作者承认财务支持秘书长萨卢德·墨西哥（HIM / 2011/058 SSA。1009），CONACYT（SALUD-2012-01-182160）和DGAPA UNAM（PAPIIT IN109214）的研究。

该协议已经被医院Infantil deMéxico"FedericoGómez"的研究，伦理和安全委员会批准。 行为预测<ol><li>执行标准的纯音听力测试以确认所有预期参与者具有正常听力（在-8,000Hz的八度音频上为20dB听力水平（HL））。使用爱丁堡手持库存31确保所有参与者都是右撇子。 </li><li> 间隔序列的生成。 <ol><li>使用声音编辑程序生成跨越两个八度的纯音，G4-G6。 注意:在这里，描述了免费的开源声音编辑软件Audacity。其他包装可能用于此目的。 <ol><li>对于每种音调，在声音编辑软件中打开一个新项目。 </li><li>在"生成"菜单下，选择"音调"。在出现的窗口中选择正弦波形，振幅为0.8，持续时间为1秒。输入与所需音符对应的频率值（ 例如， A4为440 Hz）。点击"确定"按钮。 </li><li>在"文件"菜单下，选择"导出音频"。在打开的窗口中，输入音频文件所需的名称，然后选择WAV作为所需的文件类型。点击"保存"。 </li></ol></li><li>根据表1选择两个辅音和两个不同时间间隔，使得每个辅音间隔接近于一个不和谐间隔。 注意:例如，考虑完美的第五和八度音符的辅音间隔和增强的第四（三音）和第七音调的不和谐间隔。这些是由作者进行的研究选择的间隔。 </li><li>生成与G4和G6之间的这四个间隔对应的所有可能的笔记组合。 <ol><li>对于each间隔，在声音编辑软件中打开一个新项目，并使用"文件"菜单下的"导入音频"导入要连接的两个WAV文件。 </li><li>将光标放在第二个音调的任意位置，然后单击以选择。点击"编辑"菜单下的"全选"。在同一菜单下，点击"复制"。 </li><li>将光标放在第一个音调的任意位置，然后单击。在"编辑"菜单下，单击"移动光标到跟踪结束"，然后单击相同菜单下的"粘贴"。按照步骤1.2.1.3中的说明导出音频。 </li></ol></li><li>使用随机序列发生器来产生由100个间隔生成的序列，这些序列以伪随机方式产生，使得四个不同间隔中的每一个正好是25次30次。为此，请使用统计分析软件中的随机置换函数（参见"材料表" ）。输入四个interv作为参数，并创建一个循环，重复此过程25次。 </li><li>使用行为研究软件生成两个不同的运行。加载每个运行的WAV格式的100个间隔序列，并将每个间隔的标识与单个试验相关联30 。 注意:这里使用E-Prime行为研究软件。可以使用其他等效的行为研究软件。 </li></ol></li><li> 向参与者解释，他们将听取每个100个间隔的两个序列，其中每个序列与不同的任务相关联，并具有自己的指令集。告诉参与者，在两次运行中，仅当按下有效键时才会播放下一个间隔。 注意:一旦间隔识别序列开始，它不应该被中断，所以行动过程应尽可能地清楚所有参与者。 <ol><li>让参与者坐在笔记本电脑的前面并佩戴提供的耳机。使用优质的耳塞式耳机。将声级调整到每个主题的舒适级别。 </li><li>如果使用此处描述的行为研究软件，请使用E-Run打开步骤1.2.5中创建的任务。在出现的窗口中，输入会话和主题编号，然后单击"确定"。使用会话编号来区分每个参与者的运行。 注意:手头的任务说明将出现在屏幕上，随后是任务本身的开始。 <ol><li>首先，在一个2选择的强制选择任务中，只需让参与者确定他们听到的间隔是辅音还是不协调。让参与者在计算机键盘上按"C"键进行辅音，"D"表示不谐音。 注意:由于所有参与者都希望在音乐学院进行音乐训练，所有人都希望能够区分辅音和明显地分开声间隔。在某种意义上，第一项任务是证实这一点。 </li><li>第二，在4替代强制选择任务中，让参与者自己识别间隔。让参加者按下计算机键盘上的数字"4"，"5"，"7"和"8"，分别确定第4个，第5个，第7个和第8个音阶的间隔。 </li></ol></li><li>在每个任务结束时，按"确定"将每个参与者的结果自动保存在标有主题和会话号码以及扩展名为.edat2的单独的E-DataAid 2.0文件中。 </li><li>使用统计分析软件（ 例如， Matlab，SPSS Statistics或开源替代方案）来计算每个任务的成功率（ 即 ，确定间隔是辅音还是不一致时成功答案的百分比，以及当识别int自己），单独和作为一个组32 。 </li></ol></li></ol> fMRI实验<ol><li> 准备fMRI会议。 <ol><li>生成与步骤1.2.3相同间隔的序列，再次由两个持续时间为1秒的连续纯音组成。 注意:现在必须考虑参加者的声乐范围，所有音符必须舒适地落在每个参与者的歌唱范围内。 <ol><li>使用随机序列发生器创建30个间隔的随机序列，用于只听试验30 。对于歌唱试验，创建120个间隔的伪随机序列，供参加者收听特定间隔，然后将该目标间隔与他们的歌声进行匹配。对于伪随机序列，使用与步骤1.2.4中描述的相同的方法，再次以4个间隔作为参数，但n重复这个过程30次。 </li><li>按照与步骤1.2.5相同的程序，使用行为研究软件产生三个不同的运行，每个运行包括10个静默基准测试，其次是10次连续的只听试验，最后连续40次连续唱歌试验。 注意:在基线试验期间，四个间隔以随机顺序出现，而在歌唱试验期间，四个间隔以伪随机顺序出现，使得每个间隔最终呈现正好10次。