Name: fmri mapping of brain activity associated with the vocal production of consonant and dissonant intervals
Uploaded: 2017-05-23T13:00:00.000+00:00
Duration: 11 min 15 s
Description: Watch this Scientific Journal Video about fMRI Mapping of Brain Activity Associated with the Vocal Production of Consonant and Dissonant Intervals at JoVE.com

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="http://ecsource.jove.com/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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Cortex. 20, 1144-1152 (2010).</li><li>J&#252;rgens, U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neural+pathways+underlying+vocal+control.">Neural pathways underlying vocal control.</a> Neurosci. Biobehav. Rev. 26, 235-258 (2002).</li><li>Kleber, B., Birbaumer, N., Veit, R., Trevorrow, T., Lotze, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Overt+and+imagined+singing+of+an+Italian+aria.">Overt and imagined singing of an Italian aria.</a> Neuroimage. 36, 889-900 (2007).</li><li>Kleber, B., Zeitouni, A. G., Friberg, A., Zatorre, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experience-dependent+modulation+of+feedback+integration+during+singing:+role+of+the+right+anterior+insula.">Experience-dependent modulation of feedback integration during singing: role of the right anterior insula.</a> J. Neurosci. 33, 6070-6080 (2013).</li><li>Zarate, J. M., Zatorre, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Experience-dependent+neural+substrates+involved+in+vocal+pitch+regulation+during+singing.">Experience-dependent neural substrates involved in vocal pitch regulation during singing.</a> Neuroimage. 40, 1871-1887 (2008).</li><li>Gonz&#225;lez-Garc&#237;a, N., Gonz&#225;lez, M. A., Rend&#243;n, P. 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Cortex. 18, 837-845 (2008).</li><li>Worsley, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Statistical+analysis+of+activation+images.">Statistical analysis of activation images.</a> Functional MRI: An introduction to methods. , 251-270 (2001).</li><li>. FSL Atlases Available from: <a target="_blank" href="https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases">https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases</a> (2015)</li><li>Bidelman, G. M., Krishnan, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neural+correlates+of+consonance,+dissonance,+and+the+hierarchy+of+musical+pitch+in+the+human+brainstem.">Neural correlates of consonance, dissonance, and the hierarchy of musical pitch in the human brainstem.</a> J. 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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=&amp;#34;Sparse&amp;#34;+temporal+sampling+in+auditory+fMRI.">&amp;#34;Sparse&amp;#34; temporal sampling in auditory fMRI.</a> Hum. Brain Mapp. 7, 213-223 (1999).</li><li>Ternstr&#246;m, S., Sundberg, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Acoustical+factors+related+to+pitch+precision+in+choir+singing.">Acoustical factors related to pitch precision in choir singing.</a> Speech Music Hear. Q. Prog. Status Rep. 23, 76-90 (1982).</li><li>Ternstr&#246;m, S., Sundberg, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Intonation+precision+of+choir+singers.">Intonation precision of choir singers.</a> J. Acoust. Soc. Am. 84, 59-69 (1988).</li></ol>

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。 <p class="jove_conten...

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><tbody><tr><td>Achieva 1.5-T magnetic resonance scanner</td><td>Philips</td><td>Release 6.4</td><td></td></tr><tr><td>Audacity</td><td>Open source</td><td>2.0.5</td><td></td></tr><tr><td>Audio interface</td><td>Tascam</td><td>US-144MKII</td><td></td></tr><tr><td>Audiometer</td><td>Br&amp;uuml;el &amp;amp; Kjaer</td><td>Type 1800</td><td></td></tr><tr><td>E-Prime Professional</td><td>Psychology Software Tools, Inc.</td><td>2.0.0.74</td><td></td></tr><tr><td>Matlab</td><td>Mathworks</td><td>R2014A</td><td></td></tr><tr><td>MRI-Compatible Insert Earphones</td><td>Sensimetrics</td><td>S14</td><td></td></tr><tr><td>Praat</td><td>Open source</td><td>5.4.12</td><td></td></tr><tr><td>Pro-audio condenser microphone</td><td>Shure</td><td>SM93</td><td></td></tr><tr><td>SPSS Statistics</td><td>IBM</td><td>20</td><td></td></tr><tr><td>Statistical Parametric Mapping</td><td>Wellcome Trust Centre for Neuroimaging</td><td>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?...

