CRCNS: Effects of Weak Applied Currents on Memory Consolidation During Sleep

描述（由申请人提供）：智力优势：有令人信服的证据表明，睡眠的不同阶段在长期巩固记忆中起着至关重要的作用（马歇尔& Born 2007）。具体而言，慢波睡眠（SWS），其特征是人类脑电图（EEG）中的缓慢振荡活动（< 1 Hz），与记忆巩固有关。我们证明了在SWS期间施加到头皮的弱电流（<1 mA、<1Hz和DC）调节这些内源性EEG节律，并且可以改善人类记忆性能（马歇尔2006 a）。此外，在学习过程中应用相同的弱电流可以调节人类清醒状态下典型的持续EEG节律，并提高某些学习任务的即时表现（Kirov 2009）。然而，尽管有这些显著的现象学发现，弱电流如何调节脑振荡并诱导脑功能的可塑性变化的问题仍然没有得到根本解决。在这里，我们建议通过开发计算模型来定量地解决这个问题，这些模型受到专门的脑切片实验的严格限制，并通过有针对性的人类受试者实验进行验证。一个核心问题是：微弱的电流似乎不足以调节静止神经元的兴奋性或可塑性，但如何能对振荡和学习产生如此强大的影响？我们的中心假设是，弱电流耦合到正在进行的缓慢振荡活动，然后增强其对突触可塑性的调节作用。来自我们小组和其他人的初步数据已经提供了强有力的证据，证明施加的电流可以调节内源性节律网络的活动--这种电流的强度被认为太弱，不足以影响单个神经元的功能。与此同时，我们和其他小组研究了慢波活动和记忆巩固之间的联系，包括在人类中应用弱电流。但是到目前为止，弱电流对慢波节律和可塑性的影响之间的具体联系还没有被探索过。在计算模型的指导下，两者之间的关键经验联系将通过探测表现出SWA的体外皮层制备的弱电流刺激所导致的持久变化来寻求。有针对性的人体实验将直接测试施加的电流是否也能增强其他SWS介导的学习的巩固，正如假设所暗示的那样，或者更确切地说，如果效果仅限于校园相关的学习，从而为计算模型提供了重要的限制。 更广泛的影响：在许多实证研究中，弱施加电流正在探索其治疗抑郁症和神经性疼痛的潜在益处，以帮助中风后的运动学习，或更普遍地，以提高认知能力和改善学习。这种技术的前景是，弱电流可以非侵入性地应用，具有潜在的广泛应用范围和最小的副作用。然而，这种潜在的变革性临床工具的谜团在于，在大多数研究中，这些电流产生的电场强度比激活沉默神经元所需的电场强度低两个数量级。目前，这一领域的研究几乎完全是现象学的，对有希望的现象学观察的少数机械解释是肤浅的（例如，将所有大脑功能描述为“兴奋性的滑动尺度”），并且没有解决可塑性-因此，没有合理的基础来改进和靶向刺激方案。这项工作是第一次尝试建立机制之间的联系施加电流的内源性节律和相关的SWS相关的学习增强。显然，这样的分析将解决内源性SWS和学习之间的联系的基础科学问题，添加到一套实验工具，可用于研究认知，并阐明了无处不在的内源性节律产生的大脑的功能和因果关系的作用。 与目前对美国/德国计算神经科学合作研究的呼吁一致，该项目将结合国际研究人员在以下领域的专业知识：（1）无创电刺激对神经组织的影响（Bikson，美国），EEG信号分析和计算网络模型（Parra，美国）、人类睡眠和应用电流的学习（马歇尔，德国）以及动态系统和机器学习（Claussen/Martinetz，德国; Parra，美国）。

DESCRIPTION (provided by applicant): Intellectual Merit: There is compelling evidence that the distinct stages of sleep play an essential role in the long-term consolidation of memories (Marshall & Born 2007). Specifically, slow-wave sleep (SWS), which is hallmarked by slow oscillatory activity (< 1 Hz) in the human electro-encephalogram (EEG), has been implicated in memory consolidation. We demonstrated that weak electric currents (<1mA, <1Hz and DC) applied to the scalp during SWS modulate these endogenous EEG rhythms and can improve human memory performance (Marshall 2006a). Moreover, application of the same weak currents during learning modulates ongoing EEG rhythms that are typical for the awake state in humans and boosts immediate performance in some learning tasks (Kirov 2009). Yet, despite these remarkable phenomenological findings, the question of how weak currents can modulate brain oscillations and induce plastic changes in brain function remains fundamentally unaddressed. Here we propose to quantitatively address this question through the development of computational models that are tightly constrained by specialized brain-slice experiments and validated through targeted human subject experiments. A central question is: how can weak electric currents, that appear insufficient to modulate excitability or plasticity in quiescent neurons, exert such a powerful effect on oscillations and learning? Our central hypothesis is that weak currents couple into ongoing slow oscillatory activity that then boost their modulatory effect on synaptic plasticity. Preliminary data from our group and others already provides strong evidence for modulation of endogenous rhythmic network activity by applied currents - at intensities considered too weak to affect single neuron function. Concurrently, we and other groups have investigated links between slow wave activity and memory consolidation, including by application of weak currents in human. But a specific connection between the effects of applied weak currents on slow-wave rhythms and plasticity has so far not been explored. Guided by computational models, the crucial empirical link between the two will be sought by probing lasting changes resulting from weak-current stimulation of an in vitro cortical preparation that exhibits SWA. Targeted human experiments will directly test if applied currents also enhance the consolidation of other SWS-mediated learning as the hypothesis would suggest, or rather, if the effect is limited to hippocampus-related learning, thus providing significant constraints to the computational models. Broader Impacts: Weak applied currents are being explored in a number of empirical studies for their potential benefits to treat depression and neuropathic pain, to assist motor learning after stroke, or more generally, to enhance cognitive performance and to improve learning. The promise of this technique is that weak currents can be applied non-invasively with a potentially broad range of applications and minimal side effects. The enigma in this potentially transformative clinical tool, however, is that the electric field strengths generated by these currents in most studies are two orders of magnitude below what is required to activate an otherwise silent neuron. Currently, research in this area is almost entirely phenomenological and the few mechanistic explanations for the promising phenomenological observations are superficial (e.g. describing all brain function as a "sliding scale of excitability") and do not address plasticity - as such, there is no rational basis for improving and targeting stimulation protocols. This work is the first attempt at establishing the mechanistic link between applied currents on endogenous rhythms and the associated SWS-related learning enhancements. Evidently, such an analysis will address basic science questions about the link between endogenous SWS and learning, add to the set of experimental tools which can be used to study cognition, and, shed light on the functional and causal role of the ubiquitous endogenous rhythms generated by the brain. Consistent with present call for US/German Collaborative Research in Computational Neuroscience this project will combined the expertise of international researchers in the areas of: (1) effects of noninvasive electrical stimulation on nervous tissue (Bikson, US), EEG signal analysis and computational network models (Parra, US), human sleep and learning with applied currents (Marshall, Germany), and dynamical systems and machine learning (Claussen/Martinetz, Germany; Parra, US).