Department of Neuroscience and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA 15213
Department of Neuroscience and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA 15213.
Proc Natl Acad Sci U S A. 2017 May 16;114(20):E4085-E4094. doi: 10.1073/pnas.1619857114. Epub 2017 May 1.
Models of divisive normalization can explain the trial-averaged responses of neurons in sensory, association, and motor areas under a wide range of conditions, including how visual attention changes the gains of neurons in visual cortex. Attention, like other modulatory processes, is also associated with changes in the extent to which pairs of neurons share trial-to-trial variability. We showed recently that in addition to decreasing correlations between similarly tuned neurons within the same visual area, attention increases correlations between neurons in primary visual cortex (V1) and the middle temporal area (MT) and that an extension of a classic normalization model can account for this correlation increase. One of the benefits of having a descriptive model that can account for many physiological observations is that it can be used to probe the mechanisms underlying processes such as attention. Here, we use electrical microstimulation in V1 paired with recording in MT to provide causal evidence that the relationship between V1 and MT activity is nonlinear and is well described by divisive normalization. We then use the normalization model and recording and microstimulation experiments to show that the attention dependence of V1-MT correlations is better explained by a mechanism in which attention changes the weights of connections between V1 and MT than by a mechanism that modulates responses in either area. Our study shows that normalization can explain interactions between neurons in different areas and provides a framework for using multiarea recording and stimulation to probe the neural mechanisms underlying neuronal computations.
分裂规范化模型可以解释在广泛的条件下，包括视觉注意力如何改变视觉皮层中神经元的增益，感觉、联想和运动区域中神经元的试验平均反应。注意力与其他调节过程一样，也与神经元之间共享试验间变异性的程度变化有关。我们最近表明，除了降低相同视觉区域内相似调谐神经元之间的相关性外，注意力还增加了初级视觉皮层 (V1) 和颞中区域 (MT) 之间神经元的相关性，并且经典归一化模型的扩展可以解释这种相关性的增加。拥有一个可以解释许多生理观察的描述性模型的好处之一是，它可以用于探究注意力等过程的机制。在这里，我们使用 V1 中的电微刺激与 MT 中的记录相结合，提供了因果证据，表明 V1 和 MT 活动之间的关系是非线性的，可以很好地用分裂归一化来描述。然后，我们使用归一化模型和记录及微刺激实验表明，与调节两个区域中任一区域的响应的机制相比，注意力改变 V1 和 MT 之间连接权重的机制可以更好地解释 V1-MT 相关性的注意力依赖性。我们的研究表明，归一化可以解释不同区域之间神经元的相互作用，并为使用多区域记录和刺激来探究神经元计算的神经机制提供了框架。
