1
Neuromarketing: valence assessments of commercial brands. A
Functional Magnetic Resonance Imaging (fMRI) study.
José Paulo Santos (1) Investigation Unit in Human Development and Psychology (Unidep), ISMAI -
Superior Institute of Maia, Portugal
Applied Economy Department, Economy Faculty, Coruña University, A Coruña, Spain
Sofia Brandão Radiology Department, MRI Unit, São João Hospital, Oporto, Portugal
Daniela Seixas Institute of Histology and Embryology, Faculty of Medicine, Oporto University,
Portugal
Neuroradiology Department of São João Hospital, Oporto, Portugal
(1) Corresponding author: phone: +351 22 9866000
fax: +351 22 9825331
e-mail: jpsantos@ismai.pt
address: Av. Carlos Oliveira Campos
Castelo da Maia
4475-690 Avioso S. Pedro
Portugal
1
Neuromarketing: valence assessments of commercial brands. A Functional Magnetic
Resonance Imaging (fMRI) study.
The scientific knowledge achieved within Neuroscience should be used to understand how
consumers behave. The present work uses a neuroimaging tool, Functional Magnetic Resonance
Imaging (fMRI) to disclose how consumers attribute valences to commercial brands. The results
revealed that participants distinguish between brands that have an emotional and a social relevant
content from those that do not have. We found evidence of correspondence between brain areas
that modulate emotion, and that are involved in mentalizing, valence rating, decision-making,
future strategic planning, and reinforced-learning and reward. These findings may be used as
important markers when studying brands’ emotional and social contents.
Declaration: the authors declare that this article represents an original work and that, until date, has not been
presented or submitted for publication elsewhere.
Introduction
How do consumers think? Every marketeer has posed this question by and a lot of the investigation work within
the Marketing discipline has been trying to search for answers. However, much of that work assumes that the
consumer is a black box, with inputs (from advertising, the social environment, …) which implicate outputs,
normally behaviors. The physical constrains of the organ where the inputs are processed to generate the outputs,
rarely is considered. Neuromarketing constitutes a new approach, where the consumer’s brain is minutely
inquired to better understand how it works and how behaviors are produced.
The present work deals with commercial brands. How are commercial brands perceived by the consumers? How
the eventual emotional and social load that each brand carries is processed and how does it influence the
consumer behavior? None of these questions have yet answers that consider sufficiently the processing of the
brain.
It is widely accepted in the Marketing community that commercial brands should be loaded with symbolic
content, which can be used by the individuals to reinforce their self-concept (Grubb & Grathwohl, 1967;
Banister & Hogg, 2004; Ligas & Cotte, 1999). Self-concept doesn’t boost in singular acts, disconnected from the
environment. By the contrary, it evolves in a process of social experience, nurtured by the reactions of the peers,
so each individual creates his own self-perception. The self-concept emerges from the reactions of parents,
colleagues, teachers and all other relevant mates, and all of these reactions that result from the social interaction
will contribute for the growing of each individual self-concept. Some authors even assume subdivisions of the
global self-concept: actual self-concept, ideal self-concept, social self-concept and ideal social self-concept
(Johar & Sirgy, 1991). This emphasizes the relevance of the social environment and stresses that each individual
has a social perfect state that he wants to reach. To achieve it, he will gather the necessary tools, most of which
are commercial brands, at least in the western culture.
One way to load commercial brands with symbolic content is through stereotypes. Stereotypes are
categorizations of experiences that are part of our understanding of the social world, or sets of ideas and fixed
beliefs sustained by the members of one or more groups, about the members of other groups. So, stereotypes
2
concentrate a set of signs and emotions and, evoking that stereotype, this load is transferred to the brand (Sirgy,
et al., 1997; Jagger, 1998). Through these stereotypes, brands can bear emotional content to their users,
enhancing their self-esteem. Self-esteem is the motivation that carries the actual self-concept to the ideal selfconcept
and the social self-concept to the ideal self-concept in a self-perfecting process.
Commercial brands have emotional content (and as so, can induce emotions in the consumers) and additionally
social relevant content (and as so, can be used by the consumers for social transactions with their peers).
Consequently, there is a triangular connection between each individual, the social group where which he belongs
and commercial brands (Grubb & Grathwohl, 1967).
These models were constructed based on behavioral evidence. But there is no role for the human organ where all
these processes take place: the brain. Where, inside the brain, is the emotional content retained? Where is the
social relevance of the brand filtered? Are there any brain structures that prove that commercial brands have
emotional and social content?
The works of Mitchell et al. (Mitchell, Macrae, & Banaji, 2004; Mitchell, Macrae, & Banaji, 2005) revealed the
brain structures involved in making impressions of people and inanimate objects. The Dorsomedial Prefrontal
Cortex (dmPFC), the Inferior Frontal Gyrus (IFG), and the Orbitofrontal Cortex (OFC) were found to be brain
structures that were able to distinguish between people and objects’ impression formation. For these authors, and
specifically the Dorsomedial Prefrontal Cortex (dmPFC) “indexes the social-cognitive aspects of impression
formation (i.e., understanding the psychological characteristics of another mental agent)” (Mitchell, Macrae, &
Banaji, 2005). This means that the dmPFC is responsible for discriminating social relevant information
considering that commercial brands have social relevant content, we hypothesize that this structure should also
be important in commercial brand processing.
The Anterior Cingulate Cortex (ACC) and the Paracingulate Gyrus (PCG) are structures that correlate with the
process of mentalizing about other individuals, within the Theory of Mind (Adolphs R. , 2001; Rilling, Sanfey,
Aronson, Nystrom, & Cohen, 2004; Saxe, 2006; Gallagher & Frith, 2003). This means that these structures are
engaged when individuals make inferences about the mental states of others, which is crucial when brand
meaning is formed within the social environment.
On the other way, the Amygdala has been referred as the structure enrolled in the primary emotional processing
(Adolphs, Tranel, & Damásio, 1998; Adolphs R. , 2003; Ashwin, Baron-Cohen, Wheelwright, O'Riordan, &
Bullmore, 2007; Beaucousin, Lacheret, Turbelin, Morel, Mazoyer, & Tzourio-Mazoyer, 2007; Bechara,
Damásio, Damásio, & Lee, 1999; Canli, Sivers, Whitfield, Gotlib, & Gabrieli, 2002; Castelli, 2005; Critchley, et
al., 2000; Norris, Chen, Zhu, Small, & Cacioppo, 2004). The Amygdala “links perceptual representations of
emotional sensory stimuli with the elicitation of behavioral and cognitive responses” (Adolphs R. , 2004), which
places this subcortical region in the center of emotional, and therefore social, processing (Phelps, 2004).
Although, how the brain works is far away from being understood, there is already some scientific evidence that
shed some light over the social relevant and emotion processing. As a result, there is an opportunity to try to
prove that commercial brands have emotional and social content and to try to determine which brain structures
are enrolled in their assessment.
Functional Magnetic Resonance Imaging (fMRI) has emerged in the last decade as the preferred technique in
Social Neuroscience studies. Contrary to other techniques used in Neuroscience research in humans, fMRI is
non-invasive, which means that the risks inherent to this technique are minimal (Huettel, Song, & McCarthy,
2004). FMRI does not use either ionizing radiation or chemical substances. FMRI employs strong magnetic
field, which, to date, albeit the millions of magnetic resonance imaging (MRI) scans that are made every day,
never was connected with any kind of detrimental long term effects. FMRI has a good spatial resolution (up to 1
mm), which means that it is able to image the individualized structures that compose the brain are and it allows
to differentiate which ones are active and which ones are not active during the performance of a certain task.
FMRI relies on the response of the blood vessels that follows brain electrical activity, and as such its temporal
resolution is not excellent, but at least identical to other popular neuroimaging methods like Positron Emission
Tomography (PET). Other relative disadvantages are the physical noise (much attenuated with the use of
auricular protection), the more or less long data acquisitions and the artificial research environment, away from
the reality of everyday life. Considering fMRI’s advantages and disadvantages, it is actually one of the best
imaging methods to innocuously visualize brain function in humans in vivo. Original articles using fMRI as a
methodology have been growing in numbers each year in the worldwide scientific literature, especially in the
field of cognitive neuroscience, which will be also the core of the present study.
3
Materials and methods
Participants
The participants were 6 healthy male and 6 healthy female volunteers, right handed, native Portuguese speakers
with neither history of neurological nor psychiatric disturbances (mean age 28,4 years, 5,4 s. d.; mean schooling
16,2 years, 1,5 s. d.). Informed consent was obtained in all cases. A safety form for MRI was filled by every
participant and discussed with a Neuroradiologist and a Radiographer. This research project was approved by the
Ethics Committee of São João Hospital, Oporto, Portugal.
Behavioral procedures
The paradigm was a mixed design – block and event-related – where as baseline we used words without
emotional content, over a black background. These words were determiners, conjunctions, prepositions or
adverbs. Importantly, we didn’t use any nouns or verbs that could evoke emotions, objects or actions. As
stimulus, we employed commercial brands, with the logos and colors that were characteristic for each and every
one in everyday life. The baseline period was equal to the stimulus period, 30 seconds long. Within each 30
seconds period, 5 slides were visually displayed, 6 seconds each. The slide set was then composed by 16 baseline
periods and 16 stimulus periods, totaling 160 slides.
For the selection of the commercial brands to use as stimulus, 147 students of the Superior Institute of Maia
(ISMAI), Portugal, filled in an inquiry with 237 commercial brands. The purpose of this inquiry was to decide on
the brands most well known. The brands supposedly with emotional content (chosen by the students either with a
“negative” or a “positive” valence) were intermingled pseudo-randomly with the brands with supposedly nonemotional
content (those that received an assessment of “indifferent”).
Before the MRI scanning session, the volunteers filled in an inquiry that had the exactly same sequence of
commercial brands that was within the slide set they were about to visualize inside the MRI scanner. For each
brand the volunteers chose between four states: “unknown”, “negative”, “indifferent”, and “positive”. In this
way, before the run, they trained the brands’ assessments which were then required to be repeated through the
scanning session. These inquiries were used afterwards to construct the basic shapes for the event-related
analysis.
Image acquisition
A whole brain anatomical structural scan was acquired for each volunteer in a Siemens® Trio high field (3 Tesla)
MRI scanner, using a T1-weighted MPRAGE protocol (256 x 256 matrix, FOV = 256 mm, 3.0 mm axial slices).
Functional images were acquired using T2*-weighted EPI (TR = 3000 ms, TE = 30 ms, 64 x 64 matrix, FOV =
192 mm, 3.0 mm axial slices). Gradient field mapping was additionally acquired for image quality control.
A trained Neuroradiologist reviewed all the anatomical scans. No incidental findings were found.
Image analysis
FMRI data processing was carried out using FEAT (FMRI Expert Analysis Tool) Version 5.90, part of FSL
(FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl).
The following pre-statistics processing was applied; motion correction using MCFLIRT (Jenkinson, Bannister,
Brady, & Smith, 2002); slice-timing correction using Fourier-space time-series phase-shifting; non-brain
removal using BET (Smith, 2002); spatial smoothing using a Gaussian kernel of FWHM 5mm; grand-mean
intensity normalization of the entire 4D dataset by a single multiplicative factor; highpass temporal filtering
(Gaussian-weighted least-squares straight line fitting, with sigma=30.0s). Time-series statistical analysis was
carried out using FILM with local autocorrelation correction (Woolrich, Ripley, Brady, & Smith, 2001).
Registration to high resolution structural and/or standard space images was carried out using FLIRT (Jenkinson
& Smith, 2001; Jenkinson, Bannister, Brady, & Smith, 2002).