每次试验的持续时间为10秒，整个运行持续10分钟。由于每个受试者经过3次实验，实验的总持续时间为30分钟。然而，允许参与者进入和退出扫描仪，有时间来设置和测试麦克风，以获得解剖扫描的时间，并且在功能运行之间的时间，应该为每个参与者分配约1小时的扫描仪时间。 </li></ol></li><li>向参与者说明如第2.1.1.2节所述的要呈现的试验序列，并回应其可能存在的任何疑问。指导参与者在唱歌试验期间不要张开嘴巴，保持嘴唇静止，同时产生"m"声。 </li><li>将非磁性，MR兼容耳机连接到笔记本电脑。将声级调整到每个主题的舒适级别。 </li><li>将小型电容麦克风连接到音频接口，然后使用屏蔽双绞线连接到笔记本电脑。 注意:麦克风电源，音频接口和笔记本电脑都应位于收纳扫描仪的房间外面。 </li><li>检查麦克风频率响应。 注意:本测试的目的是确认麦克风在扫描仪内部的行为与预期的一致。 <ol><li>在声音编辑软件中启动一个新的项目并选择冷凝器麦克风作为输入设备。 </li><li>产生一个440 Hz的测试音，持续时间为10秒，如1.2.1节所述，频率和持续时间的适当值。 </li><li>使用笔记本电脑上的默认声音再现软件，按"播放"，通过头戴式耳机在头枕（头枕顶部）和外部（控制室）扫描仪的位置发送测试音，麦克风位于两侧的耳机。 </li><li>在声音编辑软件中按"录制"，在每个位置记录大约1秒的测试音。 </li><li>从每个案例的"分析"菜单中选择"绘制光谱"，并通过检查每个位置接收到的信号的基频为440 Hz，将麦克风的响应与扫描仪内外的测试音进行比较。 </li></ol></li><li>将电磁话筒粘贴到参与者的脖子上喉。 </li><li>参与者佩戴耳机。将参与者放置在磁共振（MR）扫描仪中。 </li></ol></li><li> fMRI会话。 <ol><li>在会议开始时，打开磁共振用户界面（MRUI）软件包。使用MRUI来对采集范例进行编程。 注意:不同型号之间的界面有些变化。 <ol><li>从屏幕菜单中选择"患者"选项。输入参与者的姓名，年龄和体重。 </li><li>点击"考试"按钮。首先，从可用选项中选择"头"，然后选择"大脑"。 </li><li>选择"3D"，然后选择"T1等距"，相关参数为以下值:重复时间（TR）= 10.2 ms，回波时间（TE）= 4.2 ms，翻转角= 90°，体素大小= 1 x 1 x 1 mm 3 。 注意:对于每个参与者，T1加权解剖体积将be采用梯度回波脉冲序列进行解剖参考。 </li><li>点击"程序"，选择EchoPlanaImage_diff_perf_bold（T2 *），相关参数的值如下:TE = 40 ms，TR = 10 s，采集时间（TA）= 3 s，TR中的延迟为7 s，角度= 90°，视场（FOV）= 256 mm 2 ，矩阵尺寸= 64 x 64.使用"Dummy"选项获取5卷，同时输入总体数量"55"。 注意:这些值允许根据图1所示的稀疏采样范例采集功能T2 *加权全头扫描，其中采集回波平面成像（EPI）"虚拟"扫描并丢弃以允许T1饱和效果。请注意，在一些MRUI中，TR的值应为3 s，因为它被认为是采集发生的总时间。 </li><li>点击"复制"制作这个序列的副本ENCE。将光标放在序列列表的底部，然后单击"粘贴"两次以设置三个连续的稀疏采样序列。 </li><li>单击"开始"开始T1加权解剖体积采集。 </li><li>对参与者进行三次运行，如步骤2.1.1.2所述。使用扫描仪触发器将运行的开始与扫描仪的采集同步。 <ol><li>按照第1.3.2节所述的相同过程开始三个运行中的每一个，区分使用会话编号的运行。使用与步骤1.3.3中所述相同的步骤保存三次完整运行的结果。 注意:试用演示的时间安排系统地跳动±500 ms。 </li></ol></li></ol></li></ol></li></ol><img alt="图1" src="/files/ftp_upload/55419/55419fig1.jpg" /> 图1:S解析抽样设计。 （ A ）仅涉及双音间隔（2秒）的试验中的事件的时间线，而不会随后的公开繁殖。 （ B ）涉及听力和歌唱任务的审判事件的时间表。 <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55419/55419fig1large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> 3.数据分析<ol><li> 使用设计用于按照标准程序分析脑成像数据序列的软件预处理功能数据33 。 注意:所有数据处理都是使用相同的软件完成的。 <ol><li>使用提供的菜单选项将图像重新对准标准蒙特利尔神经研究所（MNI）立体定位空间34的第一个体积，重采样和空间归一化（最终体素大小:2 x 2 x 2 mm 3 ）。 </LI&gt; <li>使用提供的菜单选项，使用各向同性，8 mm，半最大宽度（FWHM）高斯内核平滑图像。 </li><li>为了建模BOLD响应，选择单仓有限脉冲响应（FIR）作为基础功能（1级）或箱式功能，跨越卷采集时间（3秒） 28 。 注意:像这样的稀疏采样协议通常不需要与血流动力学响应函数进行卷积，就像事件相关功能磁共振成像的情况一样。 </li><li>对每个事件的BOLD响应应用高通滤波器（"唱歌网络"为1,000秒，其他地方为360秒）。 注意:将所有歌唱任务建模在一起将达到400秒35 。 </li></ol></li></ol>

