认知神经科学英文写作经验—图片，图注，文献引用， 公式，统计报告，补充材料 (3)

从格式上搭好架构之后，我们需要往里填充内容，但是在聚焦在内容之前，我希望对于论文中的其他方面的格式习惯进一步进行标准化，与之前一样，做到以下这些方面几乎不需要英语知识，任何一个研究生都能完成。

图片

• 图片和图注在写作过程中直接插入文章，不要放在正文最后。

• 分清图注(caption)和图例(legend)。图注是每个图片下面那段解释的话，图例是一个图中表示不同颜色的线或者柱是什么意思。

• 画图能用代码画图就不要用手动点击。请尽量用matlab或者python的代码出图，不推荐用excel或者origin之类的软件画图，因为图要反复修改手动会让你改到吐而且容易出错。

• 请为每一张图单独保存一张代码文件和pdf图片放在同一个文件夹里以方便修改，比如Figure4.m, Figure4.py.

• 所有从matlab或者python导出的图片请存成pdf矢量图格式，以能在illustrator里面打开编辑和保存为准。

• 所有图片记得去掉四周空白边，紧凑布局。

• 所有图片的背景底色全部设置为透明，不要白色。

• 图片里面所有文字数字(e.g., 坐标尺度，横纵坐标标签)请用Arial字体, 公式因为用latex除外。

• 每个subplot要有A,B,C..标识，标在每个子图的左上角。这些子图表示上下左右要互相对齐。

• 请检查每个subplot里面

  • 横纵坐标以及标度数字是否看的清楚。
  • 横纵坐标名称，单位。
  • 图例(legend是不是表达清楚，比如包括被试数)。
  • 思考这个图需要error bar么，如果需要已经加上了么？

• 图片在正文中的引用格式为 Fig. 4A (注意是Fig + . + 空格 + 4A ), Fig. 4A&B, Fig. 4A-C

• 颜色选取

  • 在看的清楚的条件下能用黑白就不要用彩色。
  • 同一个实验条件/一组被试在同一篇文章的不同图中尽量保持一个颜色。
  • 请仔细思考一个子图里面的颜色是不是和其他子图以及文章中其他图协调。

图注

• 图注是图片下面一段解释语言。

• 图注整体左右各缩进两格，单倍行距(注意正文是1.5倍行距)，字体字号和正文一样。

• 图注的开头用，Figure 1. 不能用缩写Fig. 5.

• 图注的标题加粗，比如以下的 Visual working memory performance in SZ and HC。也可以没有标题

• 图注中针对不同subplot, 可以用 A. (字母斜体加粗，点加粗)来分开介绍。

• 图注中提到不同的子图，可以用panel A或者subplot A来指代，比如

  The shaded areas in panel A and all error bars in panels B and C represent ±SEM across subjects.

  SZ have larger resource allocation variability than HC (panel B).

• 图例中要有对error bar或者其他data variability的解释，比如

  The shaded areas in panel A and all error bars in panels B and C represent ±SEM across subjects.

• 图注中要有对显著符号的解释，比如

  Significance symbol conventions are *: p < 0.05; **: p < 0.05; ***: p < 0.001; n.s.: non-significant.

这里提供1个例子，详情请见papertemplate

Example

Figure 5. Schematic illustrations (A,C), predictions (B,D) and empirical results (E,F) for component- dependent and pattern-dependent VPL. A. The component-dependent VPL takes place at the lowest level of motion processing, as indicated by the red rectangle. Here, training on a component stimulus should only transfer to the plaid stimulus that comprises the trained component. Moreover, training on a plaid stimulus should only transfer to its two constituent components. B. Learning effects as predicted by component- dependent learning in panel A. C,D. Illustrations of the pattern-dependent perceptual learning and its predicted learning effects, following conventions in panels A and B. Here, plasticity involves the middle stage of motion processing. E. Duration thresholds at pre-/post-test across stimulus conditions in the component (left panel) and the plaid training (right panel), respectively. F. Learning effects quantified as percent of improvement (PI%) across stimulus conditions and training regimes. The overall pattern mimics the predictions in panel D, indicating plasticity associated with the middle-level of motion analysis. For all subplots, error bars denote ± 1 SEM across subjects. Significance symbol conventions are *p < 0.05; **p < 0.01; ***p < 0.001; n.s.: non- significant. Same definitions of error bars and symbol conventions are kept for all figures in this paper.

文献引用

• 在Word里面插入文献一律用Endnote。注意文献管理软件可以根据任意个人喜好选择其他软件，但是写论文插入文献的时候一律用Endnote。一般可以从比如readcube/mendeley/zotero选择文献之后导入到Endnote。

• 每写一篇论文，请单独创建一个.enl或者.enlp的Endnote library文件，并和论文的word文件放在同一个文件夹。

• 确定期刊后，查阅期刊的文献格式要求。

• 用Endnote的时候，在正文内的引用，请加上对后面文献的超链接和下划线，可以在word的Endnote插件里面设置。例如

  Imaging scientists often use multivariate pattern analysis (MVPA) to assess the accuracy of population codes (Tong and Pratte, 2012; Haxby et al., 2014).

• 正文中直接引文格式和author+year的格式。点击原有的以插入的文献，right click the citation — Edit Citations — Display as : Author (Year)

  For example, the seminal study by Zohary et al. (1994) demonstrated that TCNCs limit the amount of information in a neural population.