Higher-level analysis was carried out using FLAME (FMRIB's Local Analysis of Mixed Effects) stage 1 only,
i.e., without the final MCMC-based stage (Beckmann, Jenkinson, & Smith, 2003; Woolrich, Behrens,
Beckmann, Jenkinson, & Smith, 2004).
Z (Gaussianised T/F) statistic images were thresholded using clusters determined by Z>2.3 and a (corrected)
cluster significance threshold of P=0.05 (Worsley, 2001).
4
Interesting structures were isolated using ROIs - Region-of-Interest. The masks to pre-threshold the ROIs were
made based on the atlases “Harvard-Oxford Cortical Structural Atlas” and “Harvard-Oxford Subcortical
Structural Atlas” which accompany FSL View v3.0, part of FSL 4.0.
Results
Along the scans, the twelve participants made explicit cognitive assessments of commercial brands. Four
possible valences were available: “unknown”, “negative”, “indifferent”, and “positive”. As chosen brands were
previously filtered by an inquiry, the “unknown” answers were negligible (1%). The remaining answers were
14% for the valence “negative”, 32% for “indifferent” and 53% for “positive”.
Negative valence
The overall activation of negative valence is shown in Figure 1. The respective cluster assignments are listed in
Table 1.
The most remarkable result is that this paradigm produced activations extensively in the whole brain. Of
relevance, are the activations in the Frontal Lobe: Frontal Orbital Cortex, Frontal Pole, Inferior Frontal Gyrus
(both in Pars Opercularis and Pars Triangularis) and Paracingulate Gyrus. With special interest for the present
study, there was also activations in the Insular Cortex, Cingulate Gyrus (Anterior Division) and in the regions
that constitute the Striatum, the Putamen and the Caudate, together with the neighbor Pallidum. A first approach
indicates that, in this task, there is participation of the cognitive functions (usually located in the Frontal Lobe)
and decision-making (which processing usually passes by the Striatum). Also participates the limbic structure
Cingulate Gyrus, where were identified a special class of neurons, the Von Economo neurons or spindle-cells
(Nimchinsky, Gilissen, Allman, Perl, Erwin, & Hof, 1999; Allman, Hakeem, Erwin, Nimchinsky, & Hof, 2001),
which are suspected to detect discrepancies in the environment.
Another part of the data that needs some explanation is the apparent overlap in the Paracingulate Gyrus and in
the Cingulate Gyrus (Anterior Division). The maximum of the cluster (MNI152: -2, 16 42) in the probabilistic
atlases is 68% in the Paracingulate and 18% in the Cingulate. So, it is more probable that the maximum is in the
Paracingulate Gyrus than in the Cingulate Gyrus (Anterior Division). However, the center of gravity of the
cluster of the Paracingulate (MNI152: -1, 23, 37) is 45% in the Paracingulate and 30% in the Cingulate and the
center of gravity of the cluster of the Cingulate (MNI152: -1, 20, 37) is 34% in the Paracingulate and 40% in the
Cingulate. So the conclusion is that this is a cluster that effectively occupies both the Paracingulate Gyrus and
the Cingulate Gyrus (Anterior Division), albeit its maximum intensity is in the Paracingulate Gyrus.
Figure 1 - Activations produced by the negative assessments.
5
Table 1 – Data of the clusters produced by the negative assessments.
Z max Center of Gravity
# Structure
(1)
Cluster
voxels z X Y Z X Y Z
L 724 4.29 -30 26 -2 -40 26 -7
1 Frontal Orbital Cortex
R 400 4.09 34 28 -8 41 24 -7
2 Frontal Pole L 749 3.85 -28 60 -16 -37 53 2
3 Inf. Frontal Gyrus – Pars Opercularis L 749 3.56 -42 12 22 -50 18 10
4 Inf. Frontal Gyrus – Pars Triangularis L 730 3.59 -38 28 -4 49 24 6
L 582 4.29 -30 26 -2 -36 18 -1
5 Insular Cortex
R 373 4.09 34 28 -8 40 20 -6
6 Paracingulate Gyrus L 774 4.42 -2 16 42 -1 23 37
7 Cingulate Gyrus (Anterior Division) L 595 4.42 -2 16 42 -1 20 37
8 Caudate L 195 3.04 -12 10 0 -13 11 3
L 294 3.16 -30 10 0 -21 8 0
9 Putamen
R 244 3.46 22 14 -4 21 9 0
L 128 3.11 -16 6 -2 -17 3 0
10 Pallidum
R 101 3.05 18 6 6 19 4 0
L 655 4.33 -26 -52 -18 -32 -59 -17
11 Temporal Occipital Fusiform Cortex
R 768 5.16 32 -44 -24 34 -51 -19
L 1762 4.92 -26 -92 -18 -28 -78 -15
12 Occipital Fusiform Gyrus
R 1420 4.70 22 -92 -16 29 -78 -15
L 801 4.11 -40 2 42 -40 14 35
13 Middle Frontal Gyrus
R 290 3.68 52 12 38 45 6 43
L 386 4.11 -40 2 42 -38 -1 43
14 Precentral Gyrus
R 496 3.68 52 12 38 47 3 40
15 Occipital Pole L 5354 4.92 -26 -92 -18 0 -94 -4
L 566 3.81 -26 -64 58 -36 -60 47
R 810 4.22 16 Lateral Occipital Cortex (Superior Division) 36 -90 2 31 -88 8
R 511 4.22 -18 -98 4 -27 -90 12
17 Intracalcarine Cortex R 315 4.05 2 -96 -10 -3 -93 -7
All the coordinates are MNI152.
(1) L – left; R – right
Indifferent valence
The overall activation of negative valence is shown in Figure 2. The respective cluster assignments are listed in
Table 2.
Figure 2 - Activations produced by the indifferent assessments.
6
As in the previous section, negative valence, there are activations extensively in the whole brain. Almost the
same structures that activated previously, also registered activations in the indifferent valence. In this valence
there is a supplementary activation in the Hippocampus, a structure usually linked to declarative and mnemonic
memories (Critchley, et al., 2000), encoding relations between items and context. This is crucial when recalling
based on recognition (Paller & Wagner, 2002), which suggests that participants draw the Hippocampus to evoke
memories about the brands.
Table 2 - Data of the clusters produced by the indifferent assessments.
Z max Center of Gravity
# Structure
(1)
Cluster
voxels z X Y Z X Y Z
L 1328 4.90 -40 22 -10 -39 26 -9
1 Frontal Orbital Cortex
R 927 5.17 32 28 -8 38 26 -9
L 2320 4.99 -46 52 -10 -35 50 3
R 959 4.04 2 Frontal Pole 46 50 -16 34 51 -7
R 499 4.01 46 34 32 46 37 20
L 1740 4.55 -48 20 18 -48 16 17
3 Inf. Frontal Gyrus – Pars Opercularis
R 728 4.43 54 16 28 49 18 23
L 1139 4.55 -48 20 18 -48 25 9
4 Inf. Frontal Gyrus – Pars Triangularis
R 856 3.91 54 20 32 47 28 14
L 935 4.90 -40 22 -10 -35 18 -4
5 Insular Cortex
R 682 5.17 32 28 -8 36 20 -6
6 Paracingulate Gyrus L 1400 5.15 -4 18 44 0 26 35
7 Cingulate Gyrus (Anterior Division) L 982 4.94 -4 18 42 0 23 34
L 295 4.59 -24 -30 -10 -24 -28 -9
8 Hippocampus
R 191 4.58 18 -34 -4 22 -32 -5
L 375 4.08 -14 12 0 -12 8 6
9 Caudate
R 321 3.79 8 2 4 13 9 5
L 652 3.47 28 18 -2 24 5 -1
10 Putamen
R 646 4.08 -18 2 4 -22 7 -2
L 395 4.29 -14 2 6 -17 -1 0
11 Pallidum
R 467 4.06 14 0 6 18 -2 0
L 881 4.68 -26 -54 -20 -33 -58 -17
12 Temporal Occipital Fusiform Cortex
R 1027 5.30 32 -44 -24 35 -52 -19
L 1973 5.35 -36 -88 -20 -28 -77 -15
13 Occipital Fusiform Gyrus
R 1624 4.34 20 -92 -16 29 -77 -14
L 1381 4.39 -48 20 20 -43 16 32
14 Middle Frontal Gyrus
R 1301 4.43 54 16 28 46 22 30
L 1120 4.18 -40 12 20 -46 6 28
15 Precentral Gyrus
R 594 4.43 54 16 28 48 5 36
16 Occipital Pole L 6149 5.62 -36 -90 -20 -1 -94 -4
L 2577 4.77 -28 -88 24 -29 -74 34
17 Lateral Occipital Cortex (Superior Division)
R 2305 4.46 26 -88 12 30 -76 29
18 Intracalcarine Cortex R 417 3.94 26 -88 10 1 -92 -3
All the coordinates are MNI152.
(1) L – left; R – right
Positive valence
The overall activation of negative valence is shown in Figure 3. The respective cluster assignments are listed in
Table 3.
As in both previous sections, negative and indifferent valences, there are activations extensively in the whole
brain. Almost the same structures that activated previously, also registered activations in the positive valence. In
this valence there are two supplementary activations: the Frontal Medial Cortex within the Frontal Lobe and the
Amygdala within the Limbic System. These activations have special relevance as they only occurred when
participants attributed the positive rating, but not when the stimuli were indifferent. This suggests that they may
mediate a preference, which is a core interest within Marketing discipline.
7
Table 3 - Data of the clusters produced by the positive assessments.
Z max Center of Gravity
# Structure
(1)
Cluster
voxels z X Y Z X Y Z
1 Frontal Medial Cortex L 232 4.27 -6 46 -22 -7 43 -20
L 1458 4.53 -32 30 -14 -36 28 -11
2 Frontal Orbital Cortex
R 728 3.86 30 38 -14 38 28 -9
L 2883 4.62 -42 48 -10 -29 49 1
3 Frontal Pole
R 608 3.86 30 38 -14 28 45 -14
L 1357 4.21 -50 20 18 -48 16 17
4 Inf. Frontal Gyrus – Pars Opercularis
R 319 3.68 46 8 36 48 16 26
L 972 4.21 -50 20 18 -48 24 8
R 244 3.90 5 Inf. Frontal Gyrus – Pars Triangularis 38 34 12 44 30 16
R 164 3.12 42 32 2 49 25 -4
L 752 4.38 -32 22 -4 -35 18 -3
6 Insular Cortex
R 462 3.68 36 22 -2 38 20 -5
7 Paracingulate Gyrus L 1469 4.17 -6 24 34 -1 24 36
8 Cingulate Gyrus (Anterior Division) L 1165 4.17 -6 24 34 0 21 35
L 86 4.09 -32 -10 -16 -29 -9 -16
9 Amygdala
R 121 3.40 32 -6 -16 30 -3 -18
L 616 4.83 -24 -32 -6 -26 -28 -10
10 Hippocampus
R 356 3.98 24 -32 -2 26 -32 -4
L 359 3.78 -8 10 2 -12 6 7
11 Caudate
R 316 3.73 8 6 8 14 3 10
L 697 3.50 28 -8 -4 24 3 0
12 Putamen
R 561 3.93 -18 4 0 -22 5 1
L 439 3.93 -18 4 0 -18 -3 -1
13 Pallidum
R 559 4.01 14 -4 -4 20 -3 -1
L 1152 4.37 -42 -68 -20 -34 -57 -17
14 Temporal Occipital Fusiform Cortex
R 1407 5.36 32 -42 -68 -20 -34 -57
L 2214 6.24 -34 -82 -22 -28 -77 -15
15 Occipital Fusiform Gyrus
R 1994 4.72 28 -92 -14 29 -76 -14
L 1200 4.16 -28 0 46 -41 15 34
16 Middle Frontal Gyrus
R 592 3.90 38 34 12 44 15 34
L 1041 4.11 -28 -6 50 -44 2 34
17 Precentral Gyrus
R 733 3.88 36 2 50 46 1 41
18 Occipital Pole L 7147 5.06 36 -98 -2 0 -94 -3
L 1903 4.71 -28 -86 22 -27 -79 26
19 Lateral Occipital Cortex (Superior Division)
R 1823 4.63 24 -88 -2 29 -81 19
20 Intracalcarine Cortex L 923 5.03 -20 -88 0 0 -90 -1
21 Supracalcarine Cortex R 333 4.40 2 -96 -10 4 -92 3
All the coordinates are MNI152.