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作者声明没有利益冲突。

这项工作描述了一种协议，其中使用歌唱作为在辅音和不和谐间隔的生产期间研究脑活动的手段。尽管唱歌提供了用于制作音乐间隔22的最简单的方法，但它不允许制作和弦。然而，虽然辅音概念的大多数物理表征在某种程度上依赖于同时音符的叠加，但一些研究表明，用对应于辅音或不和谐和弦的音符构成的间隔仍被认为是辅音或不和谐，分别为4,6,15,41,42。 行为间隔感知任务用于建立，参与者可以通过扫描如果他们能够充分区分间隔。因此，它们在磁共振器内表现良好。执行这些识别任务时，不能达到预定阈值的参与者不应进行fMRI实验。该选择过程的主要目的是确保参与者之间的表现差异不是由于知觉能力不足造成的。选择参加者应具有类似程度的声乐和音乐训练，并且如果可能，也应该有类似的曲调。如果他们的声乐范围有很大差异，那么他们需要执行的歌唱任务期间呈现的间隔范围必须是个性化的。 麦克风设置对于采集是可靠的和无伪影的关键。麦克风本身的类型非常重要，虽然可以使用光学28或专门设计的MR兼容29 </<html> sup&gt;麦克风，已经表明，电容式麦克风的灵敏度不受成像环境43中强磁场的存在的影响。实际上，在这种情况下可以使用小型Lavalier电容式麦克风，只要使用屏蔽双绞线电缆将麦克风连接到前置放大器，该前置放大器必须放置在放置MR扫描仪的房间的外部。这种布置将防止成像伪影44的出现 ，但是研究人员还应该确保扫描器不会干扰麦克风的性能。为此，可以通过MR兼容的耳机将测试音发送到位于MR扫描仪内部的麦克风，然后将以这种方式获得的信号与通过向现在放置在外部的麦克风发送相同的音调而获得的信号进行比较扫描仪MR扫描仪内的声压级可能非常高xref"&gt; 45，所以麦克风必须尽可能靠近源头，通过询问参与者哼唱而不是公开唱歌，可以最大程度地减少口腔内和周围的运动，将麦克风放在喉部下方由磁带录制，可以获得对歌手声音的忠实录音，录音自然会非常嘈杂 - 这是不可避免的 - 但是如果研究人员主要对音调感兴趣，而不是表达或表达单词，则可以使用各种软件包来清理足够的信号，以检测每个唱歌的基本频率。标准方法是使用音频编辑软件通过汉明窗口过滤时间信号，然后使用自相关内置于某些语音和语音软件包中的算法来识别唱歌的基本原理，然后可以为每个参与者计算声音准确度。潜在的应用从记录中获得的数据包括将音调或节奏精度与训练程度或间隔距离相关联。 使用稀疏采样设计来获取功能图像，以便最小化由扫描噪声25,28,29,46,47引起的BOLD或听觉掩蔽。每个受试者经历3次实验，每次持续10分钟。在每次运行中，首先要求受试者在10次无声基准试验期间沉默，然后被动地听到10个间隔的块，最后再听并唱出40个间隔的另一个块。保持个人运行尽可能短的目的之一是避免参与者疲劳。尽管如此，它已经得出结论，将来可能会更好地包括同样数量的听力和歌唱试验，其中然后可以交替地呈现。这将有增加统计能力的作用。例如，跑步可以包括5个无声基准测试的2个块，5个只听试验的4个块和4个唱歌试验块。然后，块将交替地呈现给参与者，每个跑步的总持续时间为500秒。 参与者在谐振器内被动地听到的主要原因是具有从运动活动中减去听觉活动的方法。因此，唱歌活动与"唱歌网"25,27,28,29,36,37的有利比较对于研究的正确验证是不可或缺的。请注意，"唱歌网络"的激活是非常强大和成熟的，通常是de通过单样本t检验和p = 0.05的校正簇显着性阈值进行检测。通过根据显着体素阈值p &lt;0.001的双向重复因子方差分析（ANOVA）来识别对应于唱歌不和谐/辅音和辅音/不和谐间隔之间的对比度的激活，对于多次比较28,29未经校正。预计参加者将会发现唱歌不和谐间隔比唱辅音间隔更有挑战性48,49 ;因此，预期对于上述两个对比中的每一个的不同激活。结果表明，唱歌不和谐间隔涉及对辅音间隔产生的神经机制的重新编程。在唱歌期间，产生的声音与预期的声音进行比较，然后进行任何必要的调整通过整合来自听觉和躯体感觉途径的外部和内部反馈。 González-García，González和Rendón30的文章包括了对这些结果的详细讨论和从中得出的结论。 该协议提供了一个相当简单的方法，用于研究音乐制作的神经相关性和用于监测运动和听觉系统的活动。它可用于跟踪二元条件之间的脑激活差异，例如唱歌辅音或不和谐间隔，以及唱歌狭窄或宽间隔30 。它也非常适合研究训练对与歌唱特定频率相关的各种任务的影响。另一方面，由于在扫描期间获得的唱歌声音中包含的噪声非常大，因此难以使用该保护ocol来分析与音调或音色质量有关的任务，特别是因为这些质量在嗡嗡声时无法正确测量。

