我们要感谢安德鲁 Cripps 和雷丁大学的资源单位。这项研究由 BBSRC (格兰特号: BB/K010123/1) 资助。与这项工作相关的数据可从 Y.Z. (ying.zheng@reading.ac.uk 英 zheng@reading) 免费获得。

所有的实验都是按照英国内政部 (《动物 (科学规程) 法》, 1986) 进行的, 并由英国雷丁大学的研究伦理委员会批准。
1. 动物制剂
注意: 所有的实验都使用了女性李斯特的大鼠。这是一个非生存的程序。
<ol><li>把老鼠的体重记录在实验室的秤上。</li>
	<li>麻醉5% 异氟醚和1升/分的氧流量。</li>
	<li>把老鼠放在一个立体定位器上, 用纸巾在它的身体下面, 用它的牙齿通过咬杆休息。纸巾将使热垫的插入更容易 (见步骤 2.3) 和捕捉任何粪便从老鼠在实验过程中。</li>
	<li>通过一个硬塑料鼻锥安装在鼻子钳上连续管理异氟醚, 在3% 的浓度为0.5 升/分钟的氧气流量的大鼠适配器. 将锥体连接到小动物异氟醚麻醉系统。</li>
</ol>2. 手术程序
<ol><li>在大鼠休息的纸巾下面插入一个恒温加热垫, 用两个耳条固定鼠头, 用直肠温度计监测体温。</li>
	<li>剃掉老鼠头上的毛</li>
	<li>将眼部软膏涂抹于眼部, 防止角膜干燥。</li>
	<li>在暴露颅骨前, 应将利多卡因滴到头皮上, 轻轻按摩至皮肤。</li>
	<li>在头皮上做一个大约2-3 厘米的中线切口, 用手术刀来露出颅骨的表面。</li>
	<li>小心地将颞肌肉对侧向的触须垫用 Jacquette 器和一对锯齿和弯曲的解剖钳从颅骨刺激。必要时用棉签清洁颅骨。</li>
	<li>用编织的丝绸, 不可吸收的缝合, 栓分开的肌肉对头皮与紧结, 然后栓缝合牢固地对立体定向框架18。</li>
	<li>使用立体定向坐标定位的桶皮层, 2.5 毫米尾管到 bregma 和6毫米侧向中线19。用铅笔或记号笔在体感皮层的位置画一个点。</li>
	<li>
用牙科钻头在标记的位置钻一个毛刺孔。为防止颅骨在钻孔过程中过热, 应将无菌生理盐水 (氯化钠 0.9%) 应用于工作区每10-15 秒。钻探过程包括以下3步骤:
	<ol>
<li>钻一个直径 < 2 毫米孔到头骨使用钻头 #4 (0.055 直径)。当心不要钻到硬脑膜上。</li>
		<li>用钻头 #1/4 (直径 0.019) 将孔的底部变薄至半透明。</li>
		<li>使用27克针刺穿硬脑膜, 允许插入微电极。</li>
	</ol>
</li>
	<li>将大鼠, 固定在一个立体定向的框架上, 转移到一个安装在隔振工作站顶部的法拉第笼上。</li>
	<li>将一个血传感器钳连接到血控制单元, 对鼠的后爪进行连续监测以下生理参数: 心率、呼吸率、动脉氧饱和度、脉搏扩张和呼吸扩张。这些参数在 PC 显示器上连续显示, 反映了大鼠的生理状况和麻醉深度。</li>
	<li>更换硬塑料鼻锥的异氟醚管理和鼻钳的大鼠适配器与 microflex 呼吸器装有一个透明的软鼻子锥, 这是修改 (图 1A), 使容易晶须刺激的一侧的晶须垫不损害异氟醚的管理。</li>
	<li>插入两个不锈钢刺激电极到晶须垫暴露的切出在鼻子锥。</li>
	<li>将刺激电极连接到一个孤立的电流刺激器。</li>
	<li>用镊子提起颈部中线的皮肤, 用剪刀作 1 ~ 2 厘米切口, 准备放置参考电极。注意不要切断肌肉组织。</li>
</ol>3. Co 局部脑电图/LFP 设置
<ol><li>用棉签清洁和干燥毛刺孔周围的头骨。</li>
	<li>小心地将传导性脑电图膏放在 eeg 蜘蛛电极的一个扁平一侧。在蜘蛛电极上留下一个小洞, 清除脑电波膏, 允许多层微电极穿过孔而不接触粘贴和蜘蛛电极。这可以防止 EEG 电极和微电极之间的电接触。</li>
	<li>将蜘蛛电极与头骨上的毛刺孔对齐, 并将脑电波糊朝向头骨。</li>
	<li>小心地将蜘蛛电极压在头骨上, 通过脑电图膏与头骨进行牢固接触。用注射器上的针头将毛刺孔上的任何糊状物去除。</li>
	<li>除去蜘蛛电极周围的过多的脑电波膏, 使蜘蛛电极和头骨之间的接触空间被限制在电极的大小 (图 1B)。</li>
</ol><img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56447/56447fig1.jpg"> 图 1: 并发脑电图/LFP 记录的常规设置.(A) 设置由一个改进的鼻锥, 以便于在异氟醚麻醉下的晶须垫刺激, 两个刺激电极插入晶须垫, 一个蜘蛛电极定位在头骨上方的桶皮层对侧刺激电极, 通过蜘蛛电极插入到桶皮层的多通道微电极, 以及放置在老鼠颈部后部切口内的参考电极。(B) 通过显微镜将蜘蛛电极安全地放置在头骨上的脑电图贴。微电极入到在蜘蛛电极下钻入头骨的毛刺孔中。头皮被绑在立体定向框架上的外科手术线 (缝合) 来控制。<a href="//cloudflare.jove.com/files/ftp_upload/56447/56447fig1large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<ol start="6"><li>将脑电图膏涂抹在参考电极上, 并将其安全地放在大鼠颈部后部的切口内。</li>
	<li>通过一个低阻抗信号的被动信号分配器将 EEG 电极连接到前置放大器 (图 2)。确保蜘蛛电极的阻抗低于5ω。如果不是, 检查 eeg 膏是否与颅骨有良好的接触, 并将电极牢牢地压在 eeg 糊上。如有必要, 添加更多脑电图膏。</li>
	<li>在立体定向架上安装一微臂。连接一个线性16通道微电极 (100 µm 间距, 每个站点177µm2) 到16通道的急性 headstage, 将安全地夹在微臂上。</li>
	<li>在脑电图和微电极上涂抹脑电图贴在参考电极上, 然后将它们安全地放置在切口内 (图 1A)。</li>
	<li>调整微臂的角度, 使微电极与皮质表面垂直。这个角度通常在25-35 °之间。</li>
	<li>在显微镜下通过转动微旋钮降低微电极, 使电极尖端对准毛刺孔底部的微小开口, 直到最上部的电极穿透皮质表面。必须注意避免将微电极强制到硬脑膜表面, 因为这会破坏电极。</li>
	<li>将16通道微电极与通过光纤电缆连接到数据采集单元的前置放大器耦合 (图 2)。</li>
	<li>打开前置放大器、数据采集单元和连接到设备的计算机。打开刺激盒。</li>
	<li>通过缓慢地将微的 z 轴旋钮旋转到1500µm20的深度, 将微电极正常插入皮质表面。</li>
	<li>微调整的深度, 应用一列车刺激的晶须垫和观察16通道诱发 LFP 在 pc 显示器上使用的软件的数据采集单元安装在 pc 上。小心地转动 z 轴旋钮在微直到最高振幅的诱发 LFP 发生在通道7附近 (因为这与第四层在皮层)。 注: 信息学侧脑电电极设置: 对于一些实验, 第二个蜘蛛电极被放置在信息学侧侧的完整头骨上方的桶皮层。该装置允许在静止状态下进行双侧脑电图记录, 以研究毛刺孔对 eeg 信号的影响。 注: 建立脑电图电极的手术方法与上述相同, 但在步骤2.6 中, 头部两侧的颞肌肉小心地与颅骨分离, 缝合背部并牢固地绑在相应的一侧立体定位框架。 注: 同期脑电图/LFP 设置也与上述描述相同, 与一个额外的步骤, 第二个蜘蛛电极加载脑电图糊, 然后紧紧压在头骨上方的信息学侧筒皮层。</li>
</ol><img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56447/56447fig2.jpg"> 图2。一个信号流图.老鼠被放在法拉第笼子里。刺激电极通过其安装在 PC 上的软件, 接收由数据采集单元控制的刺激器盒中的命令。将微电极记录的神经信号传送到法拉第笼内的预放大器。EEG 探针记录的神经信号通过信号分配器传输到前置放大器。预放大器通过光纤电缆连接到法拉第笼外的数据采集单元。然后将神经数据存储在 pc 上的本地驱动器上, 同时它们也可以显示在 pc 显示器上。一种移动式小动物异氟醚系统从法拉第笼外管理异氟醚。<a href="//cloudflare.jove.com/files/ftp_upload/56447/56447fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
