Jun 2019



Precise Targeting of Single Microelectrodes to Orientation Pinwheel Centers

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In the mammalian visual system, early stages of visual form perception begin with orientation selective neurons in primary visual cortex (V1). In many species (including humans, monkeys, tree shrews, cats, and ferrets), these neurons are organized in pinwheel-like orientation columns. To study the functional organization within orientation pinwheels, it is important to target pinwheel subdomains precisely. We therefore developed a technique to provide a quantitative determination of the location of pinwheel centers (PCs). Previous studies relied solely on blood vessel images of the cortical surface to guide electrode penetrations to PCs in orientation maps. However, considerable spatial error remained using this method. In the present study, we improved the accuracy of targeting PCs by ensuring perpendicularity of electrodes and by utilizing the orientation tuning of local field potentials (LFP) recorded at or near the optically determined positions.

Keywords: Orientation domain (方向功能区), Single microelectrode (单微电极), Pinwheel center (PC) (风车中心区), Local field potentials (LFP) (局部场电位), Optical imaging (OI) (光学成像)


Within the visual cortex, orientation pinwheels (PCs) are singularity centers around which neuronal orientation preference systematically shifts. PCs have been the focus of many studies on how the brain encodes different aspects of object shape, such as linear oriented segments, curved segments, corners, and T junctions (Hubel and Wiesel, 1974; Das and Gilbert, 1999; Hashemi-Nezhad and Lyon, 2012). Single-unit recording has been the most common method for studying organization within orientation pinwheels (Hubel and Wiesel, 1974). However, due to limitations of blood vessel guided localization of microelectrodes and uncertainties of electrode perpendicularity (Nauhaus and Ringach, 2007), it is quite challenging to accurately target microelectrodes to pinwheel centers (PCs). Hashemi-Nezhad and Lyon (2012) used electrodes coated with Dil to nicely demonstrate that electrodes were truly perpendicular; however, the vasculature-based method still contained localization error. Nauhaus and Ringach (2007), carefully matched the electrode locations in a Utah array with locations in an optical imaged orientation map and achieved accurate PC localization, but such an approach offers little control over where the electrodes end up within orientation domains or pinwheel centers. Using 2-photon methods, Ohki et al. (2006) reported that the true PC is only 130 µm in diameter, underscoring the need for highly accurate electrode targeting (see also Nauhaus et al., 2008).

In this study, we developed a method for targeting PCs with high accuracy. This was achieved by: (1) Assuring perpendicular penetrations by imaging a large field of view with a narrow depth of field (~50 μm, front-to-front lens with f1.2 (Ratzlaff and Grinvald, 1991), and then ensuring the electrode paralleled exactly the axis of the optical imaging. Using this procedure, we have estimated that the deviation of electrodes from perpendicular is less than 2 deg (see Figure 3D). (2) Carefully targeting electrodes to PCs based on blood vessel guidance. (3) Further determining the precise PC center by assessing whether the local field potentials (LFP) exhibit ‘non-sine-like’ responses. We have previously shown (Li et al., 2019) using this methodology that penetrations with sine-like LFP response and small scatter in orientation preference are not true PC locations, while those with non-sine-like response and large scatter in orientation preference (> 60 deg, Maldonado et al., 1997) are the true PC locations. This additional non-sine-like criterion is essential for highly accurate determination of PC locations and has provided new understanding of orientation subdomain organization (Li et al., 2019). These detailed procedures are described below.

Materials and Reagents

  1. Cover glass
  2. Tungsten-in-glass microelectrodes (impedance: ~5 MΩ; tip diameter: ~1 μm):
    These electrodes were homemade. Detailed description of procedures for electrode construction can be found in previous paper (Li et al., 1995). Briefly, tungsten-in-glass electrodes were prepared from tungsten wire (diameter 200 µm, Shanghai Tungsten and molybdenum products company, type: S-EST6135) and capillary glass (inner diameter: 0.3 mm, outer diameter: 1 mm, borosilicate glass, Shanghai Glass Works, type: SGW-95). The desired impedance of ~5 MΩ was measured (Ωmega-Tip-Z, World Precision Instruments,USA ) and corresponded to tungsten tip length of ~10 µm and the tip diameter of ~1 µm (Figure 1).

