Assignment 5, Part A: Individual Explanation of Imagination and Creativity
For EME 6646: Learning, Instructional Design, and Cognitive Neuroscience
By Richard Thripp
University of Central Florida
June 15, 2017
Measuring Creativity: Neuroimaging or Psychometrics?
When researchers using neuroimaging techniques seek to compare brain activity between people who are especially creative and people who are of average creativity, how do they do so? One might think this would be accomplished by using neuroimaging techniques to determine who is more creative. However, the pretty pictures of brain activity we see in many journal articles are actually the result of averaging and subtraction (Sawyer, 2011). In truth, most of the brain is active almost all the time—what we are really looking at is whether particular regions are comparatively less or more active than others, and this difference is often only 3% if we are lucky (Sawyer, 2011). Brain scans where certain “creative” regions of the brain are shown in bright red may lead the reader astray, not suggesting such a tiny differential in brain activity.
Perhaps because our current ability to measure actual brain activity is not a useful indicator of creativity, neuroimaging cannot yet be directly used to determine an individual’s level of creativity. Thus, even studies employing neuroimaging typically fall back on psychometric measures. For example, Jaušovec (2000) empirical investigation is titled “Differences in cognitive processes between gifted, intelligent, creative, and average individuals while solving complex problems: An EEG study” (p. 213). At first glance, one might think electroencephalogram (EEG) is being used to determine whether someone fits into the four categories of “gifted,” “intelligent,” “creative,” or “average.” However, Jaušovec actually used the Weschler Adult Intelligence Scale (WAIS or “IQ test”) and the Torrance Test of Creative Thinking (TTCT) to organize participants into these categories, defining “gifted” as doing well on both tests, “average” as not doing well on either, and the other categories as doing well on one test but not the other. Then, he found minor differences in EEG readings when participants solved open- or closed-problem tasks, and concluded that intelligence and creativity are probably different, and that patterns of brain activity are related to creativity and intelligence. Knowing that even the best psychometric tests have substantial measurement error (e.g., IQ tests measure not only intelligence, but familiarity with written language and academic environments), that grouping people as Jaušovec (2000) did introduces further error (I have reproduced his grouping table below), and that EEG itself lacks spatial resolution, Jaušovec’s methods seem so muddy as to be unfit to produce any conclusions. However, it is not as though I have cherry-picked an unknown, dubious study—according to Google Scholar his article has an impressive 239 citations! With recent arguments further suggesting that EEG’s temporal resolution is overblown (Burle et al., 2015), our confidence ability to draw conclusions diminishes further.
Figure 1. Grouping table for intelligence and creativity categories by Jaušovec (2000).
While EEG is not in the same vein of neuroimaging as magnetic-resonance imaging (MRI), near-infrared spectroscopy (NIRS), or positron emission tomography (PET), the use of psychometrics as an organizing device, and of subtractive averaging as a method to present pretty pictures implying big results, remain applicable. I have difficulty seeing the ethical differences between subtractive averaging and removing the zero axis on a bar chart to show bars of vastly different heights that would otherwise have been only slightly different.
Neuroimaging and Psychometrics in Creativity Research: A Corroboration Model
Psychometrics, the science of mental measurement, by definition is messy and imprecise. However, corroborating psychometric instruments with neuroimaging techniques may help us more accurately understand creativity. This is what Arden, Chavez, Grazioplene, and Jung (2010) advocate in their literature review and position piece on neuroimaging creativity. Researchers are all using different criteria to measure and interpret creativity, but there has been no concerted effort toward detailing the “psychometric properties of creative cognition” (Arden et al., 2010, p. 152), which is needed to be able to compare studies to each other. Nevertheless, employing neuroimaging has already allowed us to debunk, or at least fail to find support for, common hypotheses such as creativity being linked to the right brain or improved neural function (Arden et al., 2010). If we continue to improve the reliability and validity of creativity research along both psychometric and neuroimaging dimensions, we will improve our limited understanding of creativity, which is particularly needed areas such as novelty and originality (Fink, Benedek, Grabner, Staudt, & Neubauer, 2007). Limited spatial resolution prevents us from accurately isolating brain activity, while at the same time, the prevailing paradigm of neuroscience creativity research remains oriented toward finding the specific areas of the brain are associated with creativity (Arden et al., 2010; Sawyer, 2011), while the correct answer may be that all of them are—although some more so than others. Modern techniques as reviewed by Jung, Mead, Carrasco, and Flores (2013), such as structural magnetic-resonance imaging (sMRI), diffusion tensor imaging (DTI), and proton magnetic resonance spectroscopy (1H-MRS) are critical to isolating the structural characteristics of creative cognition, and might be seen as a complement, rather than a replacement, to the proxy measures that psychometrics constitute. Finally, lesion studies reveal that areas of the brain may actually compete in parallel to reach creative solutions, with the right medial prefrontal cortex (mPFC) winning out in healthy subjects, even though it produces inferior results (Jung et al., 2013). When corroborated with psychometric measures, this may lead us to an amusing finding whereby high creativity might be associated with brain problems (i.e., lesions in the left language errors).