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

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

Brain Imaging Investigation of the Neural Correlates of Observing Virtual Social Interactions

The ability to gauge social interactions is crucial in the assessment of others&#x2019; intentions. Factors such as facial expressions and body language affect our decisions in personal and professional life alike 1. These "friend or foe" judgements are often based on first impressions, which in turn may affect our decisions to "approach or avoid". Previous studies investigating the neural correlates of social cognition tended to use static facial stimuli 2. Here, we illustrate an experimental design in which whole-body animated characters were used in conjunction with functional magnetic resonance imaging (fMRI) recordings. Fifteen participants were presented with short movie-clips of guest-host interactions in a business setting, while fMRI data were recorded; at the end of each movie, participants also provided ratings of the host behaviour. This design mimics more closely real-life situations, and hence may contribute to better understanding of the neural mechanisms of social interactions in healthy behaviour, and to gaining insight into possible causes of deficits in social behaviour in such clinical conditions as social anxiety and autism 3.

This article demonstrates an experimental design in which whole-body animated characters are used in conjunction with functional magnetic resonance imaging (fMRI) to investigate the neural correlates of observing virtual social interactions.

观察虚拟社会交往中的神经关联的脑成像研究

The ability to gauge social interactions is crucial in the assessment of others&#x2019; intentions. Factors such as facial expressions and body language ...

神经科学

Correlating Behavioral Responses to fMRI Signals from Human Prefrontal Cortex: Examining Cognitive Processes Using Task Analysis

The aim of this methods paper is to describe how to implement a neuroimaging technique to examine complementary brain processes engaged by two similar tasks. Participants' behavior during task performance in an fMRI scanner can then be correlated to the brain activity using the blood-oxygen-level-dependent signal. We measure behavior to be able to sort correct trials, where the subject performed the task correctly and then be able to examine the brain signals related to correct performance. Conversely, if subjects do not perform the task correctly, and these trials are included in the same analysis with the correct trials we would introduce trials that were not only for correct performance. Thus, in many cases these errors can be used themselves to then correlate brain activity to them. We describe two complementary tasks that are used in our lab to examine the brain during suppression of an automatic responses: the stroop1 and anti-saccade tasks. The emotional stroop paradigm instructs participants to either report the superimposed emotional 'word' across the affective faces or the facial 'expressions' of the face stimuli1,2. When the word and the facial expression refer to different emotions, a conflict between what must be said and what is automatically read occurs. The participant has to resolve the conflict between two simultaneously competing processes of word reading and facial expression. Our urge to read out a word leads to strong 'stimulus-response (SR)' associations; hence inhibiting these strong SR's is difficult and participants are prone to making errors. Overcoming this conflict and directing attention away from the face or the word requires the subject to inhibit bottom up processes which typically directs attention to the more salient stimulus. Similarly, in the anti-saccade task3,4,5,6, where an instruction cue is used to direct only attention to a peripheral stimulus location but then the eye movement is made to the mirror opposite position. Yet again we measure behavior by recording the eye movements of participants which allows for the sorting of the behavioral responses into correct and error trials7 which then can be correlated to brain activity. Neuroimaging now allows researchers to measure different behaviors of correct and error trials that are indicative of different cognitive processes and pinpoint the different neural networks involved.

The goal of our research is to correlate behavior to brain activity. Accurate behavioral measures and imaging techniques allow us to elucidate brain-behavior relationships.

关联从人类前额叶皮层的fMRI信号的行为反应：检查的认知过程，使用任务分析

The aim of this methods paper is to describe how to implement a neuroimaging technique to examine complementary brain processes engaged by two similar ...

Functional Imaging of Auditory Cortex in Adult Cats using High-field fMRI

Current knowledge of sensory processing in the mammalian auditory system is mainly derived from electrophysiological studies in a variety of animal models, including monkeys, ferrets, bats, rodents, and cats. In order to draw suitable parallels between human and animal models of auditory function, it is important to establish a bridge between human functional imaging studies and animal electrophysiological studies. Functional magnetic resonance imaging (fMRI) is an established, minimally invasive method of measuring broad patterns of hemodynamic activity across different regions of the cerebral cortex. This technique is widely used to probe sensory function in the human brain, is a useful tool in linking studies of auditory processing in both humans and animals and has been successfully used to investigate auditory function in monkeys and rodents. The following protocol describes an experimental procedure for investigating auditory function in anesthetized adult cats by measuring stimulus-evoked hemodynamic changes in auditory cortex using fMRI. This method facilitates comparison of the hemodynamic responses across different models of auditory function thus leading to a better understanding of species-independent features of the mammalian auditory cortex.

Functional studies of the auditory system in mammals have traditionally been conducted using spatially-focused techniques such as electrophysiological recordings. The following protocol describes a method of visualizing large-scale patterns of evoked hemodynamic activity in the cat auditory cortex using functional magnetic resonance imaging.

听觉皮层在成年猫用高场磁共振成像功能成像

Current knowledge of sensory processing in the mammalian auditory system is mainly derived from electrophysiological studies in a variety of animal ...

