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Dynamic Effective Connectivity of Inter-Areal Brain Circuits

机译:区域间大脑回路的动态有效连接

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Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity), related to the elusive question “Which areas cause the present activity of which others?”. Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions) can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early proposals, we advance here that dynamic interactions between brain rhythms provide as well the basis for the self-organized control of this “communication-through-coherence”, making thus possible a fast “on-demand” reconfiguration of global information routing modalities.
机译:大脑区域之间的解剖连接会影响神经元回路之间的信息流以及神经元活动的同步。但是,这种结构性连通性与有效连通性(或更确切地说是因果连通性)不一致,这与难以捉摸的问题“哪个地区导致了其他地区目前的活动?”有关。有效的连通性是有针对性的,并且灵活地取决于上下文和任务。在这里,我们表明动态有效的连接性可以从相干神经活动的集体组织中的转变中产生。结合仿真和半分析方法,我们研究了相互作用的皮层区域的中尺度网络图案,建模为尖峰神经元的大型随机网络或简单速率单位。通过对模型神经活动的时间序列进行因果分析,我们显示了由相同结构连接性主题生成的不同动力学状态对应于不同的有效连接性主题。由于自发的对称性破坏和局部脑节律之间的有效夹带,这样的有效基序可以显示主要的方向性,尽管所考虑的结构基序中的所有联系都是相互的。然后我们表明,有效的连通性配置之间的转换(例如,区域间交互作用的方向反转)可以通过短暂的扰动输入可靠地触发,相对于正在进行的局部振荡适当定时,而无需塑性突触变化。最后,我们分析了在本地神经元种群的突增模式中编码的信息如何在固定的结构连通性基元上传播,从而证明了有效有效连通性的变化调节了信息传递的效率和方向性。先前的研究强调了相干振荡在建立远距离区域之间的有效通信中所起的作用。除了这些早期的建议之外,我们在这里进一步提出,脑节律之间的动态交互作用也为这种“通过连贯性进行交流”的自组织控制提供了基础,从而使全球信息的快速“按需”重构成为可能路由方式。

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