我们承认维也纳果蝇资源中心提供果蝇菌株。此外，在本研究中使用从布卢明顿果蝇库存中心获得的种群（NIH P40OD018537）。这项研究部分得到欧盟FP7大型综合网络Gencodys向KK，HvB和AS以及NSERC发现和CIHR项目拨款的支持

注意:在下面列出的协议中，描述了一系列的收集，训练和测试。为了测试结果的可重复性，这些步骤应该在多天并行并且分开的苍蝇组（ 表1）重复。该方案基于从蛋到成虫的10天生命周期，当在25℃，70％湿度和12小时光/暗循环的恒定条件下饲养苍蝇时，这是正常的。该协议的所有方面假设条件在整个测定中保持不变。时间在灯开启前（BLO）或照明灯开启（ALO）后的小时表示，因为这可以根据研究人员的首选时间方便地进行设置。仅使用二氧化碳气体初次收集幼稚的雄蝇，并收集预先的女性。该求求条件协议由以下步骤组成: <ol><li> Ë建立预选的女性收藏文化</li><li>建立收集男性考试科目的文化</li><li>房屋的准备</li><li>建立用于生产标准化预先女性的交配瓶</li><li>收集男性考试科目</li><li>训练</li><li>测试</li><li>视频数据分析和统计</li></ol> 1.预设女性收藏文化的建立<ol><li>准备精力充沛16 。煮沸0.8％（w / v）琼脂，8％（w / v）酵母，2％（w / v）酵母提取物，2％（w / v）蛋白胨，3％（w / v）蔗糖，6％ w / v）葡萄糖，0.05％（w / v）MgSO 4和0.05％（w / v）CaCl 2水溶液15分钟。在加入0.05％（w / v）的对羟基苯甲酸甲酯（小心:有毒）和0.5％（v / v）丙酸（注意:有毒）之前，将溶液冷却至70℃。搅拌均匀，同时冷却至50℃，得到均匀溶液。 </li><li>之前的食物是这样的在室温下盖起来，向每个175mL塑料小瓶中加入〜50mL的功率食品。让食物进一步冷却。用插头关闭小瓶。 注意:Powerfood是一种专门用于生产大量苍蝇的专门食品混合物，大概是通过诱导产蛋。 Powerfood不用于生产用于行为分析的男性蝇（步骤2），因为非典型饮食和潜在的拥挤可能会影响发育。 </li><li>在第11天（ 表1 ），启动5-20野生型培养物，大约60-100只（男性和女性的混合物）在动力食品小瓶中;这些将在步骤4中用于制作标准化的预先女性17 。在每个小瓶中加入滤纸以增加幼虫可以蛹的面积;这将增加可以减少的苍蝇数量。 </li><li>在整个实验中定期重复步骤1.1-1.3，以获得足够的新近飞翔的苍蝇作为输入"建立用于生产标准化前置女性的交配小瓶"（步骤4）。 </li></ol> 2.建立男性考试科目收集文化<ol><li>准备正常食物16 ，用0.5％（w / v）琼脂，2.75％（w / v）酵母，5.2％（w / v）玉米粉，11％（w / v）糖，0.05％（w / v） ）对羟基苯甲酸甲酯和0.5％（v / v）丙酸的水溶液，如步骤1.1和1.2所述。关闭175毫升塑料小瓶与一个飞瓶插头。 </li><li>在第-10天（ 表1 ），在每个含有正常食物的175mL小瓶中放置大约10-20名男性，约30-75名女性（ 材料/设备表 ）。添加滤纸以增加瞳孔的表面积并最大限度地提高生产率。 </li><li>根据基因型建立三至六个175 mL小瓶，以获得所需数量的测试对象雄性。 注意:根据所需要的生产力，可能需要更多的小瓶otype。 </li></ol> 3.住房块的准备（ 图2A ） <ol><li>在微波炉中每个住宅区块融化约50 mL的功率食品，或者将其新鲜烹调。 </li><li>使用多分配器移液管向96孔平底块的每个孔中加入500μL功率食品。 </li><li>让食物在室温下固化。 </li><li>用PCR粘合剂膜覆盖块体，并使用针头每孔至少4个孔，为苍蝇提供新鲜空气。 </li><li>为了能够打开每个孔，使用剃刀刀片在每排之间纵向切割粘合剂膜。在胶片的一端离开胶片。 </li><li>块可以在4℃下储存长达2天。 注意:使用前，让块重新平衡至室温。 </li></ol> 4.建立标准化预售女性生产的配套样品瓶<ol><li>在第-1天，删除和丢弃所有成年野生型苍蝇从预选的女性收集文化在2-5小时BLO。 </li><li>使用抽吸器（ 图2B ）从这些小瓶中以2-3小时间隔（ 例如， 30分钟，2.5小时和5小时ALO）收集苍蝇，并将它们放入补充有少量酵母的新功率食品小瓶中粘贴和滤纸。 </li><li>为了避免拥挤和促进最佳交配气氛，不要将超过150-200只苍蝇转移到每个新的小瓶中。确保所有女性的交配，提供至少25％的男性。确保足够的雌性存在于交配小瓶中以适应实验的大小。 注意:由于这是协议中的关键步骤，请确保只有新鲜的苍蝇，没有老苍蝇，幼虫或蛹被转移到新的交配小瓶。 </li><li>孵育这些"交配小瓶"四天，以便足够的时间让所有的女性交配。 </li></ol>上校男性测试科目的选择<ol><li>在2-3小时BLO的第1天（ 表1 ），使用CO 2从雄性收集瓶中除去所有成年苍蝇（步骤2）， 但让更多的苍蝇在接下来的几个小时内消失。 </li><li>在接下来的5-6小时内，使用二氧化碳每20-30分钟清除一次新近放飞的苍蝇，并使用吸气器将每个雄性放在住房块的单个井中（步骤3）（ 图2B ）。 </li><li>用粘合剂PCR膜重新密封孔。 注意:这是协议中的关键步骤。男性应该经常收集。收集的男性应该在接近时间的房屋隔离，当它们表现出淡色的色素沉着和半透明的腹部存在胎粪时。 注意:温和使用吸气器可以转移苍蝇;然而，不当使用会强调苍蝇，导致测定方法的差异（参见讨论）。 </li><li>瞄准公司每个基因型最多可以检测到48位男性。这对于分析初始和训练条件所需的最大数量的男性提供了一小部分，允许在以后的转移步骤中发生一些损失。 </li></ol> 6.培训<ol><li>使用二氧化碳从配套小瓶中取出苍蝇（步骤4.2），并将预先选定的雌雄与男性分开。 </li><li>使用吸气器，在一排新的房屋块中的每个井中添加一个麻醉的，预先的女性。 </li><li>使用吸气器和无麻醉，将个体初生男性从步骤5.2中设置的房屋块转移到含有预先存在的女性的井中。将男性放入井后，立即用粘合膜重新密封;不要让男人逃跑。 注意:通过利用自然"负性地质变化"行为将雄蝇从吸气器转移到房屋块（参见讨论）。 </li><li>重复步骤6.2-6.3直到足够的雄 - 雌对成立。理想地，根据基因型建立24对，两排全部住房块。将剩余的初始男性留在第5.2步中设置的原始住房块。 </li><li>在训练期间保持男性 - 女性对不受干扰（ 表2 ， 图1B ）。 注意:在这段时间内，男性将被法庭判决，并被预先的女性拒绝。对于学习和STM，培训期为1小时，对于LTM，培训期为7-9小时。 </li><li>结束训练（ 表2 ， 图1B ），使用吸气器轻轻分离男性与预先的女性;不要使用麻醉。将分离的男子放在一个新的住房区。 </li><li>使用吸气器将所有幼稚的男性轻轻地从第5.2步中设置的房屋块轻轻地传输到新的房屋块。 注意:此步骤对于STM和lea是可选的但是对于LTM来说，这是非常重要的，因为苍蝇被安置了另外24小时才能测试LTM。 </li><li>对于STM和LTM，允许男性在测试前分别休息1小时和〜24小时（ 表2 ， 图1B ）（步骤7）。 </li><li>为了学习，立即测试训练有素和幼稚的男性（步骤7）。 </li></ol> 7.测试<ol><li>使用CO 2从交配小瓶收集苍蝇（步骤4.2），并将预先的雌性和雄性分离。 </li><li>让女性在含有正常食物的小瓶中从麻醉中恢复至少1小时。 </li><li>提前安装录像机（ 图2C ），以便在测试开始前准备好所有设备。 </li><li>根据不同的学习时间表，STM和LTM开始测试（ 表2 ， 图1B ）。训练后立即进行测试用于学习，训练1小时后，LTM培训24小时。 </li><li>如果正在测试学习（步骤6.7，训练有素;步骤6.8，天真），使用吸气器，将个体男性从休息的住房区块或训练住房区块中移出，到隔离区域的一半的求偶场上（ 图2D ;见建筑图的文件S1）。 注意:使用自然的"负性地质变化"行为应足以将雄蝇从抽吸器转移到求偶场（讨论）。 </li><li>快速但轻轻地将入口移动到下一个竞技场，重复步骤7.5，直到所有18个场地都包含一个男性。 </li><li>使用吸气器和无二氧化碳，将一个预先的女性（收集在步骤7.2中）添加到所有18个场地的另一半。 </li><li>小心地将求爱室放在照相机下面，井的开口朝下（ 图2C </stron克&gt;）。 </li><li>移除场地的分隔线，以允许男性和预先女性之间的直接相互作用。 </li><li>立即开始记录行为至少10分钟。 注意:当使用双摄像头设置时，可以在重叠的时间范围内并行记录两个求偶板，以最大限度地提高效率。 </li><li>使用手持吸尘器清空求爱场所，并允许求爱室在重新使用前通风。 </li><li>重复步骤7.4-7.11直到所有基因型和条件的测试（ 即天真和训练）已经完成。 </li></ol> 8.视频数据分析与统计<ol><li>计算求偶指数（CI），定义为男性法庭在测试期间的前10分钟内对每个单独的雄性飞行所占的时间百分比。 注意:这可以通过观察刻板的求爱行为（ 图1A ）或您的手动完成唱电脑软件，用于自动量化求爱行为（讨论）。 注意:建议在三天内分析每个病情40-60名男性，以达到足够的统计学能力，并判断CI数据的一致性。 </li><li>计算学习指数（LI），定义为与未成年男性相比，训练男性平均CI的百分比降低（LI =（CI naive - CI 训练 ）/ CI 天真 ）。评估每一天的LI测试，并将其与从所有测试日合并计算的累积LI进行比较。 </li><li>使用"基因型"和"CI"作为标题单独的两列选项卡数据文件。 注意:这些标题区分大小写。每个CI的基因型名称必须包括基因型的描述，后跟下划线和训练条件（ 例如，基因型-N和基因型-LTM等，其中N =naïve和LTM =长期记忆;参见补充文件S2作为示例）。该注释是必不可少的，因为该功能将基于"基因型"列中第一个下划线之后的字符识别经过训练和幼稚的苍蝇。 </li><li> 使用Analystn R脚本（补充文件S3）进行随机化测试，以判断来自不同基因型的LI值之间的差异的统计学显着性。 <ol><li>将脚本（补充文件S3）导入到R 18中 ，其定义了一个称为"analnn"的函数。 注意:函数定义是:analaryn &lt; - function（nboot = 10,000，naivelevel =&#39;N&#39;，refmutation = NA，datname = NA，header = TRUE，seed = NA，writeoutput = TRUE）。 </li><li>通过在R命令行中输入"analearn（）"并通过弹出窗口选择要分析的数据文件（在步骤8.3中生成）来启动该功能。 </li><li>选择参考突变，其中是控制基因型，输入相应的数字并按enter键。 注意:选择参考基因型后，脚本需要几秒钟才能执行10,000次引导重复。 </li><li>观察输出表（表3），其中包含基因型，学习条件（ 即学习，STM或LTM），平均CI天真，平均CI训练，LI，控制的LI与实验条件之间的差异（LI dif），LI dif的95％置信区间的下限（LL）和上限（UL），以及表示没有显着差异的概率的p值。 注意:analnn将将输出文本文件存储在数据文件所在的目录中。但是，输出表也出现在R-Studio控制台中。默认名称是根据提供的数据文件的名称构建的。 </li><li>在分析函数中有几个可以用来改变de的参数功能的故障设置来调整自举参数。 注意:"nboot"定义了引导重复次数，默认设置为10,000。该值可以更改为大于零的任何整数。表5列出了可用于更改功能的默认设置的几个参数。但是，建议不要使用数量少的自举重复生成的数据。 </li></ol></li></ol>