4. 电刺激和神经记录
注: 所有神经数据的采样频率为 24.41 kHz, 具有16位分辨率。试验包括在试验开始时的一次电刺激。每项试验持续十年代, 这也是间刺激间隔 (ISI)。每一个刺激都是一个1.2 毫安持续0.3 毫秒的方波电流脉冲用于研究毛刺孔的作用, 并记录250s 的连续休眠状态。
<ol><li>打开正在使用的计算机上的录制软件。</li>
	<li>从 "OpenProject" 的下拉菜单中选择 "加载项目...", 为实验加载正确的电路。将出现一个新窗口 ("工作台") (图 3)。</li>
</ol><img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56447/56447fig3.jpg"> 图3。数据获取单元的软件 GUI 的显示.它允许上传合适的电路, 设置刺激参数, 记录和可视化数据。<a href="//cloudflare.jove.com/files/ftp_upload/56447/56447fig3large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<ol start="3"><li>
创建一个新的目录 (称为 "坦克" 的软件) 存储神经录音。
	<ol>
<li>单击窗口顶部的 "文件", 然后选择 "数据任务管理"。将出现一个新窗口 ("坦克管理")。</li>
		<li>在 "容器管理" 窗口中, 按鼠标右键以显示菜单。选择 "创建新坦克"。将出现另一个新窗口 ("创建数据池")。</li>
		<li>在 "创建数据池" 窗口中, 选择计划创建新数据目录的路径, 然后输入新目录的名称。然后按 "确定"。此窗口将消失。</li>
		<li>新目录将出现在 ' 坦克管理 ' 窗口, 但在灰色。通过右键单击注册此目录, 然后从下拉菜单中选择 "注册罐"。新目录的名称左侧将出现一个红色的星号和一个绿色箭头 (图 4)。</li>
		<li>通过右键单击 "容器管理" 窗口并在下拉菜单中选择 "刷新罐列表", 注销未使用的任何以前的目录。</li>
		<li>单击 "确定" 退出 "容器管理" 窗口。</li>
	</ol>
</li>
</ol><img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/56447/56447fig4.jpg"> 图 4: 显示已注册数据目录的软件 GUI.<a href="//cloudflare.jove.com/files/ftp_upload/56447/56447fig4large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<ol start="4"><li>
在 "范围" 中注册新目录, 在实验中显示神经信号。
	<ol>
<li>单击 "OpenProject" 窗口中的 "范围" 图标。将出现一个新窗口 ("范围")。</li>
		<li>右键单击 "范围" 窗口中的鼠标, 然后在下拉菜单中选择 "刷新罐列表"。新目录的名称将以灰色显示。</li>
		<li>单击新目录。红色星和绿色箭头将出现在新目录的名称左边, 现在是黑色的。</li>
	</ol>
</li>
	<li>通过单击窗口顶部的 "安装", 在 "工作台" 窗口中设置数据获取的实验参数。将出现一个新窗口。选择 "扫描回路", 设置试验的长度和要记录的试验数。</li>
	<li>检查刺激框是否打开。</li>
	<li>按 "工作台" 窗口中的 "记录" 按钮。将出现一个新窗口。输入要为实验运行保存的数据文件的名称, 但在这个阶段不按返回按钮, 因为需要设置 EEG 记录参数。</li>
	<li>
使用预放大器上的图形用户界面 (GUI) 设置 EEG 记录参数。触摸屏幕 (任何地方) 的前置放大器唤醒屏幕。选择 "解锁" 以解锁显示 (图 5)。
	<ol>
<li>在 "2: 脑电图" 面板中按左图标。将显示新的显示。</li>
		<li>按 ' 耦合 ', 并选择 ' AC '。</li>
		<li>按 "参考模式" 并选择 "本地"。</li>
		<li>按 "桑普率", 然后选择 "25KHz"。</li>
		<li>按 "确定" 返回到原始显示。</li>
	</ol>
</li>
</ol><img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/56447/56447fig5.jpg"> 图 5: 预放大器上的 GUI.它允许设置 EEG 记录参数 (例如、采样频率和引用首选项)。<a href="//cloudflare.jove.com/files/ftp_upload/56447/56447fig5large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<ol start="9"><li>通过按下 "2: 脑电图" 面板中的中间图标, 检查脑电图探头的阻抗。如果太高, 在探头上添加更多的脑电图膏。按 "确定" 返回到原始显示。</li>
	<li>等待二十年代, 以避免记录脑电图记录的初始波动。</li>
	<li>返回到 PC 监视器 (在二十年代等待之后), 然后按键盘上的 "返回" 键。脑电图和 LFP 信号将被记录。</li>
</ol>5. 数据分析
<ol><li>
前处理的诱发 LFP 和脑电图信号的试验的基础上, 使用以下步骤。
	<ol>
<li>通过20样本 (相当于0.82 毫秒) 将神经数据及时移回。这是用于收集 TDT 本身的神经数据的电路所产生的延迟。通过转移数据, 时间零点与刺激的开始是一致的。</li>
		<li>移除刺激伪影, 将神经数据从0到1毫秒, 用一条直线连接数据点在0毫秒, 数据点在1毫秒。</li>
		<li>零意味着每一个试验减去的平均值的神经信号200毫秒前刺激开始。</li>
		<li>低通滤波器在800赫兹以下的数据使用4的th命令, 在两个方向上都有一个类型过滤器, 以避免在数据中引入任何时间偏移。</li>
		<li>对齐跨动物的多层流数据。对于每个动物的 LFP 数据, 应用逆电流源密度 (样条中心, 源半径 R = 0.5 mm) 分析21与高斯滤镜 (λ = 50 µm), 以找到第四层下沉1, 这是由最大的负峰值发生在皮质深度低于脑膜表面在前15毫秒的刺激开始。CSD 和相应的 LFP, 然后根据它们在动物中的下沉位置对数据进行排列。共水槽位于 IV 层, ~ 600 µm 以下的脑膜表面。</li>
		<li>对齐后, 使用通道2、7和12的重新调整的 LFP 作为代表的神经反应的 supragranular, 颗粒状, 和 infragranular 层, 分别在桶皮层。</li>
	</ol>
</li>
	<li>通过平均100试验前处理数据, 计算平均诱发 LFP 和脑电图。</li>
	<li>为了研究毛刺孔对 eeg 的影响, 将 eeg 信号下采样到1000赫兹, 并计算出在250s 周期内侧向侧 (有一个孔在颅骨中) 和信息学侧面 (完好的头骨) 蜘蛛电极记录的功率谱密度 (PSD)休息状态。PSD 是从 0.1-100 赫兹的 Matlab 使用的函数 "pmtm", 这是基于多方法22。</li>
	<li>将频率范围划分为以下已知的频带: 三角洲 (δ): 0.1-4 赫兹, θ (): 4-8 赫兹, α (α): 8-13 hz, β (β): 13-31 hz, 伽玛 (γ): 31-100 赫兹. 计算每个波段内的平均 PSD。</li>
	<li>在每个频带内, 使用该公式计算出在信息学侧脑电波之间, Perr之间的归一化差异: <img alt="Equation" src="/files/ftp_upload/56447/56447eq1.jpg"> 其中, Pc 和pi 是信息学侧脑电图的平均 PSD, 分别在感兴趣的频率波段。</li>
	<li>在每个频带内, 执行一个样本 t 检验, 以测试在两个半球记录的 EEG 信号 PSD 之间没有显著差异 (在0.05 的意义级别) 的假设。</li>
</ol>

