Optimal recall from bounded metaplastic synapses: predicting functional adaptations in hippocampal area CA3.

A venerable history of classical work on autoassociative memory has significantly shaped our understanding of several features of the hippocampus, and most prominently of its CA3 area, in relation to memory storage and retrieval. However, existing theories of hippocampal memory processing ignore a key biological constraint affecting memory storage in neural circuits: the bounded dynamical range of synapses. Recent treatments based on the notion of metaplasticity provide a powerful model for individual bounded synapses; however, their implications for the ability of the hippocampus to retrieve memories well and the dynamics of neurons associated with that retrieval are both unknown. Here, we develop a theoretical framework for memory storage and recall with bounded synapses. We formulate the recall of a previously stored pattern from a noisy recall cue and limited-capacity (and therefore lossy) synapses as a probabilistic inference problem, and derive neural dynamics that implement approximate inference algorithms to solve this problem efficiently. In particular, for binary synapses with metaplastic states, we demonstrate for the first time that memories can be efficiently read out with biologically plausible network dynamics that are completely constrained by the synaptic plasticity rule, and the statistics of the stored patterns and of the recall cue. Our theory organises into a coherent framework a wide range of existing data about the regulation of excitability, feedback inhibition, and network oscillations in area CA3, and makes novel and directly testable predictions that can guide future experiments.

First principles interatomic potential for tungsten based on Gaussian process regression

An accurate description of atomic interactions, such as that provided by first principles quantum mechanics, is fundamental to realistic prediction of the properties that govern plasticity, fracture or crack propagation in metals. However, the computational complexity associated with modern schemes explicitly based on quantum mechanics limits their applications to systems of a few hundreds of atoms at most. This thesis investigates the application of the Gaussian Approximation Potential (GAP) scheme to atomistic modelling of tungsten - a bcc transition metal which exhibits a brittle-to-ductile transition and whose plasticity behaviour is controlled by the properties of $\frac{1}{2} \langle 111 \rangle$ screw dislocations. We apply Gaussian process regression to interpolate the quantum-mechanical (QM) potential energy surface from a set of points in atomic configuration space. Our training data is based on QM information that is computed directly using density functional theory (DFT). To perform the fitting, we represent atomic environments using a set of rotationally, permutationally and reflection invariant parameters which act as the independent variables in our equations of non-parametric, non-linear regression. We develop a protocol for generating GAP models capable of describing lattice defects in metals by building a series of interatomic potentials for tungsten. We then demonstrate that a GAP potential based on a Smooth Overlap of Atomic Positions (SOAP) covariance function provides a description of the $\frac{1}{2} \langle 111 \rangle$ screw dislocation that is in agreement with the DFT model. We use this potential to simulate the mobility of $\frac{1}{2} \langle 111 \rangle$ screw dislocations by computing the Peierls barrier and model dislocation-vacancy interactions to QM accuracy in a system containing more than 100,000 atoms.

Characterizing the class of local metal sheet thickening processes

The need to create high-value products for specialist applications, and the search for efficient forming routes that obviate the need for some machining steps, is driving Interest In a novel class of forming processes aiming to create locally thickened features within sheet work- pieces. A number of novel forming processes have been proposed to meet this need, but it is as yet unclear which processes will be most effective in creating local thickening of various geometries, and many process configurations have yet to be tried. This paper aims to provide some basic principles for designing and characterising process behaviour. A simplified generic description of sheet thickening processes is provided, with two tools of variable operating on a sheet workpiece in plane strain, with different tool separations and motions parameterised. A comprehensive numerical study of the behaviour of this class of processes is conducted in Abaqus to predict the main characteristics of the material flow in each configuration. The results are used to classify the different basic behaviours that can be achieved by the sheet-bulk thickening processes and to give guidance on future process development, capability and applicability. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Weinheim.