    Figure 1. Photograph of tungsten-in-glass microelectrode. 1 grid mark is 2.5 µm Image shows electrode tip length of of ~10 µm, and tip diameter of ~1 µm.

  3. Animals
    These procedures were developed using 16 anesthetized adult cats of both sexes. The following procedures can be applied to the visual cortex of other species as well.
  4. Ketamine hydrochloride
  5. 1% atropine sulfate eyedrops
  6. Agar
  7. Barbiturate


  1. Neural data acquisition system (Blackrock Microsystems Inc., Cerebus, Cerebus 32)
  2. Video camera (Andor Technology, Andor, model: iXon DU897 )
  3. Lenses (Nikon, NIKKOR, D = 50 mm, f = 1.2)
  4. Visual stimulus Generator (Cambridge Research Systems Ltd. ViSaGe MKII)
  5. Stereotaxic apparatus (Narishige, SN-3N)


  1. Matlab (Mathworks, ww2.mathworks.cn), and the matlab code as the supplemental file


  1. Animal Preparation Procedures
    Detailed descriptions of procedures for animal surgery and anesthesia can be found in previous studies (Song and Li, 2008).
    1. Anesthetize cats before surgery with ketamine hydrochloride (30 mg/kg), and then perform endotracheal intubation and venous cannulations. After surgery, the animal was placed in a stereotaxic frame for performing a craniotomy and conducting neurophysiological procedures. During recording, maintain anesthesia (urethane 20 mg/kg/h), paralysis (gallamine triethiodide 10 mg/kg/h), and blood sugar and fluids (glucose 200 mg/kg/h in Ringer’s solution 3 ml/kg/h i.v.). Monitor continuously heart rate, electrocardiography, electroencephalography (EEG), end-expiratory CO2, and rectal temperature. Anesthesia is considered to be sufficient when the EEG indicates a stable sleep-like state marked by sleep spindles. Reflexes, including cornea, eyelid, and withdrawal reflexes are tested at regular intervals.
    2. The eyes are prepared for vision experiments: Retract nictitating membranes and dilate the pupils using 1% atropine sulfate eyedrops. Apply contact lenses and use additional corrective lenses to achieve focus of the retina on a computer monitor in front of the animal.
    3. Perform a craniotomy and durotomy above area 17 (V1) and cement a stainless steel chamber on the surrounding skull. To dampen cortical pulsations, either seal the chamber with a cover glass and fill with silicone oil, or cover cortex with 4% agar and a cover glass.
    4. At the end of the experiment, sacrifice the animal by an overdose of barbiturate administered intravenously (dosage, 5 ml, 6% barbiturate).

  2. Optical Imaging Procedures
    1. Position camera and lens over the optical window. Crude positioning of the camera was enabled using a homemade camera arm to which a micromanipulator with 100 millimeter of freedom (manually adjust x, y, z position). Fine positioning of the camera was achieved by electrically adjusting the x, y, z position (10 millimeter freedom) and the declination angle α (45 degree freedom) with a micromanipulator platform. The optical instrument is a 14-bit video camera (Andor Technology, Northern Ireland) equipped with two front-to-front connected 50 mm Nikon lenses.
    2. Illluminate the cortical surface as evenly as possible using green light (546 nm) illumination. Obtain a reference image of the blood vessel pattern (see Figure 2A).
    3. Focus the camera ~400 μm below the surface of the cortex and collect optical images using red light illumination (605 nm, a wavelength optimal for hemodynamic oximetry signals).
    4. Obtain orientation preference maps. The intrinsic signals were recorded in response to binocularly viewed full-screen, high-contrast (100%) sinewave gratings. The main set of stimuli included drifting gratings, presented at 8 equally spaced orientations, in both directions (16 conditions). Each stimulus was presented 20 times for 9 s followed by an inter stimulus interval of 16 s. The visual stimuli were generated by a Cambridge Systems VSG graphics board. Stimuli were presented on a high-resolution monitor screen (40 × 30 cm) at a 100 Hz vertical refresh rate. The screen background was maintained at the identical mean luminance as the stimulus patches (10 cd/m2). The monitor was placed 57cm from the animal’s eyes.
    5. Generate colored-coded orientation preference maps (Figure 2B) via pixel-by-pixel vector summation of the 8 orientations (Bonhoeffer and Grinvald, 1991). In some experiments, drifting gratings were presented at 16 equally spaced orientations (at 11.25° intervals).
    6. Carefully choose only highly accurate and reproducible maps. That is, first generate maps from different subsets of trials. Then select only maps in which there is no displacement (shifted by no more than 13-26 μm) of pinwheel centers. These are deemed acceptable (Mariño et al., 2005).

