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Multiple “buy buttons” in the brain: Forecasting chocolate sales at point-of-sale based on functional brain activation using fMRI


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We set out to forecast consumer behaviour in a supermarket based on functional magnetic resonance imaging (fMRI). Data was collected while participants viewed six chocolate bar communications and product pictures before and after each communication. Then self-reports liking judgement were collected. fMRI data was extracted from a priori selected brain regions: nucleus accumbens, medial orbitofrontal cortex, amygdala, hippocampus, inferior frontal gyrus, dorsomedial prefrontal cortex assumed to contribute positively and dorsolateral prefrontal cortex and insula were hypothesized to contribute negatively to sales. The resulting values were rank ordered. After our fMRI-based forecast an instore test was conducted in a supermarket on n = 63.617 shoppers. Changes in sales were best forecasted by fMRI signal during communication viewing, second best by a comparison of brain signal during product viewing before and after communication and least by explicit liking judgements. The results demonstrate the feasibility of applying neuroimaging methods in a relatively small sample to correctly forecast sales changes at point-of-sale.
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Multiple buy buttonsin the brain: Forecasting chocolate sales at
point-of-sale based on functional brain activation using fMRI
Simone Kühn
, Enrique Strelow
, Jürgen Gallinat
UniversityClinic Hamburg-Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246 Hamburg, Germany
Justus-Liebig University of Gießen, Department of Business Administration and Economics, Licher Straße 74, 35394 Gießen, Germany
abstractarticle info
Article history:
Received 7 December 2015
Revised 5 May 2016
Accepted 6 May 2016
Available online xxxx
We set out to forecast consumer behaviour in a supermarket based on functional magnetic resonance imaging
(fMRI). Data was collected while participants viewed six chocolate bar communications and product pictures
before and after each communication. Then self-reports liking judgement were collected. fMRIdata was extract-
ed from aprioriselected brain regions: nucleusaccumbens, medial orbitofrontalcortex, amygdala, hippocampus,
inferior frontal gyrus, dorsomedial prefrontal cortexassumed to contributepositively and dorsolateral prefrontal
cortex and insula were hypothesized to contribute negatively to sales. The resulting values were rank ordered.
After our fMRI-based forecast an instore test was conducted in a supermarket on n = 63.617 shoppers. Changes
in sales werebest forecasted by fMRI signal during communication viewing, second bestby a comparison of brain
signal during product viewing before and after communication and least by explicit liking judgements.
The results demonstrate the feasibility of applying neuroimaging methods ina relatively small sample to correct-
ly forecast sales changes at point-of-sale.
© 2016 Published by Elsevier Inc.
forecasting sales
reward processing
The notion of using neuroscientic methods in marketing research
has become more and more established, as popular science book titles
such as Neuromarketing: Understanding the Buy Buttons in Your
Customer's Brain,Brainuence: 100 Ways to Persuade and Con-
vince Consumers with Neuromarketing,Unconscious Branding:
How Neuroscience Can Empower and Inspire Marketingsuggest.
However, in daily practice of marketers classical explicit (meaning
consciously accessible to the participant) market research tech-
niques, such as focus groups and surveys, are commonly used to pro-
vide answers to questions such as which of three different
advertisements is going to be successful on the market (Ariely and
Berns, 2010). The use of implicit (meaning not necessarily con-
sciously accessible to the participant) neuroscientic methods in
contrast, such as electroencephalography (EEG) focussing on event
related potentials (ERPs) or functional magnetic resonance imaging
(fMRI) measuring the so-called blood oxygen level dependent
(BOLD) effect in the brain seems still quite rare. Instead the common
practice of current neuromarketing approaches relies on deriving
abstract knowledge and principles from neuroscientic studies to
guide consulting. This may originate from the fact that most of the
published studies on neuromarketing are rather academic and do
not lend themselves to immediate application to hands-on market-
ing problems. However, these previous reports may provide a valid
basis for the selection of brain regions that could potentially be
relevant in forecasting of shopper behaviour in response to adver-
tisement and more precisely perhaps: forecasting actual consumer
decisions at the point-of-sale.
In a seminal experimental study Knutson and colleagues asked par-
ticipants to observe pictures of products in an MRI scanner and provide
manual responses to indicate a purchase decision, at the end of the ex-
perimenttwo trials were selected to count and subjects actually bought
the items (Knutson et al., 2007). The fMRI data indicated that activity in
nucleus accumbens (NAcc) was associated with a preference for the
product, whereas high prices elicited activation in the insula (Ins) and
reduced activity in the medial orbitofrontal cortex (mOFC). Although
the purchase decision was situated in a laboratory context, and was
based on the presentation of different pictures of products only,the de-
cision whether to buy for the suggested price was accompanied by
higher activity in NAccand mOFC and the decision not to buy by Ins ac-
tivity. This implies that when trying to predict purchases Ins activity
should be considered as a prohibiting factor. Most recently, a study
succeeded in forecasting aggregated market-level elasticities of televi-
sion ads from NAcc (ventral striatal) brain activity measured by
means of fMRI (Venkatraman et al., 2015). Likewise real-life success of
people in the request of microloans on the Internet have been forecast-
ed by neural activity in NAcc in response to photographs of the re-
questers (Genevsky and Knutson, 2015). Similarly, we have recently
demonstrated that NAcc activity is also observed when participants
see their favourite brand label and when anticipating the receipt of a
particular Coke drink (Kuhn and Gallinat, 2013). Likewise, willingness
to pay has been shown to be associated with activity in mOFC in an
NeuroImage xxx (2016) xxxxxx
Corresponding author.
E-mail address: (S. Kühn).
YNIMG-13178; No. of pages: 7; 4C: 3, 4
1053-8119/© 2016 Published by Elsevier Inc.
Contents lists available at ScienceDirect
journal homepage:
Please citethis article as: Kühn, S., et al., Multiple buy buttonsin the brain: Forecasting chocolate sales at point-of-sale based on functionalbrain
activation using f, NeuroImage (2016),
experiment where subjects had to place bids on the right to eat different
foods (Plassmann et al., 2007, 2010). Interestingly, in these willingness
to pay studies the dorsolateral prefrontal cortex (DLPFC) seemed to play
a similar role as the mOFC when participant were explicitly asked to es-
timate how much money they would be willing to spend on food. How-
ever, this may be due to a working memory process elicited by the task
that requires recall of previous bids to put the current bid into perspec-
tive. In particular since a study investigatingthe effects of electoralcam-
paigns on changes in attitude towards the political candidate in
questionrevealed that higher activation of DLPFC leadmore negative at-
titude changes (Kato et al., 2009). In line with the interpretation that
mOFC signals pleasantness (Kuhn and Gallinat, 2012), mOFC activation
during viewing of the electoral campaigns predicted positive attitude
changes towards the candidate. Asimilar pattern of results has beende-
scribed in a study where participants had to make binary choices be-
tween either coffee or beer brands. When one of the shown products
was the market leader this was accompanied by a decrease in DLPFC
and in increase of mOFC activation (Deppe et al., 2005).
