Department of Otolaryngology-Head and Neck Surgery, Coleman Memorial Laboratory, UCSF Center for Integrative Neuroscience, University of California, San Francisco, CA 94158-0444, USA.
Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Cereb Cortex. 2020 May 14;30(5):3130-3147. doi: 10.1093/cercor/bhz299.
Classic spectrotemporal receptive fields (STRFs) for auditory neurons are usually expressed as a single linear filter representing a single encoded stimulus feature. Multifilter STRF models represent the stimulus-response relationship of primary auditory cortex (A1) neurons more accurately because they can capture multiple stimulus features. To determine whether multifilter processing is unique to A1, we compared the utility of single-filter versus multifilter STRF models in the medial geniculate body (MGB), anterior auditory field (AAF), and A1 of ketamine-anesthetized cats. We estimated STRFs using both spike-triggered average (STA) and maximally informative dimension (MID) methods. Comparison of basic filter properties of first maximally informative dimension (MID1) and second maximally informative dimension (MID2) in the 3 stations revealed broader spectral integration of MID2s in MGBv and A1 as opposed to AAF. MID2 peak latency was substantially longer than for STAs and MID1s in all 3 stations. The 2-filter MID model captured more information and yielded better predictions in many neurons from all 3 areas but disproportionately more so in AAF and A1 compared with MGBv. Significantly, information-enhancing cooperation between the 2 MIDs was largely restricted to A1 neurons. This demonstrates significant differences in how these 3 forebrain stations process auditory information, as expressed in effective and synergistic multifilter processing.
经典的听觉神经元频谱时间感受野 (STRF) 通常表示为单个线性滤波器,代表单个编码的刺激特征。多滤波器 STRF 模型更准确地表示初级听觉皮层 (A1) 神经元的刺激-反应关系,因为它们可以捕获多个刺激特征。为了确定多滤波器处理是否是 A1 所特有的,我们比较了单滤波器与多滤波器 STRF 模型在麻醉猫的内侧膝状体 (MGB)、前听觉场 (AAF) 和 A1 中的效用。我们使用尖峰触发平均 (STA) 和最大信息量维度 (MID) 方法来估计 STRF。在 3 个站点中比较第一最大信息量维度 (MID1) 和第二最大信息量维度 (MID2) 的基本滤波器特性,发现 MGBv 和 A1 中的 MID2 具有更宽的光谱整合,而 AAF 则相反。MID2 的峰潜伏期比所有 3 个站点中的 STA 和 MID1 长得多。在所有 3 个区域的许多神经元中,2 滤波器 MID 模型捕获了更多信息,并产生了更好的预测,但 AAF 和 A1 比 MGBv 更为明显。重要的是,2 个 MID 之间的信息增强合作主要局限于 A1 神经元。这表明这 3 个前脑站点在处理听觉信息方面存在显著差异,表现为有效的协同多滤波器处理。