      Figure 2. Highly accurate and quantitative determination of PC locations. A. Vascular pattern of the cortical surface. B. The color-coded orientation map of the cortex in (A). C. Two neighboring pinwheel centers (PC, locations 1 and 2) and three evenly spaced intervening points (DP, domain point, location 3; DM, domain midway, locations 4 and 5) in the orientation domain. The eight stimulus orientations are color coded at 22.5° intervals. Scale bars in (A) and (B): 500 μm. Scale bar in (C): 100 μm.

  3. Electrophysiological Recording Procedures
    1. Single unit isolation
      1. Insert and advance the electrode through the cortex, and record the signals using the Cerebus System.
      2. Spike signals were band-pass filtered at 250-7,500 Hz and sampled at 30 kHz. Only well-isolated cells satisfying the strict criteria for single-unit recordings (fixed shape of the action potential and the absence of spikes during the absolute refractory period) are selected and saved for further analyses.
    2. Single unit functional characterization
      1. All cells recorded were located in the area of the cortex representing the central 10° of the visual field. When the single-cell action potentials were isolated, the preferred orientation, SF, and TF of each cell were determined. Each cell was stimulated monocularly through the dominant eye, with the no dominant eye occluded. To locate the center of the CRF, a narrow rectangular sine wave grating patch (0.5° to 1.0° wide, 3.0° to 5.0° long, 100% contrast) was moved at successive positions along axes perpendicular or parallel to the optimal orientation of the cell, and the response to its drift was measured.
      2. The grating was set at the optimal orientation and SF and drifted in the preferred direction at the optimal speed for the recorded cells. The peak of the response profiles for both axes was defined as the center of the CRF. We determined the size of the CRF by performing an occlusion test, in which a mask consisting of a circular blank patch and centered on the CRF was gradually increased in size on a background drifting grating (Song and Li, 2008).
    3. LFP recording
      1. Obtain the orientation tuning of LFP signals.
      2. Present visual stimuli for LFP recordings (10° sine wave grating at 50% contrast), and pseudorandom sequences of gratings of varying orientation and spatial phase, each flashed for 32 ms.
      3. To analyze stimulus-evoked LFP responses, filter the recordings between 3 Hz and 100 Hz, and compute z scores by averaging responses across trials (for more detail, please see Figure 1 in Katzner et al. [2009]).

  4. Procedure for Determining Pinwheel Centers Accurately
    The following 3 steps ensure high accuracy of targeting PCs. (1) Identifying preliminary PC locations based on blood vessel maps. (2) Ensuring perpendicularity of electrodes. And (3) Selecting sites based on ‘non-sine-like’ LFPs.
    1. Preliminarily identify pinwheel centers based on surface blood vessel pattern aligned to the orientation map (see Figures 2A and 2B).
    2. Make electrode penetrations perpendicular to the cortical surface. To ensure that the electrode penetration is perpendicular to the cortical surface, extra effort must be expended (Figures 3A-3C). First, to ensure the camera’s angle is exactly perpendicular to the plane of the cortex, image a large field of view (e.g., 1 cm) with a narrow depth of field (~50 μm, front-to-front lens with f1.2 [Ratzlaff and Grinvald, 1991]). We then obtain α value of the declination angle (α, shown in Figure 3D). Adjusted the declination angle of clamping device (clamp electrode) in Narishige stereotaxic instrument (whose mechanical accuracy is about 10 µm), made it equaling to α value, to ensure the electrode parallels exactly the axis of optical imaging. Using this procedure, we have estimated that the deviation of electrodes from perpendicular is less than 2 deg (shown in Figure 3D).

