Sensing the Sounds of Silence: A Pilot Study on the Detection of Model Mice of Autism Spectrum Disorder from Ultrasonic Vocalisations
Sensing the Sounds of Silence: A Pilot Study on the Detection of Model Mice of Autism Spectrum Disorder from Ultrasonic Vocalisations
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感知寂静的声音：通过超声波发声检测自闭症谱系障碍模型小鼠的初步研究
DOI：
10.1109/embc46164.2021.9630793
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Yamamoto Y.
中科院分区：
文献类型：
--
作者：
Qian K;Koike T;Tamada K;Takumi T;Schuller BW;Yamamoto Y.
Studying the animal models of human neuropsychiatric disorders can facilitate the understanding of mechanisms of symptoms both physiologically and genetically. Previous studies have shown that ultrasonic vocalisations (USVs) of mice might be efficient markers to distinguish the wild type group and the model of autism spectrum disorder (mASD). Nevertheless, in-depth analysis of these ‘silence’ sounds by leveraging the power of advanced computer audition technologies (e. g., deep learning) is limited. To this end, we propose a pilot study on using a large-scale pre-trained audio neural network to extract high-level representations from the USVs of mice for the task on detection of mASD. Experiments have shown a best result reaching an unweighted average recall of 79.2 % for the binary classification task in a rigorous subject-independent scenario. To the best of our knowledge, this is the first time to analyse the sounds that cannot be heard by human beings for the detection of mASD mice. The novel findings can be significant to motivate future works with according means on studying animal models of human patients.
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DOI：
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期刊：
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