音乐会的某些组合通常被认为是辅音，并且它们通常与愉悦的感觉相关联。其他组合通常被称为不和谐，并且与不愉快或未解决的感觉相关1 。尽管假设文化和训练在辅音2的感觉中发挥了一定的作用，但似乎很明智，最近表明，辅音和不和谐间隔和和弦的感觉差异可能不如以前认为的音乐文化更少， 3可能甚至源于简单的生物基础4,5,6 。为了防止对术语协调的含糊的理解，Terhardt 7引入了感觉协调的概念，而不是音乐语境中的协调例如，和谐可能会很好地影响对给定和弦或间隔的响应。在本协议中，只有孤立的两音符间隔被精确地用于单独与感觉协调相关的激活，而没有来自上下文相关处理的干扰8 。 通过纯粹的物理手段来表征谐音的尝试开始于亥姆霍兹9 ，他将感觉到的与不协调的和弦相关的粗糙度归因于相邻频率分量之间的跳动。然而，最近，已经表明，感觉协调不仅与缺乏粗糙度有关，而且与谐波性有关，也就是说给定音调或和弦的部分与未听到的音调的对准低频10,11 。行为研究证实主观协调确实受到pu的影响依赖物理参数，如频率距离12，13 ，但是更广泛的研究结论性地证明，物理现象不能仅仅解释感觉到的和谐与不和谐之间的差异14,15,16,17。然而，所有这些研究在收听各种间隔或和弦时都会报告这些差异。使用正电子发射断层扫描（PET）和功能磁共振成像（fMRI）的各种研究已经显示，在听到辅音或不和谐间隔和和弦8,18,19,20时，皮质区域变得活跃的显着差异。本研究的目的是探讨差异在大脑活动中产生而不是听，辅音和不和谐的间隔。 在音乐制作过程中，感官运动控制的研究通常涉及使用乐器，并且经常需要制造专门为其在神经成像21期间使用而修改的乐器。然而，唱歌似乎从一开始就提供了一个适当的机制来分析音乐制作过程中的感官运动过程，因为乐器是人类的声音本身，声乐器不需要任何修改以适应成像22 。虽然与歌唱方面相关的神经机制，如音调控制23 ，声乐模仿24 ，训练诱导的适应变化25以及外部反馈的整合25 ， <s上课="外部参照"&gt; 26，27，28，29，已经是过去二十年的一些研究的主题，歌唱辅音和不和谐间隔的神经相关性最近才被描述30 。为此目的，本文介绍了一种旨在确定参与者对辅音和不和谐间隔的充分认识的行为测试。接下来是对参与者进行功能磁共振成像的研究，演唱了各种辅音和不和谐的间隔。 fMRI协议相对简单，但与所有MRI研究一样，必须非常小心正确设置实验。在这种情况下，特别重要的是在唱歌任务中尽可能减少头部，嘴巴和嘴唇的运动，使与身体上的歌唱行为直接相关的效果的识别更直接。这种方法可能用于通过唱歌来调整涉及音乐制作的各种活动的神经机制。

<table border="0" cellpadding="0" cellspacing="0" width="926">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Achieva 1.5-T magnetic resonance scanner</td>
			<td style="width:297px;">Philips</td>
			<td style="width:119px;">Release 6.4</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Audacity</td>
			<td style="width:297px;">Open source</td>
			<td style="width:119px;">2.0.5</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Audio interface&#160;</td>
			<td style="width:297px;">Tascam</td>
			<td style="width:119px;">US-144MKII&#160;</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Audiometer</td>
			<td style="width:297px;">Br&#252;el &#38; Kjaer</td>
			<td style="width:119px;">Type 1800</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">E-Prime Professional</td>
			<td style="width:297px;">Psychology Software Tools, Inc.</td>
			<td style="width:119px;">2.0.0.74</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Matlab</td>
			<td style="width:297px;">Mathworks</td>
			<td style="width:119px;">R2014A</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">MRI-Compatible Insert Earphones</td>
			<td style="width:297px;">Sensimetrics</td>
			<td style="width:119px;">S14</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Praat</td>
			<td style="width:297px;">Open source</td>
			<td style="width:119px;">5.4.12</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Pro audio condenser microphone</td>
			<td style="width:297px;">Shure</td>
			<td style="width:119px;">SM93</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">SPSS Statistics</td>
			<td style="width:297px;">IBM</td>
			<td style="width:119px;">20</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:343px;">Statistical Parametric Mapping</td>
			<td style="width:297px;">Wellcome Trust Centre for Neuroimaging</td>
			<td style="width:119px;">8</td>
			<td></td>
		</tr>
	</tbody>
</table>

fmri mapping of brain activity associated with the vocal production of consonant and dissonant intervals

协调和不和谐感知的神经相关性得到了广泛的研究，而不是辅助和不和谐生产的神经相关性。最直截了当的音乐制作方式是唱歌，但是从成像的角度来看，它比听力有更多的挑战，因为它涉及到运动活动。音乐间隔的精确唱歌需要听觉反馈处理和声控马达控制之间的整合，以便正确地产生每个音符。该方案提供了一种允许监测与声母和不和谐间隔的声音产生相关联的神经激活的方法。四个音乐间隔，两个辅音和两个不和谐被用作刺激，用于听觉辨别测试和涉及首先听和然后再现给定间隔的任务。参加者，所有在音乐学院的女声学生，使用功能磁性研究演唱任务期间的演奏成像（fMRI），听力任务作为控制条件。以这种方式，观察到运动和听觉系统的活动，并且还获得了在歌唱任务期间的声音准确度的量度。因此，该协议还可用于跟踪与唱歌不同类型的间隔相关联的激活或更准确地唱出所需的音符。结果表明，唱歌不和谐间隔需要更多的神经机制的参与，负责来自听觉和感觉运动系统的外部反馈的整合，而不是唱歌辅音间隔。