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An Introduction to Drosophila melanogaster.</a> JoVE. , (2017).</li><li>R Core Team. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=R:+A+Language+and+Environment+for+Statistical+Computing.">R: A Language and Environment for Statistical Computing.</a> R Foundation for Statistical Computing. , (2016).</li><li>Stepien, B. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RNA-binding+profiles+of+Drosophila+CPEB+proteins+Orb+and+Orb2).">RNA-binding profiles of Drosophila CPEB proteins Orb and Orb2).</a> Proc. Natl. Acad. Sci. USA. 113, E7030-E7038 (2016).</li><li>Basu, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Randomization+Analysis+of+Experimental+Data:+The+Fisher+Randomization+Test.">Randomization Analysis of Experimental Data: The Fisher Randomization Test.</a> J Am Stat Assoc. 75, 575-582 (1980).</li><li>Dankert, H., Wang, L., Hoopfer, E. D., Anderson, D. J., Perona, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+monitoring+and+analysis+of+social+behavior+in+Drosophila.">Automated monitoring and analysis of social behavior in Drosophila.</a> Nat Methods. 6, 297-303 (2009).</li><li>Reza, M. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+analysis+of+courtship+suppression+learning+and+memory+in+Drosophila+melanogaster.">Automated analysis of courtship suppression learning and memory in Drosophila melanogaster.</a> Fly. 7, 105-111 (2013).</li><li>Schneider, J., Levine, J. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+identification+of+social+interaction+criteria+in+Drosophila+melanogaster.">Automated identification of social interaction criteria in Drosophila melanogaster.</a> Biol. Lett. 10, 20140749 (2014).</li></ol>