      Figure 3. Illustration of electrode deviation from perpendicular. A. The yellow dots are the positions of 10 penetrations. Orange frame is the ROI (region of interest) in B. B. With the fine-tipped electrodes, there is a very little cortical deformation when the electrode is inserted. Scale bars in (A) and (B): 500 μm. C. We designed a lens (105-mm) with a close-up tube producing a working distance of 17 centimeters, which allows enough distance to make electrode penetrations obtaining images. D. The electrode was kept parallel to the optical axis by aligning the electrode at exactly the same angle as the CCD camera holder. The angle between the optical axis and the line perpendicular to the cortex (Δα) is Δα =actan (field_depth/field_length). As our depth of field is about 50 μm and the field of view is several millimeters, then we estimate Δα is less than 2 deg.

    3. Selecting sites based on ‘non-sine-like’ LFPs
      1. Make a penetration at or near presumed PC within the superficial layers (depth < 600 μm) and record the LFP orientation tuning curve and fit with sinewave function. Then calculate the non-sine-like index (NSI) of this sinewave. See Data analysis. Repeat this for several penetrations within the very local region (about 200-500 μm diameter area around the preliminary PC) until a non-sine-like LFP curve is obtained (NSI > 0.10). Explanation: Based on our recent work (Li et al., 2019), we demonstrated that true PCs have ‘non-sine like’ LFPs (NSI > 0.1), while locations away from PCs exhibit ‘sine-like’ LFPs (Li et al., 2019). Figures 4A and 4B shows a ‘false’ PC site. The recorded LFP orientation tuning curve (4A) is sine-like (NSI = 0) and several single unit recordings in this penetration (4B) have low orientation scatter (MOS = 18°). Figures 4C and 4D shows a ‘true’ PC site. The recorded LFP orientation tuning curve (4C) is non–sine-like (NSI = 0.34) and several single unit recordings (4D) have high orientation scatter (MOS = 65°), a consistent marker of PCs (Maldonado et al., 1997). Across 26 sites, we showed there is a strong positive relationship between NSI and MOS (shown in the Figure 1F in reference [Li et al., 2019]; when the NSI > 0.1, the MOS > 60°). Thus an LFP of NSI > 0.1 provides precise localization of the pinwheel center.

        Figure 4. Comparison of LFP and single unit recordings in true PC site and false PC site. A. Examples of the sine-like LFP orientation tuning at the false PC site (NSI = 0, highly sine-like). B. Single unit recordings (four neurons) in same penetration as A. The MOS among these cells is 18°. C. An example of the non-sine-like LFP orientation tuning curve at the true PC site (NSI = 0.34). D. Single unit recordings (four neurons) in the same penetration as C. The MOS among these cells is 65°.

      2. Record the position of the non-sine-like site. This is the first PC position (point 1 in Figure 2C).
      3. Repeat Steps D3a-D3b, and obtain an adjacent PC position (point 2 in Figure 2C).

  5. Procedure for Determining DP and DM Positions
    1. Determine domain point (DP) by calculating the geometric midpoint of the two PCs identified in Step D (see Figure 2C).
    2. Determine domain midway (DM) by calculating the geometric midpoint of PC and DP (see Figure 2C).
    Note: DM and DP are non-PC sites and both have sine-like LFPs.

  6. Proceed with Electrophysiological Study of Orientation Subdomains
    Once these key orientation domain anchors (PC, DP, DM) are determined, continue with electrophysiological characterization of orientation subdomains.

Data analysis

  1. Calculating NSI of an LFP curve
    1. Place the electrode, record a single unit and locate its receptive field. Determine the orientation tuning curve of the LFP at that site by presenting gratings at 8 orientations (see Figures 4A and 4C). Fit the LFP curve to a sine model. C0 denotes the LFP orientation tuning curve, which consists of K samplepoints, i.e., (x1, C0(x1)), (x2, C0(x2)),…, (xK, C0(xK)). The fitted curve is denoted by C'0.
    2. Calculate the fitting error(q0).
    3. Get the surrogate curves (C1 to C1000) by randomly shuffled the K sample-points of the LFP curve 1000 times and calutating the fitting errors of the surrogate curves (q1 to q1000).
    4. Calulate the NSI. The is defined as the p-value. It is ranged from 0 to 1, with 0 as highly sine-like and 1 as highly non-sine-like. The percentage of qj which is smaller than q0.

