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Modulation of Cortical Oscillations by Low-Frequency Direct Cortical Stimulation Is State-Dependent

机译:低频直接皮层刺激对皮质振荡的调制取决于状态

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摘要

Cortical oscillations play a fundamental role in organizing large-scale functional brain networks. Noninvasive brain stimulation with temporally patterned waveforms such as repetitive transcranial magnetic stimulation (rTMS) and transcranial alternating current stimulation (tACS) have been proposed to modulate these oscillations. Thus, these stimulation modalities represent promising new approaches for the treatment of psychiatric illnesses in which these oscillations are impaired. However, the mechanism by which periodic brain stimulation alters endogenous oscillation dynamics is debated and appears to depend on brain state. Here, we demonstrate with a static model and a neural oscillator model that recurrent excitation in the thalamo-cortical circuit, together with recruitment of cortico-cortical connections, can explain the enhancement of oscillations by brain stimulation as a function of brain state. We then performed concurrent invasive recording and stimulation of the human cortical surface to elucidate the response of cortical oscillations to periodic stimulation and support the findings from the computational models. We found that (1) stimulation enhanced the targeted oscillation power, (2) this enhancement outlasted stimulation, and (3) the effect of stimulation depended on behavioral state. Together, our results show successful target engagement of oscillations by periodic brain stimulation and highlight the role of nonlinear interaction between endogenous network oscillations and stimulation. These mechanistic insights will contribute to the design of adaptive, more targeted stimulation paradigms.
机译:皮质振荡在组织大规模功能性大脑网络中起着基本作用。已经提出了具有时间模式波形的非侵入性脑刺激,例如重复经颅磁刺激(rTMS)和经颅交流电刺激(tACS)来调制这些振荡。因此,这些刺激方式代表了有希望的新方法,用于治疗其中这些振荡被削弱的精神病。但是,周期性的大脑刺激改变内源性振荡动力学的机制尚有争议,并且似乎取决于大脑的状态。在这里,我们用静态模型和神经振荡器模型证明,在丘脑-皮质回路中的反复兴奋以及皮质-皮质连接的募集,可以解释脑刺激作为大脑状态的函数而增强的振荡。然后,我们对人类皮质表面进行了同时侵入性记录和刺激,以阐明皮质振荡对周期性刺激的响应,并支持计算模型的发现。我们发现(1)刺激增强了目标振荡功率,(2)这种增强使刺激持久,并且(3)刺激的效果取决于行为状态。在一起,我们的结果表明通过周期性的脑刺激成功实现了目标的振荡参与,并突出了内源性网络振荡和刺激之间的非线性交互作用。这些机制的见解将有助于设计自适应的,更有针对性的刺激范例。

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