Vocalization categorization behavior explained by a feature-based auditory categorization model.
Vocalization categorization behavior explained by a feature-based auditory categorization model.
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DOI：
10.7554/elife.78278
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发表时间：
2022-10-13
期刊：
影响因子：
7.7
通讯作者：
Sadagopan S
中科院分区：
文献类型：
--
作者：
Kar M;Pernia M;Williams K;Parida S;Schneider NA;McAndrew M;Kumbam I;Sadagopan S
发声动物会产生多种不同种类的叫声，这些叫声具有很高的主体之间和主体内部的可变性，听众必须对这些叫声进行概括才能完成分类。支持这种概括能力的行为策略和神经机制在很大程度上尚未被探索。我们之前提出了一个理论模型，该模型通过检测中等复杂性的特征来完成呼叫分类，这些特征可以最好地将每个呼叫类别与所有其他类别进行对比。我们进一步证明了初级听觉皮层的一些神经反应与这种模型是一致的。在这里，我们询问基于特征的模型是否可以预测呼叫分类行为。我们训练模型和豚鼠（GPs）使用自然呼叫进行呼叫分类任务。然后，我们通过使用时间和频谱改变的呼叫来测试模型和GPs的分类。模型和全球定位系统都对时间操纵具有惊人的弹性，但对中度频移很敏感。关键是，该模型预测了GP行为中约50%的方差。通过采用不同的模型训练策略和检查有助于解决特定任务的特征，我们可以深入了解动物用于分类呼叫的可能策略。我们的结果验证了一个模型，该模型使用检测中等复杂性的对比特征来完成呼叫分类。
Vocal animals produce multiple categories of calls with high between- and within-subject variability, over which listeners must generalize to accomplish call categorization. The behavioral strategies and neural mechanisms that support this ability to generalize are largely unexplored. We previously proposed a theoretical model that accomplished call categorization by detecting features of intermediate complexity that best contrasted each call category from all other categories. We further demonstrated that some neural responses in the primary auditory cortex were consistent with such a model. Here, we asked whether a feature-based model could predict call categorization behavior. We trained both the model and guinea pigs (GPs) on call categorization tasks using natural calls. We then tested categorization by the model and GPs using temporally and spectrally altered calls. Both the model and GPs were surprisingly resilient to temporal manipulations, but sensitive to moderate frequency shifts. Critically, the model predicted about 50% of the variance in GP behavior. By adopting different model training strategies and examining features that contributed to solving specific tasks, we could gain insight into possible strategies used by animals to categorize calls. Our results validate a model that uses the detection of intermediate-complexity contrastive features to accomplish call categorization.
影响因子：
9.2
作者：
Russ, Brian E.;Orr, Lauren E.;Cohen, Yale E.
通讯作者：
Cohen, Yale E.
影响因子：
3.7
作者：
Ojima H;Taira M;Kubota M;Horikawa J
通讯作者：
Horikawa J