(1) L – left; R – right
Figure 3 - Activations produced by the positive assessments.
8
Contrasts between valences
Table 4 summarizes the statistically significant contrasts between valences and Table 5 contains the data of the
clusters.
Table 4 - Statistically significant contrasts between valences.
Contrast over Negative Indifferent Positive
Negative - No Activations No Activations
Indifferent
- Lateral Occipital Cortex
(Superior Division) (#1)
- No Activations
Positive
- Occipital Pole /
Supracalcarine Cortex /
Intracalcarine Cortex (#2)
- Frontal Medial Cortex /
Paracingulate Gyrus /
Frontal Pole (#3)
-
Table 5 - Data of the clusters that is statistically significant when contrasting between valences.
Z max Center of Gravity
# Structure
(1)
Cluster
voxels z X Y Z X Y Z
#1 Lateral Occipital Cortex (Superior Division) L 468 3.00 -30 -76 28 -20 -77 42
#2 Occipital Pole / Supracalcarine Cortex / Intracalcarine Cortex L 467 3.15 -2 -92 8 0 -87 7
#3 Frontal Medial Cortex / Paracingulate Gyrus / Frontal Pole L 341 3.25 -4 56 0 -4 49 -8
All the coordinates are MNI152.
(1) L – left; R – right
The most important activation occurred between the positive over the indifferent valences. There is a cluster that
occupies the Frontal Medial Cortex and a small region within the Frontal Pole and the ventral part of the
Paracingulate Cortex. This brings special relevance for the Frontal Medial Cortex as it reached statistical
significance when comparing positive rated brands over indifferent.
Discussion
In the positive valence assessment by the subjects, we found brain activations in the Frontal Medial Cortex, in
the Amygdala and in the Supracalcarine Cortex. These areas were not shared by the assessment made of
indifferent valences. The Supracalcarine Cortex is one of the brain regions that participate in visual processing.
The used paradigm was not designed to study visual areas; the complexity of the commercial brand’s logos
compared with the more simple word design used as contrast, might account for this finding, not important for
the purpose of our study.
We found activations in the Amygdala in the positive valence assessment but not in the indifferent valence
assessment, although this difference wasn’t enough to reach significance when contrasting between valences.
Nevertheless, this is a very important activation as normally two roles are assigned to this subcortical brain
structure. The amygdala is involved in reactions to fear, and also filters the emotional content of a stimulus
(Adolphs R. , 2004; Phelps, 2004). It is unlikely that the activations observed in the Amygdala were due to fear,
because it only occurred when the participants rated as “positive” the valence of the commercial brands seen.
“The Amygdala (…) receives highly processed visual information from the anterior temporal cortices, and stores
codes for subsequent processing of such perceptual information in other brain regions. In this way, it can
influence memory, attention, decision making and other cognitive functions on the basis of the social
significance of the stimuli that are being processed” (Adolphs R. , 2003). The Amygdala occupies a crucial role
as a roundabout within the emotional, and even more broadly, within the social processing (Castelli, 2005). We
speculate that, if a commercial brand pretends to reach social relevance, its image within the consumers’ brains
should activate their Amygdales.
The Frontal Medial Cortex was activated in the positive valence assessment, but not again in the indifferent
valence assessment, in this case achieving statistical significance. This structure is also known as Ventromedial
Prefrontal Cortex (vmPFC). The Frontal Medial Cortex and the Amygdala are interconnected structures
(Stefanacci & Amaral, 2002), both enrolled in emotional processing and modulation (Martin & Weisberg, 2003).
The famous case of Phineas Gage, reported by Damásio and co-workers , resulted in a lesion in the vmPFC
(Damásio, 1994). Phineas Gage became unable to have a social appropriate behavior. This is characteristic of
individuals with impaired vmPFC processing, albeit their normal language, memory and perception abilities
(Adolphs R. , 1999). While the Amygdala is more stimuli-driven, generating impulsive reactions, the Frontal
9
Medial Cortex is more “rational”; it is also responsible for processing long-term rewards, which are strategically
planned by the individual (Bechara A. , 2004; Bechara & Damásio, 2005; Adolphs R. , 2006; Montague, King-
Casas, & Cohen, 2006). We hypothesize that self-concept may be represented in the Frontal Medial Cortex as
this is the structure that encompasses future strategies and aims, which means ideal states. The fact that this
structure was evoked only by positive rated stimuli, suggests that commercial brands could act as a reference,
essential for future planning and achieving a social status. As so, the activation of the Frontal Medial Cortex can
be a representation of desire.
The results of the negative valence assessment must be interpreted very carefully. This valence was the less used
by the participants (14%), which means that the data collected can be not enough for the statically tools to
extract results from the raw data. This means that maybe there were activations that didn’t reach the threshold to
be considered, because they were disguised by the experiment’s noise.
There were structures that activated under all stimuli. For example, the Frontal Orbital Cortex, which
anatomically is close to the previously discussed Frontal Medial Cortex. The Frontal Orbital Cortex is a structure
described to be engaged in cultural (i.e. social relevant) transactions (Erk, Spitzer, Wunderlich, Galley, &
Walter, 2002). Generally, this structure is involved in reward processing (Walter, Abler, Ciaramidaro, & Erk,
2005), filtering relevant cues (Kelley & Berridge, 2002; Miller & Cohen, 2001; Pelzmann, Hudnik, & Miklautz,
2005), which is fundamental information within the social environment. Lesions in this area are known to bias
individuals towards improper decisions (Damásio, 1994). Being the Frontal Orbital Cortex specialized in
detecting reward, it is without surprise that we verify that it was activated in all kinds of stimuli, positive,
negative and indifferent, because the participants were judging the value of commercial brands.
In vicinity to both Frontal Medial Cortex and Frontal Orbital Cortex is the Frontal Pole, which also was activated
in all the different types of stimuli. This structure is far large and thought to be far more complex, as several
roles are assigned to distinct subregions. In the work of Mitchell et al. (Mitchell, Macrae, & Banaji, Forming
impressions of people versus inanimate objects: Social-cognitive processing in the medial prefrontal cortex,
2005) there was an activation with a maximum at (MNI: -9, 54, 36) when subjects formed impressions between
people and objects. In the present work, this coordinate was localized in the Frontal Pole, more exactly in a
subregion known as Dorsomedial Prefrontal Cortex – dmPFC. The Dorsomedial Prefrontal Cortex only reached
significant activation in the positive valence assessment. This correspondence is important as those authors
suggested that the Dorsomedial Prefrontal Cortex ”(…) specifically indexes the social-cognitive aspects of
impression formation (i.e., understanding the psychological characteristics of another mental agent)”. As so, the
parallel between people impression formation and commercial brand impression formation can be established,
which is one more argument favoring that brands may have an important role in the social context. Proceeding
with the parallel established, positive rated commercial brands activated this subregion of the Frontal Pole, but
the indifferent rated brands did not. This may suggest that positive rated brands are seen by the individual as
being closer to people (and hence with emotional and social relevant load), but indifferent rated brands are seen
as mere objects.
Discussing further the Frontal Lobe of the brain, all the valence assessments registered activations in the Inferior
Frontal Gyrus, in two subregions named Pars Opercularis and Pars Triangularis. In the left hemisphere, these
structures correspond to what is known as Broca’s area, a region fundamental for language processing (Hickok
& Poeppel, 2007; Matthews, et al., 2003). Intriguingly, the contrast words used didn’t have an emotional content
and neither suggested objects nor actions. As so, non-emotional language areas shouldn’t contrast and, therefore
shouldn’t produce any activations, although language processing is complex and a long way from being
completely understood. Anyway, these activations may suggest that other explanations can exist and these
should be investigated. One hypothesis is that the mirror neurons are supposed to be found within these areas
(Rizzolatti & Craighero, 2004; Rizzolatti, 2005). It is believed today that the role of the mirror neurons is far
more complex than just mirroring actions of other individuals. They are supposed to have an important role in
language, imitation and emotions (Carr, Iacoboni, Dubeau, Mazziotta, & Lenzi, 2003; Gallese, Keysers, &
Rizzolatti, 2004). As the reading process should have been canceled due to the lack of contrast between the
stimulus and the baseline in our experiment, and still we could find activations in these areas, it can be
hypothesized that brands are symbols that humans can use for imitation or for emotion decoding. Further
investigation, with paradigms more sensible for this concern, should confirm or not this trend.
The Insula is believed to have a relay role between action representation within the Prefrontal Cortex and the
Limbic System, linking the mirror neuron system (Carr, Iacoboni, Dubeau, Mazziotta, & Lenzi, 2003). The
Insular activation in our experiment confers to the previous hypothesis more consistency, which would load
brands with an important social role, already assumed to have from the Marketing theories.
10
When an individual makes inferences about the mental states of others, he is mentalizing. This is one of the
processes of the Theory of Mind – ToM (Adolphs R. , 2001; Rilling, Sanfey, Aronson, Nystrom, & Cohen,
2004; Saxe, 2006; Gallagher & Frith, 2003). The Paracingulate Gyrus, another structure that was activated
throughout all valence assessments,, was found to be also activated when the process of mentalizing occurs.
Within the theory of Symbolic Interactionism (Ligas & Cotte, 1999) the value of a brand is asserted within the
social group. The Symbolic Interactionism is a complex play between the social action, the self-reflexive nature
of the individual and the negotiation of each one’s self-concept within the social context. As so, Theory of Mind
plays a crucial role, as each individual, along the transactional process, must infer the mental states (beliefs,
aims, intentions, strategies, …) of his peers. These activations suggest that participants already played this
“game” before and that each brand had a previous quotation and meaning inside the individual brain.
The Cingulate Gyrus – Anterior Division (also known as Anterior Cingulate Gyrus – ACC) is a structure that has
a special type of neurons, the spindle cells (Nimchinsky, Gilissen, Allman, Perl, Erwin, & Hof, 1999). These
neurons exist in humans, hominids and pongids, but not in lesser apes, which is a signal that is recent in
evolution. It is thought to have a role in the coordination that would be essential in developing the capacity to
focus on difficult problems (Allman, Hakeem, Erwin, Nimchinsky, & Hof, 2001). One possible explanation for
its activation in our study could be the degree of complexity of the task the participants were engaged in
extracting and evaluating commercial brands’ emotional and social content.
The Striatum components, the Putamen and the Caudate Nucleus, participated extensively in this experiment.
Both structures are usually connected with reward and reinforced learning (Critchley, et al., 2000; Kelley &
Berridge, 2002; Montague, King-Casas, & Cohen, 2006). Their neighbor structure, the Pallidum, is also believed
of linking social information to reward circuits (Insel & Fernald, 2004).