作者没有什么可以披露的。

求偶条件测定法是分析果蝇学习和记忆的典型范例。这里提出的协议遵循前面6,7,8,9所述的一般方法，但包括独特方面，如实用指南，专门设备和用于随机化测试的数据分析脚本9,12。使用该协议，可以使用96孔平底块（ 图2A ）并行分析大量苍蝇，以收集和训练雄性。这些块用PCR粘合剂膜密封，这使得苍蝇在需要时容易接近。此外，这里描述的独特的求爱室允许在近二维空间中同时配对18个男 - 女对，最适合视频分析。定制的求爱室易于使用，并提供建筑计划（ 文件S1 ， 图2D ）。该协议从用于收集测试对象到收集视频数据的文化的建立需要大约20天（ 表1 ）。视频数据分析需要额外的时间。根据我们的经验，STM测定非常强大。 LTM测定也相当健壮，但对混合环境变量更敏感，因此可能难以掌握。 动物行为可以变化很大。因此，必须小心执行协议中的关键步骤以减少此方差。首先，温和地使用吸气器（ 图2B ）可以减轻粗暴处理或吹出太强烈的压力。提出个人转让方式从吸气器出发是通过使用负面的地理位置。随着苍蝇往往走起来，可以简单地将吸嘴的尖端向上;在飞行到达提示之前，轻轻的打击就足以让飞出。此外，为了让男性在测试之前进入求爱室，打击往往是没有必要的。 另一个重要的步骤是收集和产生男性考试科目。所有的男性在年轻的时候都必须收集，社会上是天真的。这可以通过在羽化的高峰期期间频繁收集来实现（步骤5.2）。如果在这个紧张的时间内没有收集到男性，他们可能会有早期的社交互动，这可能导致学习不良或CI的高度变异性。应评估的男性测试对象的另一个因素是遗传背景。不同的遗传背景将表现出不同程度的初始求爱，并且一般活动或运动能力也可能不同。当compa环多重基因型，应考虑遗传背景，以避免可能影响李分数的这些混杂因素。此外，应仔细评估CI数据的分布。 CI数据可以是参数和非参数，这取决于基因型或其他环境因素。在某些情况下，如果CI的分布显着地偏离正态分布，那么使用中位数CI而不是用于计算LI的平均值可能会更好。然而，在我们的经验中，中位数或平均CI的使用在数据的统计解释方面没有任何差异，平均CI的使用是文献中的常见做法。 对于成功的求爱条件，在训练期间积极拒绝预先女性的男性求爱意图至关重要。重要的是确保在该测定中使用的预先使用的雌性已经被有效地交配并且是因此不允许交配。这种预先建立在步骤4中制备的交配小瓶中，其中雄性和雌性苍蝇一起饲养4天（ 表1 ）。随后，可以通过定期检查测试视频和在训练期间观察男性 - 女性对来监测交配。如果交配确实发生，在预备的女性的准备过程中可以采取几种措施。首先，在最佳育种条件下，应先预选女性。可以用酵母糊和折叠滤纸补充小瓶以增加潜在的配对面。在这里描述的条件下，苍蝇的孵化已经在过去产生了强大的预先的雌性，但是这可能在不同的实验室和使用不同的遗传菌株中变化。因此，可能需要通过改变孵育时间和条件来优化预先女性的产生。 求爱行为的定量是该协议的另一个关键步骤。这可以手动或使用专门的软件程序自动完成。自动量化速度快，原则上是无偏见的。已经出版了几个节目21,22,23 ;然而，它们不是直接使用，通常需要专门的视频格式和高级计算技能。手动量化容易准确，但是劳动密集度高，受个体差异和偏差的影响。重要的是要强调，该协议不能满足视频格式化对于CI的自动化量化可能需要的要求。对于手动量化，使用任何简单的视频录制设备，可能产生足够质量的视频，以准确地观察求爱行为。对于自动量化，可能会有所不同要求取决于所使用的软件，如果需要自动量化，用户应彻底调查。 结合可用于苍蝇遗传操作的广泛工具，求偶条件测定提供了强大的读数，可用于解剖学习和记忆中涉及的分子机制和神经元网络。

在许多物种中，学习和记忆的分子机制是保守的。嗅觉学习和记忆缺陷的果蝇黑腹果蝇突变体系的开创性工作筛选为基础学习和记忆的过程提供了关键的分子洞察1 。这些研究确定了一些参与学习和记忆的第一个基因，如芸香花2 ， 失忆 3和猝死4 ，揭示环磷酸腺苷（cAMP）信号传导的关键作用5 。 记忆突变体的早期遗传筛选主要使用嗅觉调理进行。然而，随着时间的推移，出现了几种测量其他形式的学习和记忆的方法。最广泛使用的学习和记忆范式之一以及这里描述的测定法被称为c这是由Siegel和6号馆首先描述的，然后由其他几个研究组7,8,9提炼。求偶调理取决于在交配过程中由男性沉积的雌性腹部上存在特定的信息素（醋酸顺式乙酰胆碱）。感觉女性腹部的cVA自然降低了求偶行为，当加上女性拒绝的行为时，cVA对男性求爱减少的影响显着增强。通过观察其独特的求偶行为，可以容易地量化男性苍蝇的反应，其特征在于朝向和跟随雌性，叩击，延伸和振动翼，舔和尝试交配10 （ 图1A ）。雄蝇学会区分<html>接受处女和不接受交配的女性11之间的h，并且在性拒绝之后，他们向不接受的女性展示了9天的求偶行为。这种自然行为可用于阐明学习，短期记忆（STM）和长期记忆（LTM）8,9,12的机制。学习被定义为在训练期间立即减少求偶行为，通常被称为即时回忆记忆，在暴露于配偶女性6,8之后0至30分钟测量。在训练后30分钟和1小时之间测量STM，而训练后24小时最常测量LTM（ 图1B ）。 STM可以使用1小时训练期诱导，但只持续2-3小时s ="xref"&gt; 6，8。在大多数学习范例中，LTM只能通过间歇反复训练来诱导。 Mcbride 等 （1999） 8显示，三次间隔1小时的培训课程足以诱导持续长达9天的求偶记忆，与单次1小时训练课程诱导的2-3小时相反。 McBride 等人 8还表明，单一的5小时训练课程产生了长达9天的相似的LTM反应。苍蝇不要在这个5小时期间不断地进行法庭训练，实际上是在一次训练中产生自己的间歇训练来诱导LTM。从实践的角度来看，这是非常重要的，大大增加了该测定法可用于研究LTM的容易程度。目前的协议主要针对LTM 11,12采用7小时的单次训练。几项研究调查不同在求偶学习的不同方面具有特定缺陷的突变条件。例如，蘑菇体消融影响STM和LTM，但不学习8 。 遗忘基因的突变首先被定义为使用嗅觉调理3的记忆的特异性调节因子，影响STM而不是学习6 。翻译调节子orb2（oo18 RNA结合（orb）CPEB2亚科）和蜕皮激素信号的破坏专门影响LTM 9,13。因此，求爱条件是解剖学习和记忆不同阶段的机制的有用范例。 这项工作展示了一个优化的实验设置，允许求和条件的相对高通量的测试。此外，它描述了统计分析脚本，并讨论了测定的关键因素。是sh自己在这里认为果蝇基因磷酸二羟基丙酮酰基转移酶 （ Dhap-at ） 在LTM的神经元中是必需的，但不适用于STM。该基因的人类直系同源物， 甘油磷酸O-酰基转移酶 （ GNPAT ），在2型14型的根茎性软骨发育不全症突变中，其特征在于严重的智力障碍，癫痫发作和其他几种临床特征15的常染色体沉默症。在这种情况下，求偶调节可用于功能验证人类疾病基因在学习和记忆中的作用，为机械研究提供依据。