      Where n is the number of the qj values which are smaller than q0.


This work was supported by the Major State Research Program (2018YFB1305101, 2015AA020515, 2013CB 329401) and the Natural Science Foundation of China (81430010, 91420302, and 31627802).

Competing interests

The authors declare that they have no competing interests.


This study was performed in strict accordance with the recommendations contained in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health and approved by the Committee on the Ethics of Animal Experiments of the Shanghai Institute for Biological Sciences, Chinese Academy of Sciences (permit no. ERSIBS-621001C).


  1. Bonhoeffer, T. and Grinvald, A. (1991). Iso-orientation domains in cat visual cortex are arranged in pinwheel-like patterns. Nature 353(6343): 429-431. 
  2. Das, A. and Gilbert, C. D. (1999). Topography of contextual modulations mediated by short-rangeinteractions in primary visual cortex. Nature 399(17): 655-661.
  3. Hashemi-Nezhad, M. and Lyon, D. C. (2012). Orientation tuning of the suppressive extraclassical surround depends on intrinsic organization of V1. Cereb Cortex 22(2): 308-326.
  4. Hubel, D. H. and Wiesel, T. N. (1974). Sequence regularity and geometry of orientation columns in the monkey striate cortex. J Comp Neurol 158(3): 267-293.
  5. Katzner, S., Nauhaus, I., Benucci, A., Bonin, V., Ringach, D. L. and Carandini, M. (2009). Local origin of field potentials in visual cortex. Neuron 61(1): 35-41.
  6. Li, C. Y., Xu, X. Z. and Tigwell, D. (1995). A simple and comprehensive method for the construction, repair and recycling of single and double tungsten microelectrodes. J Neurosci Methods 57(2): 217-220.
  7. Li, M., Song, X. M., Xu, T., Hu, D., Roe, A. W. and Li, C. Y. (2019). Subdomains within orientation columns of primary visual cortex. Science Advances, eaaw0807.
  8. Maldonado, P. E., Godecke, I., Gray, C. M. and Bonhoeffer, T. (1997). Orientation selectivity in pinwheel centers in cat striate cortex. Science 276(5318): 1551-1555.
  9. Mariño, J., Schummers, J., Lyon, D. C., Schwabe, L., Beck, O., Wiesing, P., Obermayer, K. and Sur, M. (2005). Invariant computations in local cortical networks with balanced excitation and inhibition. Nat Neurosci 8(2): 194-201.
  10. Nauhaus, I., Benucci, A., Carandini, M. and Ringach, D. L. (2008). Neuronal selectivity and local map structure in visual cortex. Neuron 57(5): 673-679.
  11. Nauhaus, I. and Ringach, D. L. (2007). Precise alignment of micromachined electrode arrays with V1 functional maps. J Neurophysiol 97(5): 3781-3789.
  12. Ohki, K., Chung, S., Kara, P., Hubener, M., Bonhoeffer, T. and Reid, R. C. (2006). Highly ordered arrangement of single neurons in orientation pinwheels. Nature 442(7105): 925-928.
  13. Ratzlaff, E. H. and Grinvald, A. (1991). A tandem-lens epifluorescence macroscope: hundred-fold brightness advantage for wide-field imaging. J Neurosci Methods 36(2-3): 127-137.
  14. Song, X. M. and Li, C. Y. (2008). Contrast-dependent and contrast-independent spatial summation of primary visual cortical neurons of the cat. Cereb Cortex 18(2): 331-336.


[摘要 ] 在哺乳动物的视觉系统中,视觉形式感知的早期阶段始于初级视觉皮层(V1)中的定向选择性神经元,在许多物种(包括人,猴子,树rew,猫和雪貂)中,这些神经元都是有组织的在类似风车的方向柱中,要研究方向风车内的功能组织,精确定位风车子域非常重要,因此我们开发了一种技术来定量确定风车中心(PC)的位置。血管图像的皮质表面引导电极贯穿件电脑在定向图。然而,相当多的空间误差留守采用这种方法。在本研究中,我们改进了瞄准个人电脑通过确保垂直度电极和利用方向调节精度在光学确定的位置或附近记录的局部场电势(LFP)的变化。