Along this discussion, several times it was suggested that commercial brands have both emotional and social
content, because its processing shared common structures, thought to be involved in the processing of those
contents. In the cited literature, parallel was made with seeing faces, learning actions, listening to speech,
cultural objects, and so on, all recognized as relevant in social interactions. Brand processing is ubiquitous in the
brain, engaging thus diverse brain areas, due to its multidimensionality. This is a common point with social
processing, which is also complex and distributed throughout the brain, with many structures contributing for the
overall processing.
Acknowledgments
We thank to Professor Isabel Ramos the support for the use of the MRI scanner.
References
Adolphs, R. (2003). Cognitive Neuroscience of Human Social Behaviour. Nature Reviews Neuroscience , 4, 165-178.
Adolphs, R. (2004). Processing of Emotional and Social Information by the Human Amygdala. In M. S. Gazzaniga, The Cognitive
Neurosciences III (pp. 1017-1030). Cambridge: MIT Press.
Adolphs, R. (1999). Social Cognition and the Human Brain. Trends in Cognitive Sciences , 3 (12), 469-479.
Adolphs, R. (2001). The Neurobiology of Social Cognition. Current Opinion in Neurobiology , 11, 231-239.
Adolphs, R. (2006). What is special about social cognition? In J. T. Cacioppo, P. S. Visser, & C. L. Pickett, Social Neuroscience: People
Thinking About Thinking People (pp. 269-285). Cambridge: MIT Press.
Adolphs, R., Tranel, D., & Damásio, A. R. (1998). The Human Amygdala in Social Judgment. Nature , 393, 470-474.
Allman, J. M., Hakeem, A., Erwin, J. M., Nimchinsky, E., & Hof, P. (2001). The Anterior Cingulate Cortex: The Evolution of an Interface
between Emotion and Cognition. Annals of the New York Academy of Sciences , 935 (1), 107-117.
Ashwin, C., Baron-Cohen, S., Wheelwright, S., O'Riordan, M., & Bullmore, E. T. (2007). Differential Activation of the Amygdala and the
“Social Brain” During Fearful Face-processing in Asperger Syndrome. Neuropsychologia , 45 (1), 2-14.
Banister, E. N., & Hogg, M. K. (2004). Negative symbolic consumption and consumers’ drive for self-esteem: the case of the fashion
industry. European Journal of Marketing , 38 (7), 850-868.
Beaucousin, V., Lacheret, A., Turbelin, M. R., Morel, M., Mazoyer, B., & Tzourio-Mazoyer, N. (2007). FMRI Study of Emotional Speech
Comprehension. Cerebral Cortex , 17 (2), 339-352.
11
Bechara, A. (2004). The role of emotion in decision-making: Evidence from neurological patients with orbitofrontal damage. Brain and
Cognition , 55, 30-40.
Bechara, A., & Damásio, A. R. (2005). The somatic marker hypothesis: A neural theory of economic decision. Games and Economic
Behavior , 52, 336-372.
Bechara, A., Damásio, H., Damásio, A. R., & Lee, G. P. (1999). Different Contributions of the Human Amygdala and Ventromedial
Prefrontal Cortex to Decision-Making. The Journal of Neuroscience , 19 (13), 5473-5481.
Beckmann, C., Jenkinson, M., & Smith, S. M. (2003). General Multi-level Linear Modelling for Group Analysis in FMRI. Neuroimage , 20,
1052-1063.
Canli, T., Sivers, H., Whitfield, S. L., Gotlib, I. H., & Gabrieli, J. D. (2002). Amygdala Response to Happy Faces as a Function of
Extraversion. Science , 296, 2191.
Carr, L., Iacoboni, M., Dubeau, M. C., Mazziotta, J. C., & Lenzi, G. L. (2003). Neural Mechanisms of Empathy in Humans: A Relay from
Neural Systems for Imitation to Limbic Areas. Proceedings of the National Academy of Sciences , 100 (9), 5497-5502.
Castelli, F. (2005). Understanding Emotions from Standardized Facial Expressions in Autism and Normal Development. Autism , 9 (4), 428-
449.
Critchley, H., Daly, E., Philips, M., Brammer, M., Bullmore, E., Williams, S., et al. (2000). Explicit and Implicit Neural Mechanisms for
Processing of Social Information from Facial Expressions: A Functional Magnetic Resonance Imaging Study. Human Brain Mapping , 9 (2),
93-105.
Damásio, A. R. (1994). Descarte’s Error—Emotion, Reason and the Human Brain. New York: Penguin Putnam.
Erk, S., Spitzer, M., Wunderlich, A. P., Galley, L., & Walter, H. (2002). Cultural Objects Modulate Reward Circuitry. Neuroreport , 13 (18),
2499-2503.
Gallagher, H. L., & Frith, C. D. (2003). Functional Imaging of "Theory of Mind". Trends in Cognitive Sciences , 7 (2), 77-83.
Gallese, V., Keysers, C., & Rizzolatti, G. (2004). A Unifying View of the Basis of Social Cognition. Trends in Cognitive Sciences , 8 (9),
396-403.
Grubb, E. L., & Grathwohl, H. L. (1967). Consumer self-concept, symbolism and market behavior: a theoretical approach. Journal of
Marketing , 31, 22-27.
Hickok, G., & Poeppel, D. (2007). The Cortical Organization of Speech Processing. Nature Reviews Neuroscience , 8, 393-402.
Huettel, S. A., Song, A. W., & McCarthy, G. (2004). Functional Magnetic Resonance Imaging. Sunderland: Sinauer Associates.
Insel, T. R., & Fernald, R. D. (2004). How the Brain Processes Social Information: Searching for the Social Brain. Annual Reviews in
Neuroscience , 27, 697-722.
Jagger, E. (1998). Marketing the self, buying and other: dating in a postmodern, consumer society. Sociology , 32 (4), 795-814.
Jenkinson, M., & Smith, S. M. (2001). A Global Optimisation Method for Robust Affine Registration of Brain Images. Medical Image
Analysis , 5 (2), 143-156.
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002). Improved Optimisation for the Robust and Accurate Linear Registration and
Motion Correction of Brain Images. Neuroimage , 17 (2), 825-841.
Johar, J. S., & Sirgy, J. M. (1991). Value-expressive versus utilitarian advertising appeals: when and why to use which appeal. Journal of
Advertising , 20 (3), 23-33.
Kelley, A. E., & Berridge, K. C. (2002). The Neuroscience of Natural Rewards: Relevance to Addictive Drugs. The Journal of Neuroscience
, 22 (9), 3306-3311.
Ligas, M., & Cotte, J. (1999). The process of negotiating brand meaning: a symbolic interactionist perspective. Advances in Consumer
Research , 26 (1), 609-614.
Martin, A., & Weisberg, J. (2003). Neural Foundations for Understanding Social and Mechanical Concepts. Cognitive Neuropsychology , 20
(3/4/5/6), 575-587.
Matthews, P. M., Adcock, J., Chen, Y., Fu, S., Devlin, J. T., Rushworth, M. F., et al. (2003). Towards Understanding Language Organisation
in the Brain using fMRI. Human Brain Mapping , 18, 239-247.
12
Miller, E. K., & Cohen, J. D. (2001). An Integrative Theory of Prefrontal Cortex Function. Annual Reviews in Neuroscience , 24, 167-202.
Mitchell, J. P., Macrae, C. N., & Banaji, M. R. (2004). Encoding specific effects of social cognition on the neural correlates of subsequent
memory. Journal of Neuroscience , 24 (21), 4912-4917.
Mitchell, J. P., Macrae, C. N., & Banaji, M. R. (2005). Forming impressions of people versus inanimate objects: Social-cognitive processing
in the medial prefrontal cortex. Neuroimage , 26 (1), 251-257.
Montague, P. R., King-Casas, B., & Cohen, J. D. (2006). Imaging Valuation Models in Human Choice. Annual Reviews in Neuroscience ,
29, 417-448.
Nimchinsky, E. A., Gilissen, E., Allman, J. M., Perl, D. P., Erwin, J. M., & Hof, P. R. (1999). A Neuronal Morphologic Type Unique to
Humans and Great Apes. Proceedings of the National Academy of Sciences USA , 96, 5268-5273.
Norris, C. J., Chen, E. E., Zhu, D. C., Small, S. L., & Cacioppo, J. T. (2004). The Interaction of Social and Emotional Processes in the Brain.
Journal of Cognitive Neuroscience , 16 (10), 1818-1829.
Paller, K. A., & Wagner, A. D. (2002). Observing the Transformation of Experience Into Memory. Trends in Cognitive Sciences , 6 (2), 93-
102.
Pelzmann, L., Hudnik, U., & Miklautz, M. (2005). Reasoning or Reacting to Others? How Consumers Use the Rationality of Other
Consumers. Brain Research Bulletin , 67, 438-442.
Phelps, E. A. (2004). The Human Amygdala and Awareness: Interactions Between Emotion and Cognition. In M. S. Gazzaniga, The
Cognitive Neurosciences III (pp. 1005-1015). Cambridge: MIT Press.
Rilling, J. K., Sanfey, A. G., Aronson, J. A., Nystrom, L. E., & Cohen, J. D. (2004). The Neural Correlates of Theory of Mind Within
Interpersonal Interactions. Neuroimage , 22, 1694-1703.
Rizzolatti, G. (2005). The Mirror Neuron System and its Function in Humans. Anatomy and Embryology , 210, 419-421.
Rizzolatti, G., & Craighero, L. (2004). The Mirror Neuron System. Annual Reviews in Neuroscience , 27, 169-192.
Saxe, R. (2006). Four Brain Regions for One Theory of Mind? In J. T. Cacioppo, P. S. Visser, & C. L. Pickett, Social Neuroscience: People
Thinking About Thinking People (pp. 83-101). Cambridge: MIT Press.
Sirgy, J. M., Grewal, D., Mangleburg, T. F., Park, J.-O., Chon, K.-S., Claiborne, C. B., et al. (1997). Assessing the predictive validity of two
methods of measuring self-image congruence. Journal of the Academy of Marketing Science , 25 (3), 229-241.
Smith, S. (2002). Fast Robust Automated Brain Extraction. Human Brain Mapping , 17 (3), 143-155.
Stefanacci, L., & Amaral, D. G. (2002). Some Observations on Cortical Inputs to the Macaque Monkey Amygdala: An Anterograde Tracing
Study. Jopurnal of Comparative Neurology , 451, 301-323.
Walter, H., Abler, B., Ciaramidaro, A., & Erk, S. (2005). Motivating Forces of Human Actions: Neuroimaging Reward and Social
Interaction. Brain Research Bulletin , 67, 368-381.
Whalen, P. J., Rauch, S. L., Etcoff, N. L., McInerney, S. C., Lee, M. B., & Jenike, M. A. (1998). Masked Presentations of Emotional Facial
Expressions Modulate Amygdala Activity without Explicit Knowledge. The Journal of Neuroscience , 18 (1), 411-418.
Woolrich, M. W., Behrens, T. E., Beckmann, C. F., Jenkinson, M., & Smith, S. M. (2004). Multi-level Linear Modelling for FMRI Group
Analysis Using Bayesian Inference. Neuroimage , 21 (4), 1732-1747.
Woolrich, M. W., Ripley, B. D., Brady, J. M., & Smith, S. M. (2001). Temporal Autocorrelation in Univariate Linear Modelling of FMRI
Data. Neuroimage , 14 (6), 1370-1386.
Worsley, K. J. (2001). Statistical analysis of activation images. In P. Jezzard, P. M. Matthews, & S. M. Smith, Functional MRI: An
Introduction to Methods. New York: Oxford University Press.
Zald, D. H. (2003). The Human Amygdala and the Emotional Evaluation of Sensory Stimuli. Brain Research Reviews , 41, 88-123.
