Jackdaws form categorical prototypes based on experience with category exemplars.

IF 2.7 3区 医学 Q1 ANATOMY & MORPHOLOGY Brain Structure & Function Pub Date : 2024-04-01 Epub Date: 2023-06-01 DOI:10.1007/s00429-023-02651-w
Aylin Apostel, Lukas Alexander Hahn, Jonas Rose
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Abstract

Categorization represents one cognitive ability fundamental to animal behavior. Grouping of elements based on perceptual or semantic features helps to reduce processing resources and facilitates appropriate behavior. Corvids master complex categorization, yet the detailed categorization learning strategies are less well understood. We trained two jackdaws on a delayed match to category paradigm using a novel, artificial stimulus type, RUBubbles. Both birds learned to differentiate between two session-unique categories following two distinct learning protocols. Categories were either introduced via central category prototypes (low variability approach) or using a subset of diverse category exemplars from which diagnostic features had to be identified (high variability approach). In both versions, the stimulus similarity relative to a central category prototype explained categorization performance best. Jackdaws consistently used a central prototype to judge category membership, regardless of whether this prototype was used to introduce distinct categories or had to be inferred from multiple exemplars. Reliance on a category prototype occurred already after experiencing only a few trials with different category exemplars. High stimulus set variability prolonged initial learning but showed no consistent beneficial effect on later generalization performance. High numbers of stimuli, their perceptual similarity, and coherent category structure resulted in a prototype-based strategy, reflecting the most adaptive, efficient, and parsimonious way to represent RUBubble categories. Thus, our birds represent a valuable comparative animal model that permits further study of category representations throughout learning in different regions of a brain producing highly cognitive behavior.

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鸦雀根据对类别范例的经验形成类别原型。
分类是动物行为的一种基本认知能力。根据感知或语义特征对元素进行分组有助于减少处理资源,并促进适当的行为。鸦科鸟类掌握了复杂的分类能力,但对详细的分类学习策略却不甚了解。我们使用一种新颖的人工刺激类型--RUBubbles,对两只松鸦进行了延迟匹配分类范式训练。这两只鸟通过两种不同的学习方案学会了区分两个会话中的独特类别。类别是通过中心类别原型(低变异性方法)或使用不同类别范例的子集引入的,必须从中识别出诊断特征(高变异性方法)。在这两种方法中,刺激物相对于中心类别原型的相似性最能解释分类结果。豺始终使用一个中心原型来判断类别成员资格,无论该原型是用于引入不同的类别,还是必须从多个示例中推断出来。在经历了几次不同类别范例的试验后,就已经开始依赖类别原型了。刺激集的高变异性延长了最初的学习时间,但对后来的泛化表现却没有持续的有利影响。大量的刺激物、感知上的相似性以及连贯的类别结构形成了一种基于原型的策略,反映了表示 RUBubble 类别的最适应、最有效和最简洁的方法。因此,我们的鸟类是一种有价值的比较动物模型,可以进一步研究产生高度认知行为的大脑不同区域在整个学习过程中的类别表征。
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来源期刊
Brain Structure & Function
Brain Structure & Function 医学-解剖学与形态学
CiteScore
6.00
自引率
6.50%
发文量
168
审稿时长
8 months
期刊介绍: Brain Structure & Function publishes research that provides insight into brain structure−function relationships. Studies published here integrate data spanning from molecular, cellular, developmental, and systems architecture to the neuroanatomy of behavior and cognitive functions. Manuscripts with focus on the spinal cord or the peripheral nervous system are not accepted for publication. Manuscripts with focus on diseases, animal models of diseases, or disease-related mechanisms are only considered for publication, if the findings provide novel insight into the organization and mechanisms of normal brain structure and function.
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