<ol>
	<li>Mitzdorf, U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Current+source-density+method+and+application+in+cat+cerebral+cortex:+investigation+of+evoked+potentials+and+EEG+phenomena.">Current source-density method and application in cat cerebral cortex: investigation of evoked potentials and EEG phenomena.</a> Physiol Rev. 65 (1), 37-100 (1985).</li><li>Logothetis, N. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Underpinnings+of+the+BOLD+Functional+Magnetic+Resonance+Imaging+Signal.">The Underpinnings of the BOLD Functional Magnetic Resonance Imaging Signal.</a> J Neurosci. 23 (10), 3963-3971 (2003).</li><li>Buzs&#225;ki, G., Anastassiou, C. A., Koch, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+origin+of+extracellular+fields+and+currents+—+EEG,+ECoG,+LFP+and+spikes.">The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes.</a> Nat Rev Neurosci. 13 (6), 407-420 (2012).</li><li>Einevoll, G. T., Kayser, C., Logothetis, N. K., Panzeri, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modelling+and+analysis+of+local+field+potentials+for+studying+the+function+of+cortical+circuits.">Modelling and analysis of local field potentials for studying the function of cortical circuits.</a> Nat Rev Neurosci. 14 (11), 770-785 (2013).</li><li>Zheng, Y., 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=Balanced+excitation+and+inhibition:+Model+based+analysis+of+local+field+potentials.">Balanced excitation and inhibition: Model based analysis of local field potentials.</a> Neuroimage. 63 (1), 81-94 (2012).</li><li>Bruyns-Haylett, M., 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=The+neurogenesis+of+P1+and+N1:+A+concurrent+EEG/LFP+study.">The neurogenesis of P1 and N1: A concurrent EEG/LFP study.</a> Neuroimage. 146, 575-588 (2017).</li><li>Nunez, P. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Electric Fields of the Brain: The Neurophysics of EEG. , (1981).</li><li>Jackson, A. F., Bolger, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+neurophysiological+bases+of+EEG+and+EEG+measurement:+A+review+for+the+rest+of+us.">The neurophysiological bases of EEG and EEG measurement: A review for the rest of us.</a> Psychophysiology. 51 (11), 1061-1071 (2014).</li><li>Cohen, M. X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Where+Does+EEG+Come+From+and+What+Does+It+Mean?.">Where Does EEG Come From and What Does It Mean?.</a> Trends Neurosci. 40 (4), 208-218 (2017).</li><li>Bojak, I., Oostendorp, T., Reid, A., K&#246;tter, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Connecting+Mean+Field+Models+of+Neural+Activity+to+EEG+and+fMRI+Data.">Connecting Mean Field Models of Neural Activity to EEG and fMRI Data.</a> Brain Topogr. 23 (2), 139-149 (2010).</li><li>Coombes, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Large-scale+neural+dynamics:+Simple+and+complex.">Large-scale neural dynamics: Simple and complex.</a> Neuroimage. 52 (3), 731-739 (2010).</li><li>Deco, G., Jirsa, V. K., Robinson, P. A., Breakspear, M., Friston, 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=The+dynamic+brain:+from+spiking+neurons+to+neural-masses+and+cortical+fields.">The dynamic brain: from spiking neurons to neural-masses and cortical fields.</a> PLoS Comput. Biol. 4 (8), e1000092 (2008).</li><li>Pinotsis, D. A., Friston, 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=Neural+fields,+spectral+responses+and+lateral+connections.">Neural fields, spectral responses and lateral connections.</a> Neuroimage. 55 (1), 39-48 (2011).</li><li>Riera, J. J., 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=Pitfalls+in+the+dipolar+model+for+the+neocortical+EEG+sources.">Pitfalls in the dipolar model for the neocortical EEG sources.</a> J Neurophysiol. 108 (4), 956-975 (2012).</li><li>Valdes, P. A., Jimenez, J. C., Riera, J., Biscay, R., Ozaki, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nonlinear+EEG+analysis+based+on+a+neural+mass+model.">Nonlinear EEG analysis based on a neural mass model.</a> Biol Cybern. 81 (5), 415-424 (1999).</li><li>Musall, S., von Pf&#246;stl, V., Rauch, A., Logothetis, N. K., Whittingstall, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+Neural+Synchrony+on+Surface+EEG.">Effects of Neural Synchrony on Surface EEG.</a> Cereb Cortex. 24 (4), 1045-1053 (2014).</li><li>Snyder, A. C., Morais, M. J., Willis, C. M., Smith, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+network+influences+on+local+functional+connectivity.">Global network influences on local functional connectivity.</a> Nat Neurosci. 18 (5), 736-743 (2015).</li><li>Mayhew, J., 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=Spectroscopic+analysis+of+neural+activity+in+brain:+Increased+oxygen+consumption+following+activation+of+barrel+cortex.">Spectroscopic analysis of neural activity in brain: Increased oxygen consumption following activation of barrel cortex.</a> Neuroimage. 12 (6), 664-675 (2000).</li><li>Paxinos, G., Watson, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The Rat Brain in Stereotaxic Coordinates. , (2005).</li><li>Martindale, J., 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=The+hemodynamic+impulse+response+to+a+single+neural+event.">The hemodynamic impulse response to a single neural event.</a> J Cereb Blood Flow Metab. 23 (5), 546-555 (2003).</li><li>Pettersen, K. H., Devor, A., Ulbert, I., Dale, A. M., Einevoll, G. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Current-source+density+estimation+based+on+inversion+of+electrostatic+forward+solution:+Effects+of+finite+extent+of+neuronal+activity+and+conductivity+discontinuities.">Current-source density estimation based on inversion of electrostatic forward solution: Effects of finite extent of neuronal activity and conductivity discontinuities.</a> J Neurosci Methods. 154 (1-2), 116-133 (2006).</li><li>Thomson, D. J., et al., Fitzgerald, W. J., 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=Multitaper+analysis+of+nonstationary+and+nonlinear+time+series+data.">Multitaper analysis of nonstationary and nonlinear time series data.</a> Nonlinear and Nonstationary Signal Processing. , 317-394 (2000).</li><li>Bae, J., Deshmukh, A., Song, Y., Riera, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Brain+Source+Imaging+in+Preclinical+Rat+Models+of+Focal+Epilepsy+using+High-Resolution+EEG+Recordings.">Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings.</a> Journal of Visualized Experiments : JoVE. (100), e52700 (2015).</li><li>Baumann, S. B., Wozny, D. R., Kelly, S. K., Meno, F. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+electrical+conductivity+of+human+cerebrospinal+fluid+at+body+temperature.">The electrical conductivity of human cerebrospinal fluid at body temperature.</a> IEEE Trans Biomed Eng. 44 (3), 220-223 (1997).</li><li>Wendel, 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=The+Influence+of+Age+and+Skull+Conductivity+on+Surface+and+Subdermal+Bipolar+EEG+Leads.">The Influence of Age and Skull Conductivity on Surface and Subdermal Bipolar EEG Leads.</a> Computational Intelligence and Neuroscience. 2010, (2010).</li><li>Flemming, L., 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=Evaluation+of+the+distortion+of+EEG+signals+caused+by+a+hole+in+the+skull+mimicking+the+fontanel+in+the+skull+of+human+neonates.">Evaluation of the distortion of EEG signals caused by a hole in the skull mimicking the fontanel in the skull of human neonates.</a> Clin Neurophysiol. 116 (5), 1141-1152 (2005).</li></ol>

