Pereira-Obilinovic Ulises, Froudist-Walsh Sean, Wang Xiao-Jing
Center for Neural Science, New York University, New York, NY, USA.
The Allen Institute for Neural Dynamics, Seattle, WA, USA.
bioRxiv. 2024 Dec 11:2024.11.01.621513. doi: 10.1101/2024.11.01.621513.
Neocortex-wide neural activity is organized into distinct networks of areas engaged in different cognitive processes. To elucidate the underlying mechanism of flexible network reconfiguration, we developed connectivity-constrained macaque and human whole-cortex models. In our model, within-area connectivity consists of a mixture of symmetric, asymmetric, and random motifs that give rise to stable (attractor) or transient (sequential) heterogeneous dynamics. Assuming sparse low-rank plus random inter-areal connectivity constrained by cognitive networks' activation maps, we show that our model captures key aspects of the cognitive networks' dynamics and interactions observed experimentally. In particular, the anti-correlation between the default mode network and the dorsal attention network. Communication between networks is shaped by the alignment of long-range communication subspaces with local connectivity motifs and is switchable in a bottom-up salience-dependent routing mechanism. Furthermore, the frontoparietal multiple-demand network displays a coexistence of stable and dynamic coding, suitable for top-down cognitive control. Our work provides a theoretical framework for understanding the dynamic routing in the cortical networks during cognition.
新皮质范围内的神经活动被组织成参与不同认知过程的不同区域网络。为了阐明灵活网络重新配置的潜在机制，我们开发了受连接性约束的猕猴和人类全皮质模型。在我们的模型中，区域内连接由对称、不对称和随机基序的混合组成，这些基序产生稳定（吸引子）或瞬态（序列）异质动力学。假设稀疏低秩加受认知网络激活图约束的随机区域间连接，我们表明我们的模型捕捉了实验观察到的认知网络动力学和相互作用的关键方面。特别是，默认模式网络和背侧注意网络之间的反相关性。网络之间的通信由远程通信子空间与局部连接基序的对齐塑造，并可在自下而上的显著性依赖路由机制中切换。此外，额顶叶多需求网络显示出稳定编码和动态编码的共存，适用于自上而下的认知控制。我们的工作为理解认知过程中皮质网络的动态路由提供了一个理论框架。