Tool-path design for metal spinning

Toolpath design in spinning is an open ended problem, with a large number of solutions, and remains an art acquired by practice. To be able to specify a toolpath without the need for experimental trials, further understanding of the process mechanics Is required. At the moment, the mechanics of the process Is not completely understood, due to the complex deformation and because long solution times required for accurate numerical modelling of the process Inhibit detailed study. This paper proposes and applies a new approach to modelling the process and aims to contribute to the understanding of process mechanics, In particular with respect to the mechanisms of failure and and to apply this understanding for toolpath design In spinning. A new approach to numerical modelling Is proposed and applied to Investigate the process. The findings suggest that there are two different causes and two different modes of wrinkling In spinning, depending on the stage In the process and direction of roller movement. A simple test Is performed to estimate the limits of wrinkling and provide a guideline for toolpath design In a typical spinning process. The results show that the required toolpath geometry in the early stages of the process is different from that In later stages. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Weinheim.

The forming of variable cross-section I-beams by hot rolling

A process is presented for the forming of variable cross-section I-beams by hot rolling. Optimized I-beams with variable cross-section offer a significant weight advantage over prismatic beams. By tailoring the cross-section to the bending moment experienced within the beam, around 30% of the material can be saved compared to a standard section. Production of such beams by hot rolling would be advantageous, as It combines high volume capacity with high material yields. Through controlled variation of the roll gap during multiple passes, beams with a variable cross-section have been created using shaped rolls similar to those used for conventional I-beam rolling. The process was tested experimentally on a small scale rolling mill, using plasticine as the modelling material. These results were then compared to finite element simulations of individual stages of the process conducted using Abaqus/Standard. Results here show that the process can successfully form a beam with a variable depth web. The main failure modes of the process, and the limitations on the achievable variations In geometry are also presented. Finally, the question of whether or not optimal beam geometries can be created by this process Is discussed. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Weinheim.

Steel and aluminium in a low carbon future

Production of steel and aluminium creates 10% of global carbon emissions from energy and processes. Demand is likely to double by 2050, but climate scientists are recommending absolute reductions of at least 50% and these are Increasingly entering law. How can reductions of this order happen? Only 10-20% savings can be expected in liquid metal production, so the primary industry is pursuing carbon sequestration as the main solution. However, this Is as yet unproven at scale, and as well as carrying some risk, the capital and operating costs are likely to be high, but are as yet unknown. In parallel with these strategies we can also examine whether we can reduce demand for liquid metal. 'Material efficiency' may allow delivery of existing services with less requirement for metal, for instance through designing products that use less metal, reducing process scrap, diverting scrap for other use, re-using components or delaying end of life. Overall demand reduction could occur if goods were used more intensely, alternative means were used to deliver the same services, or total demand were constrained. The paper analyses all possible options, to define and evaluate scenarios that meet the 2050 target, and discuss the steps required to bring them about. The paper concludes with suggestions for key areas where future research In metal forming can support a future low carbon economy. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Weinheim.

Correlations strike back (again): The case of associative memory retrieval

It has long been recognised that statistical dependencies in neuronal activity need to be taken into account when decoding stimuli encoded in a neural population. Less studied, though equally pernicious, is the need to take account of dependencies between synaptic weights when decoding patterns previously encoded in an auto-associative memory. We show that activity-dependent learning generically produces such correlations, and failing to take them into account in the dynamics of memory retrieval leads to catastrophically poor recall. We derive optimal network dynamics for recall in the face of synaptic correlations caused by a range of synaptic plasticity rules. These dynamics involve well-studied circuit motifs, such as forms of feedback inhibition and experimentally observed dendritic nonlinearities. We therefore show how addressing the problem of synaptic correlations leads to a novel functional account of key biophysical features of the neural substrate.