<table border="0" cellpadding="0" cellspacing="0" width="1074">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">P{KK101437}VIE-260B</td>
			<td style="width:159px;">VDRC</td>
			<td style="width:119px;">101437</td>
			<td style="width:343px;">Dhat-at-RNAi in 60100 background&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">P{KK108109}VIE-260B</td>
			<td style="width:159px;">-</td>
			<td style="width:119px;">-</td>
			<td>Control-RNAi in 60100 background (gift from K. Keleman)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">w+, UAS-dcr2/yhh;;elav-Gal4 (III)&#160;</td>
			<td style="width:159px;">-</td>
			<td style="width:119px;">-</td>
			<td>panneuronal driver line</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Containers for plant tissue culture</td>
			<td style="width:159px;">VWR</td>
			<td style="width:119px;">960177</td>
			<td>175 mL plastic vials</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Folded filters</td>
			<td style="width:159px;">Whatman</td>
			<td style="width:119px;">10311643</td>
			<td>Filter paper to enlarge area flies can pupate on&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Flat-bottom blocks (96-wells)</td>
			<td style="width:159px;">Qiagen</td>
			<td style="width:119px;">19579</td>
			<td>Used for housing blocks</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">MicroAmp Clear Adhesive Film</td>
			<td style="width:159px;">Applied Biosystems</td>
			<td style="width:119px;">4306311</td>
			<td>PCR adhesive film as lid on flat-bottom blocks</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Razor blade</td>
			<td style="width:159px;">-</td>
			<td style="width:119px;">-</td>
			<td>Any sharp will do</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Needle&#160;</td>
			<td style="width:159px;">-</td>
			<td style="width:119px;">-</td>
			<td>0.8 mm diameter</td>
		</tr>
		<tr height="168">
			<td height="168" style="height:168px;width:453px;">Aspirator</td>
			<td style="width:159px;">-</td>
			<td style="width:119px;">-</td>
			<td style="width:343px;">Cut a 1mL pipet tip with scissors in order to have two pieces. The narrow tip of the pipettip is placed as fly entrance in a ~80 cm flexible hose. To prevent a fly from getting in the hose, a normal piece of cotton or small mesh gaze is placed in between the tip and the hose. The other half of the pipettip can be used as mouth piece at the end of the hose.&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Courtship chambers</td>
			<td style="width:159px;">-</td>
			<td style="width:119px;">-</td>
			<td>file S1 can be opened with indicated CAD software&#160;</td>
		</tr>
		<tr height="210">
			<td height="210" style="height:210px;width:453px;">Camcorder</td>
			<td style="width:159px;">Sony</td>
			<td style="width:119px;">-</td>
			<td style="width:343px;">camera specification: &#62;4M pixels, full HD. 
			For manual quantification, any simple video recording device has the potential to produce a video of sufficient quality to observe courtship behavior accurately. For automated quantification, there will likely be different requirements depending on the software to be used, and users should investigate this thoroughly if automated quantification is desired.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Name</td>
			<td style="width:159px;">Company</td>
			<td style="width:119px;">Catalog Number</td>
			<td>Comments</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">power food</td>
			<td style="width:159px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Agar</td>
			<td style="width:159px;">Sigma</td>
			<td style="width:119px;">A7002</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Yeast</td>
			<td style="width:159px;">Bruggeman</td>
			<td style="width:119px;">-</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Yeast extract</td>
			<td style="width:159px;">MP biomedicals</td>
			<td>0210330391&#160;</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Peptone</td>
			<td style="width:159px;">Sigma</td>
			<td style="width:119px;">P6838</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Sucrose</td>
			<td style="width:159px;">Sigma</td>
			<td style="width:119px;">S9378</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Glucose</td>
			<td style="width:159px;">Sigma</td>
			<td style="width:119px;">G7021</td>
			<td></td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;width:453px;">MgSO4</td>
			<td style="width:159px;">Sigma</td>
			<td style="width:119px;">M2643</td>
			<td></td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;width:453px;">CaCl2</td>
			<td style="width:159px;">Merck</td>
			<td>1023780500</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Methylparabene (CAUTION)</td>
			<td style="width:159px;">Sigma</td>
			<td style="width:119px;">H5501</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Propionic acid (CAUTION)</td>
			<td style="width:159px;">Sigma</td>
			<td style="width:119px;">P1386</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Demineralized water</td>
			<td style="width:159px;">-</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Yeast paste</td>
			<td style="width:159px;">-</td>
			<td style="width:119px;"></td>
			<td>yeast grains and water mixture in a 1:1 ratio</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Name</td>
			<td style="width:159px;">Company</td>
			<td style="width:119px;">Catalog Number</td>
			<td>Comments</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">normal food</td>
			<td style="width:159px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Agar</td>
			<td style="width:159px;">MP biomedicals</td>
			<td>215017890</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Yeast</td>
			<td style="width:159px;">bruggeman</td>
			<td style="width:119px;">-</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Corn flour</td>
			<td style="width:159px;">de Molen</td>
			<td style="width:119px;">-</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Sugar</td>
			<td style="width:159px;">de Molen</td>
			<td style="width:119px;">-</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Methylparabene (CAUTION)</td>
			<td style="width:159px;">Sigma</td>
			<td style="width:119px;">H5501</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Propionic acid (CAUTION)</td>
			<td style="width:159px;">Sigma</td>
			<td style="width:119px;">P1386</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:453px;">Demineralized water</td>
			<td style="width:159px;">-</td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
	</tbody>
</table>

drosophila courtship conditioning as a measure of learning and memory

通过在模型生物体（如果蝇， 黑腹果蝇）中使用简单的行为分析，已经阐明了对学习和记忆底层的分子机制的许多见解。 果蝇可用于了解由与智力障碍（ID）和自闭症相关的人类认知障碍相关基因突变引起的认知缺陷的基本神经生物学。这项工作描述了一种使用被称为求爱条件的果蝇的经典范例来测试学习和记忆的方法。男性苍蝇法庭女性使用明显的易于识别的行为模式。预定的女性不接受交配，并将拒绝男性的交配尝试。为了回应这一拒绝，男性苍蝇减少了他们的求偶行为。随着时间的推移，这种学习减少求偶行为是衡量学习和记忆能力的指标。基本的num该测定的理论输出是求偶指数（CI），其定义为男性在10分钟间隔期间花费的时间的百分比。学习指数（LI）是与没有以前的社交相遇的天真苍蝇相比，已经暴露于预先的女性的苍蝇中的CI的相对减少。为了对基因型之间的LIs进行统计学比较，使用了自举的随机化测试。为了说明测定法如何用于解决与学习和记忆有关的基因的作用，本文对此表征了二羟丙酮磷酸酰基转移酶 （ Dhap-at ）的泛神经元敲低。 Dhap-at ， 甘油磷酸O-酰基转移酶 （ GNPT ）的人类直系同源物参与了2型严重软骨发育不全症，特征为严重的ID的常染色体沉默综合征。使用求偶条件测定法，确定Dhap-at是长期记忆所必需的，但不是短期记忆。该结果作为进一步研究潜在分子机制的基础。