<html>我们实验中的所有11名参与者都是温室一级的女性声乐学生，他们在间隔识别任务中执行得很好，供选择进行扫描。间隔识别任务的成功率为65.72±21.67％，如预期的那样低于识别不谐音和辅音间隔的成功率，为74.82±14.15％。 为了验证研究的基本设计，我们希望在已知构成"歌唱网络"的地区歌唱中确定神经活动，如以前的研究25,26,27,28,29,30中定义的， 31 ，ass ="xref"&gt; 32,33,34,35,36,37。通过感兴趣的一级线性对比观察唱歌的效果，这对应于唱歌而不是听力。使用单样本t检验，由Z&gt; 3确定的簇和p = 0.05的簇显着性阈值，校正家族智慧错误（FWE） 38 。对于解剖标签，使用了SPM解剖工具箱33和哈佛 - 牛津皮层和皮质下结构图谱。观察到明显活化的脑区是主要体感皮层（S1），次生体感皮质（S2），主要运动皮层（M1），辅助运动区（SMA），运动前皮层（PM），布罗德曼面积44（BA 44），初级听觉皮层（PAC），上颞回（STG），颞极，前隔膜，壳核，丘脑和小脑。这些激活与上述关于"唱歌网络"的研究报告相符，并且在图2中示出 。注意，在图2和图3中，x坐标垂直于矢状平面，y坐标垂直于冠状平面，z坐标垂直于横向或水平面。 一旦基本设计得到验证，对于每个参与者，计算出两个进一步的一级线性对比度，对应于不同音调而不是辅音间隔，并且与辅音间隔相反地唱歌辅音。然后将这些线性对比度带入二级随机效应模型，该模型涉及一组二次重复测量分析nce（ANOVA），与因子相关和不和谐。以这种方式，检查激活或失活的区域的可能的相互作用，根据显着性体素阈值确定感兴趣的兴趣，p &lt;0.001，多个比较28,29未校正。对于由唱歌不和谐而不是辅音间隔引起的对比，右侧S1，右侧PAC，左侧中脑，右侧后岛，左侧杏仁核和左侧壳核观察到增加的激活。这些激活如图3所示 。关于补充对比，在辅音间隔期间没有检测到激活的显着变化。 <img alt="图2" src="/files/ftp_upload/55419/55419fig2.jpg" /> 图2:构成"唱歌网"的地区激活。 ACTIVAT离子图呈现为p = 0.05的簇显着阈值，校正误差（FWE）。 BOLD答复以任意单位报告。 <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55419/55419fig2large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图3" src="/files/ftp_upload/55419/55419fig3.jpg" /> 图3:声音和辅音间隔的对比。呈现激活图，未经校正的多重比较，簇显着阈值p = 0.001。 BOLD答复以任意单位报告。 <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55419/55419fig3large.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>间隔</td><td>半音数</td><td>基本比例</td></tr><tr><td> 齐奏 </td><td> 0 </td><td> 1:1 </td></tr><tr><td> 次要次数 </td><td> 1 </td><td> 16:15 </td></tr><tr><td>主要第二</td><td> 2 </td><td> 9:8 </td></tr><tr><td>次要第三</td><td> 3 </td><td> 6:5 </td></tr><tr><td> 第三名 </td><td> 4 </td><td> 5:4 </td></tr><tr><td> 完美的第四 </td><td> 五 </td><td> 4:3 </td></tr><tr><td> 全音 </td><td> 6 </td><td> 45:32 </td></tr><tr><td> 完美的第五 </td><td> 7 </td><td> 3:2 </td></tr><tr><td>次要第六</td><td> 8 </td><td> 8:5 </td></tr><tr><td> 主要第六 </td><td> 9 </td><td> 5:3 </td></tr><tr><td>次要第七</td><td> 10 </td><td> 16:9 </td></tr><tr><td> 大七 </td><td> 11 </td><td> 15:8 </td></tr><tr><td> 八度 </td><td> 12 </td><td> 2:1 </td></tr></tbody></table> 表1:辅音和音调间隔。辅音间隔以粗体显示，而不一致的间隔以斜体显示。观察到一个间隔越多，在用于表示它的频率比中出现的整数越小。对于作为频率比的函数的协调和不和谐的深入讨论，参见Bidelman＆Krishnan 40 。

Watch this Scientific Journal Video about fMRI Mapping of Brain Activity Associated with the Vocal Production of Consonant and Dissonant Intervals at JoVE.com

fMRI Mapping of Brain Activity Associated with the Vocal Production of Consonant and Dissonant Intervals

聆听辅音和不和谐间隔的神经相关性已得到广泛的研究，但是与辅音和不和谐音间隔的产生相关的神经机制则不甚了解。在这篇文章中，行为检测和功能磁共振成像与区间识别和唱歌任务结合起来来描述这些机制。

功能磁共振成像映射与辅音和解调间隔的声音生成相关的脑活动

The neural correlates of consonance and dissonance perception have been widely studied, but not the neural correlates of consonance and dissonance ...

fmri-mapping-brain-activity-associated-with-vocal-production

Nanyang Technological University

Research

JoVE Journal

Behavior

7.2K 次观看.  Hospital Infantil de México "Federico Gómez". 聆听辅音和不和谐间隔的神经相关性已得到广泛的研究，但是与辅音和不和谐音间隔的产生相关的神经机制则不甚了解。在这篇文章中，行为检测和功能磁共振成像与区间识别和唱歌任务结合起来来描述这些机制。 

视频: fMRI Mapping of Brain Activity Associated with the Vocal Production of Consonant and Dissonant Intervals

Functional Magnetic Resonance Imaging (fMRI) with Auditory Stimulation in Songbirds

The neurobiology of birdsong, as a model for human speech, is a pronounced area of research in behavioral neuroscience. Whereas electrophysiology and molecular approaches allow the investigation of either different stimuli on few neurons, or one stimulus in large parts of the brain, blood oxygenation level dependent (BOLD) functional Magnetic Resonance Imaging (fMRI) allows combining both advantages, i.e. compare the neural activation induced by different stimuli in the entire brain at once. fMRI in songbirds is challenging because of the small size of their brains and because their bones and especially their skull comprise numerous air cavities, inducing important susceptibility artifacts. Gradient-echo (GE) BOLD fMRI has been successfully applied to songbirds 1-5 (for a review, see 6). These studies focused on the primary and secondary auditory brain areas, which are regions free of susceptibility artifacts. However, because processes of interest may occur beyond these regions, whole brain BOLD fMRI is required using an MRI sequence less susceptible to these artifacts. This can be achieved by using spin-echo (SE) BOLD fMRI 7,8 . In this article, we describe how to use this technique in zebra finches (Taeniopygia guttata), which are small songbirds with a bodyweight of 15-25 g extensively studied in behavioral neurosciences of birdsong. The main topic of fMRI studies on songbirds is song perception and song learning. The auditory nature of the stimuli combined with the weak BOLD sensitivity of SE (compared to GE) based fMRI sequences makes the implementation of this technique very challenging.