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

It is now appreciated that condition-relevant information can be present within distributed patterns of functional magnetic resonance imaging (fMRI) brain activity, even for conditions with similar levels of univariate activation. Multi-voxel pattern (MVP) analysis has been used to decode this information with great success. FMRI investigators also often seek to understand how brain regions interact in interconnected networks, and use functional connectivity (FC) to identify regions that have correlated responses over time. Just as univariate analyses can be insensitive to information in MVPs, FC may not fully characterize the brain networks that process conditions with characteristic MVP signatures. The method described here, informational connectivity (IC), can identify regions with correlated changes in MVP-discriminability across time, revealing connectivity that is not accessible to FC. The method can be exploratory, using searchlights to identify seed-connected areas, or planned, between pre-selected regions-of-interest. The results can elucidate networks of regions that process MVP-related conditions, can breakdown MVPA searchlight maps into separate networks, or can be compared across tasks and patient groups.

Informational connectivity measures the correspondence between time courses of multi-voxel information across different brain regions. Multi-voxel pattern discriminability time series are extracted from regions and compared, revealing networks that are not identified in a typical functional connectivity approach.

利用信息化连通性来衡量的功能磁共振成像多体素穿越时空信息的同步崛起

It is now appreciated that condition-relevant information can be present within distributed patterns of functional magnetic resonance imaging (fMRI) brain ...

在表达性言语中识别熟悉的说话人的脑电图研究

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis

Recognizing familiar speakers from vocal streams is a fundamental aspect of human verbal communication. However, it remains unclear how listeners can still discern the speaker's identity in expressive speech. This study develops a memorization-based individual speaker identity recognition approach and an accompanying electroencephalogram (EEG) data analysis pipeline, which monitors how listeners recognize familiar speakers and tell unfamiliar ones apart. EEG data captures online cognitive processes during new versus old speaker distinction based on voice, offering a real-time measure of brain activity, overcoming limits of reaction times and accuracy measurements. The paradigm comprises three steps: listeners establish associations between three voices and their names (training); listeners indicate the name corresponding to a voice from three candidates (checking); listeners distinguish between three old and three new speaker voices in a two-alternative forced-choice task (testing). The speech prosody in testing was either confident or doubtful. EEG data were collected using a 64-channel EEG system, followed by preprocessing and imported into RStudio for ERP and statistical analysis and MATLAB for brain topography. Results showed an enlarged late positive component (LPC) was elicited in the old-talker compared to the new-talker condition in the 400-850 ms window in the Pz and other wider range of electrodes in both prosodies. Yet, the old/new effect was robust in central and posterior electrodes for doubtful prosody perception, whereas the anterior, central, and posterior electrodes are for confident prosody condition. This study proposes that this experiment design can serve as a reference for investigating speaker-specific cue-binding effects in various scenarios (e.g., anaphoric expression) and pathologies in patients like phonagnosia.

作者聚焦:调查情感韵律对语音识别和感知的影响

The study introduces a training-testing paradigm to investigate old/new effects of event-related potentials in confident and doubtful prosodic scenarios. Data reveals an enhanced late positive component between 400-850 ms at Pz and other electrodes. This pipeline can explore factors beyond speech prosody and their influence on cue-binding target identification.

使用事件相关电位分析在表达性语音中实现稳健声音身份识别的基于记忆的训练和测试范式

Recognizing familiar speakers from vocal streams is a fundamental aspect of human verbal communication. However, it remains unclear how listeners can ...

Mapping the After-effects of Theta Burst Stimulation on the Human Auditory Cortex with Functional Imaging