求偶条件测定可用于测量果蝇的学习和记忆。为了证明这一点，这里给出的结果分析与控制苍蝇相比，STM和LTM与具有Dhap-at的神经元特异性敲低的苍蝇相比。控制雄性表达靶向秀丽隐杆线虫特异性基因的RNA干扰发夹序列，推定的锌指蛋白C02F5.12 19 。该对照菌株在相同遗传背景下确保了敲除和对照之间相同数量的上游激活序列（UAS）元件，并且对照RNAi发夹解决了RNAi系统的任何非特异性作用。对照男性（基因型: UAS-dcr2 / +; P {KK108109} VIE-260B / +; elav-Gal4 / + ）显示了对于两种STM的训练对初始的CI的显着降低（ 图3A ， p = 1.2×10- 4 ，Mann-Whitney U检验）和LTM（ 图3B ， p = 1.2×10 -4 ，Mann-Whitney U检验）。这个结果反映了这些苍蝇的学习和记忆的正常能力。对于STM，训练有素的幼虫（ 图3A ， p = 1.2×10 -4 ，Mann-Whitney U检验）。然而，它们在LTM训练后没有显示出CI的显着降低（ 图3B ， p = 0.33，Mann-Whitney U-检验）。 Mann-Whitney U检验用于比较初始和训练苍蝇的平均CI，这是由于某些条件下CI数据的非参数分布（ 图3A和3B ）。通过CI的分析观察到的差异由LI针对每个基因型反映出来，其测量百分比减少在幼稚与受过训练的苍蝇中的CI（ 图3C ）。在对照组和对照组的Dhap-at敲低蝇中，LI（ p = 0.115，10,000次引导重复， 图3C ， 表3 ）之间的LI没有显着差异 ，而LTM中的L1在Dhap-at击倒蝇中显着较低（ p = 0.0034，10,000次引导重复， 图3C ， 表3 ）。为了比较基因型之间的LI，随机化测试20适用于Kamyshev 等人首先推荐的方法。 7被使用。由于LI是来自人口数据的单一值（ 即平均CI初始和平均CI训练），所以依赖于实验派生分布的标准统计方法不适用。随机化测试是无分布的，并且使用自举（ 即随机抽样）ng），以产生从实际数据导出的假设数据集。分析脚本（File S3）为每个基因型生成一组假设的LI，并计算对照和测试基因型（LIdiff）之间的差异。该过程重复10,000次，结果值用于确定LIdiff的95％置信区间（ 表3 ）。该数据用于生成指示两种基因型的LI不同的概率的p值。这里显示的结果表明，Dhap-at在LTM神经元中是必需的，但不适用于STM。 为了控制日常变异性，在复制天数之间比较CI和LI（ 表4 ）。尽管每天都观察到LI的一些波动，但结果通常是可重复的。重要的是要注意，CI数据可能会因控制str而有很大差异ain使用和环境条件的测试。这里显示的CI数据是典型的这种对照基因型，但其他基因型可能表现出更高或更低的平均CI和分布。 <img alt="图1" class="xfigimg" src="/files/ftp_upload/55808/55808fig1.jpg" /> 图1:求助指数的确定和实验概况。 （ A ）展示了对女性飞行的刻板男性求爱行为的图像。示出了不同阶段的求偶行为:方向（I），以下（II），机翼振动（延伸）和攻丝（III），舔（IV）和尝试交配（V）。 （ B ）相对于孵化器轻循环的训练和测试时间的示意图，以小时为单位。培训时间用条形表示，STM和LTM的休息时间用虚线表示，测试起始点用箭头表示。请注意LTM的测试时间是训练后的第二天。 <a href="http://ecsource.jove.com/files/ftp_upload/55808/55808fig1large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图2" class="xfigimg" src="/files/ftp_upload/55808/55808fig2.jpg" /> 图2:用于果蝇求助调理分析的设备。 （ A ）住房块是一个平坦的底部块，每个孔具有500μL的功率食物。用qPCR粘合剂膜密封，每个孔至少有4个孔，使用直径为0.8mm的注射器针产生。使用剃刀刀片将各行纵向切割成条，以允许打开和关闭。 （ B ）无需麻醉，需要抽吸器轻柔转移雄性和雌性苍蝇。插图显示吸气器的尖端，用一块棉花封闭注意提示内的苍蝇​​。 （ C ）设置双摄像机系统，同时录制两个求爱室。 （ D ）拥有18个场地的求偶室。使用滑动进入孔将苍蝇放置在场地中。白色分隔线可以同时打开，以发起男性和女性之间的相互作用。 <a href="http://ecsource.jove.com/files/ftp_upload/55808/55808fig2large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图3" class="xfigimg" src="/files/ftp_upload/55808/55808fig3.jpg" /> 图3:控制中的STM和LTM的分析和敲击飞行中的Dhap。 （ AB ）显示对于STM（A）和LTM（B）测试的对照（灰色）和Dhap-at敲低（白色）基因型的初始（N）和训练（T）蝇的CI值的分布的盒图。 （ C ）Correspo对于STM和LTM测试的控制和Dhap-at击倒飞行的确定 LI值。使用随机试验（10,000次引导重复）比较对照和敲低基因型之间的LI差异。误差条表示在不同测试日计算出的LI值的平均值的标准误差。基因型为: w +，UAS-dcr2 / + ; P {KK108109} VIE-260B / + ;和elav-Gal4 / + （对照） 和w +，UAS-dcr2 / + ; VIE-260B / +;和elav-Gal4 / + （ Dhap-at- RNAi）。 <a href="http://ecsource.jove.com/files/ftp_upload/55808/55808fig3large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td></td><td> 一般 </td><td> 搜集 </td><td> 培养 </td><td> 测试 </td></tr><tr><td> day -11 </td><td>开始预先的女性收藏文化（步骤1.3） </td><td></td><td></td><td></td></tr><tr><td>天-10 </td><td>开始收集男性受试者的文化（第2.2步） </td><td></td><td></td><td></td></tr><tr><td>第1天</td><td></td><td>代表。 1 </td><td></td><td></td></tr><tr><td>第2天</td><td></td><td>代表。 2 </td><td></td><td></td></tr><tr><td>第3天</td><td></td><td>代表。 3 </td><td></td><td></td></tr><tr><td>第4天</td><td></td><td>代表。 4 </td><td>代表。 1 </td><td></td></tr><tr><td>第5天</td><td></td><td></td><td>代表。 2 </td><td>代表。 1 </td></tr><tr><td>第6天</td><td></td><td></td><td>代表。 3 </td><td>代表。 2 </td></tr><tr><td>第7天</td><td></td><td></td><td>代表。 4 </td><td>代表。 3 </td></tr><tr><td>第8天</td><td></td><td></td><td></td><td>代表。 4 </td></tr><tr><td>第9天</td><td>视频数据分析和统计（步骤8） </td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td></tr><tr><td colspan="2"> rep =重复</td><td></td><td></td><td></td></tr></tbody></table> 表1 : 用于在个别天数上测试三次复制的LTM的示例时间表。 <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td></td><td> 学习 </td><td> STM </td><td> LTM </td></tr><tr><td>训练时间</td><td> 1小时。 </td><td> 1小时。 </td><td> 8小时。 </td></tr><tr><td>休息时间</td><td> 0小时。 </td><td> 1小时。 </td><td> 〜24小时。 </td></tr><tr><td>开始训练</td><td> 0H。 ALO </td><td> 0小时。 ALO </td><td> 4小时BLO </td></tr><tr><td>停止训练</td><td> 1小时。 ALO </td><td> 1小时。 ALO </td><td> 4小时ALO </td></tr><tr><td>开始测试</td><td> 1小时。 ALO </td><td> 2小时ALO </td><td> 0小时。 ALO（第二天） </td></tr><tr><td colspan="4"> ALO =灯亮后，BLO =开灯前，STM =短期记忆，LTM =长期记忆</td></tr></tbody></table> 表2 : 学习，STM和LTM的培训时间，培训时间和测试时间。 <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td> 基因型 </td><td> 学习 条件 </td><td> CI 幼稚 </td><td> CI 熟练 </td><td> 李 </td><td> 李 区别</td><td> 下限 （95％信心间隔） </td><td> 上限 （95％信心间隔） </td><td> p值 </td></tr><tr><td>控制</td><td> STM </td><td> 0.467 </td><td> 0.116 </td><td> 0.752 </td><td> NA </td><td> NA </td><td> NA </td><td> NA </td></tr><tr><td> DHAP-AT-RNA干扰</td><td> STM </td><td> 0.699 </td><td> 0.257 </td><td> 0.633 </td><td> 0.119 </td><td> -0.030 </td><td> 0.265 </td><td> 0.116 </td></tr><tr><td>控制</td><td> LTM </td><td> 0.590 </td><td> 0.384 </td><td> 0.348 </td><td> NA </td><td> NA </td><td> NA </td><td> NA </td></tr><tr><td> DHAP-AT-RNA干扰</td><td> LTM </td><td> 0.697 </td><td> 0.650 </td><td> 0.068 </td><td> 0.280 </td><td> 0.103 </td><td> 0.446 </td><td> 0.003 </td></tr></tbody></table><stro表3:从Analearn脚本生成的统计数据。 从分析脚本中产生的统计数据。包含基因型，学习条件（ 即学习，STM或LTM）的引导R脚本的输出文件意味着CI天真，平均CI训练，LI，控制LI与实验条件之间的差异（LI dif） ，LI dif的95％置信区间的下限（LL）和上限（UL），以及表示无显着差异的概率的p值。 <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td></td><td></td><td> 控制 </td><td></td><td></td><td> DHAP-AT-RNA干扰 </td><td></td><td></td></tr><tr><td></td><td></td><td> 平均CI天真 </td><td> 平均CI训练 </td><td> 李 </td><td> 平均CI天真 </td><td> 平均CI训练 </td><td> 李 </td></tr><tr><td> STM </td><td>第1天</td><td> 0.300 </td><td> 0.125 </td><td> 0.584 </td><td> 0.679 </td><td> 0.239 </td><td> 0.648 </td></tr><tr><td></td><td>第二天</td><td> 0.634 </td><td> 0.107 </td><td> 0.831 </td><td> 0.720 </td><td> 0.276 </td><td> 0.617 </td></tr><tr><td></td><td>每天</td><td> 0.467 </td><td> 0.116 </td><td> 0.752 </td><td> 0.699 </td><td> 0.257 </td><td> 0.633 </td></tr><tr><td> LTM </td><td>第1天</td><td> 0.590 </td><td> 0.441 </td><td> 0.252 </td><td> 0.630 </td><td> 0.646 </td><td> -0.027 </td></tr><tr><td></td><td>第二天</td><td> 0.640 </td><td> 0.363 </td><td> 0.432 </td><td> 0.709 </td><td> 0.710 </td><td> -0.002 </td></tr><tr><td></td><td>第3天</td><td>0.547 </td><td> 0.349 </td><td> 0.363 </td><td> 0.738 </td><td> 0.598 </td><td> 0.190 </td></tr><tr><td></td><td>每天</td><td> 0.590 </td><td> 0.384 </td><td> 0.348 </td><td> 0.697 </td><td> 0.650 </td><td> 0.068 </td></tr></tbody></table> 表4 : 在独立测试日获得的CI和LI值。 <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td> "naivelevel"确定将识别每个基因型的天真值的文本。默认值为"N"，但可以更改为任何其他字母数字文本。 </td></tr><tr><td>默认情况下，"refmutation"设置为"NA"（不适用），但可以更改为控件或基因型的名称，以执行统计比较。 这将导致script自动选择对照基因型。 </td></tr><tr><td> "datname"是指数据文件的名称，可以在此参数中指定，而不是默认的文件选择。 </td></tr><tr><td> "头"可用于指示数据文件是否包含列标题。 默认值为"TRUE"，但是当此参数更改为"FALSE"时，可以使用不带标题的文件。 </td></tr><tr><td> "seed"初始化随机数生成器，默认设置为"NA"，并在每次使用脚本时确保随机数。 通过设计，即使使用相同的数据文件，引导分析也会在每次运行时产生稍微不同的结果。 当种子被大于零的任何整数指定时，获得同一组随机引导样本。 </td></tr><tr><td> "写出<html> put"可以设置为"TRUE"或"FALSE"，以确定是否生成输出文件。默认值为"TRUE"。 </td></tr></tbody></table> 表5:分析函数中可用于修改功能的默认设置以调整引导参数的参数 补充文件S1:求爱室的建筑计划。可以使用允许.stp扩展名（CAD文件）的任何应用程序打开该文件 。 <a href="http://ecsource.jove.com/files/ftp_upload/55808/FileS1.zip" target="_blank">请点击这里下载此文件。</a> 补充文件S2 : 分析脚本的输入文件示例 。S2.zip"target ="_ blank"&gt;请点击此处下载此文件。 补充文件S3 : Anal.n.R脚本。该文件可以用R-studio 18打开。 <a href="http://ecsource.jove.com/files/ftp_upload/55808/FileS3.zip" target="_blank">请点击这里下载此文件。</a>