Another brain structure that has also previously been implicated in
reward processing, next to its more widely known involvement of pro-
cessing emotions, is the amygdala (Amyg) (Hampton et al., 2007;
Jenison et al., 2011). Anatomically, the Amyg is connected with the
mOFC, which puts it into an ideal position to inuence the computation
of values (Price, 2003). While trying to predict the outcome of simulated
political voting judgements, candidates that were voted for more fre-
quently elicited stronger activation in bilateral amygdala when seen
by the voters (Rule et al., 2010). In a very similar study seeing the can-
didates that lost real votes elicited stronger activity in the Ins (Spezio
et al., 2008).
In addition to the above-mentioned brain regions that have quite
frequently been reported to be involved in consumer decisions, we
thought about the potential role of the hippocampus (HC), the inferior
frontal gyrus (IFG) and dorsomedial prefrontal cortex (dmPFC) that
may signal a higher degree of personal involvement during the percep-
tion of communications. The HC is known to be activated when memo-
ries are newly formed (Paller and Wagner, 2002). In a study that
investigated the superior persuasive effects of expert statements the
resulting enhanced memory effects were also ascribed to a higher acti-
vation of the HC (Klucharev et al., 2008). Recently it has been shown
that higher engagement of fronto-temporal regions, including the HC
lead to better remembrance of health messages presented an advertise-
ment context (Seelig et al., 2014).
The IFG has been implicated in a multitude of cognitive functions, in-
cluding speech production and response inhibition, however, the IFG
has likewise been identied as an integral part of the brains action un-
derstanding and imitation network (Kuhn et al., 2013). In monkeys
so-called mirror neurons have been found using single-cell recordings
in area F5 of which the human equivalent is assumed to be situated in
the human pars opercularis of the IFG (Molenberghs et al., 2012).
These mirror neurons are active when an animal acts but also when
an animal observes the very same action performed by someone else
(Molenberghs et al., 2009). It has been speculated that these neurons
are important in the process of understanding actions of other people
and by helping to simulate actions thereby contributing to theory of
mind abilities, namely the capacity to attribute mental states to oneself
and to others (Gallese et al., 2004). Similarly, the dmPFC has been impli-
cated in theory of mind processes and mentalizing (Schurz et al., 2014).
It has been suggested that the role of the dmPFC in metalizing is in
thinkingabout theself and in simulatingmental states for similar others
(Mahy et al., 2014) and may therewith reect a higher degree of
engagement when activated during perception of advertisement
The aim of the present study was, to forecast changes of sales of a
highly popular chocolate bar in response to communications placed di-
rectly at point-of-sale using fMRI methods. In order to do so we exposed
a small sample of individuals to communications of that chocolate bar
and measured BOLD signal in the above-mentioned eight ROIs (NAcc,
mOFC, DLPFC, Ins, Amyg, HC, IFG, dmPFC). We used this fMRI signal to
rank order thetested communications according to their potential to in-
crease sales at the population level in a supermarket. In order to com-
pare predictive performance of BOLD signal with subjective report, we
additionally asked participants to rank the ads from least favourite to
most favourite.
Eighteen healthy female subjects with a mean age of 39.9 years
(SD = 10.72, range: 2356 years) participated on the basis of informed
consent. We recruited women exclusively since they are known to be
the typical buyers of chocolate in supermarkets. All womendid indicate
that they regularly buy the product we intended to investigate (3.3
times per week on average, SD = 5.3, range: 112). The study was
conducted according to the Declaration of Helsinki, with approval of
the local ethics committee. All subjects had normal or corrected-
to-normal vision and normal hearing. No subject had a history of
neurological, major medical, or psychiatric disorder. All participants
were right-handed as assessed by the Edinburgh handedness question-
naire (Oldeld, 1971).
fMRI Procedure
During the fMRI experiment, participants were presented with
different pictures including a product picture as well as six different
communications that were generated by the company (the toothbrush
picture was intended as a control communication). They were
instructed to watch the pictures carefully. Each trial started with a
xation cross presented for a jittered duration of 68 s (steps of
500 ms), then a product picture was presented for 2 s (see Fig. 1A for
a schematic overview) and after another xation cross presented for
the jittered duration of 68 s (steps of 500 ms), a communication was
shown for 3 s (Fig. 1B). Finally, after a third xation cross presentation
(jittered duration of 68 s in steps of 500 ms) the product picture was
shown again for 2 s. Taken together each trial had an average length
of 28 s. The experiment consisted of 2 runs, each containing 36 trials,
with an overall duration of approximately 17 min per run. Therewith
each of the six communications was shown 12 times across the experi-
ment. The sequence of stimuli was randomized and we controlled for
transition probabilities of events.
After the fMRI session participants were interviewed and asked to
order the communications according to their liking, while seeing all
six in front of them. Before and after scanning participants were asked
how hungry they felt and how strong their craving for sweets was at
that particular moment in time. Participants responded using a scale
ranging from 1 notatallto 8 very much.
Scanning Procedure
Images were collected on a 1.5 T Avanto MRI scanner system
(Siemens Medical Systems, Erlangen, Germany) using a 20-channel
head coil. First, high-resolution anatomical images were acquired using
a three-dimensional T1-weighted magnetization prepared gradient-
echo sequence (MPRAGE) based on the ADNI protocol (www.adni-info.
org); repetition time = 2.560 s, echo time = 5.05 ms, ip angle =7°;
256 × 256 × 192 matrix, resolution 1x1x1 mm
voxel size. Whole
brain functional images were collected on the same scanner using a
T2*-weighted EPI sequence sensitive to BOLD contrast using sparse sam-
pling (TR = 2000 ms, TE = 35 ms, image matrix = 64 × 64, FOV =
192 mm, ip angle =80°, slice thickness = 3.5 mm, 29 near-axial slices,
aligned with the AC/PC line using parallel imaging implemented in
2S. Kühn et al. / NeuroImage xxx (2016) xxxxxx
Please citethis article as: Kühn, S., et al., Multiple buy buttonsin the brain: Forecasting chocolate sales at point-of-sale based on functionalbrain
activation using f, NeuroImage (2016),
fMRI Data Pre-processing and Main Analysis
The fMRI data were analysed using SPM8 software (Wellcome
Department of Cognitive Neurology, London, UK). The rst 4 volumes
of all EPI series were excluded from the analysis to allow the
magnetisation to reach a dynamic equilibrium. Data processing started
with slice time correction and realignment of the EPI datasets. A mean
image for all EPI volumes was created, to which individual volumes
were spatially realigned by means of rigid body transformations. The
structural image was co-registered with the mean image of the EPI se-
ries. Then the structural image was normalised to the Montreal Neuro-
logical Institute (MNI) template for the random effects analysis. The
normalisation parameters were then applied tothe EPI images to ensure
an anatomically informed normalisation. A commonly applied lter of
8 mm FWHM (full-width at half maximum) was used. Low-frequency
drifts in the time domain were removed by modelling the time series
for each voxel by a set of discrete cosine functions to which a cut-off
of 128 s was applied. The statistical analyses were performed using
the general linear model (GLM). We modelled each picture (product
and presentation of thecommunication) by means of a separate regres-
sor. These vectors were convolved with a canonical haemodynamic re-
sponse function (HRF)and its temporal derivativesto form regressors in
a design matrix. Furthermore, six movement regressors were entered
into the GLM. The parameters of the resulting general linear model
were estimated. We built contrasts between the six different
communication regressors and the implicit baseline as well as between
product presentation after the six different communications compared
to productpresentations before the communications. We extracted per-
cent signal change values in anatomically pre-dened ROIs from these
contrasts: bilateral insula (AAL atlas, (Tzourio-Mazoyer et al., 2002)),
bilateral amygdala (AAL atlas), bilateral medial orbitofrontal cortex
(AAL atlas: frontal middle orbital and gyrus rectus), bilateral hippocam-
pus (AAL atlas), bilateral inferior frontal gyrus (AAL atlas), bilateral
dorsomedial prefrontal cortex (AAL atlas: middle superior frontal),
bilateral dorsolateral prefrontal cortex (Brodmann area 9 and 46) and
bilateral accumbens (Harvard-Oxford subcortical atlas as used in FSL).