[背景 ] 在视觉皮层内,定向风车(PC)是神经元定向偏好围绕其系统地移动的奇异中心。PC已成为关于大脑如何编码对象形状的不同方面(例如线性定向段,弯曲段)的许多研究的重点段,角和T型路口(Hubel和Wiesel,1974年; Das和Gilbert,1999年; Hashemi-Nezhad和Lyon,2012年)。单单元记录是研究方向风车内组织的最常用方法(Hubel和Wiesel, (1974年),但由于血管引导的微电极定位局限性和电极垂直度的不确定性(Nauhaus 和Ringach ,2007年),将微电极准确地对准风车中心(PC)颇具挑战性,Hashemi-Nezhad和Lyon (2012年)。)涂覆有使用的电极语来 很好地证明,电极是真正垂直;然而,基于脉管-方法仍然包含本地化error.Nauhaus和Ringach (2007) ,小心地用位置中的光学匹配在犹他州阵列电极位置成像的定向图,取得准确的PC定位,Ohki 等人(2006)报道,使用2光子方法,真正的PC直径仅为130µm,因此,这种方法几乎无法控制电极在取向域或风车中心内的位置。 强调了对高精度电极靶向的需求(另见Nauhaus 等,2008 )。

在这项研究中,我们开发了一种针对PC的高精度方法,该方法可通过以下步骤实现:(1)通过以窄景深(约50μm ,从前到前的镜头)成像大视野来确保垂直穿透用f1.2 (Ratzlaff and Grinvald ,1991 ),然后确保电极与光学成像轴精确平行。使用此过程,我们估计电极与垂直线的偏差小于2度(见图3D) (2)小心地定位电极以基于血管指导的个人电脑。(3)通过评估是否局部场电位(LFP)exhibit'non正弦状的回应。我们以前曾表明进一步确定所述精确PC中心(栗等人,2019)使用这种方法,即具有正弦样LFP响应且取向偏向性较小的穿透不是真正的PC位置,而具有非正弦样响应且取向偏向性较大的穿透(> 60度,Maldonado 等(1997 )。这是真正的PC位置。此额外的非正弦样准则对于高度准确地确定PC位置至关重要,并且提供了对方向子域组织的新理解(Li 等,2019)。这些详细过程如下所述。

关键字:方向功能区, 单微电极, 风车中心区, 局部场电位, 光学成像



玻璃钨微电极(阻抗:〜5MΩ;尖端直径:〜1μm ):
这些电极是自制的,有关电极构造程序的详细说明可以在以前的文章中找到(Li Et Al。,1995 )。简而言之,用钨丝(直径为200的Myuemu,上海的钨和钼)制备玻璃中的钨电极。产品公司,型号:S-EST6135)和毛细管玻璃(内径:0.3 毫米,外径:1 毫米,硼硅酸盐玻璃,上海玻璃厂,型号:SGW-95)。测量到的所需阻抗约为5MΩ(Ωmega -Tip-Z,世界精密仪器公司,美国),对应的钨尖端长度为〜10 µm,尖端直径为〜1 µm(图1)。

D:\ Reformatting \ 2020-4-7 \ 1902968--1421 Anna Roe 802564 \ Figs jpg \ Fig1.jpg

1图。照片的钨-在-玻璃微电极。1网格Mark是2.5 Myuemu图像显示了电极头长度的中〜10 Myuemu和末端直径为〜1 Myuemu。






神经数据采集系统(Blackrock Microsystems Inc.,Cerebus ,Cerebus 32)
摄像机(Andor Technology,Andor ,型号:iXon DU897)
镜头(尼康,尼克尔,D = 50毫米,f = 1.2)
视觉刺激发生器(剑桥研究系统有限公司,ViSaGe MKII)



Matlab(Mathworks ,ww2.mathworks.cn),并将matlab代码作为补充文件




术前用盐酸氯胺酮(30 mg / kg)麻醉猫,然后进行气管插管和静脉插管。 20毫克/千克/小时),麻痹(加拉明三乙10毫克/公斤/小时),和血糖和流体(葡萄糖200毫克/公斤/小时在林格氏溶液3米升/公斤/小时IV )。连续监测心脏速率,心电图,脑电图(EEG),呼气末CO 2 和直肠温度。当EEG表现为以睡眠梭形为特征的稳定的睡眠样状态时,麻醉被认为是足够的。包括角膜,眼睑和退缩反射定期进行测试。
在实验结束时,通过静脉注射过量的巴比妥酸盐(剂量为5 ml,6 %的巴比妥酸盐)处死动物。