• 有些官网下载的Endnote style (i.e., .ens文件) 并不好用，请仔细检查正文后在Endnote软件里修改原有的style。

• 有时候Endnote里面对期刊的第一缩写或者第二缩写并不对，请手动修改。

公式

• 请利用在线latex公式生成网站比如 https://www.codecogs.com/latex/eqneditor.php，不要用自带的公式编辑器。
• 用latex语言在线编辑好公式之后，请选择svg (i.e., 矢量图)格式下载，然后直接拖曳进word文档。
• 每一个公式，写出了之后要紧接着解释公式中不常见的运算符号以及所有变量的意义。

统计报告

在描述结果的时候经常要报告统计结果，有这样几个注意事项

• 所有数值(F value, t value, r value, p value, etc)，保留小数点后三位。
• P value尽量写出实际数值，而不是简单的p < 0.05，当数值实在太小很难写出时用p < 0.001。
• 注意变量符号数字之间的空格，比如 p = 0.032. p, =, 和0.032之间分别用空格隔开。不要用 p= 0.032, p =0.032, 或者p=0.032.

这里就t-test，correlation和ANOVA三种最常见的统计报告形式，其中重点讲解ANOVA的表达方法。

• ttest (报告t 值以及自由度，p value，和effect size, cohen'd value)

  A is significant higher than B (t(30) = 1.752, p = 0.032, d = 0.324).

• Correlation (报告r 值 和 p 值)

  There is a significant correlation between A and B (r = 0.235, p = 0.132).

• ANOVA , 关于ANOVA，我们首先要报告这样几个要素，

  • anova的设置。比如因变量是什么，组内自变量是什么，组间自变量是什么，协变量(如果有的话)是什么
  • 按照先主效应后交互作用的顺序，报告所有可能的主效应和交互作用。在具体报告主效应时，可以优先报告和主旨相关的主效应，交互作用同理。有些不重要的，可以放入补充材料(SI)里面。
  • 每一个主效应和交互作用，无论是否显著，要报告，F 值，自由度，p 值，还有Eta square value。
  • 每一个显著的主效应，要报告显著的方向，比如A is significantly larger/smaller than B，不能简单的说A is significantly different from B.
  • 每一个显著的交互作用，还要报告交互作用的方向，比如说明在A情况下，X大于Y; 但是在B情况下，X小于Y。
  • ANOVA的事后检验，要报告多重矫正的设置和方法以及p值，在SPSS里面有Bonferroni，Sidak, no correction三者可选.

• 下面提供两个例子

Example 1:

A 2*2*2*8*2 ANOVA was performed with group (action/control) as a between-subject factor; test (pre/post2), run (first/second), external noise level (eight levels), and performance level (79.37% and 70.71%) as within- subject factors; and log signal contrast threshold as the de- pendent variable. The interaction between test (pre/post2) and group (action/control) was significant and in the predicted direction (F(1,14) = 3.25, P = 0.02, η²= 0.29), indicating that action trainees continued to show improved performance in the task months to a year after training.

Example 2:

Data were analysed with a 3 × 2 × 2 MANCOVA, with training group (control, AVG, MAT) and nystagmus as a between-subjects factor and eccentricity (12° and 25°) as a within-subjects factor. The main effect of training group was statistically reliable (F(2,14) = 4.14, p = 0.039; η² = 0.63). Pairwise comparisons revealed significantly better performance in the MAT group relative to the control group (p = 0.045, Bonferroni corrected), with no significant differences between AVG and control groups (p = 0.30) and between MAT and AVG groups (p = 0.43). The main effect of nystagmus was not significant (F(1,14) = 0.33, p = 0.58, η² = 0.08). Also, we noted a strong interaction of training and eccentricity (F(2,19) = 9.34, p = 0.004; η² = 0.94). Pairwise comparisons revealed no significant differences between control and experimental groups at near periphery (AVG, p = 0.82; MAT, p = 0.47) but significant differences at far periphery (AVG, p = 0.032; MAT, p = 0.002, Bonferroni corrected).

补充材料

补充材料一般分为title page，补充notes内容，和references。主要格式有以下规则。

• 行距1.5倍，字体字号，标记行数页码数，公式，图片，图注，文献引用等除非特殊说明一律和正文相同。

• 不一样的是，图片图注标记引用为Figure S1. Fig. S1. 公式标记引用为(S1), Eq. S1. 例如:

  # 图注

  Figure S1. A is a function of B.

  # 公式

  $a + b = c \tag{S1}$

  # 图片和公式在主文和补充材料里面的引用

  We observe a strong effect of A in Fig. S1A&B.

  Eq. S1 shows the linear relationship between A and B.

• 请查阅期刊补充材料的称谓，常见的有supplimentary/supplemental information/materials/appendix. 如果称谓错误编辑有可能会打回修改。

• 在主文中对补充材料的引用，例如:

  We used a strict criteria for new subjects (see details in Supplimentary Note 4).

补充材料title page

补充材料的title page一般包括论文title，authors，table of content，格式(请注意大小写加粗下划线对齐等)例如:

SUPPLEMENTAl INFORMATION for

Pratical tips of academic writing in cognitive neuroscience for Chinese young researchers

San Zhang, Si Li, Wu Wang

 

Table of Contents

Supplemental Note 1: Dual N-back working memory learning task

Supplemental Note 2: Procedures of Study 1, Cross-Sectional Study

Supplemental Note 3: Procedures of Study 2, Training Study

补充材料正文

补充材料一般以比如Supplimental Note XX 等为题目，格式(请注意下面大小写加粗下划线对齐等)例如

Supplemental Note 1: Dual N-back Working Memory Learning Task

The three studies used the same dual N-back working memory task albeit slightly different training procedures. We thus document the task details as follows.

......

Supplemental Note 2: Experimental procedures of Study 1, cross-sectional study

The three studies (i.e., cross-sectional study, training study, and replication study) used the same dual N-back working memory task albeit slightly different training procedures. We thus document the task details as follows.