For the extraction we used the Matlab scripts from MarsBaR (http:// Then we computed an average forecast
value by summarizing the BOLD signal in the following way:
fMRI sales forecast value ¼NAcc2þmOFC2þAmyg þHC þIFG
WeighingNAcc and mOFC more strongly by multiplying it times two
to account for the stronger and more consistent literature-based
evidence for the involvement of these two brain regions in purchase
decisions (Knutson et al., 2007; Plassmann et al., 2007, 2008, 2010;
Schaefer et al., 2011; Schaefer and Rotte, 2007). We did this separately
Fig. 1. (A) Schematic drawing of the experimental paradigm, (B) Depiction of the six different communicationsused in the present study(top to bottom: woman, couple, hands without
text, hands with text, group, toothbrush), (C) Photograph of the quarter palette placement at point-of-sale in the supermarket.
3S. Kühn et al. / NeuroImage xxx (2016) xxxxxx
Please citethis article as: Kühn, S., et al., Multiple buy buttonsin the brain: Forecasting chocolate sales at point-of-sale based on functionalbrain
activation using f, NeuroImage (2016),
for the BOLD signal during communications and the BOLD change from
product presentation before and after the communication.
Validation of fMRI ndings in a supermarket
After the fMRI data was acquired and the data analysis and there-
with the forecast of sales was nished, the pretested communications
were tested at a point-of-sale of the product in a German supermarket.
The communications were placed behind a quarter palette of the prod-
uct in the direct neighbourhood and in addition to the regular product
placement in the shelf (Fig. 1C). Six weeks were selected during the
year that were not inuenced by festive periods, holiday seasons or
the fact that the product was on special offer and assessed sales of the
product from the quarter palette on each day allowing a direct compar-
ison of the sales between the different communications tested. The
communications were tested in the following order: group, couple,
hands, hands with text, woman and toothbrush each for one week.
The presentation of theproduct on a quarter palette was nothing entire-
ly new for thecustomers since this is a common additional placement in
supermarkets in Germany. Therefore we think we can exclude that the
rst time exposure lead to a signicant increase in sales. Due to the fact
that we selected comparable weeks some placements were presented
weeks apart, which may further reduce order effects. Since the choco-
late bar is so popular in Germany we do not think that customers are
likely to have tried the product the rst time within our acquisition pe-
riod in the supermarket. However future studies may consider to re-
peatedly and randomly assess sales in response to communications in
order to exclude effects of the order of presentation.
Post-hoc comparison of fMRI ROIs and their association with sales
After the sales data was acquired we computed post-hoc Spearman
rho correlation coefcients to explore the association between the sep-
arate ROIsand different models of ROI combination and sales. We would
like to point out that correlationsderived from a sample of n = 6 may be
highly error-prone, however they may offer a way to compare the value
of different ROIs against one another in forecasting sales.
Interview results
When participants were explicitly asked for their opinion on which
communication they liked best ve participants chose thehands without
text (Fig. 1B middle left), four chose the toothbrush (Fig. 1B lower right),
three chose the couple (Fig. 1B upper right) or the group (Fig. 1Blower
left), two chose the woman (Fig. 1B upper left) and one chose the
hands with text (Fig. 1Bmiddleright)(Fig. 2A).
fMRI results based on our a priori hypothesis
We extracted BOLD signal from ROIs in NAcc, mOFC, Amyg, DLPFC,
Ins, HC, IFG and dmPFC. Based on our a-priori hypotheses and derived
from previous literature of reward processing we added the signal of
all brain regions except for DLPFC and Ins, which we subtracted, and
weighted mOFC and NAcc by inserting it twice in the formula. The
resulting activation scores were not related to pre- or post-test hunger
or sweet craving ratings (pN0.12; hunger before scan: 3.25 (SD =
1.96), hunger after scan: 4.69 (2.12), sweet craving before scan: 4.83
(1.98), sweet craving after scan: 5.06 (2.31)). Based on this we comput-
ed the average fMRI-derived sales forecast across participants and rank
ordered the resulting values.
First we did this for the BOLD signal measured during the presenta-
tion of the communication where the group ranked rst, the woman
ranked second, the toothbrush ranked third, the couple ranked fourth,
the hands without text ranked fth, and the hands with text ranked last
(Fig. 2B).
Second we repeated this analysis but this time extracting BOLD
signal measured during the presentation of the product. In order to
evaluate changes caused by showing the communication in between
two product presentations we subtracted BOLD signal during prod-
uct viewing after from the same signal before viewing the communi-
cation (fMRI sales forecast value during product viewing after
communication minus fMRI sales forecast value during product
viewing before communication). These average fMRI-derived sales
forecast change scores were again rank ordered and resulted in the
Fig. 2. Rankingof the six communications based on (A) the explicit judgementof the participants,(B) BOLD signal extracted from eight regions of interest andcomputed by means of our a
priori proposed fMRI-derivedsales prediction value (=NAcc*2 + mOFC*2+ Amyg + HC + IFG+ dmPFC -DLPFC-Ins),(C) BOLD signal changefrom seeing the product after compared to
before thecommunication based on the proposed sales prediction value,(D) behaviouraldata from a eld study measuring actual product salewhen the product was offered on a quarter
palette with the corresponding communication in the back.
4S. Kühn et al. / NeuroImage xxx (2016) xxxxxx
Please citethis article as: Kühn, S., et al., Multiple buy buttonsin the brain: Forecasting chocolate sales at point-of-sale based on functionalbrain
activation using f, NeuroImage (2016),
following order: the couple ranked rst, followed by the group,the
woman,hands with text,toothbrush and then the hands without text
(Fig. 2C).