Ⅰ、KMBZ-009 改善心理应激所致认知障碍和抑郁样行为的研究 Ⅱ、银杏叶提取物及复方制剂改善老年鼠空间学习记忆的突触可塑性机理

1、KMBZ-009 改善高台应激所致认知障碍和应激相关的抑郁样行为及其相关机理 研究。 虽然适当的应激会提高动物的学习记忆功能，但过量的应激特别是无法逃避 的应激，往往导致依赖海马或前额叶的学习记忆功能受损，这与应激改变脑内应 激激素（皮质酮，皮质醇等）和神经递质的释放，影响突触传递和可塑性（包括 长时程增强和长时程抑制，LTP 和LTD）有关。一些疾病的发生、发展和恶化， 比如抑郁症（Depression）、创伤后应激障碍（PTSD），往往也和应激相关联，其 神经化学基础被证实与内分泌系统和单胺类（如五羟色，去甲肾上腺素，多巴胺） 神经递质系统的功能密切相关。遗憾的是，到目前为止还没有发现能治疗应激的 药物。本实验室过去的研究证实：KMBZ-009(申报新药时的名称为芬克罗酮，英 文名Phenchlobenpyrrone)——一种新的取代吡咯烷酮类化合物，通过调节细胞 内钙，改变脑内神经递质的释放，从而影响脑高级功能。KMBZ-009 对神经递质 释放影响是否能减轻应激导致的认知障碍及应激相关疾病的发生还没有进行研 究。本研究采用Morris 水迷宫、行为操作箱、绝望游泳、膜片钳和活体电生理 技术研究了KMBZ-009 对高台应激所致认知障碍和应激相关的抑郁样行为的影响 及其相关机理。 研究结果发现，高台应激或皮质酮注射造成大鼠空间记忆提取障碍，这与其 导致的海马CA1 区突触可塑性改变有关，而KMBZ-009 能成剂量依赖性地逆转应 激对空间记忆提取的损伤作用，这与它阻断应激或皮质酮异化的LTD 和恢复应激 或皮质酮损伤的LTP 密切相关。KMBZ-009 能部分地降低因应激而升高的血清皮 质酮含量，此外，KMBZ-009 对大鼠海马CA1 区锥体神经元的兴奋和抑制电流的 影响可能也参与了其对应激的调节作用。KMBZ-009 能显著增加海马CA1 区锥体 神经元上AMPA 受体介导的兴奋性突触后电流（EPSC）的幅度，但不影响其动力 学特性。NMDA 受体介导的EPSC 不受KMBZ-009 的影响；GABA 受体介导的抑制突 触后电流（IPSC）的幅度几乎不受KMBZ-009 的影响，而其受体动力学特性明显 被KMBZ-009 改变，表现为IPSC 恢复的时间显著延长。KMBZ-009 对CA1 区兴奋 抑制电流的调节作用，使大鼠海马细胞具有更强的维持细胞稳态的能力，从而避免应激导致神经元功能的损害。KMBZ-009 对抗应激对认知得损伤作用提示其可 能会减少动物的抑郁样行为，本实验结果发现，KMBZ-009 确实能明显减少小鼠 在强迫游泳（FST）中的不动时间，增加大鼠在72 秒低频差式强化（DRL-72s） 模型中的强化率，并降低其反应率。其机制是KMBZ-009 增加正常动物中枢神经 系统胞外NE 水平，激活alpha 和beta 肾上腺素受体，从而使得实验动物的抑郁 样行为明显减少。 2、KMBZ-009 减轻氧化应激对细胞活力、线粒体电位及海马LTP 的损伤作用。 前人的研究表明，氧自由基过多是导致老年痴呆患者和老年人神经细胞凋亡 与认知障碍的因素之一。KMBZ-009 和阿尼西坦是吡咯烷酮类化合物，研究显示 均具有促智作用。有报道指出阿尼西坦能减少神经胶质细胞在缺血缺氧时氧自由 基的生成，从而避免细胞受到氧应激损伤。本研究采用神经元原代培养和离体电 生理学方法，观察了KMBZ-009 和阿尼西坦对氧应激神经元的保护作用。结果发 现，KMBZ-009 和阿尼西坦均能保护氧应激神经元的线粒体的功能，对抗氧自由 基对神经元细胞活力的损伤，从而有效逆转了氧化应激对海马脑片CA1 区LTP 的 损伤作用。KMBZ-009 的作用效果比阿尼西坦的效果强10 倍。 3、银杏叶提取物及复方制剂改善老年大鼠空间学习记忆的突触可塑性机理。 有研究表明，银杏叶和三七叶提取物能调节神经系统的功能。本研究采用 Morris 水迷宫和活体电生理技术研究了银杏三七复方制剂及银杏叶提取物（以 标准银杏叶提取物——金纳多作为阳性对照药）改善老年大鼠空间学习记忆障碍 的突触可塑性机理研究。结果发现：老年大鼠空间学习记忆能力较差，高频诱导 不能在其海马CA1 区引发LTP，当长期服用金纳多或复方制剂一个月后，老年动 物的空间学习记忆功能得到明显改善，这可能与药物增强海马LTP 有密切关系。 复方制剂的作用效果与金纳多的效果相当。 4、悬尾应激损伤避暗作业学习行为的多巴胺D1 受体机制。 近年来的研究表明，DA 系统对应激非常敏感，应激改变PFC 内DA 的含量， 从而导致依赖于PFC 的工作记忆受损。但目前尚不知道应激对DA 系统的影响是 否涉及依赖杏仁核和海马的情绪学习记忆功能。因此，我们采用被动回避作业和 行为药理学的方法，初步探讨了此问题。结果发现：和对照组动物相比，随着悬 尾应激持续时间的增加（5min、10min、20min），动物在避暗作业作业重测试中的步入潜伏期明显缩短，当动物被悬尾应激后回到鼠笼中休息20min，其步入潜 伏期无明显变化；腹腔注射DA D1 受体拮抗剂SCH23390 呈剂量依赖性地缩短动 物的步入潜伏期，但SCH23390 腹腔注射和悬尾应激共同处理实验动物时，此种 D1 受体拮抗剂能有效逆转应激对步入潜伏期的影响；进一步的研究发现，应激 或D1 受体拮抗剂对痛觉感受的影响不是其改变动物步入潜伏期的主要因素。本 研究结果表明悬尾应激导致脑内多巴胺释放过度增加，杏仁核（可能还有海马及 相关神经回路）内的D1 受体被过度激活，从而导致小鼠在操作被动回避任务时 的记忆获得障碍。

