A long-term goal of visual neuroscience is to develop and test quantitative models that account for the moment-by-moment relationship between neural responses in early visual cortex and human performance in natural visual tasks. This review focuses on efforts to address this goal by measuring and perturbing the activity of primary visual cortex (V1) neurons while nonhuman primates perform demanding, well-controlled visual tasks. We start by describing a conceptual approach-the decoder linking model (DLM) framework-in which candidate decoding models take neural responses as input and generate predicted behavior as output. The ultimate goal in this framework is to find the actual decoder-the model that best predicts behavior from neural responses. We discuss key relevant properties of primate V1 and review current literature from the DLM perspective. We conclude by discussing major technological and theoretical advances that are likely to accelerate our understanding of the link between V1 activity and behavior.

中文翻译：

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将 V1 活动与行为联系起来。


视觉神经科学的一个长期目标是开发和测试定量模型，以解释早期视觉皮层的神经反应与人类在自然视觉任务中的表现之间的即时关系。本综述的重点是通过测量和扰乱非人类灵长类动物执行要求严格、控制良好的视觉任务时初级视觉皮层 (V1) 神经元的活动来实现这一目标。我们首先描述一种概念方法——解码器链接模型（DLM）框架——其中候选解码模型将神经响应作为输入并生成预测行为作为输出。该框架的最终目标是找到实际的解码器——最能根据神经反应预测行为的模型。我们讨论了灵长类动物 V1 的关键相关特性，并从 DLM 的角度回顾了当前的文献。最后，我们讨论了可能加速我们对 V1 活动和行为之间联系的理解的重大技术和理论进展。