Actual sales in supermarket
In a eld study we measured actual sales of the product at point-of-
sale on a quarter palette, each communication over a period ofone week
devoid of holidays, festivities, or special offers of the product. The best
selling communication was the group with 59 products from 10.318
customers in that particular week(each 175th shopper bought), follow-
ed by the woman with 57 products when 10.442 visited the market
(each 183rd shopper bought). Third ranked was the couple with 52
sold products from 10.666 customers (each 205th shopper bought),
then the toothbrush with 53 of 10.908 shoppers (each 206th shopper
bought), the hands with text with 51 or 10.764 customers (each 211st
shopper bought) and nally the hands without text with 45 products
sold when 10.519 visited the market (each 234th shopper bought)
(Fig. 2D).
Post-hoc comparison of fMRI ROIs their potential to forecast sales
In order to explore the potential value of the separate ROIs in fore-
casting sales we ran post-hoc correlations between the ROIs as well as
different alternative combinations of the ROIs and sales. The values
from our a priori hypothesized weighted formula resulted in a high cor-
relation coefcient (r
= 0.94, p = 0.005, see Fig. 3). When considering
each ROI separately the following associations were observed: NAcc:
= 0.43, p = 0.40, mOFC: r
= 0.94, p = 0.005, DLPFC: r
= 0.60, p = 0.21, Amyg: r
= 0.14, p = 0.79, HC:
= 0.66, p = 0.16, IFG: r
= 0.37, p = 0.47, dmPFC: r
= 0.09, p =
0.87. The results show that the mOFC is by far the most predictive ROI
when considered in isolation. When the formula contains all a priori se-
lected ROIs but without the weighting, the correlation coefcient
dropped considerably (r
= 0.37, p = 0.47). When the weighting was
only applied to mOFC, not to NAcc, the association likewise dropped
= 0.89, p = 0.019), indicating that the NAcc does play a crucial
role, at least when considering more than one ROI at the same time.
Interestingly, when running a linear regression model, which unfor-
tunately could not be fully estimated due to the small sample size, the
enter, forward and backward method include mOFC (standardized
beta coefcient 0.81), Ins (0.54), HC (0.52), dmPFC (0.27), NAcc
(0.21) but exclude the ROIs DLPFC, Amyg, and IFG. In order to explore
the role of the Ins in more depth, since its contribution seemed to be
positive in the individual bivariate correlation analyses but negative in
the regression analyses and we likewise assumed its inuence on sales
to be negative by subtracting its signal from the other brain regions ac-
tivity we computed our formula once without subtractingIns (r
= 0.89,
p = 0.019) and once with adding instead of subtracting Ins (r
Within the scope of the present study we were able to forecast
changes in sales of a popular chocolate bar by testing six different com-
munications placed in a supermarket by means of fMRI. We chose a par-
ticularly well-known chocolate bar brand in order to ensure that the
customers in the supermarket were well acquainted with it and have
probably all tasted and most likely bought the product before. We ex-
posed a small sample of individuals to the communications and to a
product picture presented before and after the communication while
situated in an MRI scanner and quantied BOLD signal in eight apriori
dened ROIs (NAcc, mOFC, DLPFC, Ins, Amyg, HC, IFG, dmPFC). After
scanning we asked participants explicitly for a ranking according to
their liking of the different communications. Then we tested each of
the communications at point-of-sale in a supermarket (one week
each) and counted sales of the chocolate bar on a population level. Actu-
al sales (Fig. 2D) were best forecasted by a ranking of BOLD signal com-
puted across the apriorisetofROIsduringtheperceptionofthe
communication (Fig. 2B). The rst and the second rank were forecasted
correctly then 3rd and 4th rank were exchanged as well as 5th and 6th.
The change in BOLD signal during product viewing after compared to
before the communication (Fig. 2C) was shown forecasted the actual
behaviour (Fig. 2D) second best and predictability from participants
self-report turned out to perform the worst (Fig. 2A).
The unique feature of the present study is, that this is the rst study
forecasting actual sales in a supermarket on a population level from
neuroimaging data of a relatively small and feasible sample of partici-
pants. Furthermore the ROIs were selected aprioribased on the
neuromarketing literature that is currently available. In these respects
the present study goes beyond most previously published studies in
neuromarketing that successfully tackle brain regions that are related
to certain cognitive and affective processes during product viewing or
simulated shopping situations (Knutson et al., 2007; Plassmann et al.,
2008; Schaefer et al., 2006), but do not actually forecast consumer be-
haviour extending out of the sample to a supermarket environment.
Moreover it is rarely the case that predictive studies actually formulate
a forecast rst and test this a priori forecast independently of the out-
come. Even advanced machine learning algorithms that have by
now also been used in a neuromarketing context (Calvert and
Brammer, 2012; Smith et al., 2014; Tusche et al., 2010)need to take
the actual outcome, e.g. the simulated decision to buy a product, into
account before being able to establish an algorithm that can forecast be-
haviour. An independent test of the resulting algorithm on a completely
new set of data includingnew participants is however almost never un-
dertaken. A frequently observed phenomenon in machine learning
studies is, that the respective algorithm forecasts behaviour very well
under the exact conditions under which the training data set had been
acquired, but does not generalize to novel experimental setups
(Pereira et al., 2009). Our a priori literature-based ROI selection may
be at an advantage here because it is less selective and less targeted to
our particular data set and therewith may provide a higher potential
to generalize across different domains and therewith perform better
in a context of different types of communications and products. Future
studies should be undertaken to demonstrate generalizability across
Fig. 3. Scatterplot depicting the post-hoc association between our a priori proposed fMRI-
derived sales pr ediction valu e (=NA cc*2 + mOFC*2 + Amyg + HC + IFG + dmPFC
-DLPFC-Ins), and actual product sale expressed in percent of the customers that bought
the product on the communication.
5S. Kühn et al. / NeuroImage xxx (2016) xxxxxx
Please citethis article as: Kühn, S., et al., Multiple buy buttonsin the brain: Forecasting chocolate sales at point-of-sale based on functionalbrain
activation using f, NeuroImage (2016),
different consumer goods and test the value of the proposed formula in
other contexts.
To our knowledge only two studies have used a similar design to the
one used in the present study. One predicted behaviour in the health
sector (Falk et al., 2012). Smokers saw anti-smoking television cam-
paigns in an fMRI scanner and from this data the study predicted the
call volume of a line taking phone calls from smokers needing help
with quitting, measured after each of the presented campaign was pub-
licly launched. The prediction was based on a single a priori dened ROI
consisting of a small subregion of the medial prefrontal cortex in
Brodmann's area 10, which would correspond to a subsegment of our
mOFC ROI. This ROI was the result from a previous study of the authors
in which they investigated persuasion of messages on the need to use
sunscreens to avoid cancer (Falk et al., 2010). The reported results of
the prediction of smokers' help-seeking behaviour point into a similar
direction as our present ndings on shopper behaviour, namely that
self-report judgements are not predictive of actual behaviour on the
population level, whereas brain activity during viewing of the com-
munication is. The second study compared six methods used in
neuromarketing research namely self-reports, implicit measures,
eye tracking, biometrics, electroencephalography, and fMRI and
found that NAcc activity in fMRI best predicted advertising elasticity
(Venkatraman et al., 2015). The present study is very similar to the
second study, however in contrast we prospectively forecasted
real-life sales in a supermarket with communications that have
never been previously shown.