应激和成瘾对海马突触可塑性及学习记忆的影响

海马突触可塑性是从细胞和分子水平上来阐述学习记忆机制，是学习记忆比 较直观的物质基础的一个体现。成瘾，是一种病态的、不可控制的吸食成瘾性药 物的行为，从某种角度来看，它也是一种记忆，通过篡夺正常生理神经通路产生 比正常生理反应强烈的可塑性，进而形成更有害的记忆。成瘾和学习记忆有很多 通路上甚至机制上的交叉，所以一部分研究学习记忆的方法可以用来研究成瘾。 应激，会影响正常的生理状态，并引发进一步的生化反应，进而影响到海马突触 可塑性和学习记忆。应激既然可以影响到学习记忆，而且成瘾的部分特征和学习 记忆又很相似，同时成瘾过程中基本上也伴随着应激，那么，应激在成瘾过程中 到底起着什么样的作用呢?它又是如何起作用的呢？ 本文的实验致力于回答其中的部分问题，我们通过对吗啡成瘾过程中海马的 突触可塑性和学习记忆的研究发现：单次急性吗啡处理会在非应激动物上诱导出 突触增强，但是应激可以逆转吗啡引起的突触增强，诱导出长时程的突触抑制， 但是皮质酮的拮抗剂RU38486 可以阻断这种效果。皮质酮和吗啡可以产生动物 延迟逃避的现象，说明应激在成瘾过程中的重要影响。本实验对于应激在成瘾方 面的影响进行了研究，进一步的揭开了应激在其中的部分作用机制，这对于以后 的成瘾的形成及复吸的治疗都有一定的贡献。

特异性干扰肽对海马突触可塑性的影响及其功能研究

在哺乳动物复杂的神经网络中，突触是信息传递的枢纽，其突触传递效能的持续性变化被称为突触可塑性（synaptic plasticity）。长时程增强（long-term potentiation，LTP）和长时程抑制（long-term depression，LTD）现象是两种经典的突触可塑性形式，被视作学习和记忆可能的物质基础，得到了广泛地关注。其中，海马CA1区谷氨酸能突触处的LTP和LTD目前研究得最为广泛。 α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid（AMPA）受体作为介导兴奋性谷氨酸能突触基础传递的主要受体，是海马CA1区LTP和LTD正常表达的必要条件。近期的研究表明，AMPA受体通过胞吞、胞吐及侧向移动等方式在细胞膜和细胞内进行着持续地循环。因此，通过调节AMPA受体的上、下膜，进而影响突触后膜上AMPA受体的数量，便能对LTP和LTD产生影响。在本研究中，我们利用生物信息学的手段，以AMPA受体为靶点，设计出了旨在特异阻断LTP或LTD的多肽。运用离体脑片全细胞记录方式，在海马CA1区证明了干扰肽Pep-A2能够特异地阻断LTP而不影响LTD，Pep-A3能够特异地阻断LTD而不影响LTP。并初步探究了其关键的作用位点，为进一步理解LTP和LTD具体的分子机理打下了基础。成瘾作为异常的学习记忆过程，势必涉及到突触可塑性的变化。而特异性地阻断LTP和LTD，对药物成瘾效果的影响却鲜有报道（Wang YT，2007）。在另一部分工作中，我们采用穿膜肽Tat-A2和Tat-A3，在吗啡条件化位置偏爱（morphine conditioned place preference，morphine CPP）模型小鼠的测试前进行系统给药，结果发现两种干扰肽均能阻断或损伤其CPP的表达过程。这一现象，提示我们LTP和LTD在条件化位置偏爱的表达过程中都是不可或缺的，同时也为人们更好地理解成瘾过程的机理，及开发专一有效的治疗药物提供了新的思路。

