FMRI: what you need to know
How do you frame your message to nudge people towards a healthier lifestyle? Which USP is the most tempting? Functional magnetic resonance imaging (fMRI) might just provide the answer. This neuromarketing tool measures changes in the brain’s blood flow to visualize underlying processes of consumer behavior.
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The potential uses of fMRI are widespread: according to Hilke Plassmann, Associate Professor at INSEAD Business School, it can help brands select among different product designs or versions of an advertisement, understand how marketing campaigns affect consumers, and learn more about the tastes and biases of their target markets (Plassmann, 2016). This article provides a short introduction to fMRI: what it is, how it works, and when you should (not) opt for it.
Measuring blood flow
When fMRI was introduced in the early 1990s, it was a true revolution: the first safe, (relatively) non-invasive method to peek inside the human brain, pinpointing exactly where in the brain activity occurs. fMRI doesn’t measure neural activity itself, however: it detects changes in oxygenated blood flows in response to cognitive tasks, correlating to neural activity (Lee et al., 2017). This ‘blood-oxygen-level-dependent’ (BOLD) signal offers unique insights into which brain regions are activated. Researchers use fMRI data to address fundamental questions about the nature of consumer decision-making, consumer experiences, and value learning. These insights are used to complement explicit responses, to help companies understand both the conscious and the unconscious factors influencing consumer behavior.
fMRI is conducted using a large, cylindrical MRI machine, with a powerful magnet and radio waves. The subject removes all metal items and lies down on a table, which is slid headfirst into the device. He or she is given earplugs to mask the hammering sound of the MRI machine. As fMRI is very sensitive to movement, a brace helps to hold the head still, to avoid blurring the brain image. For each subject, some time is needed for calibration, to identify the subject’s specific brain areas.
When the test starts, the subject performs the allocated tasks using a button box to communicate responses, for instance, while comparing prices or product packages. During this process, activated brain regions call for more oxygen, causing an increased blood flow to a brain region, which is picked up by the machine’s magnets. Images of the brain are recorded slice by slice, each containing statistical data. This data is then processed by algorithms into a 3D representation. Active brain areas are typically represented in highlighted colors. A novice might think these are actual pictures of the brain, as these representations are extremely detailed, but that’s not the case – they’re only representations.
fMRI for marketing purposes
How can these brain representations help a marketer or brand? There isn’t always a single answer, as the activation of a brain area could mean many things. For instance, the primary function attributed to the insula is disgust, but the insula is also associated with positive emotions. Other regions of the brain do have more distinct functions, such as the nucleus accumbens and orbitofrontal cortex. These regions are associated with motivation and value, and play key roles in decision-making.
To draw any conclusion, scientists interpret data with the help of a neural network. This is a series of algorithms that tries to recognize underlying relationships in a set of data, through a process that mimics the functioning of the human brain. A neural network represents a combination of active brain areas that are proven (by peer-reviewed research) to represent a likelihood of emotions (like anger, fear, trust or desire), which leads to a prediction of the desired outcome (e.g. this outdoor ad will lead to more sales than the other).
Compare thousands of fMRI studies on Neurosynth
On the platform www.neurosynth.org you’ll find meta-analyses of thousands of published fMRI studies, covering over 200 distinct psychological concepts. The automated software combines related studies and synthesizes the results. Each study is tagged, so you can easily explore different terms. Try it for yourself, and find out why fMRI results can be so hard to interpret – simply search for the terms ‘happy’ and ‘disgust’.
Is fMRI expensive?
Renting a machine can be relatively expensive, with reported hourly rates ranging between $500 and $1000. Yet, Matthias Wirth, Managing Director of The Neuromarketing Labs, calls the idea that fMRI scans are expensive and take a long time a myth. “That was (maybe) true 10 years ago. Due to advances in technology, economies of scale and a steep learning curve, experienced providers can today present results within a week and tests can be conducted for less than 5000 euros.”
Other fMRI proponents argue that the costs are relatively low compared to the total cost of, say, a TV advertisement. They point out that, depending on the research design and questions, smaller sample sizes (of up to 30 subjects) may be sufficient, which brings down some of the costs (Dimoka, Pavlou, Venkatraman, 2015). Paul Pavlou, Chief Research Officer at Temple University, explains, “If you want to do things like segmentation, then you obviously need larger samples … but if you’re trying to make more general predictions, then essentially these [smaller, red.] sample sizes are sufficient, based on what we know from the neuroscience literature so far” (2015).
Another way to downsize costs is to run studies for multiple clients on one group of subjects, which saves preparation and calibration time per individual.
In contrast to EEG, fMRI offers a look deep inside the consumer's brain. It helps us better understand – and predict – consumer behavior. In fact, researchers of the ‘NeuroStandards 2.0’ project found that fMRI has better predictive powers than other neuromarketing techniques (Venkatraman et al., 2015). The study, which compared the effectiveness of six commonly used methods, showed that fMRI is indeed the best at predicting advertising success.
NeuroStandards 2.0 was not the first study to demonstrate fMRI’s predictive powers. In 2007, a team of scientists discovered that specific activation patterns of the brain could predict whether a consumer would or would not buy a box of chocolates (Knutson et al., 2007). In another study, researchers successfully predicted the popularity of new pop songs, by recording activity in the brains of teens listening to the music (Berns & Moore, 2012).
These examples show that fMRI is applicable to a wide range of studies – whether it’s predicting advertising success, forecasting chocolate sales, or predicting the popularity of pop songs.
When vs. where
As the BOLD response occurs with a delay of 2-5 seconds, fMRI can’t indicate exactly when activity happens in relation to the stimuli. It has a so-called ‘low temporal resolution’. In contrast, EEG offers a high temporal resolution – but it comes with a low spatial resolution (where exactly is this activity happening). We asked Dr. Roeland Dietvorst, Scientific Director at Alpha.One, one of the few companies offering both technologies as a market research instrument, in which situation fMRI has their preference over EEG. “Normally we use EEG for the measurement of dynamic stimuli, like video, TV shows, commercials, online user experience. In such cases, it is interesting to see the brain responding moment-to-moment. We use fMRI mainly for static stimuli, like packaging design, campaign slogans, pay-offs, outdoor messaging” (R. Dietvorst, personal communication, October 30, 2018).
We could argue that the best is yet to come, as fMRI has only been around for a few decades. The development of MRI machines is a continuous process, in which commercial manufacturers require R&D on the equipment and techniques to improve efficiency and reduced costs.
It is also likely that the issue with low temporal resolution will be solved in the future. Reiman et al. (2015) point out that “a possible solution to the temporal problem is to carefully create ‘digestible’ experimental stimuli” (p. 613). A researcher could design an experiment whereby changeable stimuli are presented separately, for one to two seconds each, to differentiate between the two at different time points (Reiman et al., 2015).
An alternative solution would be to combine fMRI with EEG. According to Rumpf and Breuer (2016), “leading researchers in neuroscience already make use of an integrated approach where fMRI (due to its high spatial resolution) and EEG (due to its high temporal resolution) are recorded simultaneously to achieve both a high spatial and temporal resolution” (pp. 12-13).
Prof. Gemma Calvert, Nanyang Business School
Dr. Roeland Dietvorst, Alpha.One
Armin Junge, incore GmbH
Michelle Niedziela, PhD, HCD Research
Dr. Enrique Strelow, Ferrero
Matthias Wirth, The Neuromarketing Labs
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