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Neuroscience in branding: A functional magnetic resonance imaging study on brands’ implicit and explicit impressions

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Abstract

Although the use of neuroscientific knowledge to investigate marketing issues has been widely discussed, to date, few empirical studies have been published. This study is a first approach in the development of a theory of the perception of brands, which is based on neuroscience. In a Functional Magnetic Resonance Imaging experiment, we stimulated participants with commercial brands’ logos, with and without explicit instructions on how to assess them, in an attempt to capture the real-life experience of evaluating brands. We found common activations in both situations in the medial frontal pole, the paracingulate gyrus, the frontal orbital cortex, the frontal medial cortex, and in the hippocampus. In a general scheme of brands’ perception, we hypothesised a relationship between Theory of Mind and meta-representations, in particular self-reflexive ones: ‘I think about what others are thinking about me’. We suggest that brands have an important social dimension. Brands may function like a social currency, which every individual uses to assess others, and which others are expected to use in their assessments of the individual. Brands are most probably social tools.

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Authors and Affiliations

  1. ISMAI – Superior Institute of Maia, Av. Carlos Oliveira Campos – Castêlo da Maia, Avioso S. Pedro, 4475-690, Portugal

    José Paulo Santos, Daniela Seixas, Sofia Brandão & Luiz Moutinho

Authors
  1. José Paulo Santos
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  2. Daniela Seixas
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  3. Sofia Brandão
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  4. Luiz Moutinho
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Corresponding author

Correspondence to José Paulo Santos.

Additional information

1recently completed the PhD programme from the Institute of Economy and Management, Technical University of Lisbon, Portugal, with the theme Neuroscience in Branding. He has 15 years of professional experience in industrial management, focusing on business-to-business brands, and, more recently, end-customer brands. Also, Santos researches at Socius, focusing on consumer behaviour. His research interests include Social Neuroscience and associated neuroscientific techniques as fMRI and fNIRS, sociology of brands, Symbolic Interactionism, and self-concept drive by brands.

2has a primary degree in medicine, and is currently a neuroradiologist at São João Hospital, Portugal. She is also a PhD student at the Faculty of Medicine of the University of Porto, in collaboration with the Pain Imaging Neuroscience Group, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), University of Oxford, United Kingdom. Seixas's main research interests are neuroimaging techniques applied to neuroscience research: she is at present studying pain in neurological diseases using DTI and fMRI, and also collaborating in neuromarketing research. She has published a recent review on ethics in fMRI studies.

3completed her BD in Radiology from the Superior School of Health Technologies of Porto, Porto, Portugal and is currently pursuing an MD on Biomedical Engineering, and another MD on Medical Informatics, at the Faculty of Medicine of the University of Porto. Her thesis focuses on segmentation of deep grey nuclei using SPM5 software tools. Brandão has been working since 1999 at the São João Hospital, in the Resonance Magnetic Unit. She is also a lecturer in the Imagiology area. She has several published papers in medical and technical conferences. Her research interests include Resonance Magnetic techniques.

APPENDIX

APPENDIX

This section is intended to give a basic knowledge in order to interpret the results and conclusions in this article correctly. We recommend complementary readings that focus on some important aspects on this technique so that deeper understanding may be achieved (Jezzard et al, 2001; Huettel et al, 2004).

What is measured in fMRI?

The last word in fMRI, imaging, means that this technique delivers mainly images. In this article, the figures of brain images included are used to report the results. In fact, these pictures are not like common photos; they result from the overlaying of two distinct images. The one that lies below is the anatomic and is an image of the physical brain, that is, its biological tissues. It is acquired using a T1-weighted MPRAGE protocol (see Methods section) and is finely detailed. The side of a pixel is usually around 1 mm (in the present study it is 0.75 mm). The image that is above corresponds to the first letter of fMRI: functional. This image represents the blood-oxygen-level-dependent (BOLD) signal, is acquired at a different stage (although usually within the same session) using a T2*-weighted EPI sequence (see Methods section), and it is not as detailed as the anatomical; usually the side of the pixels is around 3 mm (as in the present study).

