Fritz Jonathan B, Elhilali Mounya, David Stephen V, Shamma Shihab A
Centre for Auditory and Acoustic Research, University of Maryland, College Park, MD 20742, USA.
Hear Res. 2007 Jul;229(1-2):186-203. doi: 10.1016/j.heares.2007.01.009. Epub 2007 Jan 16.
Acoustic filter properties of A1 neurons can dynamically adapt to stimulus statistics, classical conditioning, instrumental learning and the changing auditory attentional focus. We have recently developed an experimental paradigm that allows us to view cortical receptive field plasticity on-line as the animal meets different behavioral challenges by attending to salient acoustic cues and changing its cortical filters to enhance performance. We propose that attention is the key trigger that initiates a cascade of events leading to the dynamic receptive field changes that we observe. In our paradigm, ferrets were initially trained, using conditioned avoidance training techniques, to discriminate between background noise stimuli (temporally orthogonal ripple combinations) and foreground tonal target stimuli. They learned to generalize the task for a wide variety of distinct background and foreground target stimuli. We recorded cortical activity in the awake behaving animal and computed on-line spectrotemporal receptive fields (STRFs) of single neurons in A1. We observed clear, predictable task-related changes in STRF shape while the animal performed spectral tasks (including single tone and multi-tone detection, and two-tone discrimination) with different tonal targets. A different set of task-related changes occurred when the animal performed temporal tasks (including gap detection and click-rate discrimination). Distinctive cortical STRF changes may constitute a "task-specific signature". These spectral and temporal changes in cortical filters occur quite rapidly, within 2min of task onset, and fade just as quickly after task completion, or in some cases, persisted for hours. The same cell could multiplex by differentially changing its receptive field in different task conditions. On-line dynamic task-related changes, as well as persistent plastic changes, were observed at a single-unit, multi-unit and population level. Auditory attention is likely to be pivotal in mediating these task-related changes since the magnitude of STRF changes correlated with behavioral performance on tasks with novel targets. Overall, these results suggest the presence of an attention-triggered plasticity algorithm in A1 that can swiftly change STRF shape by transforming receptive fields to enhance figure/ground separation, by using a contrast matched filter to filter out the background, while simultaneously enhancing the salient acoustic target in the foreground. These results favor the view of a nimble, dynamic, attentive and adaptive brain that can quickly reshape its sensory filter properties and sensori-motor links on a moment-to-moment basis, depending upon the current challenges the animal faces. In this review, we summarize our results in the context of a broader survey of the field of auditory attention, and then consider neuronal networks that could give rise to this phenomenon of attention-driven receptive field plasticity in A1.
A1神经元的听觉滤波器特性能够动态适应刺激统计规律、经典条件反射、工具性学习以及不断变化的听觉注意力焦点。我们最近开发了一种实验范式,通过让动物关注显著的声学线索并改变其皮质滤波器以提高表现,从而使我们能够在线观察皮质感受野可塑性,此时动物正面临不同的行为挑战。我们提出,注意力是引发一系列事件的关键触发因素,这些事件导致了我们所观察到的动态感受野变化。在我们的范式中,雪貂最初使用条件性回避训练技术进行训练,以区分背景噪声刺激(时间上正交的波纹组合)和前景音调目标刺激。它们学会了将该任务推广到各种不同的背景和前景目标刺激。我们在清醒行为动物中记录皮质活动,并计算A1中单个神经元的在线光谱时间感受野(STRF)。当动物执行涉及不同音调目标的光谱任务(包括单音和多音检测以及双音辨别)时,我们观察到STRF形状出现了清晰、可预测的与任务相关的变化。当动物执行时间任务(包括间隙检测和点击速率辨别)时,发生了另一组与任务相关的变化。独特的皮质STRF变化可能构成一种“任务特异性特征”。皮质滤波器的这些光谱和时间变化在任务开始后2分钟内就会相当迅速地发生,在任务完成后同样迅速消退,或者在某些情况下会持续数小时。同一个细胞可以通过在不同任务条件下差异地改变其感受野来进行多重功能。在单单元、多单元和群体水平上都观察到了与任务相关的在线动态变化以及持续的可塑性变化。听觉注意力可能在介导这些与任务相关的变化中起关键作用,因为STRF变化的幅度与针对新目标的任务中的行为表现相关。总体而言,这些结果表明A1中存在一种由注意力触发的可塑性算法,该算法可以通过转换感受野迅速改变STRF形状,以增强图形/背景分离,通过使用对比度匹配滤波器滤除背景,同时增强前景中的显著声学目标。这些结果支持这样一种观点,即大脑灵活、动态、专注且具有适应性,能够根据动物当前面临的挑战,瞬间重塑其感觉滤波器特性和感觉运动联系。在这篇综述中,我们在对听觉注意力领域进行更广泛调查的背景下总结我们的结果,然后思考可能导致A1中这种注意力驱动的感受野可塑性现象的神经网络。