Department of Neurobiology and Anatomy McGovern Medical School, University of Texas at Houston, Houston, TX, 77030, US.
Department of Electrical and Computer Engineering, Rice University, Houston, TX, 77005, US.
Nat Commun. 2023 Jan 6;14(1):87. doi: 10.1038/s41467-022-35656-w.
Theoretical studies have long proposed that adaptation allows the brain to effectively use the limited response range of sensory neurons to encode widely varying natural inputs. However, despite this influential view, experimental studies have exclusively focused on how the neural code adapts to a range of stimuli lying along a single feature axis, such as orientation or contrast. Here, we performed electrical recordings in macaque visual cortex (area V4) to reveal significant adaptive changes in the neural code of single cells and populations across multiple feature axes. Both during free viewing and passive fixation, populations of cells improved their ability to encode image features after rapid exposure to stimuli lying on orthogonal feature axes even in the absence of initial tuning to these stimuli. These results reveal a remarkable adaptive capacity of visual cortical populations to improve network computations relevant for natural viewing despite the modularity of the functional cortical architecture.
理论研究长期以来一直认为，适应使大脑能够有效地利用感觉神经元有限的响应范围来对广泛变化的自然输入进行编码。然而，尽管这种观点具有影响力，但实验研究却完全专注于神经代码如何适应沿着单个特征轴的一系列刺激，例如方向或对比度。在这里，我们在猕猴视觉皮层（V4 区）进行了电记录，以揭示单个细胞和群体的神经代码在多个特征轴上发生了显著的适应性变化。无论是在自由观看还是被动注视期间，即使在对这些刺激没有初始调谐的情况下，细胞群体在快速暴露于正交特征轴上的刺激后，都能提高其对图像特征的编码能力。这些结果揭示了视觉皮层群体的显著适应性能力，即使在功能皮层结构的模块化情况下，它们也能改善与自然观看相关的网络计算。