使用绿光(546 nm)照明尽可能均匀地照亮皮质表面,获取血管图样的参考图像(见图2A)。
将照相机聚焦在〜400 微米的皮质的表面下方,并收集用红光照明(605纳米,最佳波长为血流动力学血氧饱和度信号)的光学图像。
获得方向偏好图,响应双目全屏高对比度(100%)正弦波光栅记录内在信号,主要的刺激包括漂移光栅,在两个方向上均以8个等距方向呈现(16每个刺激进行20次,持续9 s,然后间隔16 s,由Cambridge Systems VSG图形板产生视觉刺激,并在高分辨率监视器屏幕(40×30 cm)上显示刺激)在垂直方向上以100 Hz的频率刷新。以与刺激斑块相同的平均亮度(10 cd / m 2 )固定屏幕背景。显示器离动物的眼睛57厘米。
通过8个方向的像素逐像素矢量求和生成彩色编码的方向偏好图(图2B)(Bonhoeffer和Grinvald ,1991年)。在一些实验中,在16个等距方向(11.25 ° 间隔)处给出了漂移光栅。)。
仔细选择仅高度准确且可重现的地图,即首先从不同的试验子集生成地图,然后仅选择没有位移的地图(偏移不超过13-26 μ米风车中心),这些被认为是可接受的(马里ñ ö 等人,2005 )。

D:\ Reformatting \ 2020-4-7 \ 1902968--1421 Anna Roe 802564 \ Figs jpg \ Fig2.jpg

图2 ,高精度的定量测定PC位置。一个。血管模式的皮质表面,乙,颜色编码的方位图的皮质(A)。Ç 。两个相邻的风车中心(PC,位置1和2 )和方向域中的三个均匀间隔的插入点(DP,域点,位置3; DM,域中途,位置4和5)。八个刺激方向以22.5°的间隔进行颜色编码。 (B):500 微米。比例尺在(C):100 微米。


将电极插入并推进穿过皮质,并使用Cerebus 系统记录信号。
尖峰信号在250-7,500 Hz处进行带通滤波并以30 kHz采样。只有完全隔离的单元格才能满足单个单位记录的严格标准(动作电位的形状固定,并且在绝对不应期没有尖峰)选择并保存以供进一步分析。
LFP记录的当前视觉刺激(对比度为50%的10°正弦波光栅),以及方向和空间相位不同的光栅的伪随机序列,每次闪烁32 ms。
要分析刺激引起的LFP响应,请过滤3 Hz至100 Hz之间的记录,并通过平均各个试验的响应来计算z得分(更多详细信息,请参见Katzner 等人[ 2009 ]的图1 )。

以下3个步骤可确保针对PC的高精度:(1)根据血管图确定PC的初始位置;(2)确保电极的垂直度;以及(3)基于“非正弦” LFP的位置。

请确保电极贯穿垂直于皮质表面。为了确保电极渗透垂直于皮质表面,额外的努力必须消耗(图URES 3A -3 C).Firs 吨,以确保摄像机的角度为精确地垂直于平面皮层,图像的大视场(的例如,1cm)的与场的窄深度(〜50 微米,由前至前透镜与F1.2 [ 拉茨拉夫和格林瓦尔德,1991 ])。然后,我们得到α偏角值(α ,如图3D 所示)。调整了Narishige 立体定位仪(其机械精度约为10 µm)中的夹紧装置(夹紧电极)的偏角,使其等于α 值,以确保电极平行恰好光学imaging.Using此过程的轴线,我们估计,从电极的垂直偏差小于2度(图中所示的URE 3D)。