Neuromarketing: valence assessments of commercial brands. A
Functional Magnetic Resonance Imaging (fMRI) study.
José Paulo Santos (1) Investigation Unit in Human Development and Psychology (Unidep), ISMAI -
Superior Institute of Maia, Portugal
Applied Economy Department, Economy Faculty, Coruña University, A Coruña, Spain
Sofia Brandão Radiology Department, MRI Unit, São João Hospital, Oporto, Portugal
Daniela Seixas Institute of Histology and Embryology, Faculty of Medicine, Oporto University,
Portugal
Neuroradiology Department of São João Hospital, Oporto, Portugal
(1) Corresponding author: phone: +351 22 9866000
fax: +351 22 9825331
e-mail: jpsantos@ismai.pt
address: Av. Carlos Oliveira Campos
Castelo da Maia
4475-690 Avioso S. Pedro
Portugal
1
Neuromarketing: valence assessments of commercial brands. A Functional Magnetic
Resonance Imaging (fMRI) study.
The scientific knowledge achieved within Neuroscience should be used to understand how
consumers behave. The present work uses a neuroimaging tool, Functional Magnetic Resonance
Imaging (fMRI) to disclose how consumers attribute valences to commercial brands. The results
revealed that participants distinguish between brands that have an emotional and a social relevant
content from those that do not have. We found evidence of correspondence between brain areas
that modulate emotion, and that are involved in mentalizing, valence rating, decision-making,
future strategic planning, and reinforced-learning and reward. These findings may be used as
important markers when studying brands’ emotional and social contents.
Declaration: the authors declare that this article represents an original work and that, until date, has not been
presented or submitted for publication elsewhere.
Introduction
How do consumers think? Every marketeer has posed this question by and a lot of the investigation work within
the Marketing discipline has been trying to search for answers. However, much of that work assumes that the
consumer is a black box, with inputs (from advertising, the social environment, …) which implicate outputs,
normally behaviors. The physical constrains of the organ where the inputs are processed to generate the outputs,
rarely is considered. Neuromarketing constitutes a new approach, where the consumer’s brain is minutely
inquired to better understand how it works and how behaviors are produced.
The present work deals with commercial brands. How are commercial brands perceived by the consumers? How
the eventual emotional and social load that each brand carries is processed and how does it influence the
consumer behavior? None of these questions have yet answers that consider sufficiently the processing of the
brain.
It is widely accepted in the Marketing community that commercial brands should be loaded with symbolic
content, which can be used by the individuals to reinforce their self-concept (Grubb & Grathwohl, 1967;
Banister & Hogg, 2004; Ligas & Cotte, 1999). Self-concept doesn’t boost in singular acts, disconnected from the
environment. By the contrary, it evolves in a process of social experience, nurtured by the reactions of the peers,
so each individual creates his own self-perception. The self-concept emerges from the reactions of parents,
colleagues, teachers and all other relevant mates, and all of these reactions that result from the social interaction
will contribute for the growing of each individual self-concept. Some authors even assume subdivisions of the
global self-concept: actual self-concept, ideal self-concept, social self-concept and ideal social self-concept
(Johar & Sirgy, 1991). This emphasizes the relevance of the social environment and stresses that each individual
has a social perfect state that he wants to reach. To achieve it, he will gather the necessary tools, most of which
are commercial brands, at least in the western culture.
One way to load commercial brands with symbolic content is through stereotypes. Stereotypes are
categorizations of experiences that are part of our understanding of the social world, or sets of ideas and fixed
beliefs sustained by the members of one or more groups, about the members of other groups. So, stereotypes
2
concentrate a set of signs and emotions and, evoking that stereotype, this load is transferred to the brand (Sirgy,
et al., 1997; Jagger, 1998). Through these stereotypes, brands can bear emotional content to their users,
enhancing their self-esteem. Self-esteem is the motivation that carries the actual self-concept to the ideal selfconcept
and the social self-concept to the ideal self-concept in a self-perfecting process.
Commercial brands have emotional content (and as so, can induce emotions in the consumers) and additionally
social relevant content (and as so, can be used by the consumers for social transactions with their peers).
Consequently, there is a triangular connection between each individual, the social group where which he belongs
and commercial brands (Grubb & Grathwohl, 1967).
These models were constructed based on behavioral evidence. But there is no role for the human organ where all
these processes take place: the brain. Where, inside the brain, is the emotional content retained? Where is the
social relevance of the brand filtered? Are there any brain structures that prove that commercial brands have
emotional and social content?
The works of Mitchell et al. (Mitchell, Macrae, & Banaji, 2004; Mitchell, Macrae, & Banaji, 2005) revealed the
brain structures involved in making impressions of people and inanimate objects. The Dorsomedial Prefrontal
Cortex (dmPFC), the Inferior Frontal Gyrus (IFG), and the Orbitofrontal Cortex (OFC) were found to be brain
structures that were able to distinguish between people and objects’ impression formation. For these authors, and
specifically the Dorsomedial Prefrontal Cortex (dmPFC) “indexes the social-cognitive aspects of impression
formation (i.e., understanding the psychological characteristics of another mental agent)” (Mitchell, Macrae, &
Banaji, 2005). This means that the dmPFC is responsible for discriminating social relevant information
considering that commercial brands have social relevant content, we hypothesize that this structure should also
be important in commercial brand processing.
The Anterior Cingulate Cortex (ACC) and the Paracingulate Gyrus (PCG) are structures that correlate with the
process of mentalizing about other individuals, within the Theory of Mind (Adolphs R. , 2001; Rilling, Sanfey,
Aronson, Nystrom, & Cohen, 2004; Saxe, 2006; Gallagher & Frith, 2003). This means that these structures are
engaged when individuals make inferences about the mental states of others, which is crucial when brand
meaning is formed within the social environment.
On the other way, the Amygdala has been referred as the structure enrolled in the primary emotional processing
(Adolphs, Tranel, & Damásio, 1998; Adolphs R. , 2003; Ashwin, Baron-Cohen, Wheelwright, O'Riordan, &
Bullmore, 2007; Beaucousin, Lacheret, Turbelin, Morel, Mazoyer, & Tzourio-Mazoyer, 2007; Bechara,
Damásio, Damásio, & Lee, 1999; Canli, Sivers, Whitfield, Gotlib, & Gabrieli, 2002; Castelli, 2005; Critchley, et
al., 2000; Norris, Chen, Zhu, Small, & Cacioppo, 2004). The Amygdala “links perceptual representations of
emotional sensory stimuli with the elicitation of behavioral and cognitive responses” (Adolphs R. , 2004), which
places this subcortical region in the center of emotional, and therefore social, processing (Phelps, 2004).
Although, how the brain works is far away from being understood, there is already some scientific evidence that
shed some light over the social relevant and emotion processing. As a result, there is an opportunity to try to
prove that commercial brands have emotional and social content and to try to determine which brain structures
are enrolled in their assessment.
Functional Magnetic Resonance Imaging (fMRI) has emerged in the last decade as the preferred technique in
Social Neuroscience studies. Contrary to other techniques used in Neuroscience research in humans, fMRI is
non-invasive, which means that the risks inherent to this technique are minimal (Huettel, Song, & McCarthy,
2004). FMRI does not use either ionizing radiation or chemical substances. FMRI employs strong magnetic
field, which, to date, albeit the millions of magnetic resonance imaging (MRI) scans that are made every day,
never was connected with any kind of detrimental long term effects. FMRI has a good spatial resolution (up to 1
mm), which means that it is able to image the individualized structures that compose the brain are and it allows
to differentiate which ones are active and which ones are not active during the performance of a certain task.
FMRI relies on the response of the blood vessels that follows brain electrical activity, and as such its temporal
resolution is not excellent, but at least identical to other popular neuroimaging methods like Positron Emission
Tomography (PET). Other relative disadvantages are the physical noise (much attenuated with the use of
auricular protection), the more or less long data acquisitions and the artificial research environment, away from
the reality of everyday life. Considering fMRI’s advantages and disadvantages, it is actually one of the best
imaging methods to innocuously visualize brain function in humans in vivo. Original articles using fMRI as a
methodology have been growing in numbers each year in the worldwide scientific literature, especially in the
field of cognitive neuroscience, which will be also the core of the present study.
3
Materials and methods
Participants
The participants were 6 healthy male and 6 healthy female volunteers, right handed, native Portuguese speakers
with neither history of neurological nor psychiatric disturbances (mean age 28,4 years, 5,4 s. d.; mean schooling
16,2 years, 1,5 s. d.). Informed consent was obtained in all cases. A safety form for MRI was filled by every
participant and discussed with a Neuroradiologist and a Radiographer. This research project was approved by the
Ethics Committee of São João Hospital, Oporto, Portugal.
Behavioral procedures
The paradigm was a mixed design – block and event-related – where as baseline we used words without
emotional content, over a black background. These words were determiners, conjunctions, prepositions or
adverbs. Importantly, we didn’t use any nouns or verbs that could evoke emotions, objects or actions. As
stimulus, we employed commercial brands, with the logos and colors that were characteristic for each and every
one in everyday life. The baseline period was equal to the stimulus period, 30 seconds long. Within each 30
seconds period, 5 slides were visually displayed, 6 seconds each. The slide set was then composed by 16 baseline
periods and 16 stimulus periods, totaling 160 slides.
For the selection of the commercial brands to use as stimulus, 147 students of the Superior Institute of Maia
(ISMAI), Portugal, filled in an inquiry with 237 commercial brands. The purpose of this inquiry was to decide on
the brands most well known. The brands supposedly with emotional content (chosen by the students either with a
“negative” or a “positive” valence) were intermingled pseudo-randomly with the brands with supposedly nonemotional
content (those that received an assessment of “indifferent”).
Before the MRI scanning session, the volunteers filled in an inquiry that had the exactly same sequence of
commercial brands that was within the slide set they were about to visualize inside the MRI scanner. For each
brand the volunteers chose between four states: “unknown”, “negative”, “indifferent”, and “positive”. In this
way, before the run, they trained the brands’ assessments which were then required to be repeated through the
scanning session. These inquiries were used afterwards to construct the basic shapes for the event-related
analysis.
Image acquisition
A whole brain anatomical structural scan was acquired for each volunteer in a Siemens® Trio high field (3 Tesla)
MRI scanner, using a T1-weighted MPRAGE protocol (256 x 256 matrix, FOV = 256 mm, 3.0 mm axial slices).
Functional images were acquired using T2*-weighted EPI (TR = 3000 ms, TE = 30 ms, 64 x 64 matrix, FOV =
192 mm, 3.0 mm axial slices). Gradient field mapping was additionally acquired for image quality control.
A trained Neuroradiologist reviewed all the anatomical scans. No incidental findings were found.
Image analysis
FMRI data processing was carried out using FEAT (FMRI Expert Analysis Tool) Version 5.90, part of FSL
(FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl).
The following pre-statistics processing was applied; motion correction using MCFLIRT (Jenkinson, Bannister,
Brady, & Smith, 2002); slice-timing correction using Fourier-space time-series phase-shifting; non-brain
removal using BET (Smith, 2002); spatial smoothing using a Gaussian kernel of FWHM 5mm; grand-mean
intensity normalization of the entire 4D dataset by a single multiplicative factor; highpass temporal filtering
(Gaussian-weighted least-squares straight line fitting, with sigma=30.0s). Time-series statistical analysis was
carried out using FILM with local autocorrelation correction (Woolrich, Ripley, Brady, & Smith, 2001).
Registration to high resolution structural and/or standard space images was carried out using FLIRT (Jenkinson
& Smith, 2001; Jenkinson, Bannister, Brady, & Smith, 2002).
