Holt Caleb J, Miller Kenneth D, Ahmadian Yashar
Institute of Neuroscience, Department of Physics, University of Oregon, OR, USA.
Center for Theoretical Neuroscience, Swartz Program in Theoretical Neuroscience, Kavli Institute for Brain Science, and Dept. of Neuroscience, College of Physicians and Surgeons and Morton B. Zuckerman Mind Brain Behavior Institute, Columbia University, NY, USA.
bioRxiv. 2023 May 12:2023.05.11.540442. doi: 10.1101/2023.05.11.540442.
When stimulated, neural populations in the visual cortex exhibit fast rhythmic activity with frequencies in the gamma band (30-80 Hz). The gamma rhythm manifests as a broad resonance peak in the power-spectrum of recorded local field potentials, which exhibits various stimulus dependencies. In particular, in macaque primary visual cortex (V1), the gamma peak frequency increases with increasing stimulus contrast. Moreover, this contrast dependence is local: when contrast varies smoothly over visual space, the gamma peak frequency in each cortical column is controlled by the local contrast in that column's receptive field. No parsimonious mechanistic explanation for these contrast dependencies of V1 gamma oscillations has been proposed. The stabilized supralinear network (SSN) is a mechanistic model of cortical circuits that has accounted for a range of visual cortical response nonlinearities and contextual modulations, as well as their contrast dependence. Here, we begin by showing that a reduced SSN model without retinotopy robustly captures the contrast dependence of gamma peak frequency, and provides a mechanistic explanation for this effect based on the observed non-saturating and supralinear input-output function of V1 neurons. Given this result, the local dependence on contrast can trivially be captured in a retinotopic SSN which however lacks horizontal synaptic connections between its cortical columns. However, long-range horizontal connections in V1 are in fact strong, and underlie contextual modulation effects such as surround suppression. We thus explored whether a retinotopically organized SSN model of V1 with strong excitatory horizontal connections can exhibit both surround suppression and the local contrast dependence of gamma peak frequency. We found that retinotopic SSNs can account for both effects, but only when the horizontal excitatory projections are composed of two components with different patterns of spatial fall-off with distance: a short-range component that only targets the source column, combined with a long-range component that targets columns neighboring the source column. We thus make a specific qualitative prediction for the spatial structure of horizontal connections in macaque V1, consistent with the columnar structure of cortex.
受到刺激时，视觉皮层中的神经群体表现出频率在伽马波段（30 - 80赫兹）的快速节律性活动。伽马节律表现为记录的局部场电位功率谱中的一个宽共振峰，该共振峰呈现出各种刺激依赖性。特别是在猕猴初级视觉皮层（V1）中，伽马峰值频率随刺激对比度的增加而增加。此外，这种对比度依赖性是局部性的：当对比度在视觉空间中平滑变化时，每个皮层柱中的伽马峰值频率由该柱的感受野中的局部对比度控制。尚未有人提出对V1伽马振荡的这些对比度依赖性的简洁机制解释。稳定的超线性网络（SSN）是一种皮层回路的机制模型，它解释了一系列视觉皮层反应非线性和上下文调制，以及它们的对比度依赖性。在此，我们首先表明，一个没有视网膜拓扑结构的简化SSN模型能够稳健地捕捉伽马峰值频率的对比度依赖性，并基于观察到的V1神经元的非饱和和超线性输入 - 输出函数为这种效应提供了一个机制解释。鉴于这一结果，在缺乏皮层柱之间水平突触连接的视网膜拓扑SSN中，可以很容易地捕捉到对对比度的局部依赖性。然而，V1中的长程水平连接实际上很强，并且是诸如周围抑制等上下文调制效应的基础。因此，我们探究了一个具有强兴奋性水平连接的V1视网膜拓扑组织的SSN模型是否能够同时表现出周围抑制和伽马峰值频率的局部对比度依赖性。我们发现视网膜拓扑SSN能够解释这两种效应，但前提是水平兴奋性投射由两个具有不同距离空间衰减模式的成分组成：一个仅针对源柱的短程成分，与一个针对源柱相邻柱的长程成分相结合。因此，我们对猕猴V1中水平连接的空间结构做出了一个具体的定性预测，这与皮层的柱状结构一致。