Functional Magnetic Resonance Imaging fMRI with Auditory Stimulation in Songbirds

This article shows an optimized procedure for imaging of the neural substrates of auditory stimulation in the songbird brain using functional Magnetic Resonance Imaging (fMRI). It describes the preparation of the sound stimuli, the positioning of the subject and the acquisition and subsequent analysis of the fMRI data.

功能磁共振成像（fMRI）技术与听觉刺激鸣禽

The neurobiology of birdsong, as a model for human speech, is a pronounced area of research in behavioral neuroscience. Whereas electrophysiology and ...

科研

行为学

Stereotactic Injection of MicroRNA-expressing Lentiviruses to the Mouse Hippocampus CA1 Region and Assessment of the Behavioral Outcome

MicroRNAs (miRNAs) are small regulatory single-stranded RNA molecules around 22 nucleotides long that may each target numerous mRNA transcripts and dim an entire gene expression pathway by inducing destruction and/or inhibiting translation of these targets. Several miRNAs play key roles in maintaining neuronal structure and function and in higher-level brain functions, and methods are sought for manipulating their levels for exploring these functions. Here, we present a direct in vivo method for examining the cognitive consequences of enforced miRNAs excess in mice by stereotactic injection of miRNA-encoding virus particles. Specifically, the current protocol involves injection into the hippocampal CA1 region, which contributes to mammalian memory consolidation, learning, and stress responses, and offers a convenient injection site. The coordinates are measured according to the mouse bregma and virus perfusion is digitally controlled and kept very slow. After injection, the surgery wound is sealed and the animals recover. Lentiviruses encoding silencers of the corresponding mRNA targets serve to implicate the specific miRNA/target interaction responsible for the observed effect, with na&iuml;ve mice, mice injected with saline and mice injected with "empty" lentivirus vectors as controls. One month post-injection, the animals are examined in the Morris Water Maze (MWM) for assessing their navigation learning and memory abilities. The MWM is a round tank filled with colored water with a small platform submerged 1 cm below the water surface. Steady visual cues around the tank allow for spatial navigation (sound and the earth's magnetic field may also assist the animals in navigating). Video camera monitoring enables measuring the route of swim and the time to find and amount the platform. The mouse is first taught that mounting the hidden platform offers an escape from the enforced swimming; it is then tested for using this escape and finally, the platform is removed and probe tests examine if the mouse remembers its previous location. Repeated tests over several consecutive days highlight improved performance of tested mice at shorter latencies to find and mount the platform, and as more direct routes to reach the platform or its location. Failure to show such improvement represents impaired learning and memory and/or anxiety, which may then be tested specifically (e.g. in the elevated plus maze). This approach enables validation of specific miRNAs and target transcripts in the studied cognitive and/or stress-related processes.

MicroRNAs have significant roles in brain structure and function. Here we describe a method to enforce hippocampal miRNA over-expression using stereotactic injection of an engineered miRNA-expressing lentivirus. This approach can serve as a relatively rapid way to assess the in vivo effects of over-expressed miRNAs in specific brain regions.

立体定向注射的microRNA表达慢病毒的小鼠海马CA1区和行为结果的评估

MicroRNAs (miRNAs) are small regulatory single-stranded RNA molecules around 22 nucleotides long that may each target numerous mRNA transcripts and dim an ...

How to Detect Amygdala Activity with Magnetoencephalography using Source Imaging

In trace fear conditioning a conditional stimulus (CS) predicts the occurrence of the unconditional stimulus (UCS), which is presented after a brief stimulus free period (trace interval)1. Because the CS and UCS do not co-occur temporally, the subject must maintain a representation of that CS during the trace interval. In humans, this type of learning requires awareness of the stimulus contingencies in order to bridge the trace interval2-4. However when a face is used as a CS, subjects can implicitly learn to fear the face even in the absence of explicit awareness*. This suggests that there may be additional neural mechanisms capable of maintaining certain types of "biologically-relevant" stimuli during a brief trace interval. Given that the amygdala is involved in trace conditioning, and is sensitive to faces, it is possible that this structure can maintain a representation of a face CS during a brief trace interval.
It is challenging to understand how the brain can associate an unperceived face with an aversive outcome, even though the two stimuli are separated in time. Furthermore investigations of this phenomenon are made difficult by two specific challenges. First, it is difficult to manipulate the subject's awareness of the visual stimuli. One common way to manipulate visual awareness is to use backward masking. In backward masking, a target stimulus is briefly presented (&lt; 30 msec) and immediately followed by a presentation of an overlapping masking stimulus5. The presentation of the mask renders the target invisible6-8. Second, masking requires very rapid and precise timing making it difficult to investigate neural responses evoked by masked stimuli using many common approaches. Blood-oxygenation level dependent (BOLD) responses resolve at a timescale too slow for this type of methodology, and real time recording techniques like electroencephalography (EEG) and magnetoencephalography (MEG) have difficulties recovering signal from deep sources.
However, there have been recent advances in the methods used to localize the neural sources of the MEG signal9-11. By collecting high-resolution MRI images of the subject's brain, it is possible to create a source model based on individual neural anatomy. Using this model to "image" the sources of the MEG signal, it is possible to recover signal from deep subcortical structures, like the amygdala and the hippocampus*.

This article describes how to record amygdala activity with magnetoencephalography (MEG). In addition this article will describe how to conduct trace fear conditioning without awareness, a task that activates the amygdala. It will cover 3 topics: 1) Designing a trace conditioning paradigm using backward masking to manipulate awareness. 2) Recording brain activity during the task using magnetoencephalography. 3) Using source imaging to recover signal from subcortical structures.

如何检测杏仁核活动脑磁图源成像

In trace fear conditioning a conditional  stimulus (CS) predicts the occurrence of the unconditional stimulus (UCS),  which is presented after a brief ...

