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Global network influences on local functional connectivity

机译:全球网络对本地功能连接的影响

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A central neuroscientific pursuit is understanding neuronal interactions that support computations underlying cognition and behavior. Although neurons interact across disparate scales, from cortical columns to whole-brain networks, research has been restricted to one scale at a time. We measured local interactions through multi-neuronal recordings while accessing global networks using scalp electroencephalography (EEG) in rhesus macaques. We measured spike count correlation, an index of functional connectivity with computational relevance, and EEG oscillations, which have been linked to various cognitive functions. We found a non-monotonic relationship between EEG oscillation amplitude and spike count correlation, contrary to the intuitive expectation of a direct relationship. With a widely used network model, we replicated these findings by incorporating a private signal targeting inhibitory neurons, a common mechanism proposed for gain modulation. Finally, we found that spike count correlation explained nonlinearities in the relationship between EEG oscillations and response time in a spatial selective attention task.
机译:神经科学的中心追求是理解神经元相互作用,以支持基于认知和行为的计算。尽管神经元在不同的尺度上相互作用,从皮质柱到全脑网络,但研究一次只能局限于一个尺度。我们在恒河猴中使用头皮脑电图(EEG)访问全球网络的同时,通过多神经记录记录了局部相互作用。我们测量了穗计数相关性,具有计算相关性的功能连通性指数以及EEG振荡,这些均与各种认知功能相关。我们发现脑电图振荡幅度和峰值计​​数相关性之间的非单调关系,与直接关系的直观期望相反。通过广泛使用的网络模型,我们通过合并针对抑制增益的专用信号靶向私有信号来复制这些发现。最后,我们发现峰值计数相关性解释了空间选择性注意任务中脑电图振荡和响应时间之间关系的非线性。

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