In post-hoc analyses we focussed on the predictive value of thesingle
ROIs that we summarized in our formula. Albeit our mOFC was consid-
erably larger than the ROI used by Falk et al. (2010) it likewise predicted
the consumer behaviour fairly well, exactly to the same degree as the
result of our more complex ROI formula. Also NAcc seemed to play an
important role in our proposed formula since removing it, decreased
the formulas predictive value, even though the selective predictive
value of NAcc was fairly low. We hypothesize that it is preferable to
take a combination of larger brain regions into account, that are
known to play an important role in approach behaviour in order to
avoid overgeneralization of single results. However, future research is
needed to conrm this hypothesis. Interestingly, none of the other
ROIs that we included in ourformula were predictive of later supermar-
ket sales when looked at individually. However, combination the
information of the individual ROIs was highly predictive of sales. Re-
markably, although Ins on its own was positively (but insignicantly)
associated with sales when looking at the bivariate correlation of both
variables, adding instead of subtracting Ins in our formula worsened
the predictive value to insignicance. Since excluding Ins from the for-
mula altogether also lead to a drop in predictive value we conclude
that Ins indeed contributed negatively to the prediction of product
sales as we hypothesized before data acquisition in the supermarket.
At rst sight it might seem odd that the forecast is actually better
outside thetested sample (in the supermarket) than within the sample
when taking the self-report data of the very same subject into account.
However, many previous studies on consumer behaviour have indicat-
ed that consumer preferences are frequently constructed in the mo-
ment people are being asked and are often based on consumers
actions, which means that the causal path is not that preferences deter-
mine behaviour, but instead behaviour determines preferences (Ariely
and Norton, 2008). When consumers were for example asked to choose
jam or tea after tasting two differentkinds they were later on oftentimes
not able to tell when the product was switched unbeknownst of them.
In these cases they were giving reasons for choosing a product that
they had actually never chosen (Hall et al., 2010). The present data
goes beyond this notion and suggests that fMRI is not necessarily a
good predictor for the verbalizable preference judgements but rather
for consumers' actual purchase actions in the supermarket.
To summarize the present ndings,wewereabletoforecastchoco-
late bar sales in a supermarket based on BOLD fMRI signal during
viewing of communications that were later on placed behind a quarter
palette at point-of-sale. The ROIs consisting of NAcc, mOFC, Amyg, HC,
IFG, dmPFC that were assumed to contribute positively to later sales
and DLPFC and Ins that were predicted to contribute negatively to
sales, were selected aprioriand based on prior neuroimaging literature
therefore uninuenced by the resulting sales changes acquired in a Ger-
man supermarket. Interestingly, the forecast, a rank order based on the
signal during communication viewing, was superior to the forecast
based on the changes during product viewing after as compared with
before the communication was shown. However both were more accu-
rate than the explicit self-report judgement of the participants. Post-hoc
correlation and regression analyses show that mOFC reaches a similar
predictive value as our formula, but we speculate that the combination
of multiple ROIs may lead to forecasts that generalize to new datasets.
Future research is needed to test this explicitly. The present results
demonstrate the feasibility to use neuroimaging methods in a relatively
small sample of participants to forecast the inuence of communica-
tions on the actual consumer behaviour at the point-of-sale.
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... Chocolate sales in supermarket Brain activation patterns in valuation network forecasted better the real supermarket sales of chocolate bars than the participants' behavioral judgment. Kühn et al., 2016 Online microloan money lending Both NAcc and MPFC activities predicted individual lending choices and NAcc activity forecasted loan appeal success on the Internet. The predictive power of neural signals was greater than those of the behavioral choices. ...
... In 2016, Kühn and colleagues did FMRI experiment to test what kind of chocolate commercials promote most sales in the grocery store (Kühn et al., 2016). Researchers showed six versions of a well-known chocolate brand to the participants (n = 18) in the FMRI-scanner. ...
... After the FMRI data was acquired chocolate brand were tested at a point-of-sale of the product in a German supermarket; thus, allowing a direct comparison of the sales between the different advertisements tested. Again, the sample's mean brain activation patterns in valuation network forecasted better the real sales of chocolate bars in supermarket, whereas the participants' behavioral judgment did not (Kühn et al., 2016). The predictive power of the valuation network was confirmed also for adolescents by Berns and Moore (2012) for music purchases. ...
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Despite the success of artificial intelligence (AI), we are still far away from AI that model the world as humans do. This study focuses for explaining human behavior from intuitive mental models’ perspectives. We describe how behavior arises in biological systems and how the better understanding of this biological system can lead to advances in the development of human-like AI. Human can build intuitive models from physical, social, and cultural situations. In addition, we follow Bayesian inference to combine intuitive models and new information to make decisions. We should build similar intuitive models and Bayesian algorithms for the new AI. We suggest that the probability calculation in Bayesian sense is sensitive to semantic properties of the objects’ combination formed by observation and prior experience. We call this brain process as computational meaningfulness and it is closer to the Bayesian ideal, when the occurrence of probabilities of these objects are believable. How does the human brain form models of the world and apply these models in its behavior? We outline the answers from three perspectives. First, intuitive models support an individual to use information meaningful ways in a current context. Second, neuroeconomics proposes that the valuation network in the brain has essential role in human decision making. It combines psychological, economical, and neuroscientific approaches to reveal the biological mechanisms by which decisions are made. Then, the brain is an over-parameterized modeling organ and produces optimal behavior in a complex word. Finally, a progress in data analysis techniques in AI has allowed us to decipher how the human brain valuates different options in complex situations. By combining big datasets with machine learning models, it is possible to gain insight from complex neural data beyond what was possible before. We describe these solutions by reviewing the current research from this perspective. In this study, we outline the basic aspects for human-like AI and we discuss on how science can benefit from AI. The better we understand human’s brain mechanisms, the better we can apply this understanding for building new AI. Both development of AI and understanding of human behavior go hand in hand.
... Not limited to music albums, the advertising effect of printer poster can also be accurately predicted. In analyzing the neural activity of participants' viewing advertising poster for chocolate bars at different times, Kühn et al. (2016) assigned different weight to different brain region and successfully predicted the sale ranking of chocolate bars at different times, which was not possible for self-report. ...
... Some scholars have verified the reliability of fNIRS in advertising effect research by repeating previous fMRI experiments (Krampe et al., 2018;Gier et al., 2020;Meyerding and Mehlhose, 2020). Gier et al. (2020) repeated Kühn et al. (2016) study on the advertising effect of chocolate bars by measuring the neural activity of dlPFC, and obtained a high accuracy. Some scholars have also used fNIRS to measure neural activity in the dlPFC to reveal a variety of factors that influence the effectiveness of advertising, such as gender differences , preference differences (Qing et al., 2021), etc. ...