海马突触可塑性与异常记忆

5-羟色胺(5-HT)是中枢神经系统内非常重要的神经递质，广泛参与各种行为和生理过程。5-羟色胺功能低下可导致多种精神类疾病尤其是焦虑、抑郁和创伤后应激障碍等，而这些疾病都伴有学习和记忆的障碍；海马是参与学习记忆的重要脑区。海马接受5-HT神经元的直接投射且富含5-HT受体，因而海马也可以通过5-HT系统调控焦虑、抑郁及学习记忆。海马突触可塑性是学习记忆的细胞分子机制，是学习记忆的基础。我们条件性敲除转录因子Lmx1b得到中枢5-HT缺失小鼠，利用该小鼠进行中枢神经系统5-HT功能的研究。我们发现该小鼠的脑结构和运动能力正常；水迷宫空间学习能力正常，但空间记忆受损；焦虑水平降低，但是环境恐惧学习和记忆能力增强，增强的恐惧记忆能被外源给予的5-HT逆转；在中枢5-HT缺失小鼠中，应激对海马可塑性的作用即损伤LTP易化LTD消失，外源给予5-HT可以恢复应激的效果。这些结果提示应激导致海马LTP损伤可能是保护机制，缺乏这种保护机制可能导致恐惧记忆相关的创伤后应激障碍(PTSD)的易感。成瘾的核心特征是对药物的强迫性渴求和复吸。成瘾与学习记忆有很多共同的脑区和分子通路，它可能通过篡夺正常生理神经通路而产生比正常生理反应更强烈的可塑性，形成有害的异常记忆。以前的报道证实海马的兴奋性突触可塑性在成瘾过程中的适应性改变可能是成瘾的机制；但是成瘾涉及复杂的生物机制，因而不可能仅是兴奋性突触可塑性的贡献。我们研究了5-HT系统和抑制性系统（主要是GABA能系统）在成瘾中的贡献。利用中枢5-HT缺失小鼠，我们发现5-HT缺失小鼠的吗啡显著地易化了5-HT CKO的海马LTP，同时也导致成瘾行为持续不消退；5-HT和5-HT1a受体激动剂能逆转此现象。这提示毒品成瘾可能导致中枢5-HT缺失，进而增强海马LTP，使毒品相关记忆牢固不消退。GABA能系统是中枢神经系统最重要的抑制性系统，我们研究发现一次吗啡对内源性大麻受体（CB1R）依赖的抑制性突触的长时程抑制（Inhibitory long-term depression，I-LTD）没有影响，成瘾后I-LTD抑制，而吗啡成瘾后戒断导致了内源性大麻受体(CB1R)和L-型钙通道(LTCC)依赖的GABA能LTD (I-LTD)，使I-LTD增大了一倍，提示在吗啡成瘾阶段过程中，有组合突触可塑性发生，进而增强了突触可塑性的调控范围。 本论文是对中枢5-HT系统对海马兴奋性突触可塑性在焦虑、应激、成瘾等异常记忆中的调节作用以及海马抑制性系统在成瘾和戒断中的贡献进行研究，表明恐惧记忆和毒品成瘾记忆存在许多共同的细胞分子机理，对今后治疗焦虑、创伤后应激障碍和成瘾提供了新的思路。