The purpose of the anatomical image is to indicate the place in the brain to which the functional data belongs. As the brain is anatomically divided, it is then possible to assign a certain function to a specific brain region. However, this matter is not consensual and there is enough evidence that the functional organisation does not coincide with the anatomical division (Tong, 2011). In any case, naming structures in the brain where there is activity helps in communicating the findings among the scientific community.

The BOLD signal, the essence of fMRI technique, is far from being understood (Logothetis, 2008). It is believed that it indirectly represents the neural activity. Supposedly, the BOLD signal is generated when oxyhaemoglobin molecules in red blood cells release oxygen, transforming into deoxyhaemoglobin. The former molecule is diamagnetic, whereas the latter is paramagnetic. This distinct magnetic behaviour is detectable and measurable in magnetic resonance scanners and constitutes the core of the T2*-weighted EPI (functional) acquisitions.

Thus, in fMRI, perturbations in the magnetic field that occur when oxyhaemoglobin liberates oxygen are the target of measurement. This is an indirect assessment of neuronal activity. Supposedly, the consumption of glucose and oxygen increases through the delivery of energy when neurons are recruited for a cognitive process, and promotes the chemical reaction that transforms oxyhaemoglobin in a paramagnetic compound (deoxyhaemoglobin). All this process has a magnetic imprint that is measurable.

This means that absolute quantifications of neuronal activity in fMRI are neither practical nor useful. If the purpose of the study is to realise whether a certain brain region participates or not in a process, it has to be put in two (at least) different stages of oxygen consumption (activation and resting state). It is the contrast between these two stages that will allow the computation of the differences between image signal intensities, supposedly proportional to active neuronal performance. Activated brain areas will show signal intensity variations, whereas non-requested areas will not have fMRI-detectable hemodynamic changes. Moreover, when two stages are compared, if the signal in the stage of interest is stronger than in the other stage, activation in that brain region has occurred; when the opposite is shown, it is called deactivation. Thus, there is activation of a certain brain region if the stimulus of interest participates more than the contrast situations, and deactivation when the opposite happens. These phenomena are marked in functional images. Contrarily to the anatomical image, which is usually shown in grey scale, the functional image is colour-coded. Two ranges of colours are established: red to yellow representing increasing activations, and blue to light blue representing increasing deactivations.

Functional data are commonly analysed with the GLM. This method yields statistical significances, which means that the more the signal follows the model, the higher is the positive significance, which is coded with the range red to yellow; on the contrary, the higher is the negative significance, the more the signal follows the inverse of the model, which is coded with the range blue to light blue. The model that is introduced in the GLM is previously known because it represents the paradigm designed for the study. Putting it simply, the model stands for the sequence of stimuli, that is, the onset and the duration of the several types of events used to excite subjects.

Test procedures (paradigms)

Three main types of paradigms can be used in fMRI: the block design, the event-related and the mixed design. In the block design, one or more types of stimuli are alternated with a baseline (which in fact is a special type of stimulus and which is detailed below in the text). If S1 is stimulus 1, S2 is stimulus 2 and B is the baseline, a possible block design could be the sequence B S1 B S2 B S1 B S2 … Usually each block lasts for 20–30 seconds and is repeated around 10–20 times (indicative values). The number of repetitions may be dependent on the desired signal intensity for the active areas. For example, if photographs are used in the study, this does not mean that the same photo is presented for 20–30 seconds but rather that several images of the same type have to be used to limit the extinction effect, that is, stimuli has to be successively refreshed during the block in order to avoid habituation and to maintain the neurons of interest active. In event-related paradigms, stimuli and baseline are presented in alternation. The difference in block designs is that stimuli are not presented in trains; each short timing stimulus is followed by the baseline, which gets the denomination of inter-stimuli interval. Mixed designs are in between block and event-related designs; they are more like blocks that include several types of stimuli. For example, if several types of photographs are used, say landscapes (S1), buildings (S2) and human faces (S3), the presentation schema would be something like: B (S1 S3 S1 S2) B (S2 S1 S2 S3) B … Stimuli sequences and baseline must have equilibrated presentation times. Other types of paradigms are possible and can be found elsewhere (Huettel et al, 2004; Amaro and Barker, 2006).

