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

描述(由申请人提供)：智力价值：有令人信服的证据表明，睡眠的不同阶段在记忆的长期巩固中发挥着重要作用(马歇尔和波恩，2007年)。具体地说，慢波睡眠(SWS)，其特征是人类脑电(EEG)中的缓慢振荡活动(1赫兹)，已被认为与记忆巩固有关。我们证明，在短波刺激过程中，施加在头皮上的弱电流(&lt；1 mA，&lt；1 HZ和DC)可以调制这些内源性脑电节律，并可以改善人类的记忆能力(马歇尔2006a)。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脑电节律，并提高某些学习任务中的即刻表现(Kirov 2009)。然而，尽管有这些非凡的现象学发现，弱电流如何调节大脑振荡并诱导大脑功能发生可塑性变化的问题仍未得到根本解决。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，这些计算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。一个中心问题是：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，如何对振荡和学习产生如此强大的影响？我们的中心假设是，弱电流耦合成持续的慢振荡活动，然后增强它们对突触可塑性的调制作用。来自我们团队和其他人的初步数据已经为外加电流对内源性节律网络活动的调制提供了强有力的证据--外加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，我们和其他研究小组研究了慢波活动和记忆巩固之间的联系，包括通过在人类身上应用弱电流。但到目前为止，人们还没有探索外加弱电流对慢波节律的影响与可塑性之间的具体联系。在计算模型的指导下，将通过探索弱电流刺激表现出SWA的体外皮质制剂所产生的持久变化来寻找两者之间的关键经验联系。有针对性的人体实验将直接测试外加电流是否也像假设所暗示的那样加强了其他SWS介导的学习的巩固，或者更确切地说，这种影响是否仅限于与海马体相关的学习，从而为计算模型提供了显著的限制。 更广泛的影响：一些实证研究正在探索弱外加电流在治疗抑郁症和神经病理性疼痛、帮助中风后的运动学习或更广泛地提高认知能力和改善学习方面的潜在益处。这项技术的前景是，弱电流可以非侵入性地施加，具有潜在的广泛应用范围和最小的副作用。然而，这个潜在的变革性临床工具的谜团是，在大多数研究中，这些电流产生的电场强度比激活原本沉默的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到的少数机械解释是肤浅的(例如，将所有大脑功能描述为“兴奋性的滑动标尺”)，没有解决可塑性--因此，没有合理的基础来改进和定位刺激方案。这项工作是首次尝试建立内源性节律上的外加电流与相关的SWS相关学习增强之间的机制联系。显然，这样的分析将解决有关内源性SWS和学习之间联系的基础科学问题，增加可用于研究认知的实验工具集，并阐明由大脑产生的普遍存在的内源性节律的功能和因果作用。 该项目将结合国际研究人员在以下领域的专业知识：(1)非侵入性电刺激对神经组织的影响(Bikson，美国)、脑电信号分析和计算网络模型(Parra，美国)、人类睡眠和外加电流学习(马歇尔，德国)，以及动力系统和机器学习(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).