作者没有什么可透露的。

我们描述了一个实验过程, 同时记录的 co 局部脑电图和 LFP 信号的异氟醚麻醉大鼠响应晶须垫刺激。一个微电极入到大脑皮层通过一个开放的脑电图蜘蛛电极 , 这是与一个毛刺孔钻入头骨。电极通过导电性和粘附脑电浆23固定在颅骨上。用于管理异氟醚的鼻锥被修改, 使刺激电极可以轻松地插入晶须垫。
EEG 膏是有效的安装蜘蛛电极安全地对头骨, 同时提供优良的电导率在整个实验日不需要额外的应用膏。它取代了不可取的使用胶水固定的蜘蛛电极的周围的头骨, 因为胶水是不导电的, 可以增加阻抗的电极, 如果它运行之间的头骨和电极。eeg 糊在脑电凝胶上有许多优点, 在毛刺孔周围不易形成, 在实验过程中会产生干燥, 导致脑电信号不佳。
当鼠被放置在法拉第笼内时, 由于环境的电噪声大大减弱。然而, 有时神经信号仍然相当嘈杂。在大多数情况下, 这是由于参考电极没有安全定位, 因此需要重新调整或更多的脑电图粘贴使用。另一个常见的问题是诱发 LFP 的振幅较小。这可能是由于微电极没有定位在皮层区中心激活的刺激电极。而不是重新插入微电极, 这可能会对局部神经元造成更多的损害, 我们通常调整的刺激电极在晶须垫的位置, 直到一个合理的幅度的 LFP (> 3 mV) 可以观察到。
该技术的局限性之一是蜘蛛电极的空间分辨率较差, 其直径为 6 mm。这与大鼠头骨的大小相比是很大的。不幸的是, 这里使用的蜘蛛电极是最小的可供购买的。将蜘蛛电极的直径减小到2-4 毫米是可取的, 从而增加了 eeg 记录的空间特异性, 使得 eeg 信号与 supragranular LFP 信号的比较不明确。
协议中的几个关键步骤需要特别注意。首先是通过毛刺孔插入微电极。由于硬脑膜是其他完整的, 插入的精度是至关重要的。电极尖端的轻微电阻通常意味着电极没有正确定位。它必须提出, 位置调整, 并重新插入。第二个是鼻子锥在老鼠身上的位置。它不能太松散, 因为异氟醚将从锥中逃脱。它也不能太紧, 因为这会阻碍老鼠的鼻孔, 造成呼吸困难。还需要特别注意, 以确保 EEG 记录的振幅比 LFP 的顶声道记录小得多 (通常小于5到10倍)。如果它们是相似的, 这是一个迹象表明, EEG 探针已进入直接或间接接触的微电极。间接接触通常是通过脑脊髓液 (CSF), 有时填补孔钻在头骨。CSF 的电导率通常是颅骨24,25的100倍。因此, 如果在毛刺孔内的脑脊液水平足够高, 它可以与蜘蛛电极接触。为了避免这种, 应该经常清洗的孔与超级吸水性棉海绵, 如吸收矛。
通过将另一只蜘蛛电极放在信息学侧筒皮层上的完整颅骨上, 研究了颅骨上的毛刺孔 (直径 < 2 mm) 对脑电记录的影响, 从而可以比较双边脑电图记录。在图 9 和图 10中显示的结果表明, 在0.05 级意义上的效果无关紧要。影响 eeg 振幅的其他因素包括脑电膏与颅骨接触的程度, 电极被压到糊状的方式, 以及脑电波膏在颅骨上的空间范围。
同样值得注意的是, 这里所描述的协议记录了颅内脑电图, 这与人类脑电图研究中使用的头皮脑电图不同。头皮的作用就像一个电阻器或一个低通滤波器, 它将进一步减少 EEG 记录的信噪比。
最后, 通过对 ERP 的时间动态和皮质层诱发 LFP 的比较, 表明体感诱发电位在皮层 supragranular 层中的 LFP 比颗粒状和 infragranular 层中更好。这与我们先前的工作6一致, 表明 ERP 的初始段 (P1) 与在颗粒层中发生的兴奋性突触电流的流入所产生的返回电流有关, 而随后的减少 (N1) 在 ERP 中可能与丘脑传入的延迟到达皮层层 II/III 和/或来自更深皮层层的前馈信号有关。总之, eeg/LFP 的并发记录可以增强对 eeg 的神经起源的理解, 并促进脑电信号在皮层层间的神经信号的数学建模。

一般认为, 通过电极记录的 LFPs 主要反映了局部锥体神经群的同步兴奋和抑制突触活动的加权和,1,2,3,4. 我们最近的研究表明, LFP 信号的剖面可以被分离成励磁和抑制的组成部分5,6。然而, 由于 LFP 通常是通过侵入性的程序来测量的, 所以它不适合人脑的大部分研究。
另一方面, 脑电图是一种非侵入性的测量大脑电活动的技术。它被广泛应用于某些类型的神经疾病如癫痫的诊断工具, 作为人类认知研究的一个研究工具。尽管它很受欢迎, 但 EEG 的一个主要限制是无法精确地根据基础神经信号7,89来解释其时间分布。
越来越多的, 数学模型的脑电图发展, 以提高对大脑功能的理解10,11,12,13,14,15。现有的脑电模型大多是基于模型拟合的频域特征, 在自发活动期间对 eeg 数据谱进行预测, 很少有脑电模型能产生逼真的感官诱发电位。在此背景下, eeg 和 LFP 的并发记录将为开发更精确的脑电图数学模型提供重要的洞察力和制约因素。
为了解决这一需要的并发录音进一步探索神经起源的脑电图, 我们开发了一种方法, 同时记录脑电图和多层 LFP 信号在新大脑皮层的麻醉大鼠。设置类似于以前在灵长类动物中进行的脑电图/LFP 研究16,17。我们进一步研究了一个钻孔入颅骨的毛刺孔对周围的 eeg 记录的影响, 通过比较双边脑电图记录 (即, 一个半球与一个毛刺孔, 另一个半球完好) 在缺乏感官刺激.我们的结果表明, 并发脑电图/LFP 录音可以简单和有效地进行, 很少 eeg 信号失真的毛刺孔在头骨。

