Making Figures That Illuminate Discoveries

[Daisy Gallardo]

As I prepare my figures for the upcoming Neuroscience 2024 conference, I found the SfN Neuronline webinar, “Making Figures That Illuminate Discoveries,” incredibly helpful. In the session, Jennie Vallis, Lead Illustrator for Nature Reviews Neuroscience, and Curtis Neveu, PhD, Senior Research Scientist at McGovern Medical School, shared their valuable insights on effective figure making. Vallis explained how she and her team rework the illustrations, diagrams and graphs that are submitted to Nature Reviews Neuroscience to make them clearer for the reader.  

Vallis emphasized the importance of composition and hierarchy in guiding the reader's attention. She recommended arranging figure components from top to bottom and left to right. This organization follows natural eye movement, making it easier for the audience to read. The reader’s focus is guided to the most important elements by placing them at the top. Color is another tool that Vallis mentioned for establishing hierarchy in figures. Light, neutral colors can be used for elements that don’t need to stand out, such as the outline of cells or organs. Using colors for key items introduces a subtle contrast that easily focuses the audience’s attention. For example, in a figure representing a cellular pathway, she used red to emphasize the most crucial component and placed it in the center. Typically, Vallis does not use more than five colors in a figure. If needed, she uses different shades of the same hue. This approach makes the figure clearer and less overwhelming. 

Vallis recommended simplifying and separating elements to increase clarity. She stated figures should be concise and consistent. For example, in a pathway the labels for proteins can be within a box with rounded edges, while the labels for a gene can be within a square. For additional details you can add “call-out” boxes, similar to a speech bubble. The different styles of boxes within the same group can be made the same color, to maintain consistency, but can be differentiated by tone. For effective data visualization, Vallis advised, “Resist the urge to decorate your data.” If it isn’t necessary, don't add patterns or make your graphs 3D. Some graphs fit the data better than others. For example, if your pie chart has too many segments then it may be better as a horizontal bar chart. Additionally, she provided these resources for improving data visualization: https://datavizcatalogue.com/, https://datavizproject.com/ and the Information Is Beautiful book. 

The differences between the subtractive Cyan-Magenta-Yellow-Black (CMYK) and additive Red-Green-Blue (RGB) color models were clarified in this webinar. Vallis explained the color model, CMYK, subtracts red, green and blue from the white background. The CMYK model is best for color printing. Because of this, Vallis noted, Nature Reviews Neuroscience uses CMYK due to their primary mode of publication being print. For digital media, the RGB model is used as it adds light in different intensities to produce colors. In comparison to RGB, the CMYK model displays duller and more opaque colors. Vallis explained that this distinction between CMYK and RGB models causes fluorescent images to appear differently when published in Nature Reviews Neuroscience compared to how they looked when originally submitted.

To improve figure quality and accessibility, Vallis provided various resources. She mentioned that, although there are many types of color blindness, Adobe Illustrator allows you to change your view to simulate how someone with the two most common types of color blindness would see the image. Generally, replacing red and green with red and blue will make your figure more accessible. Additionally, Vallis recommended using tools like the color contrast checker (https://accessibleweb.com/color-contrast-checker/) and the color blindness simulator (https://colororacle.org/index.html) to further ensure image accessibility.