Methodological Issues in Neuroscience-Based Creativity Research
Even recent creativity research is often devoid of neuroimaging. For example, Anderson, Potočnik, and Zhou’s (2014) “Innovation and creativity in organizations: A state-of-the-science review, prospective, commentary, and guiding framework,” published in Journal of Management and focused on 2002–2013 research, defines creativity as “idea generation” and looks at studies that solely use observational and self-report data. In an organizational context, it is still unheard of to use MRI, DTI, 1H-MRS, et cetera, and even EEG is rare. Moreover, the research corpus itself is scattered and disjointed (Batey & Furnham, 2006). Consequently, sound methods are even more important for the few researchers who are able to use neuroimaging methods.
A big issue exemplified in Jaušovec (2000), and reiterated by Arden et al. (2010), are case-control designs whereby subjects are unnecessarily dichotomized into high- and low-creativity buckets, instead of respecting the continuous nature of creativity. Even psychometric measures such as Torrance tests do not classify people in binary, but rather across a range of scores. Respecting this continuity can improve statistical power.
Using expensive and cumbersome technologies such as PET or fMRI requires lying down, perfectly still, with loud whirring noises (Sawyer, 2011). Even EEG requires electrodes attached to one’s head, which impairs many creative activities. Methodologically, this is a large problem that is presently not surmountable. There is no way to measure creativity with an fMRI while a subject plays a violin (except, perhaps, a pizzicato performance). Moreover, neuroimaging studies do not measure novelty or usefulness, unlike common definitions of creativity used by non-neuroscience researchers (Sawyer, 2011).
Lastly, although there are many other methodological issues, neuroscience creativity research would be furthered by accurate reporting and disclosure of averaging, subtraction techniques, and the actual activation levels that were observed temporally and/or spatially (Sawyer, 2011). Speculation about causation should be clearly marked as such. Finally, researchers should refrain from labeling a region of the brain as a center for any specific creative task, or for creativity in general (Arden et al., 2010). Even though it generates popular press, such determinations are typically inaccurate.
Anderson, N., Potočnik, K., & Zhou, J. (2014). Innovation and creativity in organizations: A state-of-the-science review, perspective, commentary, and guiding framework. Journal of Management, 40, 1297–1333. http://doi.org/10.1177/0149206314527128
Arden, R., Chavez, R. S., Grazioplene, R., & Jung, R. E. (2010). Neuroimaging creativity: A psychometric view. Behavioural Brain Research, 214, 143–156. http://doi.org/10.1016/j.bbr.2010.05.015
Batey, M., & Furnham, A. (2006). Creativity, intelligence, and personality: A critical review of the scattered literature. Genetic, Social, and General Psychology Monographs, 132, 355–429. http://doi.org/10.3200/MONO.132.4.355-430
Burle, B., Spieser, L., Roger, C., Casini, L., Hasbroucq, T., & Vidal, F. (2015). Spatial and temporal resolutions of EEG: Is it really black and white? A scalp current density view. International Journal of Psychophysiology, 97, 210–220. http://doi.org/10.1016/j.ijpsycho.2015.05.004
Fink, A., Benedek, M., Grabner, R. H., Staudt, B., & Neubauer, A. C. (2007). Creativity meets neuroscience: Experimental tasks for the neuroscientific study of creative thinking. Methods, 42, 68–76. http://doi.org/10.1016/j.ymeth.2006.12.001
Jaušovec, N. (2000). Differences in cognitive processes between gifted, intelligent, creative, and average individuals while solving complex problems: An EEG study. Intelligence, 28, 213–237. http://doi.org/10.1016/S0160-2896(00)00037-4
Jung, R. E., Mead, B. S., Carrasco, J., & Flores, R. A. (2013). The structure of creative cognition in the human brain. Frontiers in Human Neuroscience, 7, 1–13. http://doi.org/10.3389/fnhum.2013.00330
Sawyer, K. (2011). The cognitive neuroscience of creativity: A critical review. Creativity Research Journal, 23, 137–154. http://doi.org/10.1080/10400419.2011.571191