... Bonferroni correction was used to correct the t-test results. The ranking method of activation results refers to Kühn et al. (2016) and Gier et al. (2020). Channel 4,6,7,9,16,18,19, and 21 were selected as the comparison channels, and the highest value of corresponding t-value of the channels was selected as the ranking basis. ...
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A large number of scholars have conducted detailed studies on the effectiveness of commercial advertising by using neuroimaging methods, but only a few scholars have used this method to study the effectiveness of public service announcements (PSAs). To research the relationship between the effectiveness of PSAs and the audience’s implicit awareness, functional near-infrared spectroscopy (fNIRS) was employed to record the neural activity data of participants in this study. The results showed that there was a correlation between activation of dorsolateral prefrontal cortex (dlPFC) and the effectiveness of PSAs; The activation of the dlPFC could also be used as an indicator to represent the appeal of advertising content. The results means that neuroimaging tool can also be used to investigate the effectiveness of PSAs, not just commercial advertisements and a few PSAs study, and that neural activity can predict and improve the effectiveness of PSAs before they are released.
... Ultimately, of course, the success of packaging designs is reflected in long-term sales, though here there simply tends to be less publically available research (Sugermeyer, 2021;cf. Kroese et al., 2016;Kühn et al., 2016). ...
... Assess expectations associated with design features embedded in packaging prototype (colour &/or shape/curvilinearity: Baptista et al., 2021;Matthews et al., 2019;Piqueras-Fiszman et al., 2013;Plasschaert, 1995;Tijssen et al., 2017;lines;Salgado-Montejo et al., 2015b). Assess impact of visual design decision on (short-/long-term) sales feature (e.g., colour or positioning): Sugermeyer, 2021; cf., Kühn et al., 2016;Kroese et al., 2016). [Little of the sales data makes it into the public domain, & anyway linking sales to specific design decisions is tricky.] ...
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A rapidly growing body of empirical research has recently started to emerge highlighting the connotative and/or semiotic meanings that consumers typically associate with specific abstract visual design features, such as colours (either when presented individually or in combination), simple shapes/curvilinearity, and the orientation and relative position of those design elements on product packaging. While certain of our affective responses to such basic visual design features appear almost innate, the majority are likely established via the internalization of the statistical regularities of the food and beverage marketplace (i.e. as a result of associative learning), as in the case of round typeface and sweet-tasting products. Researchers continue to document the wide range of crossmodal correspondences that underpin the links between individual visual packaging design features and specific properties of food and drink products (such as their taste, flavour, or healthfulness), and the ways in which marketers are now capitalizing on such understanding to increase sales. This narrative review highlights the further research that is still needed to establish the connotative or symbolic/semiotic meaning(s) of particular combinations of design features (such as coloured stripes in a specific orientation), as opposed to individual cues in national food markets and also, increasingly, cross-culturally in the case of international brands.
... But the first study under the neuromarketing term was conducted by McClure, et al. [5], which was highly contributed to shifting the neuromarketing field from a pure study to a practical study. Neuromarketing is a multidisciplinary field, measuring the subconscious and unconscious responses of consumers toward advertising, marketing, and branding; thereby enriching us with valuable information about consumers behavior [6,7]. ...
Despite the technological advancements in neuroimaging and physiological technologies, studies about using this technology to study the neural correlates of consumers' behavior toward external stimuli remain unclear in the academic literature. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework in this article to select relevant articles for this study. We extracted and analyzed fifty-six articles from the Web of Science (WoS) database to answer the research questions. We found eight common methods, as follow: (i) neuroimaging tools such as fMRI, fNIRS, and EEG used to study the neural responses of emotional and cognitive processes, (ii) physiological tools such as ET, EMG, GSR, ECG, and IAT to study eye movements, fixation, pupil dilation, consumers’ attitudes, visual attention, heart rate, zygomatic and corrugator facial muscles toward environment stimuli such as machines. We hope this article provides valuable insights into neuroimaging and physiological technology guiding new practitioners and researchers to choose the appropriate tool to conduct the experiment and get high-quality and reliable results.
... For instance, food commercials have been shown to elicit a significantly larger neural response than their non-food counterparts in those parts of the brain (e.g., the bilateral cuneus) that are thought to modulate food craving (Yeung, 2021). Neural responses to food ads have also been shown to correlate with the sales of indulgent foods at the point-of-sale (Kühn, Strelow, & Gallinat, 2016). What is more, and as we will see later, the latest visual-enabling technologies are now starting to offer the consumer the opportunity to interact with food virtually (Velasco, Obrist, Petit, & Spence, 2018). ...
In recent years, a growing number of academic researchers, as well as many marketing and design practitioners, have uncovered a variety of factors that would appear to enhance the visual attractiveness, or deliciousness, of food images to the typical consumer. This review, which contains both narrative and systematic elements, critically evaluates the literature concerning the various factors influencing the eye appeal of food images, no matter whether there is an edible food stimulus physically present in front of the viewer or not. We start by summarizing the evidence concerning the human brain’s ability to rapidly determine energy-density in a visual scene and pay attention accordingly. Next, we focus on the importance of embodied mental simulation when it comes to enhancing visual deliciousness. Thereafter, we review the literature on the importance of visual aesthetic features in eye-appeal. The wide range of visual attributes that help to enhance food attractiveness include symmetry, shape, freshness, glossiness, dynamic-presentation, etc. The review concludes with sections on the importance of background/ambient lighting/colour, and the tricks used by those who digitally manipulate images. Taken together, therefore, many different factors ultimately influence the visual deliciousness of food images.
... Por otra parte, de forma paralela se apoya la propuesta (Derbyshire et al., 2014;Raab et al., 2011;Spinella et al., 2007) de quienes señalan que los individuos que realizan compras compulsivas muestran deficiencias cognitivas, dificultades en la inhibición de sus respuestas y en el control de impulsos, y poseen menos autocontrol. Adicionalmente, los procesos de inhibición permiten asumir cierta actividad en la corteza orbitofrontal (OFC) y la corteza prefrontal dorsolateral (DLFC) mientras se disponen a gastar (Kühn et al., 2016;Plassmann, et al., 2007), y quien presenta problemas con el control de su dinero no puede percatarse de los gastos excesivos que realiza, así como tampoco reconoce los síntomas que lo impulsan a una compra compulsiva. ...
