State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.
Institute of AI, Hefei Comprehensive National Science Center, Hefei 230088, China.
Proc Natl Acad Sci U S A. 2023 Oct 17;120(42):e2216942120. doi: 10.1073/pnas.2216942120. Epub 2023 Oct 9.
The covariability of neural responses in the neuron population is highly relevant to the information encoding. Cognitive processes, such as attention, are found to modulate the covariability in the visual cortex to improve information encoding, suggesting the computational advantage of covariability modulation in the neural system. However, is the covariability modulation a general mechanism for enhanced information encoding throughout the information processing pathway, or only adopted in certain processing stages, depending on the property of neural representation? Here, with ultrahigh-field MRI, we examined the covariability, which was estimated by noise correlation, in different attention states in the early visual cortex and posterior parietal cortex (PPC) of the human brain, and its relationship to the quality of information encoding. Our results showed that while attention decreased the covariability to improve the stimulus encoding in the early visual cortex, covariability modulation was not observed in the PPC, where covariability had little impact on information encoding. Further, attention promoted the information flow between the early visual cortex and PPC, with an apparent emphasis on a flow from high- to low-dimensional representations, suggesting the existence of a reduction in the dimensionality of neural representation from the early visual cortex to PPC. Finally, the neural response patterns in the PPC could predict the amplitudes of covariability change in the early visual cortex, indicating a top-down control from the PPC to early visual cortex. Our findings reveal the specific roles of the sensory cortex and PPC during attentional modulation of covariability, determined by the complexity and fidelity of the neural representation in each cortical region.
神经元群体中神经反应的协变与信息编码高度相关。注意力等认知过程被发现可以调节视觉皮层中的协变,以改善信息编码,这表明协变调节在神经系统中具有计算优势。然而,协变调节是增强信息编码的一般机制,还是仅在特定处理阶段采用,取决于神经表示的性质?在这里,我们使用超高场 MRI 检查了人类大脑早期视觉皮层和后顶叶皮层(PPC)中不同注意状态下的协变,并用其来估计噪声相关性,并研究了其与信息编码质量的关系。我们的结果表明,虽然注意力降低了协变以改善早期视觉皮层中的刺激编码,但在 PPC 中没有观察到协变调制,因为协变对信息编码几乎没有影响。此外,注意力促进了早期视觉皮层和 PPC 之间的信息流,明显强调了从高维到低维表示的流动,这表明从早期视觉皮层到 PPC 的神经表示的维度减少。最后,PPC 中的神经反应模式可以预测早期视觉皮层中协变变化的幅度,表明来自 PPC 到早期视觉皮层的自上而下的控制。我们的研究结果揭示了感觉皮层和 PPC 在注意力调节协变过程中的具体作用,这取决于每个皮层区域中神经表示的复杂性和保真度。