行为音节。其次，使用标记数据训练长短期记忆分类器。我们发现分类性能在97%以上。在对一些音节进行分类时，它提供了相当于最先进的模型的性能。我们应用这种方法来研究阿尔茨海默病小鼠模型中的多动症是如何随着年龄的增长而发展的。当每个行为音节的比例在基因型和性别之间进行比较时，我们发现雌性阿尔茨海默病小鼠的特征性过度运动出现在4到8个月之间。相比之下，无论基因型和性别如何，与年龄相关的饲养减少是常见的。总的来说，SaLSa可以详细描述小鼠的行为。
Accurately and quantitatively describing mouse behavior is an important area. Although advances in machine learning have made it possible to track their behaviors accurately, reliable classification of behavioral sequences or syllables remains a challenge. In this study, we present a novel machine learning approach, called SaLSa (a combination of semi-automatic labeling and long short-term memory-based classification), to classify behavioral syllables of mice exploring an open field. This approach consists of two major steps. First, after tracking multiple body parts, spatial and temporal features of their egocentric coordinates are extracted. A fully automated unsupervised process identifies candidates for behavioral syllables, followed by manual labeling of behavioral syllables using a graphical user interface (GUI). Second, a long short-term memory (LSTM) classifier is trained with the labeled data. We found that the classification performance was marked over 97%. It provides a performance equivalent to a state-of-the-art model while classifying some of the syllables. We applied this approach to examine how hyperactivity in a mouse model of Alzheimer’s disease develops with age. When the proportion of each behavioral syllable was compared between genotypes and sexes, we found that the characteristic hyperlocomotion of female Alzheimer’s disease mice emerges between four and eight months. In contrast, age-related reduction in rearing is common regardless of genotype and sex. Overall, SaLSa enables detailed characterization of mouse behavior.