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Psychology and neuroscience offers new perspectives to understand consumer and economic behaviour. Neuroeconomics provides a new frame of reference to understand the way in which the neuroanatomical structures of the brain are involved in the financial decisions of people. Currently, measurement scales are an application alternative to assess people's executive functions and cognitive inhibition quickly. In the present study for the evaluation of cognitive inhibition we will use the Stroop Test (Golden, 1994), which examines the cognitive processes associated with cognitive flexibility; the interference resistance from external stimuli and its effect on behaviour. The plates that make up the Stroop test present different possibilities for analysis and interpretation. Within neuroeconomics, there is an area that investigates how cognitive and affective regulation is critical to achieve economic results, in addition to investigating the problems caused by consumption and spending that people have in their daily lives. There is research shown that individuals who make compulsive purchases show cognitive deficiencies and difficulties in inhibiting their responses. Furthermore, compulsive purchases correlate with financial executive functioning, particularly with impulse control, organization and planning, showing that compulsive purchases are not limited only to impulse control. In Latin America and particularly in Mexico, there are few studies on neuroeconomics or consumer neuroscience, so we consider that this research is an innovative contribution to the subject in our region. In this context, the objective of the research is to identify the association between cognitive inhibition and the money university students spend. This research evaluated the association between cognitive inhibition and the money university students spend. 40 university students participated, 47.5% men and 52.5% women, between 18 and 25 years, from the City of Querétaro, Mexico. Cognitive inhibition was evaluated with the Stroop Test. In addition, sociodemographic data and monthly expenses were asked. The results descriptively detailed the level of youth spending and the Stroop effect variables. Young people have mean scores in Word, Color, Word-Color and Interference, according to the established parameters. Regarding monthly expenses, it is observed that on average they spend $666 Mexican pesos (34.04 USD / 31.13 EUR). In addition, a deficit was found in the inhibitory control related to an increase in the level of expenditure made by university students, that is, those who spend and buy more have difficulties in their cognitive inhibition (self-control). Inhibitory control is associated with age and this time with the level of money spent. Additionally, the inhibition processes allow to assume certain activity in the orbitofrontal cortex (OFC) and the dorsolateral prefrontal cortex (DLFC), while they are ready to spend and who has problems with the control of their money, they cannot realize the excessive expenses that it does not recognize the symptoms that drive it to compulsive buying. The findings found provide evidence to the neuroeconomy, as well as to the posture of cognitive control. Furthermore, it is corroborated that performance tests are an alternative in the detection of executive functioning deficiencies in a short time of application and provide evidence in the approach to neuroeconomics through this form of measurement. This offers a novel vision to understand the personal finances of Mexicans and their economic behaviour. Financial and consumer behaviour has become our main line of research from a neuroeconomic perspective, in this sense, to continue this study we intend to incorporate affective and neurobehavioral factors involved in financial decisions in young people of our country in the future. Finally, the usefulness of the results within the neuroeconomics in Mexico and Latin America is deepened, as well as its contribution as a line of research. Keywords: Neuroeconomics, Stroop test, financial decisions, cognitive inhibition, university.
Purpose Atmospherics is undoubtedly a multi-sensory concept, despite mostly being studied on a sense-by-sense basis by architects, sensory marketers and urban designers alike. That is, our experience is nearly always the result of cross-modal/multi-sensory interactions between what we see, hear, smell and feel in a given space. As such, it is critical that researchers study the senses in concert. That said, the few empirical studies that have attempted to assess the impact of deliberately combining the senses in a retail/health-care environment have typically failed to deliver the multi-sensory boost to experience (or sales) that the multi-sensory science predicts ought to be observed. Invoking notions of processing fluency, sensory overload and sensory (in-) congruency in the field of multi-sensory atmospherics may help to explain what happened (or went wrong) in such cases. Design/methodology/approach Critical review of literature on atmospherics and sensory marketing, highlighting various difficulties of interpretation and challenges to accepted conclusions. Findings Atmospherics is a fundamentally multi-sensory concept, and cross-modal interactions are the rule, not the exception. As such, researchers need to study atmospherics in a multi-sensory context. Originality/value This critical commentary highlights the need for researchers to consider atmospherics from a multi-sensory, rather than sense-by-sense perspective.
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El Neuromarketing como campo emergente de la investigación de mercados, ha traído la oportunidad de utilizar herramientas derivadas de la neurociencia, esto justifica plantear como objetivo de este trabajo analizar la disposición del uso de un laboratorio de neuromarketing, a través de la exploración subyacente de la percepción en los sectores comercial, servicios, industrial y automotriz en Ambato-Ecuador. Tras la aplicación de una encuesta semi-estructurada se identifica que, en el componente producto, el estudio de comportamiento de compra es el más significativo, seguido del análisis de empaques, análisis de emociones, procesamiento facial, pruebas de reacción en tiendas, análisis de spots publicitarios. En el componente precio de los servicios la percepción se divide entre muy caros y caros. Respecto al componente comunicación, las características más evocadas para dar a conocer el laboratorio incluyeron redes sociales, capacitación, asesorías personalizadas. En relación con el componente plaza, los calificativos fueron la limpieza y accesibilidad mientras que, en el componente servicio destaca que los beneficios de realizar estudios con un laboratorio permitirán diseñar estrategias comerciales efectivas y aumentar las ventas. Finalmente, los cuatro sectores materializan la intención de utilizar los servicios, medida que impulsa a futuro el diseño estructural del laboratorio de neuromarketing en Ambato-Ecuador.
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n recent years, new and emerging digital technologies applied to Food Science have been gaining attention and increased interest from researchers and the food/beverage industries. Especially those digital technologies that can be used throughout the food value chain are accurate, easy to implement, affordable, and user-friendly. Hence, this special issue (SI) was dedicated to novel technology based on sensor technology and machine/deep learning modeling strategies to implement Artificial Intelligence (AI) in food and beverage production and for consumer assessment. This special issue (SI) published quality papers from researchers in Australia, New Zealand, the United States, Spain, and Mexico, including food and beverage products such as grapes and wine, chocolate, honey, whiskey, avocado pulp, and a variety of other food products.
In the past decade, decision neuroscience and neuroeconomics have developed many new insights in the study of decision making. This review provides an overarching update on how the field has advanced in this time period. Although our initial review a decade ago outlined several theoretical, conceptual, methodological, empirical, and practical challenges, there has only been limited progress in resolving these challenges. We summarize significant trends in decision neuroscience through the lens of the challenges outlined for the field and review examples where the field has had significant, direct, and applicable impacts across economics and psychology. First, we review progress on topics including reward learning, explore–exploit decisions, risk and ambiguity, intertemporal choice, and valuation. Next, we assess the impacts of emotion, social rewards, and social context on decision making. Then, we follow up with how individual differences impact choices and new exciting developments in the prediction and neuroforecasting of future decisions. Finally, we consider how trends in decision‐neuroscience research reflect progress toward resolving past challenges, discuss new and exciting applications of recent research, and identify new challenges for the field. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Emotion and Motivation This graphical abstract shows (1) progress made in the field of decision neuroscience over the past decade and (2) ongoing and future theoretical, methodological, practical, and empirical challenges affecting the field of decision neuroscience.
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In the past decade, there has been a tremendous increase in the use of neurophysiological methods to better understand marketing phenomena among academics and practitioners. However, the value of these methods in predicting advertising success remains underresearched. Using a unique experimental protocol to assess responses to 30-second television ads, the authors capture many measures of advertising effectiveness across six commonly used methods (traditional self-reports, implicit measures, eye tracking, biometrics, electroencephalography, and functional magnetic resonance imaging). These measures have been shown to reliably tap into higher-level constructs commonly used in advertising research: attention, affect, memory, and desirability. Using time-series data on sales and gross rating points, the authors attempt to relate individual-level response to television ads in the lab to the ads' aggregate, market-level elasticities. The authors show that functional magnetic resonance imaging measures explain the most variance in advertising elasticities beyond the baseline traditional measures. Notably, activity in the ventral striatum is the strongest predictor of real-world, market-level response to advertising. The authors discuss the findings and their significant implications for theory, research, and practice.