<table>
	<tbody>
		<tr>
			<td>Female Lister Hood rats</td>
			<td>Charles Rivers</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Spider electrode</td>
			<td>Unimed Electrode Supplies Ltd</td>
			<td>SCS24-426</td>
			<td></td>
		</tr>
		<tr>
			<td>EEG paste: Ten20</td>
			<td>Unimed Electrode Supplies Ltd</td>
			<td>10-20-S</td>
			<td></td>
		</tr>
		<tr>
			<td>Stereotaxic holder with dual micromanipulator arms: Dual Manipulator Stereotaxic Frame with 18&#176; Ear Bars</td>
			<td>WPI (World Precision Instruments)</td>
			<td>502603</td>
			<td></td>
		</tr>
		<tr>
			<td>Isoflurane</td>
			<td>National Vet Services Limited</td>
			<td>50878</td>
			<td></td>
		</tr>
		<tr>
			<td>Hard plastic nose cone: Anasthesia Gas Mask for Rat</td>
			<td>WPI</td>
			<td>502054</td>
			<td></td>
		</tr>
		<tr>
			<td>Small animal isoflurane anaesthetic system</td>
			<td>WPI</td>
			<td>EZ-B800A</td>
			<td></td>
		</tr>
		<tr>
			<td>Thermostatic heating pad: Rat Blanket System 230V</td>
			<td>Harvard Apparatus UK</td>
			<td>50-7221-F</td>
			<td></td>
		</tr>
		<tr>
			<td>Ophthalmic ointment: Optixcare eye lube</td>
			<td>Viovet</td>
			<td>203865</td>
			<td></td>
		</tr>
		<tr>
			<td>Lidocaine Hydrochloride (Injection 2%)</td>
			<td>Larkmead Vets</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Jacquette Scaler #1SSE, 18cm, Hollow</td>
			<td>WPI</td>
			<td>503421</td>
			<td></td>
		</tr>
		<tr>
			<td>Serrated and curved dissecting forceps</td>
			<td>WPI</td>
			<td>15915</td>
			<td></td>
		</tr>
		<tr>
			<td>Braided silk, non-absorbable suture: Mersilk Suture W502H</td>
			<td>National Vet Services Limited</td>
			<td>153746</td>
			<td></td>
		</tr>
		<tr>
			<td>Dental drill: BONE MICRO DRILL SYST 230 VAC</td>
			<td>Harvard Apparatus UK</td>
			<td>72-4860</td>
			<td></td>
		</tr>
		<tr>
			<td>Sterile Saline: Sodium chloride 0.9%</td>
			<td>Animalcare Ltd</td>
			<td>14K26BT</td>
			<td></td>
		</tr>
		<tr>
			<td>Drill bit #4 : Ball Mill, Carbide, #4</td>
			<td>Harvard Apparatus UK</td>
			<td>72-4958</td>
			<td></td>
		</tr>
		<tr>
			<td>Drill bit #4 : Ball Mill, Carbide, #1/4</td>
			<td>Harvard Apparatus UK</td>
			<td>72-4962</td>
			<td></td>
		</tr>
		<tr>
			<td>Faraday cage</td>
			<td>Newport Corporation</td>
			<td>VIS-FDC-3600</td>
			<td></td>
		</tr>
		<tr>
			<td>Vibration isolation workstation: Vision IsoStation</td>
			<td>Newport Corporation</td>
			<td>M-VIS3660-RG4-325A</td>
			<td></td>
		</tr>
		<tr>
			<td>Oximeter Control Unit and sensor: MouseOxPlus, Starr Life Sciences Corp.</td>
			<td>WPI</td>
			<td>O15001</td>
			<td></td>
		</tr>
		<tr>
			<td>Transparent soft nose cone: Microflex Non-Rebreathing Unit with a Rat Nosecone</td>
			<td>WPI</td>
			<td>EZ-103A</td>
			<td></td>
		</tr>
		<tr>
			<td>Stainless steel stimulating electrodes</td>
			<td>PlasticsOne</td>
			<td>E363/1/SPC</td>
			<td></td>
		</tr>
		<tr>
			<td>Isolated current stimulator</td>
			<td>Made in House</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>16-channel micro-electrode, 100 &#956;m spacing, area of each site 177 &#956;m2</td>
			<td>NeuroNexus</td>
			<td>A1x16-10mm-100-177-A16</td>
			<td></td>
		</tr>
		<tr>
			<td>16-channel acute headstage</td>
			<td>Tucker David Technologies Inc., TDT</td>
			<td>RA16AC-Z</td>
			<td></td>
		</tr>
		<tr>
			<td>Pre-Amplifier: Z-Series 64-Channel Neuro-Digitizing Preamp</td>
			<td>TDT</td>
			<td>PZ5-64</td>
			<td></td>
		</tr>
		<tr>
			<td>Passive signal splitter: 32-Channel Splitter Box for PZ5</td>
			<td>TDT</td>
			<td>S-BOX_PZ5</td>
			<td></td>
		</tr>
		<tr>
			<td>Data acquisition unit: RZ2 BioAmp Processor. Z-Series 4-DSP ultra high performance processor</td>
			<td>TDT</td>
			<td>RZ2-4</td>
			<td></td>
		</tr>
		<tr>
			<td>Software for Neurophysiology: OpenEX</td>
			<td>TDT</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Matlab</td>
			<td>MathWorks</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Absorption spears</td>
			<td>Fine Sicence Tools</td>
			<td>18105-01</td>
			<td></td>
		</tr>
	</tbody>
</table>

concurrent recording of co-localized electroencephalography and local field potential in rodent

尽管脑电图 (eeg) 被广泛应用于记录大脑神经活动的非侵入性技术, 但我们对脑电图的脑组织的认识仍然非常有限。通过多层微电极记录的局部场电位 (LFPs) 可以更详细地描述大脑皮层不同皮层层的同时神经活动, 但这种技术是侵入性的。将脑电图和 LFP 测量结合在一个前临床模型中, 可以极大地提高对脑电信号生成中所涉及的神经机制的认识, 并有助于推导出更逼真和生物学上准确的脑电图数学模型。本文介绍了一种在麻醉啮齿动物中获得并发和 co 局部脑电图和多层流 LFP 信号的简单方法。我们还调查了脑电信号是否有明显的影响, 在头骨钻孔的一个毛刺孔插入一个微电极。我们的结果表明, 毛刺孔有一个微不足道的影响脑电图记录。