Higher-level analysis was carried out using FLAME (FMRIB's Local Analysis of Mixed Effects) stage 1 only,
i.e., without the final MCMC-based stage (Beckmann, Jenkinson, & Smith, 2003; Woolrich, Behrens,
Beckmann, Jenkinson, & Smith, 2004).
Z (Gaussianised T/F) statistic images were thresholded using clusters determined by Z>2.3 and a (corrected)
cluster significance threshold of P=0.05 (Worsley, 2001).
4
Interesting structures were isolated using ROIs - Region-of-Interest. The masks to pre-threshold the ROIs were
made based on the atlases “Harvard-Oxford Cortical Structural Atlas” and “Harvard-Oxford Subcortical
Structural Atlas” which accompany FSL View v3.0, part of FSL 4.0.
Results
Along the scans, the twelve participants made explicit cognitive assessments of commercial brands. Four
possible valences were available: “unknown”, “negative”, “indifferent”, and “positive”. As chosen brands were
previously filtered by an inquiry, the “unknown” answers were negligible (1%). The remaining answers were
14% for the valence “negative”, 32% for “indifferent” and 53% for “positive”.
Negative valence
The overall activation of negative valence is shown in Figure 1. The respective cluster assignments are listed in
Table 1.
The most remarkable result is that this paradigm produced activations extensively in the whole brain. Of
relevance, are the activations in the Frontal Lobe: Frontal Orbital Cortex, Frontal Pole, Inferior Frontal Gyrus
(both in Pars Opercularis and Pars Triangularis) and Paracingulate Gyrus. With special interest for the present
study, there was also activations in the Insular Cortex, Cingulate Gyrus (Anterior Division) and in the regions
that constitute the Striatum, the Putamen and the Caudate, together with the neighbor Pallidum. A first approach
indicates that, in this task, there is participation of the cognitive functions (usually located in the Frontal Lobe)
and decision-making (which processing usually passes by the Striatum). Also participates the limbic structure
Cingulate Gyrus, where were identified a special class of neurons, the Von Economo neurons or spindle-cells
(Nimchinsky, Gilissen, Allman, Perl, Erwin, & Hof, 1999; Allman, Hakeem, Erwin, Nimchinsky, & Hof, 2001),
which are suspected to detect discrepancies in the environment.
Another part of the data that needs some explanation is the apparent overlap in the Paracingulate Gyrus and in
the Cingulate Gyrus (Anterior Division). The maximum of the cluster (MNI152: -2, 16 42) in the probabilistic
atlases is 68% in the Paracingulate and 18% in the Cingulate. So, it is more probable that the maximum is in the
Paracingulate Gyrus than in the Cingulate Gyrus (Anterior Division). However, the center of gravity of the
cluster of the Paracingulate (MNI152: -1, 23, 37) is 45% in the Paracingulate and 30% in the Cingulate and the
center of gravity of the cluster of the Cingulate (MNI152: -1, 20, 37) is 34% in the Paracingulate and 40% in the
Cingulate. So the conclusion is that this is a cluster that effectively occupies both the Paracingulate Gyrus and
the Cingulate Gyrus (Anterior Division), albeit its maximum intensity is in the Paracingulate Gyrus.
Figure 1 - Activations produced by the negative assessments.
5
Table 1 – Data of the clusters produced by the negative assessments.
Z max Center of Gravity
# Structure
(1)
Cluster
voxels z X Y Z X Y Z
L 724 4.29 -30 26 -2 -40 26 -7
1 Frontal Orbital Cortex
R 400 4.09 34 28 -8 41 24 -7
2 Frontal Pole L 749 3.85 -28 60 -16 -37 53 2
3 Inf. Frontal Gyrus – Pars Opercularis L 749 3.56 -42 12 22 -50 18 10
4 Inf. Frontal Gyrus – Pars Triangularis L 730 3.59 -38 28 -4 49 24 6
L 582 4.29 -30 26 -2 -36 18 -1
5 Insular Cortex
R 373 4.09 34 28 -8 40 20 -6
6 Paracingulate Gyrus L 774 4.42 -2 16 42 -1 23 37
7 Cingulate Gyrus (Anterior Division) L 595 4.42 -2 16 42 -1 20 37
8 Caudate L 195 3.04 -12 10 0 -13 11 3
L 294 3.16 -30 10 0 -21 8 0
9 Putamen
R 244 3.46 22 14 -4 21 9 0
L 128 3.11 -16 6 -2 -17 3 0
10 Pallidum
R 101 3.05 18 6 6 19 4 0
L 655 4.33 -26 -52 -18 -32 -59 -17
11 Temporal Occipital Fusiform Cortex
R 768 5.16 32 -44 -24 34 -51 -19
L 1762 4.92 -26 -92 -18 -28 -78 -15
12 Occipital Fusiform Gyrus
R 1420 4.70 22 -92 -16 29 -78 -15
L 801 4.11 -40 2 42 -40 14 35
13 Middle Frontal Gyrus
R 290 3.68 52 12 38 45 6 43
L 386 4.11 -40 2 42 -38 -1 43
14 Precentral Gyrus
R 496 3.68 52 12 38 47 3 40
15 Occipital Pole L 5354 4.92 -26 -92 -18 0 -94 -4
L 566 3.81 -26 -64 58 -36 -60 47
R 810 4.22 16 Lateral Occipital Cortex (Superior Division) 36 -90 2 31 -88 8
R 511 4.22 -18 -98 4 -27 -90 12
17 Intracalcarine Cortex R 315 4.05 2 -96 -10 -3 -93 -7
All the coordinates are MNI152.
(1) L – left; R – right
Indifferent valence
The overall activation of negative valence is shown in Figure 2. The respective cluster assignments are listed in
Table 2.
Figure 2 - Activations produced by the indifferent assessments.
6
As in the previous section, negative valence, there are activations extensively in the whole brain. Almost the
same structures that activated previously, also registered activations in the indifferent valence. In this valence
there is a supplementary activation in the Hippocampus, a structure usually linked to declarative and mnemonic
memories (Critchley, et al., 2000), encoding relations between items and context. This is crucial when recalling
based on recognition (Paller & Wagner, 2002), which suggests that participants draw the Hippocampus to evoke
memories about the brands.
Table 2 - Data of the clusters produced by the indifferent assessments.
Z max Center of Gravity
# Structure
(1)
Cluster
voxels z X Y Z X Y Z
L 1328 4.90 -40 22 -10 -39 26 -9
1 Frontal Orbital Cortex
R 927 5.17 32 28 -8 38 26 -9
L 2320 4.99 -46 52 -10 -35 50 3
R 959 4.04 2 Frontal Pole 46 50 -16 34 51 -7
R 499 4.01 46 34 32 46 37 20
L 1740 4.55 -48 20 18 -48 16 17
3 Inf. Frontal Gyrus – Pars Opercularis
R 728 4.43 54 16 28 49 18 23
L 1139 4.55 -48 20 18 -48 25 9
4 Inf. Frontal Gyrus – Pars Triangularis
R 856 3.91 54 20 32 47 28 14
L 935 4.90 -40 22 -10 -35 18 -4
5 Insular Cortex
R 682 5.17 32 28 -8 36 20 -6
6 Paracingulate Gyrus L 1400 5.15 -4 18 44 0 26 35
7 Cingulate Gyrus (Anterior Division) L 982 4.94 -4 18 42 0 23 34
L 295 4.59 -24 -30 -10 -24 -28 -9
8 Hippocampus
R 191 4.58 18 -34 -4 22 -32 -5
L 375 4.08 -14 12 0 -12 8 6
9 Caudate
R 321 3.79 8 2 4 13 9 5
L 652 3.47 28 18 -2 24 5 -1
10 Putamen
R 646 4.08 -18 2 4 -22 7 -2
L 395 4.29 -14 2 6 -17 -1 0
11 Pallidum
R 467 4.06 14 0 6 18 -2 0
L 881 4.68 -26 -54 -20 -33 -58 -17
12 Temporal Occipital Fusiform Cortex
R 1027 5.30 32 -44 -24 35 -52 -19
L 1973 5.35 -36 -88 -20 -28 -77 -15
13 Occipital Fusiform Gyrus
R 1624 4.34 20 -92 -16 29 -77 -14
L 1381 4.39 -48 20 20 -43 16 32
14 Middle Frontal Gyrus
R 1301 4.43 54 16 28 46 22 30
L 1120 4.18 -40 12 20 -46 6 28
15 Precentral Gyrus
R 594 4.43 54 16 28 48 5 36
16 Occipital Pole L 6149 5.62 -36 -90 -20 -1 -94 -4
L 2577 4.77 -28 -88 24 -29 -74 34
17 Lateral Occipital Cortex (Superior Division)
R 2305 4.46 26 -88 12 30 -76 29
18 Intracalcarine Cortex R 417 3.94 26 -88 10 1 -92 -3
All the coordinates are MNI152.
(1) L – left; R – right
Positive valence
The overall activation of negative valence is shown in Figure 3. The respective cluster assignments are listed in
Table 3.
As in both previous sections, negative and indifferent valences, there are activations extensively in the whole
brain. Almost the same structures that activated previously, also registered activations in the positive valence. In
this valence there are two supplementary activations: the Frontal Medial Cortex within the Frontal Lobe and the
Amygdala within the Limbic System. These activations have special relevance as they only occurred when
participants attributed the positive rating, but not when the stimuli were indifferent. This suggests that they may
mediate a preference, which is a core interest within Marketing discipline.
7
Table 3 - Data of the clusters produced by the positive assessments.
Z max Center of Gravity
# Structure
(1)
Cluster
voxels z X Y Z X Y Z
1 Frontal Medial Cortex L 232 4.27 -6 46 -22 -7 43 -20
L 1458 4.53 -32 30 -14 -36 28 -11
2 Frontal Orbital Cortex
R 728 3.86 30 38 -14 38 28 -9
L 2883 4.62 -42 48 -10 -29 49 1
3 Frontal Pole
R 608 3.86 30 38 -14 28 45 -14
L 1357 4.21 -50 20 18 -48 16 17
4 Inf. Frontal Gyrus – Pars Opercularis
R 319 3.68 46 8 36 48 16 26
L 972 4.21 -50 20 18 -48 24 8
R 244 3.90 5 Inf. Frontal Gyrus – Pars Triangularis 38 34 12 44 30 16
R 164 3.12 42 32 2 49 25 -4
L 752 4.38 -32 22 -4 -35 18 -3
6 Insular Cortex
R 462 3.68 36 22 -2 38 20 -5
7 Paracingulate Gyrus L 1469 4.17 -6 24 34 -1 24 36
8 Cingulate Gyrus (Anterior Division) L 1165 4.17 -6 24 34 0 21 35
L 86 4.09 -32 -10 -16 -29 -9 -16
9 Amygdala
R 121 3.40 32 -6 -16 30 -3 -18
L 616 4.83 -24 -32 -6 -26 -28 -10
10 Hippocampus
R 356 3.98 24 -32 -2 26 -32 -4
L 359 3.78 -8 10 2 -12 6 7
11 Caudate
R 316 3.73 8 6 8 14 3 10
L 697 3.50 28 -8 -4 24 3 0
12 Putamen
R 561 3.93 -18 4 0 -22 5 1
L 439 3.93 -18 4 0 -18 -3 -1
13 Pallidum
R 559 4.01 14 -4 -4 20 -3 -1
L 1152 4.37 -42 -68 -20 -34 -57 -17
14 Temporal Occipital Fusiform Cortex
R 1407 5.36 32 -42 -68 -20 -34 -57
L 2214 6.24 -34 -82 -22 -28 -77 -15
15 Occipital Fusiform Gyrus
R 1994 4.72 28 -92 -14 29 -76 -14
L 1200 4.16 -28 0 46 -41 15 34
16 Middle Frontal Gyrus
R 592 3.90 38 34 12 44 15 34
L 1041 4.11 -28 -6 50 -44 2 34
17 Precentral Gyrus
R 733 3.88 36 2 50 46 1 41
18 Occipital Pole L 7147 5.06 36 -98 -2 0 -94 -3
L 1903 4.71 -28 -86 22 -27 -79 26
19 Lateral Occipital Cortex (Superior Division)
R 1823 4.63 24 -88 -2 29 -81 19
20 Intracalcarine Cortex L 923 5.03 -20 -88 0 0 -90 -1
21 Supracalcarine Cortex R 333 4.40 2 -96 -10 4 -92 3
All the coordinates are MNI152.