海马环路中的组合突触可塑性与大鼠情绪研究

海马在某些类型的学习和记忆中起着关键的作用，而突触可塑性（synaptic plasticity）为学习和记忆的模型提供了理论基础。在海马环路中，分布着各种类型的可塑性，包括突触特异的Hebbian形式的可塑性，如长时程增强（long-term potentiation，LTP）和长时程抑制（long-term depression，LTD）；稳态可塑性（homeostatic plasticity），如突触缩放（synaptic scaling）。稳态可塑性是一种整体的调控过程，它可以调节神经元甚至神经网络的平衡；而Hebbian可塑性则是突触特异的，即每个突触进行单独调控的过程。 越来越多的研究提示稳态可塑性和Hebbian可塑性之间存在着空间间隙（spatial gap），那么，如何使得神经元可以通过Hebbian可塑性的过程来维持细胞整体的兴奋性就变得尤为重要。一些报道揭示了LTP和LTD可以在同一突触通路中同时被激活，因此，我们提出组合突触可塑性的概念，即LTP和LTD的组合，它在赋予系统灵活性的同时又可以降低噪音维持系统的稳定性。基于此，本文将围绕这个问题而开展实验工作。 通过对海马CA1区锥体神经元的微小兴奋性突触后电流（miniature excitatory synaptic current, mEPSC）进行测定分析，我们发现mEPSC的幅度分布符合双峰正态分布（double-peak normal distribution）。Theta节律刺激（theta burst stimuli, TBS）诱导后，mEPSC的幅度分布发生改变，呈现右移趋势。随后，采用干扰肽Pep-A2特异地阻断LTP而不影响LTD，我们发现Pep-A2不影响基础状态下mEPSC的幅度分布。在干扰肽Pep-A2存在下，TBS诱导对基础状态下mEPSC的幅度分布也没有影响。结果为揭示LTP和LTD的组合可塑性提供了初步的证据，对进一步理解记忆的编码过程提供了一定的基础。社交隔离可以引起实验大鼠产生焦虑样和抑郁样的行为，而性经历可以改变动物的情绪状态，降低焦虑样和抑郁样的反应。然而，性经历后进行社交隔离对大鼠情绪的影响并没有报道。在这部分工作中，雄性大鼠经历一周的社交活动（male-male paired housing）或者性活动（male-female paired housing），随后进行一段时间的隔离（1天，2天或者7天）。我们发现，经历过性活动的大鼠，无论隔离与否都表现出相似的情绪反应，包括焦虑样和抑郁样行为以及超声波（ultrasonic vocalizations，USVs）发放；而未经历过性活动的大鼠，其情绪反应随着隔离时间的不同而不同。这一现象提示我们，先前的性经历可以对抗实验动物对环境应激事件，如社交隔离的反应。

