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Cross-frequency coupling supports multi-item working memory in the human hippocampus

机译:交叉频率耦合支持人类海马中的多项目工作记忆

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摘要

Recent findings indicate that the hippocampus supports not only long-term memory encoding but also plays a role in working memory (WM) maintenance of multiple items; however, the neural mechanism underlying multi-item maintenance is still unclear. Theoretical work suggests that multiple items are being maintained by neural assemblies synchronized in the gamma frequency range (25–100 Hz) that are locked to consecutive phase ranges of oscillatory activity in the theta frequency range (4–8 Hz). Indeed, cross-frequency coupling of the amplitude of high-frequency activity to the phase of slower oscillations has been described both in animals and in humans, but has never been linked to a theoretical model of a cognitive process. Here we used intracranial EEG recordings in human epilepsy patients to test pivotal predictions from theoretical work. First, we show that simultaneous maintenance of multiple items in WM is accompanied by cross-frequency coupling of oscillatory activity in the hippocampus, which is recruited during multi-item WM. Second, maintenance of an increasing number of items is associated with modulation of beta/gamma amplitude with theta band activity of lower frequency, consistent with the idea that longer cycles are required for an increased number of representations by gamma cycles. This effect cannot be explained by a difference in theta or beta/gamma power. Third, we describe how the precision of cross-frequency coupling predicts individual WM performance. These data support the idea that working memory in humans depends on a neural code using phase information.
机译:最近的发现表明,海马不仅支持长期记忆编码,而且在多个项目的工作记忆(WM)维护中也起作用。但是,仍然不清楚多项目维护的神经机制。理论工作表明,神经组件在伽玛频率范围(25–100 Hz)中保持同步,从而保持了多个项目,这些神经组件被锁定到θ频率范围(4–8 Hz)中连续的振荡活动相位范围。确实,在动物和人类中都描述了高频活动幅度与较慢振荡相位的跨频耦合,但从未与认知过程的理论模型联系在一起。在这里,我们使用人类癫痫患者的颅内脑电图记录来测试理论工作的关键性预测。首先,我们显示在WM中多个项目的同时维护伴随着在多项目WM中招募的海马振荡活动的交叉频率耦合。其次,维持越来越多的项目与以较低频率的θ带活动性调节β/γ幅值有关,这与为伽玛循环增加表示次数需要更长的循环这一想法相一致。无法用theta或beta /γ幂的差异来解释这种影响。第三,我们描述了跨频耦合的精度如何预测单个WM性能。这些数据支持这样的思想,即人类的工作记忆依赖于使用相位信息的神经代码。

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