4只大鼠的数据均为平均时间序列。诱发脑电反应的振幅, 也被称为事件相关电位 (ERP), 通常比 LFP 的幅度小得多。图 6分别显示了 supragranular、粒状和 infragranular 层的平均 ERP 和 LFP。每个图形中的错误带是相应的标准错误。可以看出, ERP 大约比诱发 LFP 小10倍。
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/56447/56447fig6.jpg"> 图 6: 平均 (n = 4) ERP、supragranular、粒状和 infragranular LFP 的神经信号.阴影表示标准错误。<a href="//cloudflare.jove.com/files/ftp_upload/56447/56447fig6large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
对 ERP 和 LFP 的时间动态进行比较, 如图 7所示。ERP 和 supragranular LFP 在图 7A中的直接叠加说明了这两种类型的神经信号之间的振幅差的顺序。为了比较时间动态, ERP 和 LFP 都是相对于其负峰值振幅正常化。图 7B和7C分别显示规范化的 ERP 与规范化的 supragranular LFP 和规范化的粒 LFP 的叠加。
从图 7B可以看出, ERP 中的 P1 和 N1 的峰值比 supragranular 层中相应的 LFP 峰值更延迟。然而, 这两个神经信号的时间分布是相似的, 与 P1 前 N1。另一方面, ERP 的时间分布明显不同于 LFP (图 7C) 的粒度 (第四层)。重要的是, 他们不是彼此的镜像, 颗粒 LFP 由一个单一的负峰值 (反映在皮质层 IV 的主要下沉), 而 ERP 主要由两个相对极性的峰值。
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/56447/56447fig7.jpg"> 图 7: ERP 和 LFP 时间动态的比较.(A) ERP (实线) 叠加 supragranular LFP (虚线)。阴影表示标准错误。(B) 规范化的 ERP (实线), 与规范化的 supragranular LFP (虚线) 叠加。(C) 规范化的 ERP (实线) 与规范化颗粒 LFP (虚线) 叠加。<a href="//cloudflare.jove.com/files/ftp_upload/56447/56447fig7large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
ERP 信号是通过在头骨上放置一个有毛刺孔的蜘蛛电极来测量的。为了研究孔对 EEG 记录的影响, 另一只蜘蛛电极被放置在信息学侧筒皮层的完整颅骨上。注意, 以确保两个蜘蛛电极的阻抗是可比的大小, 通过调整的脑电图糊的数量使用。这里介绍了四只老鼠的数据 (它们不是上面所用的老鼠)。
图 8显示了从一只大鼠的两个电极进行的同时休眠状态 EEG 记录, 并显示在图 8A中的100s 数据, 而矩形框架 (二十年代) 中的数据则在图 8B中展开。这两种 EEG 信号在振幅相似的范围内有很大的共同变化。图 9显示了四只大鼠的 PSD, 顶行使用了频率轴上的线性刻度, 而在频率轴上使用对数刻度的底部行在低频范围内提供了扩展视图。从图 9中, PSD 中的主体之间似乎没有一致的偏差。在图 10中, 对五频段的平均 PSD 中的归一化差异进行了单样本 t 检验, 从而证实了这一点。这些频带上的归一化 PSD 差异与零 (p = 0.32、0.46、0.85、0.69 和0.97 分别) 没有显著的差别。
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/56447/56447fig8.jpg"> 图 8: 双边脑电图记录.(A) 颅骨脑电图在休眠状态下, 在颅骨 (黑色) 上有一个毛刺孔, 同时在相对半球上同时进行脑电图记录 (灰色)。(B) (A) 中矩形框架内波形的扩展视图。<a href="//cloudflare.jove.com/files/ftp_upload/56447/56447fig8large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/56447/56447fig9.jpg"> 图 9: 逆 (蓝色) 和信息学侧 (红色) 脑电图的功率谱密度 (PSD).每列显示的 PSD 为一只老鼠。顶部面板使用线性频率刻度, 而底部面板使用对数频率刻度, 使 PSD 在较低的频率范围内可视化。<a href="//cloudflare.jove.com/files/ftp_upload/56447/56447fig9large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 10" class="xfigimg" src="/files/ftp_upload/56447/56447fig10.jpg"> 图 10: 组分析.信息学侧 PSD 与五频段的归一化差: 三角洲、θ、α、β和伽玛。每个条形图显示了在频带内的平均正常化差异, 标准错误显示为误差线。<a href="//cloudflare.jove.com/files/ftp_upload/56447/56447fig10large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>

Watch this Scientific Journal Video about Concurrent Recording of Co-localized Electroencephalography and Local Field Potential in Rodent at JoVE.com

Concurrent Recording of Co-localized Electroencephalography and Local Field Potential in Rodent

该协议描述了一种简单的方法, 并发记录的联合局部脑电图 (eeg) 和多层局部场电位在麻醉大鼠。在头骨上钻孔插入微电极的毛刺孔被证明能产生轻微的 EEG 信号失真。

啮齿动物联合局部脑电图和局部电位的同步记录

Although electroencephalography (EEG) is widely used as a non-invasive technique for recording neural activities of the brain, our understanding of the ...

concurrent-recording-co-localized-electroencephalography-local-field

Research

JoVE Journal

Neuroscience

12.2K 次观看.  University of Reading. 该协议描述了一种简单的方法, 并发记录的联合局部脑电图 (eeg) 和多层局部场电位在麻醉大鼠。在头骨上钻孔插入微电极的毛刺孔被证明能产生轻微的 EEG 信号失真。

视频: Concurrent Recording of Co-localized Electroencephalography and Local Field Potential in Rodent

Systemic and Local Drug Delivery for Treating Diseases of the Central Nervous System in Rodent Models

Thorough preclinical testing of central nervous system (CNS) therapeutics includes a consideration of routes of administration and agent biodistribution in assessing therapeutic efficacy. Between the two major classifications of administration, local vs. systemic, systemic delivery approaches are often preferred due to ease of administration. However, systemic delivery may result in suboptimal drug concentration being achieved in the CNS, and lead to erroneous conclusions regarding agent efficacy. Local drug delivery methods are more invasive, but may be necessary to achieve therapeutic CNS drug levels. Here, we demonstrate proper technique for three routes of systemic drug delivery: intravenous injection, intraperitoneal injection, and oral gavage. In addition, we show a method for local delivery to the brain: convection-enhanced delivery (CED). The use of fluorescently-labeled compounds is included for in vivo imaging and verification of proper drug administration. The methods are presented using murine models, but can easily be adapted for use in rats.

Thorough preclinical testing of drugs that act in the central nervous system often involves assessing and comparing drug biodistribution in association with specific routes of administration. Here, three commonly used methods of systemic delivery (intravenous, intraperitoneal, and oral) as well as a method for local delivery (convection-enhanced delivery) are demonstrated in mice.

全身和局部给药治疗的中枢神经系统疾病的啮齿动物模型

Thorough preclinical testing of central nervous system (CNS) therapeutics includes a consideration of routes of administration and agent biodistribution ...

科研

神经科学

Examining Local Network Processing using Multi-contact Laminar Electrode Recording

Cortical layers are ubiquitous structures throughout neocortex1-4 that consist of highly recurrent local networks. In recent years, significant progress has been made in our understanding of differences in response properties of neurons in different cortical layers5-8, yet there is still a great deal left to learn about whether and how neuronal populations encode information in a laminar-specific manner.
Existing multi-electrode array techniques, although informative for measuring responses across many millimeters of cortical space along the cortical surface, are unsuitable to approach the issue of laminar cortical circuits. Here, we present our method for setting up and recording individual neurons and local field potentials (LFPs) across cortical layers of primary visual cortex (V1) utilizing multi-contact laminar electrodes (Figure 1; Plextrode U-Probe, Plexon Inc).
The methods included are recording device construction, identification of cortical layers, and identification of receptive fields of individual neurons. To identify cortical layers, we measure the evoked response potentials (ERPs) of the LFP time-series using full-field flashed stimuli. We then perform current-source density (CSD) analysis to identify the polarity inversion accompanied by the sink-source configuration at the base of layer 4 (the sink is inside layer 4, subsequently referred to as granular layer9-12). Current-source density is useful because it provides an index of the location, direction, and density of transmembrane current flow, allowing us to accurately position electrodes to record from all layers in a single penetration6, 11, 12.

A fundamental issue in our understanding of cortical circuitry is how networks in different cortical layers encode sensory information. Here we describe electrophysiological techniques utilizing multi-contact laminar electrodes to record single-units and local field potentials and present analyses to identify cortical layers.

检查本地网络处理采用多接触层电极记录

Cortical layers are ubiquitous structures throughout neocortex1-4 that consist of highly recurrent local networks. In recent years, significant progress ...