吗啡戒断的应激和突触可塑性机理

突触可塑性（syanptic plasticity）是指在某种条件下突触传递效能的持 续性变化，是从细胞和分子水平上来阐述学习记忆的机制，是学习记忆的基础， 存在多种形式，主要包括长时程增强（LTP）和长时程抑制（LTD）等。应激（stress） 就是指机体对各种内、外界刺激因素所作出的适应性反应的过程。应激会影响正 常的生理状态，并引发进一步的生化反应，进而影响到海马突触可塑性和学习记 忆。成瘾（addiction）是指对药物的使用失去控制，或者强迫性的寻求和使用 药物，而不顾由此带来的恶性后果，从某种角度来看，它也是一种记忆，通过篡 夺正常生理神经通路而产生比正常生理反应更强烈的可塑性，进而形成有害的异 常记忆，其最核心的特征就是对药物的强迫性渴求和复吸。成瘾一旦形成，可能 成为伴随一生的状态，即使经过长期的戒断，也会表现出强烈的渴求以及有复吸 的高度危险性。成瘾和学习记忆有很多神经通路甚至分子机制上的交叉，所以一 部分研究学习记忆的方法可以用来研究成瘾，反之，成瘾也是一种很好的研究学 习记忆的模型。 既然应激可以影响突触可塑性和学习记忆，而对于吸毒者来说，戒断本身就 是一种应激，那么探讨应激和戒断对突触可塑性和学习记忆的影响，对临床上的 戒毒工作将有着重要意义。基于此，本文将围绕这个问题而开展实验工作。 我们采用电生理、行为学及生化等研究方法对吗啡戒断过程中突触可塑性和 学习记忆,以及应激在其中的作用进行了一些研究。电生理的结果表明：在吗啡 戒断过程中,海马LTP 的大小呈现出倒－U 型曲线，其中戒断4 天时LTP 最大。 应激可以将最大的LTP 提前在戒断18 小时出现，而糖皮质激素受体拮抗剂米非司酮或者熄灭剂量的吗啡能够阻断最大的LTP 出现。同时，海马下托－伏隔核通 路的突触可塑性也出现类似的戒断时间依赖性的改变。行为学研究发现：戒断过 程中，大鼠的疼痛阈值降低，同时降低急性吗啡的镇痛效应，而这种变化能够被 应激或米非司酮所改变。另外，条件位置偏爱实验结果显示吗啡条件位置偏爱的 形成依赖于海马和伏隔核糖皮质激素受体。生化实验结果显示：戒断过程中，AMPA 受体亚型GluR1 和GluR2/3 及其调节分子CaMKⅡ会出现表达动态改变。 本实验对于应激和戒断对突触可塑性和学习记忆的影响进行了研究，进一步 揭开了应激在戒断中的部分作用机制，这将对于以后研究治疗毒品渴求和复吸有 一定的贡献

Dislocation nucleation governed softening and maximum strength in nano-twinned metals

In conventional metals, there is plenty of space for dislocations-line defects whose motion results in permanent material deformation-to multiply, so that the metal strengths are controlled by dislocation interactions with grain boundaries(1,2) and other obstacles(3,4). For nano-structured materials, in contrast, dislocation multiplication is severely confined by the nanometre-scale geometries so that continued plasticity can be expected to be source-controlled. Nano-grained polycrystalline materials were found to be strong but brittle(5-9), because both nucleation and motion of dislocations are effectively suppressed by the nanoscale crystallites. Here we report a dislocation-nucleation-controlled mechanism in nano-twinned metals(10,11) in which there are plenty of dislocation nucleation sites but dislocation motion is not confined. We show that dislocation nucleation governs the strength of such materials, resulting in their softening below a critical twin thickness. Large-scale molecular dynamics simulations and a kinetic theory of dislocation nucleation in nano-twinned metals show that there exists a transition in deformation mechanism, occurring at a critical twin-boundary spacing for which strength is maximized. At this point, the classical Hall-Petch type of strengthening due to dislocation pile-up and cutting through twin planes switches to a dislocation-nucleation-controlled softening mechanism with twin-boundary migration resulting from nucleation and motion of partial dislocations parallel to the twin planes. Most previous studies(12,13) did not consider a sufficient range of twin thickness and therefore missed this strength-softening regime. The simulations indicate that the critical twin-boundary spacing for the onset of softening in nano-twinned copper and the maximum strength depend on the grain size: the smaller the grain size, the smaller the critical twin-boundary spacing, and the higher the maximum strength of the material.

First principles based predictions of the toughness of a metal/oxide interface

We describe a first-principles-based strategy to predict the macroscopic toughness of a gamma-Ni(Al)/alpha-Al2O3 interface. Density functional theory calculations are used to ascertain energy changes upon displacing the two materials adjacent to the interface, with relaxation conducted over all atoms located within adjoining rows. Traction/displacernent curves are obtained from derivatives of the energy. Calculations are performed in mode I (opening), mode II (shear) and at a phase angle of 45 degrees. The shear calculations are conducted for displacements along < 110 > and < 112 > of the Ni lattice. A generalized interface potential function is used to characterize the results. Initial fitting to both the shear and normal stress results is required to calibrate the unknowns. Thereafter, consistency is established by using the potential to predict other traction quantities. The potential is incorporated as a traction/displacement function within a cohesive zone model and used to predict the steady-state toughness of the interface. For this purpose, the plasticity of the Ni alloy must be known, including the plasticity length scale. Measurements obtained for a gamma-Ni superalloy are used and the toughness predicted over the full range of mode mixity. Additional results for a range of alloys are used to demonstrate the influences of yield strength and length scale.