Best Current Practice for Obtaining High Quality EEG Data During Simultaneous fMRI

Simultaneous EEG-fMRI allows the excellent temporal resolution of EEG to be combined with the high spatial accuracy of fMRI. The data from these two modalities can be combined in a number of ways, but all rely on the acquisition of high quality EEG and fMRI data. EEG data acquired during simultaneous fMRI are affected by several artifacts, including the gradient artefact (due to the changing magnetic field gradients required for fMRI), the pulse artefact (linked to the cardiac cycle) and movement artifacts (resulting from movements in the strong magnetic field of the scanner, and muscle activity). Post-processing methods for successfully correcting the gradient and pulse artifacts require a number of criteria to be satisfied during data acquisition. Minimizing head motion during EEG-fMRI is also imperative for limiting the generation of artifacts.
Interactions between the radio frequency (RF) pulses required for MRI and the EEG hardware may occur and can cause heating. This is only a significant risk if safety guidelines are not satisfied. Hardware design and set-up, as well as careful selection of which MR sequences are run with the EEG hardware present must therefore be considered.
The above issues highlight the importance of the choice of the experimental protocol employed when performing a simultaneous EEG-fMRI experiment. Based on previous research we describe an optimal experimental set-up. This provides high quality EEG data during simultaneous fMRI when using commercial EEG and fMRI systems, with safety risks to the subject minimized. We demonstrate this set-up in an EEG-fMRI experiment using a simple visual stimulus. However, much more complex stimuli can be used. Here we show the EEG-fMRI set-up using a Brain Products GmbH (Gilching, Germany) MRplus, 32 channel EEG system in conjunction with a Philips Achieva (Best, Netherlands) 3T MR scanner, although many of the techniques are transferable to other systems.

Simultaneous electroencephalography (EEG) and functional Magnetic Resonance imaging (fMRI) is a powerful neuroimaging tool. However, the inside of an MRI scanner forms a difficult environment for EEG data recording and safety must be considered whenever operating EEG equipment inside a scanner. Here, we present an optimised EEG-fMRI data acquisition protocol.

获得高质量的脑电数据在同步功能磁共振成像的当前最佳实践

Simultaneous  EEG-fMRI allows the excellent temporal resolution of EEG to be combined with the  high spatial accuracy of fMRI. The data  from these two ...

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

The ability to adjust behavior to sudden changes in the environment develops gradually in childhood and adolescence. For example, in the Dimensional Change Card Sort task, participants switch from sorting cards one way, such as shape, to sorting them a different way, such as color. Adjusting behavior in this way exacts a small performance cost, or switch cost, such that responses are typically slower and more error-prone on switch trials in which the sorting rule changes as compared to repeat trials in which the sorting rule remains the same. The ability to flexibly adjust behavior is often said to develop gradually, in part because behavioral costs such as switch costs typically decrease with increasing age. Why aspects of higher-order cognition, such as behavioral flexibility, develop so gradually remains an open question. One hypothesis is that these changes occur in association with functional changes in broad-scale cognitive control networks. On this view, complex mental operations, such as switching, involve rapid interactions between several distributed brain regions, including those that update and maintain task rules, re-orient attention, and select behaviors. With development, functional connections between these regions strengthen, leading to faster and more efficient switching operations. The current video describes a method of testing this hypothesis through the collection and multivariate analysis of fMRI data from participants of different ages.

This video presents a method of examining age-related changes in functional connectivity of cognitive control networks engaged by targeted tasks/processes. The technique is based on multi-variate analysis of fMRI data.

针对调查中的认知控制网络与关联维度变化卡片分类性能的功能连通性年龄相关性差异的方法

The ability to adjust behavior to sudden changes in the environment develops gradually in childhood and adolescence. For example, in the Dimensional ...

Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia

Adolescence is a critical developmental period where the early symptoms of schizophrenia frequently emerge. First-degree relatives of people with schizophrenia who are at familial high risk (FHR) may show similar cognitive and emotional changes. However, the neurological changes underlying the emergence of these symptoms remain unclear. This study sought to identify differences in frontal, striatal, and limbic regions in children and adolescents with FHR using functional magnetic resonance imaging. Groups of 21 children and adolescents at FHR and 21 healthy controls completed an emotional oddball task that relied on selective attention and the suppression of task-irrelevant emotional information. The standard oddball task was modified to include aversive and neutral distractors in order to examine potential group differences in both emotional and executive processing. This task was designed specifically to allow for children and adolescents to complete by keeping the difficulty and emotional image content age-appropriate. Furthermore, we demonstrate a technique for suitable fMRI registration for children and adolescent participants. This paradigm may also be applied in future studies to measure changes in neural activity in other populations with hypothesized developmental changes in executive and emotional processing.

This paper describes how to use the emotional oddball task and fMRI to measure brain activation in children and adolescents at familial high risk for schizophrenia (FHR).&#160;FMRI was used to measure differences in fronto-striato-limbic regions during an emotional oddball task. Children with FHR exhibited abnormal functional activation during adolescence.

的额边缘活度测量在儿童使用情绪穿着或行为古怪的任务与家族性高风险的精神分裂症

Adolescence is a critical developmental period where the early symptoms of schizophrenia frequently emerge. First-degree relatives of people with ...