Simultaneous Electroencephalography, Real-time Measurement of Lactate Concentration and Optogenetic Manipulation of Neuronal Activity in the Rodent Cerebral Cortex

Although the brain represents less than 5% of the body by mass, it utilizes approximately one quarter of the glucose used by the body at rest1. The function of non rapid eye movement sleep (NREMS), the largest portion of sleep by time, is uncertain. However, one salient feature of NREMS is a significant reduction in the rate of cerebral glucose utilization relative to wakefulness2-4. This and other findings have led to the widely held belief that sleep serves a function related to cerebral metabolism. Yet, the mechanisms underlying the reduction in cerebral glucose metabolism during NREMS remain to be elucidated.
	One phenomenon associated with NREMS that might impact cerebral metabolic rate is the occurrence of slow waves, oscillations at frequencies less than 4 Hz, in the electroencephalogram5,6. These slow waves detected at the level of the skull or cerebral cortical surface reflect the oscillations of underlying neurons between a depolarized/up state and a hyperpolarized/down state7. During the down state, cells do not undergo action potentials for intervals of up to several hundred milliseconds. Restoration of ionic concentration gradients subsequent to action potentials represents a significant metabolic load on the cell8; absence of action potentials during down states associated with NREMS may contribute to reduced metabolism relative to wake.
	Two technical challenges had to be addressed in order for this hypothetical relationship to be tested. First, it was necessary to measure cerebral glycolytic metabolism with a temporal resolution reflective of the dynamics of the cerebral EEG (that is, over seconds rather than minutes). To do so, we measured the concentration of lactate, the product of aerobic glycolysis, and therefore a readout of the rate of glucose metabolism in the brains of mice. Lactate was measured using a lactate oxidase based real time sensor embedded in the frontal cortex. The sensing mechanism consists of a platinum-iridium electrode surrounded by a layer of lactate oxidase molecules. Metabolism of lactate by lactate oxidase produces hydrogen peroxide, which produces a current in the platinum-iridium electrode. So a ramping up of cerebral glycolysis provides an increase in the concentration of substrate for lactate oxidase, which then is reflected in increased current at the sensing electrode. It was additionally necessary to measure these variables while manipulating the excitability of the cerebral cortex, in order to isolate this variable from other facets of NREMS.
	We devised an experimental system for simultaneous measurement of neuronal activity via the elecetroencephalogram, measurement of glycolytic flux via a lactate biosensor, and manipulation of cerebral cortical neuronal activity via optogenetic activation of pyramidal neurons. We have utilized this system to document the relationship between sleep-related electroencephalographic waveforms and the moment-to-moment dynamics of lactate concentration in the cerebral cortex. The protocol may be useful for any individual interested in studying, in freely behaving rodents, the relationship between neuronal activity measured at the electroencephalographic level and cellular energetics within the brain.

A procedure is described for manipulating the activity of cerebral cortical pyramidal neurons optogenetically while the electroencephalogram, electromyogram, and cerebral lactate concentration are monitored. Experimental recordings are performed on cable-tethered mice while they undergo spontaneous sleep/wake cycles. Optogenetic equipment is assembled in our laboratory; recording equipment is commercially available.

同时脑电图，实时测量的啮齿动物的大脑皮质中的神经元活动的乳酸浓度与Optogenetic的操作

Although the brain represents less than 5% of the body  by mass, it utilizes approximately one quarter of the glucose used by the body  at rest1. The ...

Intracellular Recording, Sensory Field Mapping, and Culturing Identified Neurons in the Leech, Hirudo medicinalis

The freshwater leech, Hirudo medicinalis, is a versatile model organism that has been used to address scientific questions in the fields of neurophysiology, neuroethology, and developmental biology. The goal of this report is to consolidate experimental techniques from the leech system into a single article that will be of use to physiologists with expertise in other nervous system preparations, or to biology students with little or no electrophysiology experience. We demonstrate how to dissect the leech for recording intracellularly from identified neural circuits in the ganglion. Next we show how individual cells of known function can be removed from the ganglion to be cultured in a Petri dish, and how to record from those neurons in culture. Then we demonstrate how to prepare a patch of innervated skin to be used for mapping sensory or motor fields. These leech preparations are still widely used to address basic electrical properties of neural networks, behavior, synaptogenesis, and development. They are also an appropriate training module for neuroscience or physiology teaching laboratories.

Intracellular Recording, Sensory Field Mapping, and Culturing Identified Neurons in the Leech, Hirudo medicinalis

This article describes three nervous system preparations using leeches: intracellular recording from neurons in ventral ganglia, culturing neurons from ventral ganglia, and recording from a patch of innervated skin to map sensory fields.

细胞内记录，感官字段映射，并在水蛭养殖鉴定神经元，医用水蛭</i

The freshwater leech, Hirudo medicinalis, is a versatile model organism that has been used to address scientific questions in the fields of ...

Measuring Spinal Presynaptic Inhibition in Mice By Dorsal Root Potential Recording In Vivo

Presynaptic inhibition is one of the most powerful inhibitory mechanisms in the spinal cord. The underlying physiological mechanism is a depolarization of primary afferent fibers mediated by GABAergic axo-axonal synapses (primary afferent depolarization). The strength of primary afferent depolarization can be measured by recording of volume-conducted potentials at the dorsal root (dorsal root potentials, DRP). Pathological changes of presynaptic inhibition are crucial in the abnormal central processing of certain pain conditions and in some disorders of motor hyperexcitability. Here, we describe a method of recording DRP in vivo in mice. The preparation of spinal cord dorsal roots in the anesthetized animal and the recording procedure using suction electrodes are explained. This method allows measuring GABAergic DRP and thereby estimating spinal presynaptic inhibition in the living mouse. In combination with transgenic mouse models, DRP recording may serve as a powerful tool to investigate disease-associated spinal pathophysiology. In vivo recording has several advantages compared to ex vivo isolated spinal cord preparations, e.g. the possibility of simultaneous recording or manipulation of supraspinal networks and induction of DRP by stimulation of peripheral nerves.

Measuring Spinal Presynaptic Inhibition in Mice By Dorsal Root Potential Recording In Vivo

GABAergic presynaptic inhibition is a powerful inhibitory mechanism in the spinal cord important for motor and sensory signal integration in spinal cord networks. Underlying primary afferent depolarization can be measured by recording of dorsal root potentials (DRP). Here we demonstrate a method of in vivo recording of DRP in mice.

测量脊髓突触前抑制小鼠背根电位记录<em&gt;在体内</em

Presynaptic inhibition is one of the most powerful inhibitory mechanisms in the spinal cord. The underlying physiological mechanism is a depolarization of ...

Simultaneous Electrophysiological Recording and Micro-injections of Inhibitory Agents in the Rodent Brain

Here we describe a method for the construction of a single-use &#8220;injectrode&#8221; using commercially accessible and affordable parts. A probing system was developed that allows for the injection of a drug while recording electrophysiological signals from the affected neuronal population. This method provides a simple and economical alternative to commercial solutions. A glass pipette was modified by combining it with a hypodermic needle and a silver filament. The injectrode is attached to commercial microsyringe pump for drug delivery. This results in a technique that provides real-time pharmacodynamics feedback through multi-unit extracellular signals originating from the site of drug delivery. As a proof of concept, we recorded neuronal activity from the superior colliculus elicited by flashes of light in rats, concomitantly with delivery of drugs through the injectrode. The injectrode recording capacity permits the functional characterization of the injection site favoring precise control over the localization of drug delivery. Application of this method also extends far beyond what is demonstrated here, as the choice of chemical substance loaded into the injectrode is vast, including tracing markers for anatomic experiments.

Here, we craft a glass pipette with dual functions: inhibition of deep brain structures by microinjections of drugs and real-time monitoring of their effects through simultaneous electrophysiological recordings.

同时电生理记录和抑制剂在啮齿动物大脑微注射

Here we describe a method for the construction of a single-use &#8220;injectrode&#8221; using commercially accessible and affordable parts. A probing ...