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Humans sometimes share with others whom they may never meet or know, in violation of the dictates of pure self-interest. Research has not established which neuropsychological mechanisms support lending decisions, nor whether their influence extends to markets involving significant financial incentives. In two studies, we found that neural affective mechanisms influence the success of requests for microloans. In a large Internet database of microloan requests (N = 13,500), we found that positive affective features of photographs promoted the success of those requests. We then established that neural activity (i.e., in the nucleus accumbens) and self-reported positive arousal in a neuroimaging sample (N = 28) predicted the success of loan requests on the Internet, above and beyond the effects of the neuroimaging sample's own choices (i.e., to lend or not). These findings suggest that elicitation of positive arousal can promote the success of loan requests, both in the laboratory and on the Internet. They also highlight affective neuroscience's potential to probe neuropsychological mechanisms that drive microlending, enhance the effectiveness of loan requests, and forecast market-level behavior. © The Author(s) 2015.
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Greater sensory stimulation in advertising has been postulated to facilitate attention and persuasion. For this reason, video ads promoting health behaviors are often designed to be high in "message sensation value" (MSV), a standardized measure of sensory intensity of the audiovisual and content features of an ad. However, our previous functional Magnetic Resonance Imaging (fMRI) study showed that low MSV ads were better remembered and produced more prefrontal and temporal and less occipital cortex activation, suggesting that high MSV may divert cognitive resources from processing ad content. The present study aimed to determine whether these findings from anti-smoking ads generalize to other public health topics, such as safe sex. Thirty-nine healthy adults viewed high- and low MSV ads promoting safer sex through condom use, during an fMRI session. Recognition memory of the ads was tested immediately and 3 weeks after the session. We found that low MSV condom ads were better remembered than the high MSV ads at both time points and replicated the fMRI patterns previously reported for the anti-smoking ads. Occipital and superior temporal activation was negatively related to the attitudes favoring condom use (see Condom Attitudes Scale, Methods and Materials section). Psychophysiological interaction (PPI) analysis of the relation between occipital and fronto-temporal (middle temporal and inferior frontal gyri) cortices revealed weaker negative interactions between occipital and fronto-temporal cortices during viewing of the low MSV that high MSV ads. These findings confirm that the low MSV video health messages are better remembered than the high MSV messages and that this effect generalizes across public health domains. The greater engagement of the prefrontal and fronto-temporal cortices by low MSV ads and the greater occipital activation by high MSV ads suggest that that the "attention-grabbing" high MSV format could impede the learning and retention of public health messages.
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We investigate the feasibility of inferring the choices people would make (if given the opportunity) based on their neural responses to the pertinent prospects when they are not engaged in actual decision making. The ability to make such inferences is of potential value when choice data are unavailable, or limited in ways that render standard methods of estimating choice mappings problematic. We formulate prediction models relating choices to “nonchoice” neural responses, and use them to predict out-of-sample choices for new items and for new groups of individuals. The predictions are sufficiently accurate to establish the feasibility of our approach.
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Theory of mind (ToM) is a core topic in both social neuroscience and developmental psychology, yet theory and data from each field have only minimally constrained thinking in the other. The two fields might be fruitfully integrated, however, if social neuroscientists sought evidence directly relevant to current accounts of ToM development: modularity, simulation, executive, and theory theory accounts. Here we extend the distinct predictions made by each theory to the neural level, describe neuroimaging evidence that in principle would be relevant to testing each account, and discuss such evidence where it exists. We propose that it would be mutually beneficial for both fields if ToM neuroimaging studies focused more on integrating developmental accounts of ToM acquisition with neuroimaging approaches, and suggest ways this might be achieved.
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We meta-analyzed imaging studies on theory of mind and formed individual task groups based on stimuli and instructions. Overlap in brain activation between all task groups was found in the mPFC and in the bilateral posterior TPJ. This supports the idea of a core network for theory of mind that is activated whenever we are reasoning about mental states, irrespective of the task- and stimulus-formats (Mar, 2011). In addition, we found a number of task-related activation differences surrounding this core-network. ROI based analyses show that areas in the TPJ, the mPFC, the precuneus, the temporal lobes and the inferior frontal gyri have distinct profiles of task-related activation. Functional accounts of these areas are reviewed and discussed with respect to our findings.
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Brands surround us everywhere in daily life. Here we investigate the influences of brand cues on gustatory processing of the same beverage. Participants were led to believe that the brand that announced the administration of a Cola mixture provided correct information about the drink to come. We found stronger fMRI signal in right mOFC during weak compared to strong brand cues in a contrast of parametric modulation with subjective liking. When directly comparing the two strong brands cues, more activation in the right amygdala was found for Coca Cola cues compared with Pepsi Cola cues. During the taste phase the same beverage elicited stronger activation in left ventral striatum when it was previously announced by a strong compared with a weak brand. This effect was stronger in participants who drink Cola infrequently and might therefore point to a stronger reliance on brand cues in less experienced consumers. The present results reveal strong effects of brand labels on neural responses signalling reward.
The so-called embodiment of communication has attracted considerable interest. Recently a growing number of studies have proposed a link between Broca's area's involvement in action processing and its involvement in speech. The present quantitative meta-analysis set out to test whether neuroimaging studies on imitation and overt speech show overlap within inferior frontal gyrus. By means of activation likelihood estimation (ALE), we investigated concurrence of brain regions activated by object-free hand imitation studies as well as overt speech studies including simple syllable and more complex word production. We found direct overlap between imitation and speech in bilateral pars opercularis (BA 44) within Broca's area. Subtraction analyses revealed no unique localization neither for speech nor for imitation. To verify the potential of ALE subtraction analysis to detect unique involvement within Broca's area, we contrasted the results of a meta-analysis on motor inhibition and imitation and found separable regions involved for imitation. This is the first meta-analysis to compare the neural correlates of imitation and overt speech. The results are in line with the proposed evolutionary roots of speech in imitation.
Advances in machine learning as applied to functional magnetic resonance imaging (fMRI) data offer the possibility of pretesting and classifying marketing communications using unbiased pattern recognition algorithms. By using these algorithms to analyze brain responses to brands, products, or existing marketing communications that either failed or succeeded in the marketplace and identifying the patterns of brain activity that characterize success or failure, future planned campaigns or new products can now be pretested to determine how well the resulting brain responses match the desired (successful) pattern of brain activity without the need for verbal feedback. This major advance in signal processing is poised to revolutionize the application of these brain-imaging techniques in the marketing sector by offering greater accuracy of prediction in terms of consumer acceptance of new brands, products, and campaigns at a speed that makes them accessible as routine pretesting tools that will clearly demonstrate return on investment.