Auditory cortex pertains to the processing of sound, which is at the basis of speech or music-related processing1. However, despite considerable recent progress, the functional properties and lateralization of the human auditory cortex are far from being fully understood. Transcranial Magnetic Stimulation (TMS) is a non-invasive technique that can transiently or lastingly modulate cortical excitability via the application of localized magnetic field pulses, and represents a unique method of exploring plasticity and connectivity. It has only recently begun to be applied to understand auditory cortical function 2. 
An important issue in using TMS is that the physiological consequences of the stimulation are difficult to establish. Although many TMS studies make the implicit assumption that the area targeted by the coil is the area affected, this need not be the case, particularly for complex cognitive functions which depend on interactions across many brain regions 3. One solution to this problem is to combine TMS with functional Magnetic resonance imaging (fMRI). The idea here is that fMRI will provide an index of changes in brain activity associated with TMS. Thus, fMRI would give an independent means of assessing which areas are affected by TMS and how they are modulated 4. In addition, fMRI allows the assessment of functional connectivity, which represents a measure of the temporal coupling between distant regions. It can thus be useful not only to measure the net activity modulation induced by TMS in given locations, but also the degree to which the network properties are affected by TMS, via any observed changes in functional connectivity.
Different approaches exist to combine TMS and functional imaging according to the temporal order of the methods. Functional MRI can be applied before, during, after, or both before and after TMS. Recently, some studies interleaved TMS and fMRI in order to provide online mapping of the functional changes induced by TMS 5-7. However, this online combination has many technical problems, including the static artifacts resulting from the presence of the TMS coil in the scanner room, or the effects of TMS pulses on the process of MR image formation. But more importantly, the loud acoustic noise induced by TMS (increased compared with standard use because of the resonance of the scanner bore) and the increased TMS coil vibrations (caused by the strong mechanical forces due to the static magnetic field of the MR scanner) constitute a crucial problem when studying auditory processing. 
This is one reason why fMRI was carried out before and after TMS in the present study. Similar approaches have been used to target the motor cortex 8,9, premotor cortex 10, primary somatosensory cortex 11,12 and language-related areas 13, but so far no combined TMS-fMRI study has investigated the auditory cortex. The purpose of this article is to provide details concerning the protocol and considerations necessary to successfully combine these two neuroscientific tools to investigate auditory processing. 
Previously we showed that repetitive TMS (rTMS) at high and low frequencies (resp. 10 Hz and 1 Hz) applied over the auditory cortex modulated response time (RT) in a melody discrimination task 2. We also showed that RT modulation was correlated with functional connectivity in the auditory network assessed using fMRI: the higher the functional connectivity between left and right auditory cortices during task performance, the higher the facilitatory effect (i.e. decreased RT) observed with rTMS. However those findings were mainly correlational, as fMRI was performed before rTMS. Here, fMRI was carried out before and immediately after TMS to provide direct measures of the functional organization of the auditory cortex, and more specifically of the plastic reorganization of the auditory neural network occurring after the neural intervention provided by TMS. 
Combined fMRI and TMS applied over the auditory cortex should enable a better understanding of brain mechanisms of auditory processing, providing physiological information about functional effects of TMS. This knowledge could be useful for many cognitive neuroscience applications, as well as for optimizing therapeutic applications of TMS, particularly in auditory-related disorders.

Auditory processing is the basis of speech and music-related processing. Transcranial Magnetic Stimulation (TMS) has been used successfully to study cognitive, sensory and motor systems but has rarely been applied to audition. Here we investigated TMS combined with functional Magnetic Resonance Imaging to understand the functional organization of auditory cortex.

映射后的Theta突发刺激对人类听觉皮层功能成像

Auditory cortex pertains to the processing of sound, which is at the basis of speech or music-related processing1. However, despite considerable recent ...

生物学

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

The Translational Brain Mapping Program at the University of Rochester is an interdisciplinary effort that integrates cognitive science, neurophysiology, neuroanesthesia, and neurosurgery. Patients who have tumors or epileptogenic tissue in eloquent brain areas are studied preoperatively with functional and structural MRI, and intraoperatively with direct electrical stimulation mapping. Post-operative neural and cognitive outcome measures fuel basic science studies about the factors that mediate good versus poor outcome after surgery, and how brain mapping can be further optimized to ensure the best outcome for future patients. In this article, we describe the interdisciplinary workflow that allows our team to meet the synergistic goals of optimizing patient outcome and advancing scientific understanding of the human brain.

This article provides an overview of a multi-modal brain mapping program designed to identify regions of the brain that support critical cognitive functions in individual neurosurgery patients.

罗切斯特大学医学中心的转化脑图:通过个性化大脑映射保护大脑

The Translational Brain Mapping Program at the University of Rochester is an interdisciplinary effort that integrates cognitive science, neurophysiology, ...

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

摘要

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此视频中的章节

功能磁共振成像（fMRI）技术与听觉刺激鸣禽

观察虚拟社会交往中的神经关联的脑成像研究

关联从人类前额叶皮层的fMRI信号的行为反应：检查的认知过程，使用任务分析

听觉皮层在成年猫用高场磁共振成像功能成像

利用信息化连通性来衡量的功能磁共振成像多体素穿越时空信息的同步崛起

使用事件相关电位分析在表达性语音中实现稳健声音身份识别的基于记忆的训练和测试范式

使用事件相关电位分析在表达性语音中实现稳健声音身份识别的基于记忆的训练和测试范式

使用事件相关电位分析在表达性语音中实现稳健声音身份识别的基于记忆的训练和测试范式

映射后的Theta突发刺激对人类听觉皮层功能成像

罗切斯特大学医学中心的转化脑图:通过个性化大脑映射保护大脑