Acute In Vivo Electrophysiological Recordings of Local Field Potentials and Multi-unit Activity from the Hyperdirect Pathway in Anesthetized Rats

Converging evidence shows that many neuropsychiatric diseases should be understood as disorders of large-scale neuronal networks. To better understand the pathophysiological basis of these diseases, it is necessary to precisely characterize in which way the processing of information is disturbed between the different neuronal parts of the circuit. Using extracellular in vivo electrophysiological recordings, it is possible to accurately delineate neuronal activity within a neuronal network. The application of this method has several advantages over alternative techniques, e.g., functional magnetic resonance imaging and calcium imaging, as it allows a unique temporal and spatial resolution and does not rely on genetically engineered organisms. However, the use of extracellular in vivo recordings is limited since it is an invasive technique that cannot be universally applied. In this article, a simple and easy to use method is presented with which it is possible to simultaneously record extracellular potentials such as local field potentials and multiunit activity at multiple sites of a network. It is detailed how a precise targeting of subcortical nuclei can be achieved using a combination of stereotactic surgery and online analysis of multi-unit recordings. Thus, it is demonstrated, how a complete network such as the hyperdirect cortico-basal ganglia loop can be studied in anesthetized animals in vivo.

Acute In Vivo Electrophysiological Recordings of Local Field Potentials and Multi-unit Activity from the Hyperdirect Pathway in Anesthetized Rats

In this study, the methodology is presented on how to perform multi-site in vivo electrophysiological recordings from the hyperdirect pathway under urethane anesthesia.

急性<em&gt;体内</em&gt;麻醉大鼠超导途径局部场电位和多单位活动的电生理记录

Converging evidence shows that many neuropsychiatric diseases should be understood as disorders of large-scale neuronal networks. To better understand the ...

Recording and Modulation of Epileptiform Activity in Rodent Brain Slices Coupled to Microelectrode Arrays

Temporal lobe epilepsy (TLE) is the most common partial complex epileptic syndrome and the least responsive to medications. Deep brain stimulation (DBS) is a promising approach when pharmacological treatment fails or neurosurgery is not recommended. Acute brain slices coupled to microelectrode arrays (MEAs) represent a valuable tool to study neuronal network interactions and their modulation by electrical stimulation. As compared to conventional extracellular recording techniques, they provide the added advantages of a greater number of observation points and a known inter-electrode distance, which allow studying the propagation path and speed of electrophysiological signals. However, tissue oxygenation may be greatly impaired during MEA recording, requiring a high perfusion rate, which comes at the cost of decreased signal-to-noise ratio and higher oscillations in the experimental temperature. Electrical stimulation further stresses the brain tissue, making it difficult to pursue prolonged recording/stimulation epochs. Moreover, electrical modulation of brain slice activity needs to target specific structures/pathways within the brain slice, requiring that electrode mapping be easily and quickly performed live during the experiment. Here, we illustrate how to perform the recording and electrical modulation of 4-aminopyridine (4AP)-induced epileptiform activity in rodent brain slices using planar MEAs. We show that the brain tissue obtained from mice outperforms rat brain tissue and is thus better suited for MEA experiments. This protocol guarantees the generation and maintenance of a stable epileptiform pattern that faithfully reproduces the electrophysiological features observed with conventional field potential recording, persists for several hours, and outlasts sustained electrical stimulation for prolonged epochs. Tissue viability throughout the experiment is achieved thanks to the use of a small-volume custom recording chamber allowing for laminar flow and quick solution exchange even at low (1 mL/min) perfusion rates. Quick MEA mapping for real-time monitoring and selection of stimulating electrodes is performed by a custom graphic user interface (GUI).

We illustrate how to perform recording and electrical modulation of 4-aminopyridine-induced epileptiform activity in rodent brain slices using microelectrode arrays. A custom recording chamber maintains tissue viability throughout prolonged experimental sessions. Live electrode mapping and selection of stimulating pairs are performed by a custom graphical user interface.

鼠脑切片偶联微电极阵列癫痫活性的记录与调控

Temporal lobe epilepsy (TLE) is the most common partial complex epileptic syndrome and the least responsive to medications. Deep brain stimulation (DBS) ...

Evaluation of Hemisphere Lateralization with Bilateral Local Field Potential Recording in Secondary Motor Cortex of Mice

This article demonstrates complete, detailed procedures for both in vivo bilateral recording and analysis of local field potential (LFP) in the cortical areas of mice, which are useful for evaluating possible laterality deficits, as well as for assessing brain connectivity and coupling of neural network activities in rodents. The pathological mechanisms underlying Alzheimer&#39;s disease (AD), a common neurodegenerative disease, remain largely unknown. Altered brain laterality has been demonstrated in aging people, but whether or not abnormal lateralization is one of the early signs of AD has not been determined. To investigate this, we recorded bilateral LFPs in 3-5-month-old AD model mice, APP/PS1, together with littermate wild type (WT) controls. The LFPs of the left and right secondary motor cortex (M2), specifically in the gamma band, were more synchronized in APP/PS1 mice than in WT controls, suggesting a declined hemispheric asymmetry of bilateral M2 in this AD mouse model. Notably, the recording and data analysis processes are flexible and easy to carry out, and can also be applied to other brain pathways when conducting experiments that focus on neuronal circuits.

We present in vivo electrophysiological recording of the local field potential (LFP) in bilateral secondary motor cortex (M2) of mice, which can be applied to evaluate hemisphere lateralization. The study revealed altered levels of synchronization between the left and right M2 in APP/PS1 mice compared to WT controls.

小鼠二次运动皮质中双边局部场电位记录半球横向化评价

This article demonstrates complete, detailed procedures for both in vivo bilateral recording and analysis of local field potential (LFP) in the cortical ...

Investigating Long-term Synaptic Plasticity in Interlamellar Hippocampus CA1 by Electrophysiological Field Recording

The study of synaptic plasticity in the hippocampus has focused on the use of the CA3-CA1 lamellar network. Less attention has been given to the longitudinal interlamellar CA1-CA1 network. Recently however, an associational connection between CA1-CA1 pyramidal neurons has been shown. Therefore, there is the need to investigate whether the longitudinal interlamellar CA1-CA1 network of the hippocampus supports synaptic plasticity.
We designed a protocol to investigate the presence or absence of long-term synaptic plasticity in the interlamellar hippocampal CA1 network using electrophysiological field recordings both in vivo and in vitro. For in vivo extracellular field recordings, the recording and stimulation electrodes were placed in a septal-temporal axis of the dorsal hippocampus at a longitudinal angle, to evoke field excitatory postsynaptic potentials. For in vitro extracellular field recordings, hippocampal longitudinal slices were cut parallel to the septal-temporal plane. Recording and stimulation electrodes were placed in the stratum oriens (S.O) and the stratum radiatum (S.R) of the hippocampus along the longitudinal axis. This enabled us to investigate the directional and layer specificity of evoked excitatory postsynaptic potentials. Already established protocols were used to induce long-term potentiation (LTP) and long-term depression (LTD) both in vivo and in vitro. Our results demonstrated that the longitudinal interlamellar CA1 network supports N-methyl-D-aspartate (NMDA) receptor-dependent long-term potentiation (LTP) with no directional or layer specificity. The interlamellar network, however, in contrast to the transverse lamellar network, did not present with any significant long-term depression (LTD).

We used recording and stimulation electrodes in longitudinal hippocampal brain slices and longitudinally positioned recording and stimulation electrodes in the dorsal hippocampus in vivo to evoke extracellular postsynaptic potentials and demonstrate long-term synaptic plasticity along the longitudinal interlamellar CA1.