Banding patterns of muscle proteins from different fish species on a gel (Photo courtesy of Bio-Rad Laboratories, Inc.)

Are scientists rational to doctor images?

One common and alarming form of image doctoring occurs within scientific scholarly articles. The practice has become so common that image check guidelines are part of the review process, e.g. image authentication adds 30min for each submission to the Journal of Cell Biology (Young, 2008). Interestingly, sometimes scientists are not trying to fabricate results, so much as try to clear up their images, to make them less blurry. This is particularly true for images of gels — ways to detect proteins or other molecules in a sample. Linda Miller, U.S. Executive Editor, Nature & Nature journals (2005–2010), issued a statement that “We like dirt — not all gels run perfectly…Beautification is not necessary. If your data is solid, it shines through”(Young, 2008).

What is interesting about Miller’s claim is that psychologists have shown experimentally that features such as blurriness affect visual fluency, thus the degree to which a person judges a stimulus to be true (Shah & Oppenheimer, 2007). The concept of visual fluency is based on the principle that any visual stimulus requires cognitive work to process. The amount of cognitive work is reflected in the speed and accuracy of visual processing as well as in the subjective experience of ease or difficulty of visual judgments (Jacoby, Kelley, & Dywan, 1989; Winkielman et al., 2000). Visual fluency research makes it rational for scientists to want to present their data as beautifully, cleanly and easy to process as possible, because difficulty to process visual information downgrades its evidential value.

But, of course, whether it is rational to want to present data beautifully and visually fluent is beside the point of whether it is ethical or desirable to do so. To manage the pros and cons of image manipulation, prominent scientific journals, such as Nature, now have complex requirements for images (Nature Publishing Group, 2015). Edits that offer clarity or brevity are allowed, such as change of contrast and cropping. Such changes are allowed so long as alterations are applied to all images and all modifications explicitly acknowledged in the work.

There are still areas of ambiguity however. One stipulation of Nature is that contrast should not be altered so much that data disappears. However, it is possible that what is or what is not considered data in an image may be revisited in some future date under a new theoretical understanding of the content of images. Although journals require original images to be stored and available for future scrutiny, it is more likely that images will play an evidential role based on the published, manipulated version, rather than any undoctored image stored remotely and inaccessibly from the viewer.

In conclusion, while many forms of scientific image manipulation seem harmless based on current best theory, there is the risk that systematic image doctoring by scientists obfuscates information that could be data in some future scientific context.


Jacoby, L. L., Kelley, C. M., & Dywan, J. (1989). Memory attributions. In H. L. Roediger & F. I. M. Craik (Eds.), Varieties of memory and consciousness: Essays in honour of Endel Tulving (pp. 391–422). Hillsdale, NJ: Erlbaum.

Nature Publishing Group (2015) . Image integrity. Retrieved 26 September 2015 from

Shah, A. K., & Oppenheimer, D. M. (2007). Easy does it: The role of fluency in cue weighting. Judgment and Decision Making, 2(6), 371–379.

Winkielman, P., Schwarz, N., Reber, R., & Fazendeiro, T. (2003). Cognitive and affective consequences of visual fluency: When seeing is easy on the mind. In R. Baatra & L. Scott (Eds.), Persuasive imagery: A consumer response perspective. (pp. 75–89). Mahwah, NJ: Lawrence Erlbaum

Young, J. R. (2008, May 29). Journals find fakery in many images submitted to support research. Chronicle of Higher Education. Retrieved from