The Center for Vision Research, York University, Toronto, M3J 1P3, Canada.
Sci Rep. 2020 May 22;10(1):8491. doi: 10.1038/s41598-020-64969-3.
There is still much to understand about the brain's colour processing mechanisms and the transformation from cone-opponent representations to perceptual hues. Moreover, it is unclear which area(s) in the brain represent unique hues. We propose a hierarchical model inspired by the neuronal mechanisms in the brain for local hue representation, which reveals the contributions of each visual cortical area in hue representation. Hue encoding is achieved through incrementally increasing processing nonlinearities beginning with cone input. Besides employing nonlinear rectifications, we propose multiplicative modulations as a form of nonlinearity. Our simulation results indicate that multiplicative modulations have significant contributions in encoding of hues along intermediate directions in the MacLeod-Boynton diagram and that our model V2 neurons have the capacity to encode unique hues. Additionally, responses of our model neurons resemble those of biological colour cells, suggesting that our model provides a novel formulation of the brain's colour processing pathway.
关于大脑的颜色处理机制以及从锥体对立表示到感知色调的转换，仍有许多需要了解的地方。此外，尚不清楚大脑中的哪个（些）区域代表独特的色调。我们提出了一种受大脑中神经元机制启发的分层模型，用于局部色调表示，该模型揭示了每个视觉皮层区域在色调表示中的贡献。通过从锥体输入开始逐渐增加处理非线性来实现色调编码。除了采用非线性整流之外，我们还提出了乘法调制作为一种非线性形式。我们的模拟结果表明，乘法调制在 MacLeod-Boynton 图中中间方向的色调编码中具有重要贡献，并且我们的模型 V2 神经元具有编码独特色调的能力。此外，我们模型神经元的反应类似于生物颜色细胞的反应，这表明我们的模型为大脑的颜色处理途径提供了一种新的表述。