Watch this Scientific Journal Video about Drosophila Courtship Conditioning As a Measure of Learning and Memory at JoVE.com

Drosophila Courtship Conditioning As a Measure of Learning and Memory

该协议描述了称为求爱条件的果蝇学习和记忆测定。这种经典的测定是基于不接受预先的女性的性拒绝后男性求爱行为的减少。这种自然形式的行为可塑性可用于测试学习，短期记忆和长期记忆。

果蝇调理作为学习和记忆的措施

Many insights into the molecular mechanisms underlying learning and memory have been elucidated through the use of simple behavioral assays in model ...

drosophila-courtship-conditioning-as-a-measure-of-learning-and-memory

Research

JoVE Journal

Neuroscience

Drosophila Courtship Conditioning As a Measure of Learning and Memory

18.1K 次观看.  Radboud University Medical Center. 该协议描述了称为求爱条件的果蝇学习和记忆测定。这种经典的测定是基于不接受预先的女性的性拒绝后男性求爱行为的减少。这种自然形式的行为可塑性可用于测试学习，短期记忆和长期记忆。 

视频: Drosophila Courtship Conditioning As a Measure of Learning and Memory

Eye Movement Monitoring of Memory

Explicit (often verbal) reports are typically used to investigate memory (e.g. "Tell me what you remember about the person you saw at the bank yesterday."), however such reports can often be unreliable or sensitive to response bias 1, and may be unobtainable in some participant populations. Furthermore, explicit reports only reveal when information has reached consciousness and cannot comment on when memories were accessed during processing, regardless of whether the information is subsequently accessed in a conscious manner. Eye movement monitoring (eye tracking) provides a tool by which memory can be probed without asking participants to comment on the contents of their memories, and access of such memories can be revealed on-line 2,3. Video-based eye trackers (either head-mounted or remote) use a system of cameras and infrared markers to examine the pupil and corneal reflection in each eye as the participant views a display monitor. For head-mounted eye trackers, infrared markers are also used to determine head position to allow for head movement and more precise localization of eye position. Here, we demonstrate the use of a head-mounted eye tracking system to investigate memory performance in neurologically-intact and neurologically-impaired adults. Eye movement monitoring procedures begin with the placement of the eye tracker on the participant, and setup of the head and eye cameras. Calibration and validation procedures are conducted to ensure accuracy of eye position recording. Real-time recordings of X,Y-coordinate positions on the display monitor are then converted and used to describe periods of time in which the eye is static (i.e. fixations) versus in motion (i.e., saccades). Fixations and saccades are time-locked with respect to the onset/offset of a visual display or another external event (e.g. button press). Experimental manipulations are constructed to examine how and when patterns of fixations and saccades are altered through different types of prior experience. The influence of memory is revealed in the extent to which scanning patterns to new images differ from scanning patterns to images that have been previously studied 2, 4-5. Memory can also be interrogated for its specificity; for instance, eye movement patterns that differ between an identical and an altered version of a previously studied image reveal the storage of the altered detail in memory 2-3, 6-8. These indices of memory can be compared across participant populations, thereby providing a powerful tool by which to examine the organization of memory in healthy individuals, and the specific changes that occur to memory with neurological insult or decline 2-3, 8-10.

Eye movement monitoring (or eye tracking) reveals where in space the eyes linger, when and for how long. Here, we demonstrate how eye tracking can be used to investigate the integrity of memory in multiple participant populations, without requiring verbal, or otherwise explicit, reports.

眼运动监测内存

Explicit (often verbal) reports are typically used to investigate memory (e.g. "Tell me what you remember about the person you saw at the bank ...

