Behavioral phenotyping is an essential part of neuro-active drug discovery and predictive neurotoxicology. Due to limitations of conventional rodent in vivo models, chemobehavioral phenotypic analysis utilizing innovative small model organisms; such as nematodes, planarians and zebrafish are emerging as distinctively advantageous for high-throughput phenotypic discovery of neuroceuticals and evaluating deleterious effects of industrial pollutants on central nervous system. Digital film recording with subsequent analysis of video sequences using specialised animal tracking software has become a standard in obtaining behavioral biometric data. At present animal tracking algorithms are largely capable of detecting and tracking small number of animals and extracting quantitative endpoints associated with specific behavioral traits based on reconstruction of movement trajectories and occupancy heatmaps. However, despite recent and significant progress in development of diverse proxy biological models, the software algorithms still lack the ability to track multiple organisms on a large scale, automatically generate behavioral fingerprints and utilize intensive computational approaches to mine rich biometric data. This creates a significant bottleneck for effective high-throughput chemobehavioral screening in drug discovery and neurotoxicology. This review outlines recent advances as well as limitations of high-throughput animal tracking and provides an outlook on future developments in rapidly evolving field of neurobehavioral phenomics.

中文翻译：

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化学行为表型中的高通量动物追踪：当前的局限性和未来的前景

行为表型是神经活性药物发现和预测神经毒理学的重要组成部分。由于常规啮齿动物体内模型的局限性，利用创新的小型模型生物进行化学行为表型分析；线虫、涡虫和斑马鱼等动物正在成为神经药物的高通量表型发现和评估工业污染物对中枢神经系统的有害影响的独特优势。使用专门的动物跟踪软件对视频序列进行后续分析的数字电影录制已成为获取行为生物特征数据的标准。目前，动物跟踪算法在很大程度上能够检测和跟踪少量动物，并基于重建运动轨迹和占用热图提取与特定行为特征相关的定量端点。然而，尽管最近在开发各种代理生物模型方面取得了重大进展，但软件算法仍然缺乏大规模跟踪多种生物、自动生成行为指纹和利用密集计算方法来挖掘丰富的生物特征数据的能力。这为药物发现和神经毒理学中有效的高通量化学行为筛选创造了重大瓶颈。