Gan Zhenzhong, Wang Suiping, Feng Gangyi
Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, Guangzhou, Guangdong, China.
Guangdong Provincial Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, Guangdong, China.
Data Brief. 2023 Feb 10;47:108972. doi: 10.1016/j.dib.2023.108972. eCollection 2023 Apr.
How people learn and represent auditory categories in the brain is a fundamental question in auditory neuroscience. Answering this question could provide insights into our understanding of the neurobiology of speech learning and perception. However, the neural mechanisms underlying auditory category learning are far from understood. We have revealed that the neural representations of auditory categories emerge during category training, and the type of category structures drives the emerging dynamics of the representations [1]. The dataset introduced here was derived from [1], where we collected to examine the neural dynamics underlying the acquisition of two distinct category structures: rule-based (RB) and information-integration (II) categories. Participants were trained to categorize these auditory categories with trial-by-trial corrective feedback. The functional magnetic resonance imaging (fMRI) technique was used to assess the neural dynamics related to the category learning process. Sixty adult Mandarin native speakers were recruited for the fMRI experiment. They were assigned to either the RB ( = 30, 19 females) or II ( = 30, 22 females) learning task. Each task consisted of six training blocks where each consisting of 40 trials. Spatiotemporal multivariate representational similarity analysis has been used to examine the emerging patterns of neural representations during learning [1]. This open-access dataset could potentially be reused to investigate a range of neural mechanisms (e.g., functional network organizations underlying learning of different structures of categories and neuromarkers associated with individual behavioral learning success) involved in auditory category learning.
人们如何在大脑中学习和表征听觉类别是听觉神经科学中的一个基本问题。回答这个问题有助于我们深入理解言语学习和感知的神经生物学机制。然而，听觉类别学习背后的神经机制仍远未被理解。我们已经揭示，听觉类别的神经表征在类别训练过程中出现，并且类别结构的类型驱动了表征的动态形成[1]。这里介绍的数据集源自[1]，在那里我们收集数据以研究获取两种不同类别结构（基于规则的（RB）和信息整合（II）类别）背后的神经动力学。参与者通过逐次试验的纠正反馈来训练对这些听觉类别进行分类。功能磁共振成像（fMRI）技术被用于评估与类别学习过程相关的神经动力学。60名以普通话为母语的成年人被招募参与fMRI实验。他们被分配到RB（n = 30，19名女性）或II（n = 30，22名女性）学习任务。每个任务由六个训练块组成，每个训练块包含40次试验。时空多变量表征相似性分析已被用于研究学习过程中神经表征的出现模式[1]。这个开放获取的数据集有可能被重新用于研究一系列与听觉类别学习相关的神经机制（例如，不同类别结构学习背后的功能网络组织以及与个体行为学习成功相关的神经标记物）。