科研

神经科学

C. elegans Positive Butanone Learning, Short-term, and Long-term Associative Memory Assays

The memory of experiences and learned information is critical for organisms to make choices that aid their survival. C. elegans navigates its environment through neuron-specific detection of food and chemical odors1, 2, and can associate nutritive states with chemical odors3, temperature4, and the pathogenicity of a food source5.
Here, we describe assays of C. elegans associative learning and short- and long-term associative memory. We modified an aversive olfactory learning paradigm6 to instead produce a positive response; the assay involves starving ~400 worms, then feeding the worms in the presence of the AWC neuron-sensed volatile chemoattractant butanone at a concentration that elicits a low chemotactic index (similar to Toroyama et al.7). A standard population chemotaxis assay1 tests the worms' attraction to the odorant immediately or minutes to hours after conditioning.
After conditioning, wild-type animals' chemotaxis to butanone increases ~0.6 Chemotaxis Index units, its "Learning Index". Associative learning is dependent on the presence of both food and butanone during training. Pairing food and butanone for a single conditioning period ("massed training") produces short-term associative memory that lasts ~2 hours. Multiple conditioning periods with rest periods between ("spaced training") yields long-term associative memory (&lt;40 hours), and is dependent on the cAMP Response Element Binding protein (CREB),6 a transcription factor required for long-term memory across species.8
Our protocol also includes image analysis methods for quick and accurate determination of chemotaxis indices. High-contrast images of animals on chemotaxis assay plates are captured and analyzed by worm counting software in MatLab. The software corrects for uneven background using a morphological tophat transformation.9 Otsu's method is then used to determine a threshold to separate worms from the background.10 Very small particles are removed automatically and larger non-worm regions (plate edges or agar punches) are removed by manual selection. The software then estimates the size of single worm by ignoring regions that are above a specified maximum size and taking the median size of the remaining regions. The number of worms is then estimated by dividing the total area identified as occupied by worms by the estimated size of a single worm.
We have found that learning and short- and long-term memory can be distinguished, and that these processes share similar key molecules with higher organisms.6,8 Our assays can quickly test novel candidate genes or molecules that affect learning and short- or long-term memory in C. elegans that are relevant across species.

C. elegans Positive Butanone Learning, Short-term, and Long-term Associative Memory Assays

Here we describe methods to test C. elegans associative learning and short- and long-term associative memory. These population assays employ the worms abilities to chemotax toward volatile odorants, and form positive associations upon pairing food with the chemoattractant butanone. Increasing the number of conditioning periods induces long-term memory.

线虫的积极丁酮学习，短期，长期联想记忆检测

The memory of experiences and learned information is critical for organisms to make choices that aid their survival. C. elegans navigates its environment ...

Assaying Locomotor, Learning, and Memory Deficits in Drosophila Models of Neurodegeneration

Advances in genetic methods have enabled the study of genes involved in human neurodegenerative diseases using Drosophila as a model system1. Most of these diseases, including Alzheimer's, Parkinson's and Huntington's disease are characterized by age-dependent deterioration in learning and memory functions and movement coordination2. Here we use behavioral assays, including the negative geotaxis assay3 and the aversive phototaxic suppression assay (APS assay)4,5, to show that some of the behavior characteristics associated with human neurodegeneration can be recapitulated in flies. In the negative geotaxis assay, the natural tendency of flies to move against gravity when agitated is utilized to study genes or conditions that may hinder locomotor capacities. In the APS assay, the learning and memory functions are tested in positively-phototactic flies trained to associate light with aversive bitter taste and hence avoid this otherwise natural tendency to move toward light. Testing these trained flies 6 hours post-training is used to assess memory functions. Using these assays, the contribution of any genetic or environmental factors toward developing neurodegeneration can be easily studied in flies.

Assaying Locomotor, Learning, and Memory Deficits in Drosophila Models of Neurodegeneration

Behavior assays for measuring locomotor functions, learning, and memory abilities in Drosophila.

含量的运动能力，学习和记忆的赤字果蝇</em神经退行性疾病>模型

Advances in genetic methods have enabled the study of genes involved in human neurodegenerative diseases using Drosophila as a model system1. Most of ...

Morris Water Maze Test for Learning and Memory Deficits in Alzheimer&#39;s Disease Model Mice

The Morris Water Maze (MWM) was first established by neuroscientist Richard G. Morris in 1981 in order to test hippocampal-dependent learning, including acquisition of spatial memoryand long-term spatial memory 1. The MWM is a relatively simple procedure typically consisting of six day trials, the main advantage being the differentiation between the spatial (hidden-platform) and non-spatial (visible platform) conditions 2-4. In addition, the MWM testing environment reduces odor trail interference 5. This has led the task to be used extensively in the study of the neurobiology and neuropharmacology of spatial learning and memory. The MWM plays an important role in the validation of rodent models for neurocognitive disorders such as Alzheimer&#x2019;s Disease 6, 7. In this protocol we discussed the typical procedure of MWM for testing learning and memory and data analysis commonly used in Alzheimer&#x2019;s disease transgenic model mice.

Morris Water Maze Test for Learning and Memory Deficits in Alzheimer's Disease Model Mice

The Morris Water Maze is a behavioral task to test hippocampal-dependent learning and memory. It has been widely used in the study of neurobiology, neuropharmacology and neurocognitive disorders in rodent models.

在阿尔茨海默氏病模型小鼠学习和记忆障碍的Morris水迷宫测试

The Morris Water Maze (MWM) was first established by neuroscientist Richard G. Morris in 1981 in order to test hippocampal-dependent learning, including ...

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Signaling of information in the vertebrate central nervous system is often carried by populations of neurons rather than individual neurons. Also propagation of suprathreshold spiking activity involves populations of neurons. Empirical studies addressing cortical function directly thus require recordings from populations of neurons with high resolution. Here we describe an optical method and a deconvolution algorithm to record neural activity from up to 100 neurons with single-cell and single-spike resolution. This method relies on detection of the transient increases in intracellular somatic calcium concentration associated with suprathreshold electrical spikes (action potentials) in cortical neurons. High temporal resolution of the optical recordings is achieved by a fast random-access scanning technique using acousto-optical deflectors (AODs)1. Two-photon excitation of the calcium-sensitive dye results in high spatial resolution in opaque brain tissue2. Reconstruction of spikes from the fluorescence calcium recordings is achieved by a maximum-likelihood method. Simultaneous electrophysiological and optical recordings indicate that our method reliably detects spikes (&gt;97% spike detection efficiency), has a low rate of false positive spike detection (&lt; 0.003 spikes/sec), and a high temporal precision (about 3 msec) 3. This optical method of spike detection can be used to record neural activity in vitro and in anesthetized animals in vivo3,4.

Understanding the function of the vertebrate central nervous system requires recordings from many neurons because cortical function arises on the level of populations of neurons. Here we describe an optical method to record suprathreshold neural activity with single-cell and single-spike resolution, dithered random-access scanning. This method records somatic fluorescence calcium signals from up to 100 neurons with high temporal resolution. A maximum-likelihood algorithm deconvolves the underlying suprathreshold neural activity from the somatic fluorescence calcium signals. This method reliably detects spikes with high detection efficiency and a low rate of false positives and can be used to study neural populations in vitro and in vivo.

阈上的神经活动的单细胞和单穗的分辨率的光学的方法记录

Signaling of information in the vertebrate central nervous system is often carried by populations of neurons rather than individual neurons. Also ...