(1) L – left; R – right
Figure 3 - Activations produced by the positive assessments.
8
Contrasts between valences
Table 4 summarizes the statistically significant contrasts between valences and Table 5 contains the data of the
clusters.
Table 4 - Statistically significant contrasts between valences.
Contrast over Negative Indifferent Positive
Negative - No Activations No Activations
Indifferent
- Lateral Occipital Cortex
(Superior Division) (#1)
- No Activations
Positive
- Occipital Pole /
Supracalcarine Cortex /
Intracalcarine Cortex (#2)
- Frontal Medial Cortex /
Paracingulate Gyrus /
Frontal Pole (#3)
-
Table 5 - Data of the clusters that is statistically significant when contrasting between valences.
Z max Center of Gravity
# Structure
(1)
Cluster
voxels z X Y Z X Y Z
#1 Lateral Occipital Cortex (Superior Division) L 468 3.00 -30 -76 28 -20 -77 42
#2 Occipital Pole / Supracalcarine Cortex / Intracalcarine Cortex L 467 3.15 -2 -92 8 0 -87 7
#3 Frontal Medial Cortex / Paracingulate Gyrus / Frontal Pole L 341 3.25 -4 56 0 -4 49 -8
All the coordinates are MNI152.
(1) L – left; R – right
The most important activation occurred between the positive over the indifferent valences. There is a cluster that
occupies the Frontal Medial Cortex and a small region within the Frontal Pole and the ventral part of the
Paracingulate Cortex. This brings special relevance for the Frontal Medial Cortex as it reached statistical
significance when comparing positive rated brands over indifferent.
Discussion
In the positive valence assessment by the subjects, we found brain activations in the Frontal Medial Cortex, in
the Amygdala and in the Supracalcarine Cortex. These areas were not shared by the assessment made of
indifferent valences. The Supracalcarine Cortex is one of the brain regions that participate in visual processing.
The used paradigm was not designed to study visual areas; the complexity of the commercial brand’s logos
compared with the more simple word design used as contrast, might account for this finding, not important for
the purpose of our study.
We found activations in the Amygdala in the positive valence assessment but not in the indifferent valence
assessment, although this difference wasn’t enough to reach significance when contrasting between valences.
Nevertheless, this is a very important activation as normally two roles are assigned to this subcortical brain
structure. The amygdala is involved in reactions to fear, and also filters the emotional content of a stimulus
(Adolphs R. , 2004; Phelps, 2004). It is unlikely that the activations observed in the Amygdala were due to fear,
because it only occurred when the participants rated as “positive” the valence of the commercial brands seen.
“The Amygdala (…) receives highly processed visual information from the anterior temporal cortices, and stores
codes for subsequent processing of such perceptual information in other brain regions. In this way, it can
influence memory, attention, decision making and other cognitive functions on the basis of the social
significance of the stimuli that are being processed” (Adolphs R. , 2003). The Amygdala occupies a crucial role
as a roundabout within the emotional, and even more broadly, within the social processing (Castelli, 2005). We
speculate that, if a commercial brand pretends to reach social relevance, its image within the consumers’ brains
should activate their Amygdales.
The Frontal Medial Cortex was activated in the positive valence assessment, but not again in the indifferent
valence assessment, in this case achieving statistical significance. This structure is also known as Ventromedial
Prefrontal Cortex (vmPFC). The Frontal Medial Cortex and the Amygdala are interconnected structures
(Stefanacci & Amaral, 2002), both enrolled in emotional processing and modulation (Martin & Weisberg, 2003).
The famous case of Phineas Gage, reported by Damásio and co-workers , resulted in a lesion in the vmPFC
(Damásio, 1994). Phineas Gage became unable to have a social appropriate behavior. This is characteristic of
individuals with impaired vmPFC processing, albeit their normal language, memory and perception abilities
(Adolphs R. , 1999). While the Amygdala is more stimuli-driven, generating impulsive reactions, the Frontal
9
Medial Cortex is more “rational”; it is also responsible for processing long-term rewards, which are strategically
planned by the individual (Bechara A. , 2004; Bechara & Damásio, 2005; Adolphs R. , 2006; Montague, King-
Casas, & Cohen, 2006). We hypothesize that self-concept may be represented in the Frontal Medial Cortex as
this is the structure that encompasses future strategies and aims, which means ideal states. The fact that this
structure was evoked only by positive rated stimuli, suggests that commercial brands could act as a reference,
essential for future planning and achieving a social status. As so, the activation of the Frontal Medial Cortex can
be a representation of desire.
The results of the negative valence assessment must be interpreted very carefully. This valence was the less used
by the participants (14%), which means that the data collected can be not enough for the statically tools to
extract results from the raw data. This means that maybe there were activations that didn’t reach the threshold to
be considered, because they were disguised by the experiment’s noise.
There were structures that activated under all stimuli. For example, the Frontal Orbital Cortex, which
anatomically is close to the previously discussed Frontal Medial Cortex. The Frontal Orbital Cortex is a structure
described to be engaged in cultural (i.e. social relevant) transactions (Erk, Spitzer, Wunderlich, Galley, &
Walter, 2002). Generally, this structure is involved in reward processing (Walter, Abler, Ciaramidaro, & Erk,
2005), filtering relevant cues (Kelley & Berridge, 2002; Miller & Cohen, 2001; Pelzmann, Hudnik, & Miklautz,
2005), which is fundamental information within the social environment. Lesions in this area are known to bias
individuals towards improper decisions (Damásio, 1994). Being the Frontal Orbital Cortex specialized in
detecting reward, it is without surprise that we verify that it was activated in all kinds of stimuli, positive,
negative and indifferent, because the participants were judging the value of commercial brands.
In vicinity to both Frontal Medial Cortex and Frontal Orbital Cortex is the Frontal Pole, which also was activated
in all the different types of stimuli. This structure is far large and thought to be far more complex, as several
roles are assigned to distinct subregions. In the work of Mitchell et al. (Mitchell, Macrae, & Banaji, Forming
impressions of people versus inanimate objects: Social-cognitive processing in the medial prefrontal cortex,
2005) there was an activation with a maximum at (MNI: -9, 54, 36) when subjects formed impressions between
people and objects. In the present work, this coordinate was localized in the Frontal Pole, more exactly in a
subregion known as Dorsomedial Prefrontal Cortex – dmPFC. The Dorsomedial Prefrontal Cortex only reached
significant activation in the positive valence assessment. This correspondence is important as those authors
suggested that the Dorsomedial Prefrontal Cortex ”(…) specifically indexes the social-cognitive aspects of
impression formation (i.e., understanding the psychological characteristics of another mental agent)”. As so, the
parallel between people impression formation and commercial brand impression formation can be established,
which is one more argument favoring that brands may have an important role in the social context. Proceeding
with the parallel established, positive rated commercial brands activated this subregion of the Frontal Pole, but
the indifferent rated brands did not. This may suggest that positive rated brands are seen by the individual as
being closer to people (and hence with emotional and social relevant load), but indifferent rated brands are seen
as mere objects.
Discussing further the Frontal Lobe of the brain, all the valence assessments registered activations in the Inferior
Frontal Gyrus, in two subregions named Pars Opercularis and Pars Triangularis. In the left hemisphere, these
structures correspond to what is known as Broca’s area, a region fundamental for language processing (Hickok
& Poeppel, 2007; Matthews, et al., 2003). Intriguingly, the contrast words used didn’t have an emotional content
and neither suggested objects nor actions. As so, non-emotional language areas shouldn’t contrast and, therefore
shouldn’t produce any activations, although language processing is complex and a long way from being
completely understood. Anyway, these activations may suggest that other explanations can exist and these
should be investigated. One hypothesis is that the mirror neurons are supposed to be found within these areas
(Rizzolatti & Craighero, 2004; Rizzolatti, 2005). It is believed today that the role of the mirror neurons is far
more complex than just mirroring actions of other individuals. They are supposed to have an important role in
language, imitation and emotions (Carr, Iacoboni, Dubeau, Mazziotta, & Lenzi, 2003; Gallese, Keysers, &
Rizzolatti, 2004). As the reading process should have been canceled due to the lack of contrast between the
stimulus and the baseline in our experiment, and still we could find activations in these areas, it can be
hypothesized that brands are symbols that humans can use for imitation or for emotion decoding. Further
investigation, with paradigms more sensible for this concern, should confirm or not this trend.
The Insula is believed to have a relay role between action representation within the Prefrontal Cortex and the
Limbic System, linking the mirror neuron system (Carr, Iacoboni, Dubeau, Mazziotta, & Lenzi, 2003). The
Insular activation in our experiment confers to the previous hypothesis more consistency, which would load
brands with an important social role, already assumed to have from the Marketing theories.
10
When an individual makes inferences about the mental states of others, he is mentalizing. This is one of the
processes of the Theory of Mind – ToM (Adolphs R. , 2001; Rilling, Sanfey, Aronson, Nystrom, & Cohen,
2004; Saxe, 2006; Gallagher & Frith, 2003). The Paracingulate Gyrus, another structure that was activated
throughout all valence assessments,, was found to be also activated when the process of mentalizing occurs.
Within the theory of Symbolic Interactionism (Ligas & Cotte, 1999) the value of a brand is asserted within the
social group. The Symbolic Interactionism is a complex play between the social action, the self-reflexive nature
of the individual and the negotiation of each one’s self-concept within the social context. As so, Theory of Mind
plays a crucial role, as each individual, along the transactional process, must infer the mental states (beliefs,
aims, intentions, strategies, …) of his peers. These activations suggest that participants already played this
“game” before and that each brand had a previous quotation and meaning inside the individual brain.
The Cingulate Gyrus – Anterior Division (also known as Anterior Cingulate Gyrus – ACC) is a structure that has
a special type of neurons, the spindle cells (Nimchinsky, Gilissen, Allman, Perl, Erwin, & Hof, 1999). These
neurons exist in humans, hominids and pongids, but not in lesser apes, which is a signal that is recent in
evolution. It is thought to have a role in the coordination that would be essential in developing the capacity to
focus on difficult problems (Allman, Hakeem, Erwin, Nimchinsky, & Hof, 2001). One possible explanation for
its activation in our study could be the degree of complexity of the task the participants were engaged in
extracting and evaluating commercial brands’ emotional and social content.
The Striatum components, the Putamen and the Caudate Nucleus, participated extensively in this experiment.
Both structures are usually connected with reward and reinforced learning (Critchley, et al., 2000; Kelley &
Berridge, 2002; Montague, King-Casas, & Cohen, 2006). Their neighbor structure, the Pallidum, is also believed
of linking social information to reward circuits (Insel & Fernald, 2004).
