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Ramaswami, M.a b Network plasticity in adaptive filtering and behavioral habituation

机译：Ramaswami，M.a b自适应过滤和行为习惯中的网络可塑性

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The ability of organisms to seamlessly ignore familiar, inconsequential stimuli improves their selective attention and response to salient features of the environment. Here, I propose that this fundamental but unexplained phenomenon substantially derives from the ability of any pattern of neural excitation to create an enhanced inhibitory (or "negative") image of itself through target-specific scaling of inhibitory inputs onto active excitatory neurons. Familiar stimuli encounter strong negative images and are therefore less likely to be transmitted to higher brain centers. Integrating historical and recent observations, the negative-image model described here provides a mechanistic framework for understanding habituation, which is connected to ideas on dynamic predictive coding. In addition, it suggests insights for understanding autism spectrum disorders. Video Abstract: Neural mechanisms to filter predicted or irrelevant stimuli are essential for normal cognitive function. In this Perspective, Ramaswami synthesizes observations from multiple subfields of neuroscience to propose a role for inhibitory potentiation in adaptive filtering, behavioral habituation, and related phenomena.
机译：有机体无缝地忽略熟悉的，无关紧要的刺激的能力提高了它们对环境的显着特征的选择性关注和响应。在这里，我认为，这种基本但无法解释的现象基本上源于任何形式的神经兴奋通过抑制输入到活动性兴奋性神经元上的目标特异性缩放来创建自身增强的抑制（或“负”）图像的能力。熟悉的刺激会遇到强烈的负面图像，因此不太可能传播到较高的大脑中枢。结合历史和最近的观察结果，此处描述的负像模型为理解习惯提供了一种机制框架，该框架与动态预测编码的思想有关。此外，它为了解自闭症谱系障碍提供了见识。视频摘要：过滤预测的或不相关的刺激的神经机制对于正常的认知功能至关重要。在此观点中，Ramaswami综合了来自神经科学多个子领域的观察结果，提出了抑制增强作用在自适应过滤，行为习惯和相关现象中的作用。

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