Appetitive Associative Olfactory Learning in Drosophila Larvae

In the following we describe the methodological details of appetitive associative olfactory learning in Drosophila larvae. The setup, in combination with genetic interference, provides a handle to analyze the neuronal and molecular fundamentals of specifically associative learning in a simple larval brain.
Organisms can use past experience to adjust present behavior. Such acquisition of behavioral potential can be defined as learning, and the physical bases of these potentials as memory traces1-4. Neuroscientists try to understand how these processes are organized in terms of molecular and neuronal changes in the brain by using a variety of methods in model organisms ranging from insects to vertebrates5,6. For such endeavors it is helpful to use model systems that are simple and experimentally accessible. The Drosophila larva has turned out to satisfy these demands based on the availability of robust behavioral assays, the existence of a variety of transgenic techniques and the elementary organization of the nervous system comprising only about 10,000 neurons (albeit with some concessions: cognitive limitations, few behavioral options, and richness of experience questionable)7-10.
Drosophila larvae can form associations between odors and appetitive gustatory reinforcement like sugar11-14. In a standard assay, established in the lab of B. Gerber, animals receive a two-odor reciprocal training: A first group of larvae is exposed to an odor A together with a gustatory reinforcer (sugar reward) and is subsequently exposed to an odor B without reinforcement 9. Meanwhile a second group of larvae receives reciprocal training while experiencing odor A without reinforcement and subsequently being exposed to odor B with reinforcement (sugar reward). In the following both groups are tested for their preference between the two odors. Relatively higher preferences for the rewarded odor reflect associative learning - presented as a performance index (PI). The conclusion regarding the associative nature of the performance index is compelling, because apart from the contingency between odors and tastants, other parameters, such as odor and reward exposure, passage of time and handling do not differ between the two groups9.

Appetitive Associative Olfactory Learning in Drosophila Larvae

Drosophila larvae are able to associate odor stimuli with gustatory reward. Here we describe a simple behavioral paradigm that allows the analysis of appetitive associative olfactory learning.

欲求联想嗅觉学习<em&gt;果蝇</em&gt;幼虫

In the following we describe the methodological  details of appetitive associative olfactory learning in Drosophila larvae. The setup, in combination with ...

Drosophila Adult Olfactory Shock Learning

Drosophila have been used in classical conditioning experiments for over 40 years, thus greatly facilitating our understanding of memory, including the elucidation of the molecular mechanisms involved in cognitive diseases1-7. Learning and memory can be assayed in larvae to study the effect of neurodevelopmental genes8-10 and in flies to measure the contribution of adult plasticity genes1-7. Furthermore, the short lifespan of Drosophila facilitates the analysis of genes mediating age-related memory impairment5,11-13. The availability of many inducible promoters that subdivide the Drosophila nervous system makes it possible to determine when and where a gene of interest is required for normal memory as well as relay of different aspects of the reinforcement signal3,4,14,16.
Studying memory in adult Drosophila allows for a detailed analysis of the behavior and circuitry involved and a measurement of long-term memory15-17. The length of the adult stage accommodates longer-term genetic, behavioral, dietary and pharmacological manipulations of memory, in addition to determining the effect of aging and neurodegenerative disease on memory3-6,11-13,15-21.
Classical conditioning is induced by the simultaneous presentation of a neutral odor cue (conditioned stimulus, CS+) and a reinforcement stimulus, e.g., an electric shock or sucrose, (unconditioned stimulus, US), that become associated with one another by the animal1,16. A second conditioned stimulus (CS-) is subsequently presented without the US. During the testing phase, Drosophila are simultaneously presented with CS+ and CS- odors. After the Drosophila are provided time to choose between the odors, the distribution of the animals is recorded. This procedure allows associative aversive or appetitive conditioning to be reliably measured without a bias introduced by the innate preference for either of the conditioned stimuli. Various control experiments are also performed to test whether all genotypes respond normally to odor and reinforcement alone.

Drosophila Adult Olfactory Shock Learning

The method to measure adult Drosophila associative memory is described. The assay is based on the ability of the fly to associate an odor presented with a negative reinforcer (electric shock) and then recall this information at a later time, allowing memory to be measured.

果蝇嗅觉成人学习的冲击

Drosophila have been used in classical conditioning experiments for over 40 years, thus greatly facilitating our understanding of memory, including the ...

The Optokinetic Response as a Quantitative Measure of Visual Acuity in Zebrafish

Zebrafish are a proven model for vision research, however many of the earlier methods generally focused on larval fish or demonstrated a simple response. More recently adult visual behavior in zebrafish has become of interest, but methods to measure specific responses are new coming. To address this gap, we set out to develop a methodology to repeatedly and accurately utilize the optokinetic response (OKR) to measure visual acuity in adult zebrafish. Here we show that the adult zebrafish's visual acuity can be measured, including both binocular and monocular acuities. Because the fish is not harmed during the procedure, the visual acuity can be measured and compared over short or long periods of time. The visual acuity measurements described here can also be done quickly allowing for high throughput and for additional visual procedures if desired. This type of analysis is conducive to drug intervention studies or investigations of disease progression.

Zebrafish have been a valuable tool for many research areas. Here we demonstrate a method to elicit a visual response and calculate a functional visual acuity in the adult zebrafish.

在视动反应在斑马鱼视力的定量测量

Zebrafish are a proven model for vision research, however many of the  earlier methods generally focused on larval fish or demonstrated a simple  ...

In vivo Optogenetic Stimulation of the Rodent Central Nervous System

The ability to probe defined neural circuits in awake, freely-moving animals with cell-type specificity, spatial precision, and high temporal resolution has been a long sought tool for neuroscientists in the systems-level search for the neural circuitry governing complex behavioral states. Optogenetics is a cutting-edge tool that is revolutionizing the field of neuroscience and represents one of the first systematic approaches to enable causal testing regarding the relation between neural signaling events and behavior. By combining optical and genetic approaches, neural signaling can be bi-directionally controlled through expression of light-sensitive ion channels (opsins) in mammalian cells. The current protocol describes delivery of specific wavelengths of light to opsin-expressing cells in deep brain structures of awake, freely-moving rodents for neural circuit modulation. Theoretical principles of light transmission as an experimental consideration are discussed in the context of performing in vivo optogenetic stimulation. The protocol details the design and construction of both simple and complex laser configurations and describes tethering strategies to permit simultaneous stimulation of multiple animals for high-throughput behavioral testing.

In vivo Optogenetic Stimulation of the Rodent Central Nervous System

Optogenetics has become a powerful tool for use in behavioral neuroscience experiments. This protocol offers a step-by-step guide to the design and set-up of laser systems, and provides a full protocol for carrying out multiple and simultaneous in vivo optogenetic stimulations compatible with most rodent behavioral testing paradigms.

在啮齿动物中枢神经系统的体内光遗传学刺激

The ability to probe defined neural circuits in awake, freely-moving animals with cell-type specificity, spatial precision, and high temporal resolution ...

A Lateralized Odor Learning Model in Neonatal Rats for Dissecting Neural Circuitry Underpinning Memory Formation

Rat pups during a critical postnatal period (&#8804; 10 days) readily form a preference for an odor that is associated with stimuli mimicking maternal care. Such a preference memory can last from hours, to days, even life-long, depending on training parameters. Early odor preference learning provides us with a model in which the critical changes for a natural form of learning occur in the olfactory circuitry. An additional feature that makes it a powerful tool for the analysis of memory processes is that early odor preference learning can be lateralized via single naris occlusion within the critical period. This is due to the lack of mature anterior commissural connections of the olfactory hemispheres at this early age. This work outlines behavioral protocols for lateralized odor learning using nose plugs. Acute, reversible naris occlusion minimizes tissue and neuronal damages associated with long-term occlusion and more aggressive methods such as cauterization. The lateralized odor learning model permits within-animal comparison, therefore greatly reducing variance compared to between-animal designs. This method has been used successfully to probe the circuit changes in the olfactory system produced by training. Future directions include exploring molecular underpinnings of odor memory using this lateralized learning model; and correlating physiological change with memory strength and durations.

This protocol introduces lateralized early odor preference learning in rats using acute single naris occlusion. Lateralized learning permits the examination of behavioral outcomes and underpinning biological mechanisms within the same animals, reducing variance induced by between-animal designs. This protocol can be used to investigate molecular mechanisms underpinning early odor learning.

新生大鼠于A气味偏侧学习模型解剖神经回路托换记忆的形成

Rat pups during a critical postnatal period (&#8804; 10 days) readily form a preference for an odor that is associated with stimuli mimicking maternal ...