Along this discussion, several times it was suggested that commercial brands have both emotional and social
content, because its processing shared common structures, thought to be involved in the processing of those
contents. In the cited literature, parallel was made with seeing faces, learning actions, listening to speech,
cultural objects, and so on, all recognized as relevant in social interactions. Brand processing is ubiquitous in the
brain, engaging thus diverse brain areas, due to its multidimensionality. This is a common point with social
processing, which is also complex and distributed throughout the brain, with many structures contributing for the
overall processing.
Acknowledgments
We thank to Professor Isabel Ramos the support for the use of the MRI scanner.
References
Adolphs, R. (2003). Cognitive Neuroscience of Human Social Behaviour. Nature Reviews Neuroscience , 4, 165-178.
Adolphs, R. (2004). Processing of Emotional and Social Information by the Human Amygdala. In M. S. Gazzaniga, The Cognitive
Neurosciences III (pp. 1017-1030). Cambridge: MIT Press.
Adolphs, R. (1999). Social Cognition and the Human Brain. Trends in Cognitive Sciences , 3 (12), 469-479.
Adolphs, R. (2001). The Neurobiology of Social Cognition. Current Opinion in Neurobiology , 11, 231-239.
Adolphs, R. (2006). What is special about social cognition? In J. T. Cacioppo, P. S. Visser, & C. L. Pickett, Social Neuroscience: People
Thinking About Thinking People (pp. 269-285). Cambridge: MIT Press.
Adolphs, R., Tranel, D., & Damásio, A. R. (1998). The Human Amygdala in Social Judgment. Nature , 393, 470-474.
Allman, J. M., Hakeem, A., Erwin, J. M., Nimchinsky, E., & Hof, P. (2001). The Anterior Cingulate Cortex: The Evolution of an Interface
between Emotion and Cognition. Annals of the New York Academy of Sciences , 935 (1), 107-117.
Ashwin, C., Baron-Cohen, S., Wheelwright, S., O'Riordan, M., & Bullmore, E. T. (2007). Differential Activation of the Amygdala and the
“Social Brain” During Fearful Face-processing in Asperger Syndrome. Neuropsychologia , 45 (1), 2-14.
Banister, E. N., & Hogg, M. K. (2004). Negative symbolic consumption and consumers’ drive for self-esteem: the case of the fashion
industry. European Journal of Marketing , 38 (7), 850-868.
Beaucousin, V., Lacheret, A., Turbelin, M. R., Morel, M., Mazoyer, B., & Tzourio-Mazoyer, N. (2007). FMRI Study of Emotional Speech
Comprehension. Cerebral Cortex , 17 (2), 339-352.
11
Bechara, A. (2004). The role of emotion in decision-making: Evidence from neurological patients with orbitofrontal damage. Brain and
Cognition , 55, 30-40.
Bechara, A., & Damásio, A. R. (2005). The somatic marker hypothesis: A neural theory of economic decision. Games and Economic
Behavior , 52, 336-372.
Bechara, A., Damásio, H., Damásio, A. R., & Lee, G. P. (1999). Different Contributions of the Human Amygdala and Ventromedial
Prefrontal Cortex to Decision-Making. The Journal of Neuroscience , 19 (13), 5473-5481.
Beckmann, C., Jenkinson, M., & Smith, S. M. (2003). General Multi-level Linear Modelling for Group Analysis in FMRI. Neuroimage , 20,
1052-1063.
Canli, T., Sivers, H., Whitfield, S. L., Gotlib, I. H., & Gabrieli, J. D. (2002). Amygdala Response to Happy Faces as a Function of
Extraversion. Science , 296, 2191.
Carr, L., Iacoboni, M., Dubeau, M. C., Mazziotta, J. C., & Lenzi, G. L. (2003). Neural Mechanisms of Empathy in Humans: A Relay from
Neural Systems for Imitation to Limbic Areas. Proceedings of the National Academy of Sciences , 100 (9), 5497-5502.
Castelli, F. (2005). Understanding Emotions from Standardized Facial Expressions in Autism and Normal Development. Autism , 9 (4), 428-
449.
Critchley, H., Daly, E., Philips, M., Brammer, M., Bullmore, E., Williams, S., et al. (2000). Explicit and Implicit Neural Mechanisms for
Processing of Social Information from Facial Expressions: A Functional Magnetic Resonance Imaging Study. Human Brain Mapping , 9 (2),
93-105.
Damásio, A. R. (1994). Descarte’s Error—Emotion, Reason and the Human Brain. New York: Penguin Putnam.
Erk, S., Spitzer, M., Wunderlich, A. P., Galley, L., & Walter, H. (2002). Cultural Objects Modulate Reward Circuitry. Neuroreport , 13 (18),
2499-2503.
Gallagher, H. L., & Frith, C. D. (2003). Functional Imaging of "Theory of Mind". Trends in Cognitive Sciences , 7 (2), 77-83.
Gallese, V., Keysers, C., & Rizzolatti, G. (2004). A Unifying View of the Basis of Social Cognition. Trends in Cognitive Sciences , 8 (9),
396-403.
Grubb, E. L., & Grathwohl, H. L. (1967). Consumer self-concept, symbolism and market behavior: a theoretical approach. Journal of
Marketing , 31, 22-27.
Hickok, G., & Poeppel, D. (2007). The Cortical Organization of Speech Processing. Nature Reviews Neuroscience , 8, 393-402.
Huettel, S. A., Song, A. W., & McCarthy, G. (2004). Functional Magnetic Resonance Imaging. Sunderland: Sinauer Associates.
Insel, T. R., & Fernald, R. D. (2004). How the Brain Processes Social Information: Searching for the Social Brain. Annual Reviews in
Neuroscience , 27, 697-722.
Jagger, E. (1998). Marketing the self, buying and other: dating in a postmodern, consumer society. Sociology , 32 (4), 795-814.
Jenkinson, M., & Smith, S. M. (2001). A Global Optimisation Method for Robust Affine Registration of Brain Images. Medical Image
Analysis , 5 (2), 143-156.
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002). Improved Optimisation for the Robust and Accurate Linear Registration and
Motion Correction of Brain Images. Neuroimage , 17 (2), 825-841.
Johar, J. S., & Sirgy, J. M. (1991). Value-expressive versus utilitarian advertising appeals: when and why to use which appeal. Journal of
Advertising , 20 (3), 23-33.
Kelley, A. E., & Berridge, K. C. (2002). The Neuroscience of Natural Rewards: Relevance to Addictive Drugs. The Journal of Neuroscience
, 22 (9), 3306-3311.
Ligas, M., & Cotte, J. (1999). The process of negotiating brand meaning: a symbolic interactionist perspective. Advances in Consumer
Research , 26 (1), 609-614.
Martin, A., & Weisberg, J. (2003). Neural Foundations for Understanding Social and Mechanical Concepts. Cognitive Neuropsychology , 20
(3/4/5/6), 575-587.
Matthews, P. M., Adcock, J., Chen, Y., Fu, S., Devlin, J. T., Rushworth, M. F., et al. (2003). Towards Understanding Language Organisation
in the Brain using fMRI. Human Brain Mapping , 18, 239-247.
12
Miller, E. K., & Cohen, J. D. (2001). An Integrative Theory of Prefrontal Cortex Function. Annual Reviews in Neuroscience , 24, 167-202.
Mitchell, J. P., Macrae, C. N., & Banaji, M. R. (2004). Encoding specific effects of social cognition on the neural correlates of subsequent
memory. Journal of Neuroscience , 24 (21), 4912-4917.
Mitchell, J. P., Macrae, C. N., & Banaji, M. R. (2005). Forming impressions of people versus inanimate objects: Social-cognitive processing
in the medial prefrontal cortex. Neuroimage , 26 (1), 251-257.
Montague, P. R., King-Casas, B., & Cohen, J. D. (2006). Imaging Valuation Models in Human Choice. Annual Reviews in Neuroscience ,
29, 417-448.
Nimchinsky, E. A., Gilissen, E., Allman, J. M., Perl, D. P., Erwin, J. M., & Hof, P. R. (1999). A Neuronal Morphologic Type Unique to
Humans and Great Apes. Proceedings of the National Academy of Sciences USA , 96, 5268-5273.
Norris, C. J., Chen, E. E., Zhu, D. C., Small, S. L., & Cacioppo, J. T. (2004). The Interaction of Social and Emotional Processes in the Brain.
Journal of Cognitive Neuroscience , 16 (10), 1818-1829.
Paller, K. A., & Wagner, A. D. (2002). Observing the Transformation of Experience Into Memory. Trends in Cognitive Sciences , 6 (2), 93-
102.
Pelzmann, L., Hudnik, U., & Miklautz, M. (2005). Reasoning or Reacting to Others? How Consumers Use the Rationality of Other
Consumers. Brain Research Bulletin , 67, 438-442.
Phelps, E. A. (2004). The Human Amygdala and Awareness: Interactions Between Emotion and Cognition. In M. S. Gazzaniga, The
Cognitive Neurosciences III (pp. 1005-1015). Cambridge: MIT Press.
Rilling, J. K., Sanfey, A. G., Aronson, J. A., Nystrom, L. E., & Cohen, J. D. (2004). The Neural Correlates of Theory of Mind Within
Interpersonal Interactions. Neuroimage , 22, 1694-1703.
Rizzolatti, G. (2005). The Mirror Neuron System and its Function in Humans. Anatomy and Embryology , 210, 419-421.
Rizzolatti, G., & Craighero, L. (2004). The Mirror Neuron System. Annual Reviews in Neuroscience , 27, 169-192.
Saxe, R. (2006). Four Brain Regions for One Theory of Mind? In J. T. Cacioppo, P. S. Visser, & C. L. Pickett, Social Neuroscience: People
Thinking About Thinking People (pp. 83-101). Cambridge: MIT Press.
Sirgy, J. M., Grewal, D., Mangleburg, T. F., Park, J.-O., Chon, K.-S., Claiborne, C. B., et al. (1997). Assessing the predictive validity of two
methods of measuring self-image congruence. Journal of the Academy of Marketing Science , 25 (3), 229-241.
Smith, S. (2002). Fast Robust Automated Brain Extraction. Human Brain Mapping , 17 (3), 143-155.
Stefanacci, L., & Amaral, D. G. (2002). Some Observations on Cortical Inputs to the Macaque Monkey Amygdala: An Anterograde Tracing
Study. Jopurnal of Comparative Neurology , 451, 301-323.
Walter, H., Abler, B., Ciaramidaro, A., & Erk, S. (2005). Motivating Forces of Human Actions: Neuroimaging Reward and Social
Interaction. Brain Research Bulletin , 67, 368-381.
Whalen, P. J., Rauch, S. L., Etcoff, N. L., McInerney, S. C., Lee, M. B., & Jenike, M. A. (1998). Masked Presentations of Emotional Facial
Expressions Modulate Amygdala Activity without Explicit Knowledge. The Journal of Neuroscience , 18 (1), 411-418.
Woolrich, M. W., Behrens, T. E., Beckmann, C. F., Jenkinson, M., & Smith, S. M. (2004). Multi-level Linear Modelling for FMRI Group
Analysis Using Bayesian Inference. Neuroimage , 21 (4), 1732-1747.
Woolrich, M. W., Ripley, B. D., Brady, J. M., & Smith, S. M. (2001). Temporal Autocorrelation in Univariate Linear Modelling of FMRI
Data. Neuroimage , 14 (6), 1370-1386.
Worsley, K. J. (2001). Statistical analysis of activation images. In P. Jezzard, P. M. Matthews, & S. M. Smith, Functional MRI: An
Introduction to Methods. New York: Oxford University Press.
Zald, D. H. (2003). The Human Amygdala and the Emotional Evaluation of Sensory Stimuli. Brain Research Reviews , 41, 88-123.
No comments:
Post a Comment