Block design experiments are simpler to perform and to interpret, and also have the stronger signal differences between activation and baseline status; however, they are prone to habituation, lack of interest and may engage participants in undesirable cognitive strategies that are strange to the aim of the study. To overcome this last situation, event-related paradigms are preferable. Usually, event-related designs include several categories of stimuli that are randomised during the session. The main problem is that image signal intensity is considerably lower. However, if there is a significant difference, it is robust. Mixed designs are more difficult to interpret and prone to ongoing effects, where categories of stimuli are not easily distinguishable.

In this study, we used block design because it is simpler and has proven to be a very robust experimental design. This is a subtractive technique where the stimulus is contrasted with the baseline (notated as stimulus > baseline), and vice versa (baseline > stimulus). Hence, this is a relative method that identifies brain regions that participate more in one task than in the other, and does not provide causal relationships between brain regions and tasks. A certain brain region may be necessary for both tasks – stimulus and baseline – and yet participate more in one than in the other. This issue must be present for the convenient interpretation of the fMRI results.

The baseline: Highlighting what is interesting

The art within this science is therefore to design suitable contrasts that target the research question and reveal the pertinent brain structures. If the matter of investigation is very specific and sharply bounded, it is then strategically wise to choose a similar stimulus and baseline. It is worth noting once again that the output uses the baseline as a ground for comparison, and does not produce absolute statements. If the matter of investigation is broader and loosely bounded, then again it is strategically wise to choose a baseline that delivers the biggest contrast, and importantly which does not recruit cognitive processes that supposedly are essential for the stimulus. The present study falls into this last category and the particularities of choosing a suitable baseline are discussed in the Method section.

Limitations in fMRI

The reader may wonder why one type of stimulus must be repeated several times during the scanning session. The answer is that fMRI signal contains noise. Thus, a single presentation would not result in a robust signal-to-noise ratio, and several repetitions of the same stimuli category are needed in order to increase this ratio to a higher level. This fact launches considerable difficulties when researchers try to study outputs from specific situations, like movie presentation. As guiding values, one category of stimulus should be presented for around 2 min during an event-related session to be sufficiently sampled (Amaro and Barker, 2006), and the ideal number of events was already studied (Murphy and Garavan, 2005).

Another limitation of this technique is the temporal resolution. Although other techniques like electroencephalography (EEG) or magnetoencephalography (MEG) deliver millisecond accuracy, this is not the case in fMRI. A full brain acquisition of fMRI usually takes 2–3 seconds. This again poses problems when the researchers expect to use rapid-changing stimuli or when they prime fast cognitive processes. To overcome this limitation it is common practice to separate such processes in meaningful stages, each one encompassing just one cognitive step (if such is feasible), and acquiring at least one volume in each stage.

Owing to the scanner's intrinsic noise and the need to keep participants’ heads without moving, the visual sense is the easier to achieve. Sound is contaminated by the scanner's noise, taste and smell induce head movements, and touch is typically not very informative in consumer behaviour studies. However, ingenious paradigms have been designed in order to improve on these limitations (Plassmann et al, 2008).

Interpretation of the results

The interpretation of the activation brain maps should be done with some caution. For example, let us suppose that a certain cognitive task leads to the activation of a specific brain region. In the literature, it is found that the same brain region is activated under a different cognitive task. Establishing direct relationships between the two cognitive tasks is not a valid procedure, a process that is known as reverse inference (Poldrack, 2006, 2008). First, this kind of data analysis outputs correlations and not causal relationships. More complex paradigms and data analysis, for example, using classifiers, may yield causality (Haynes and Rees, 2006; Norman et al, 2006). Second, that would be a deduction that demands that the cognitive task described in the literature is a formal consequence of the brain region. This is not certain, because one brain region may participate in distinct cognitive processes, and human cognitive processes are complex phenomena that usually rely on concurrent and convergent subprocesses. It may even happen that a certain brain region participates recurrently at different times of the cognitive process. Nonetheless, it is admissible that one brain network supports one task, and studies with fMRI should look for such networks. The literature is fruitful in meta-analysis and transversal studies that aim to understand the role of a brain region/network. Such knowledge should be used to help in the interpretation of the activation maps in a process that is not deduction but abduction.

