Department of Neuroscience, Georgetown University Medical Center, Washington, DC, USA.
Department of Neuroscience, Georgetown University Medical Center, Washington, DC, USA; Institute for Advanced Study, Technische Universität München, Germany.
Neuron. 2018 Apr 18;98(2):405-416.e4. doi: 10.1016/j.neuron.2018.03.014.
Grouping auditory stimuli into common categories is essential for a variety of auditory tasks, including speech recognition. We trained human participants to categorize auditory stimuli from a large novel set of morphed monkey vocalizations. Using fMRI-rapid adaptation (fMRI-RA) and multi-voxel pattern analysis (MVPA) techniques, we gained evidence that categorization training results in two distinct sets of changes: sharpened tuning to monkey call features (without explicit category representation) in left auditory cortex and category selectivity for different types of calls in lateral prefrontal cortex. In addition, the sharpness of neural selectivity in left auditory cortex, as estimated with both fMRI-RA and MVPA, predicted the steepness of the categorical boundary, whereas categorical judgment correlated with release from adaptation in the left inferior frontal gyrus. These results support the theory that auditory category learning follows a two-stage model analogous to the visual domain, suggesting general principles of perceptual category learning in the human brain.
将听觉刺激分为常见类别对于各种听觉任务至关重要,包括语音识别。我们训练人类参与者对一大组新的变形猴叫声进行分类。使用 fMRI 快速适应(fMRI-RA)和多体素模式分析(MVPA)技术,我们获得的证据表明分类训练会导致两组截然不同的变化:左听觉皮层对猴叫声特征的调谐更加敏锐(没有明确的类别表示),而外侧前额叶皮层对不同类型的叫声具有类别选择性。此外,左听觉皮层中神经选择性的锐度,通过 fMRI-RA 和 MVPA 进行估计,预测了类别边界的陡峭程度,而类别判断与左额下回的适应释放相关。这些结果支持听觉类别学习遵循类似于视觉领域的两阶段模型的理论,这表明了人类大脑中感知类别学习的一般原则。