Transferring Cognitive Tasks Between Brain Imaging Modalities: Implications for Task Design and Results Interpretation in fMRI Studies

As cognitive neuroscience methods develop, established experimental tasks are used with emerging brain imaging modalities. Here transferring a paradigm (the visual oddball task) with a long history of behavioral and electroencephalography (EEG) experiments to a functional magnetic resonance imaging (fMRI) experiment is considered. The aims of this paper are to briefly describe fMRI and when its use is appropriate in cognitive neuroscience; illustrate how task design can influence the results of an fMRI experiment, particularly when that task is borrowed from another imaging modality; explain the practical aspects of performing an fMRI experiment. It is demonstrated that manipulating the task demands in the visual oddball task results in different patterns of blood oxygen level dependent (BOLD) activation. The nature of the fMRI BOLD measure means that many brain regions are found to be active in a particular task. Determining the functions of these areas of activation is very much dependent on task design and analysis. The complex nature of many fMRI tasks means that the details of the task and its requirements need careful consideration when interpreting data. The data show that this is particularly important in those tasks relying on a motor response as well as cognitive elements and that covert and overt responses should be considered where possible. Furthermore, the data show that transferring an EEG paradigm to an fMRI experiment needs careful consideration and it cannot be assumed that the same paradigm will work equally well across imaging modalities. It is therefore recommended that the design of an fMRI study is pilot tested behaviorally to establish the effects of interest and then pilot tested in the fMRI environment to ensure appropriate design, implementation and analysis for the effects of interest.

Transferring a paradigm with a history of use in EEG experiments to an fMRI experiment is considered. It is demonstrated that manipulating the task demands in the visual oddball task resulted in different patterns of BOLD activation and illustrated how task design is crucial in fMRI experiments.

传输认知任务的脑成像方法:对任务的设计和结果判读的功能磁共振成像研究

As cognitive neuroscience methods develop, established experimental tasks are used with emerging brain imaging modalities. Here transferring a paradigm ...

A View of Their Own: Capturing the Egocentric View of Infants and Toddlers with Head-Mounted Cameras

Infants and toddlers view the world, at a basic sensory level, in a fundamentally different way from their parents. This is largely due to biological constraints: infants possess different body proportions than their parents and the ability to control their own head movements is less developed. Such constraints limit the visual input available. This protocol aims to provide guiding principles for researchers using head-mounted cameras to understand the changing visual input experienced by the developing infant. Successful use of this protocol will allow researchers to design and execute studies of the developing child&#39;s visual environment set in the home or laboratory. From this method, researchers can compile an aggregate view of all the possible items in a child&#39;s field of view. This method does not directly measure exactly what the child is looking at. By combining this approach with machine learning, computer vision algorithms, and hand-coding, researchers can produce a high-density dataset to illustrate the changing visual ecology of the developing infant.

Infants and toddlers view the world in a fundamentally different way from their parents. Head-mounted cameras provide a tractable mechanism to understand the infant visual environment. This protocol provides guiding principles for experiments in the home or laboratory to capture the egocentric view of toddlers and infants.

自己的观点: 用头摄像头捕捉婴幼儿的自我中心观

Infants and toddlers view the world, at a basic sensory level, in a fundamentally different way from their parents. This is largely due to biological ...

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults

A real-time locating system (RTLS) can be used to track the walking activity of institutionalized older adults in long-term care who are at risk for wandering behaviors. The benefits of a RTLS are objective and continuous measurements of activity. Self-report methods of activity, especially wandering, by health care staff are vulnerable to floor effects and recall bias, and continuous clinical or research observation over the long-term can be time-consuming and expensive. Health care staff also fail to recognize the onset and/or duration of wandering behaviors, which are associated with a variety of adverse health outcomes in this population but amenable to intervention. RTLS technologies can measure the walking activity of institutionalized residents with cognitive impairment over time with a high degree of accuracy. This is particularly useful for the study of wandering, defined as walking for at least 60 seconds with few (if any) breaks in activity. Wandering is associated with disease progression, hospitalizations, falls and death. Previous work suggests older adults with poor balance ability and high sustained walking activity may be particularly susceptible to poor health outcomes. RTLS&#39;s are used to assess cognitive impairment and factors associated with gait and balance; however, supplemental paper and pencil gait/balance tools may be used to further refine risk profiles. This project discusses the use of a RTLS to measure walking activity and also gait quality and balance ability measures on this population.

This paper discusses the use of a continuous and objective real-time locating system to measure walking activity associated with wandering behaviors, focusing on older adults with cognitive impairment. Walking activity is measured by walking distance, sustained walking distance, and sustained gait speed. Also assessed are gait quality and balance ability.

利用实时定位系统测量被培养的老年人的游走行为相关的步行活动

A real-time locating system (RTLS) can be used to track the walking activity of institutionalized older adults in long-term care who are at risk for ...

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

In lesion-symptom mapping (LSM), brain function is inferred by relating the location of acquired brain lesions to behavioral or cognitive symptoms in a group of patients. With recent advances in brain imaging and image processing, LSM has become a popular tool in cognitive neuroscience. LSM can provide fundamental insights into the functional architecture of the human brain for a variety of cognitive and non-cognitive functions. A crucial step in performing LSM studies is the segmentation of lesions on brains scans of a large group of patients and registration of each scan to a common stereotaxic space (also called standard space or a standardized brain template). Described here is an open-access, standardized method for infarct segmentation and registration for the purpose of LSM, as well as a detailed and hands-on walkthrough based on exemplary cases. A comprehensive tutorial for the manual segmentation of brain infarcts on CT scans and DWI or FLAIR MRI sequences is provided, including criteria for infarct identification and pitfalls for different scan types. The registration software provides multiple registration schemes that can be used for processing of CT and MRI data with heterogeneous acquisition parameters. A tutorial on using this registration software and performing visual quality checks and manual corrections (which are needed in some cases) is provided. This approach provides researchers with a framework for the entire process of brain image processing required to perform an LSM study, from gathering of the data to final quality checks of the results.

Provided here is a practical tutorial for an open-access, standardized image processing pipeline for the purpose of lesion-symptom mapping. A step-by-step walkthrough is provided for each processing step, from manual infarct segmentation on CT/MRI to subsequent registration to standard space, along with practical recommendations and illustrations with exemplary cases.

脑梗死分割和登记在MRI或CT上的病变症状映射

In lesion-symptom mapping (LSM), brain function is inferred by relating the location of acquired brain lesions to behavioral or cognitive symptoms in a ...