A simplified brain atlas

The newcomer to neuroscientific imaging faces an unexpected difficulty: there is not a well-defined and consensual atlas of the brain. Although there is agreement in the nomenclature of the subcortical grey matter nuclei, the same is not true regarding cortical and consequently white matter structures. In the cortex, the divisions between structures are not easily distinguishable, which has led to a profusion of nomenclatures. However, historical atlases, and seminal references such as Talairach and Tournoux (1988) and the brain map designed by Brodmann (1909), paved the way to computational brain atlases and more accurate coordinate systems (Brett, 1999). In order to maintain a coherent nomenclature, in the present study we have adopted the anatomical atlases Harvard-Oxford Cortical Structural Atlas and Harvard-Oxford Subcortical Structural Atlas provided by the Harvard Centre for Morphometric Analysis (www.cma.mgh.harvard.edu).

There is another difficulty: the anatomical division of the brain and the functional division do not coincide necessarily. It is not rare to find a function spanning several neighbouring anatomic structures. Despite this setback, it is common practice to report functional activity using the anatomic nomenclature.

To increase complexity, one cognitive process cannot be assigned to a single functional spaciously defined brain region. In fact, such proposition is viewed with scepticism. Recent approaches to brain function consider that different parts of the brain operate in networks (Poldrack, 2008). Hence, grounding conclusions on isolated brain regions may lead to spurious theories, especially when complex cognitive processes are being addressed, such as brand perception. It is more reasonable to consider that such complex cognitive processes rely on the concerted activity of a group of brain regions.

Bearing in mind these considerations, Figure B1 depicts an informative but necessarily simplistic brain map of the regions that are relevant in the present study. This map may help the reader to visualise where in the brain the structures are located.

Figure B1
figure 9

A simplified brain atlas.Note: The regions that are most relevant in the present study are herein depicted. Most of these regions belong to the prefrontal cortex (the anterior part of the frontal lobe): dorsal and ventral medial frontal pole, frontal medial cortex, frontal orbital cortex, paracingulate gyrus, subcallosal cortex and inferior frontal gyrus. The hippocampus belongs to the ventral temporal lobe and the amygdala is a subcortical nuclei. In the top left pane is the coronal slice (Coronal plane, a vertical plane that divides the body in back and front (refer to http://en.wikipedia.org/wiki/Anatomical_terms_of_location#Planes for more detailed explanation and figures) at y=+30. On its left two sagittal slices (Sagittal plane, a vertical plane that divides the body in right and left) (x=−06 and x=−50), both belonging to the left hemisphere. Below the coronal pane, two axial slices (Axial plane, a horizontal plane that divides the body in top (head; in the brain also dorsal) and bottom (tail; in the brain also ventral). (z=−18 and z=+14). MNI152 coordinates (see Brett (1999) for an explanation on coordinate systems). Radiological convention (brain right hemisphere depicted on the right).

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The prefrontal cortex (that is, the anterior part of the frontal lobe) encompasses the majority of these regions (dorsal and ventral medial frontal pole, frontal medial cortex, frontal orbital cortex, paracingulate gyrus, subcallosal cortex and inferior frontal gyrus) and its function ‘has long been suspected to play an important role in cognitive control, in the ability to orchestrate thought and action in accordance with internal goals’ (Miller and Cohen, 2001). Executive functions, that is, ‘ “higher-level” cognitive functions involved in the control and regulation of “lower-level” cognitive processes and goal-directed, future-oriented behaviour’ (Alvarez and Emory, 2006), have been attributed to the prefrontal cortex. The neural basis of speech generation in the left inferior frontal gyrus was first described by Paul Broca (1861). Hence, the prefrontal cortex and its subdivisions are an important neural substratum that supports human conduct.

The hippocampus, another brain structure in Figure B1, has been suggested to support memory systems (Squire, 2004). The amygdala, which has close connections with the hippocampus (LeDoux, 2007), has also been associated to memory, and to emotions (Zald, 2003; Adolphs, 2004), and is considered a primary emotional inducer (Bechara et al, 1999).

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Santos, J., Seixas, D., Brandão, S. et al. Neuroscience in branding: A functional magnetic resonance imaging study on brands’ implicit and explicit impressions. J Brand Manag 19, 735–757 (2012). https://doi.org/10.1057/bm.2012.32

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