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3.插图图电极的背离垂直作者一个。黄点是10个穿凿的位置。橙色框是ROI(关注区域)的硼。硼。用细尖电极,有一个非常小的皮层。变形当电极插入比例尺在(A)和(B):500 Myuemu 。ç 。我们设计了一个镜头(105毫米),近距离管生产工作距离17厘米,这使得有足够的距离为了使电极穿透获得images.D 。电极被保持平行于光轴正好在相同的角度CCD照相机holder.The对准电极轴的光轴与线之间的夹角垂直于皮质(Δα )是Δα = actan (field_depth / field_length )。由于我们的景深约为50μm,并且视场为几毫米,因此我们估计Δα小于2度。


基于“非正弦” LFP选择站点。
在表层(深度< 600 Myu M )内的近似PC处或附近穿透,并记录LFP方向调整曲线并拟合正弦波函数,然后计算该正弦波的非正弦指数(NSI)。分析重复此操作在非常局部地区有几个穿凿(约200-500 MYU 中号直径周围区域初步PC),直到非类正弦曲线LFP得到(NSI> 0.10)。说明:根据我们最近的工作(李等人,2019 ),我们证明了真正的电脑有“非正弦像”个LFP(NSI> 0.1),虽然位置远离电脑展品“类正弦”个LFP (李等人,2019) 。图图4A 和图4 B显示了一个错误的PC站点。记录的LFP方向调谐曲线(4A)是正弦形(NSI = 0),并且该穿透(4B)中的几个单个单元记录的方向散射较低(MOS = 18度)。图小号4C 和4个d节目a'true” PC site.The记录LFP取向调谐曲线(图4C)是非正弦状(NSI = 0.34)和几个单独的单元 记录(4D)具有较高的方向散射(MOS = 65°),是PC的一致标记(Maldonado et al。,1997)。在26个站点中,我们发现NSI和MOS之间存在很强的正相关关系(如图所示)URE 1F在参考文献[ 李等人,2019 ];当NSI> 0.1时,MOS> 60°)因此NSI的LFP> 0.1提供了风车状中心的精确定位。

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4.对比图LFP和单一单位录音在真PC网站及假PC站点。阿。的类正弦LFP取向调整实施例在假PC站点(NSI = 0,高类正弦)。乙。单机记录(四神经元)相同渗透作为A的MOS在这些细胞中18 ° 。ç 。一个例子的非类正弦LFP取向的调谐曲线在真PC网站(NSI = 0.34)。d 。单机记录(四个神经元)的渗透率与C相同。这些细胞中的MOS为65 ° 。


重复步骤d 3 一- D3B ,并获得(在图2C中2点)相邻的PC的位置。



一旦确定了这些关键的定向域锚点(PC,DP,DM ),就可以继续进行定向子域的电生理表征。




放置电极,记录一个单位并定位其接收场,通过在8个方向上显示光栅来确定LFP在该位置的方向调谐曲线(见图4A和4C )。将LFP曲线拟合为正弦模型。ç 0 表示LFP取向的调谐曲线,其由k个Samplepoints ,即,(X 1 ,ç 0 (X 1 )),(X 2 ,ç 0 (X 2 )),..., (X ķ ,ç 0 (X ķ ))。拟合曲线被表示为通过C' 0 。
计算拟合误差(q 0 )。


获取替代曲线(c ^ 1 至ç 1000 通过随机洗牌的LFP曲线的K个样本点1000次,并)calutating 替代曲线(的拟合误差q 1 到q 1000 )。
Calulate 的NSI.The 被定义为p-value.It 为高度正弦状和1作为高度非正弦like.The百分比范围从0到1,其中0 q Ĵ 其是小于q 0 。

其中n是小于q 0 的q j个值的数量。




这项工作得到了国家重大研究计划(2018YFB1305101、2015AA020515、2013CB 329401)和中国自然科学基金(81430010、91420302和31627802)的支持。












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Copyright: © 2020 The Authors; exclusive licensee Bio-protocol LLC.
引用: Readers should cite both the Bio-protocol article and the original research article where this protocol was used:
  1. Song, X. M., Li, M., Xu, T., Hu, D. and Roe, A. W. (2020). Precise Targeting of Single Microelectrodes to Orientation Pinwheel Centers. Bio-protocol 10(11): e3643. DOI: 10.21769/BioProtoc.3643.
  2. Li, M., Song, X. M., Xu, T., Hu, D., Roe, A. W. and Li, C. Y. (2019). Subdomains within orientation columns of primary visual cortex. Science Advances, eaaw0807.