An fNIRS investigation: Episodic memory encoding in the
left dlPFC might be influenced by early brand-placement in
television commercials
Bachelor Thesis Psychobiology
Author: Pleun J. Strooper Student number: 11200723 Supervisor: A. van der Leij Second corrector: Y. Pinto
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An fNIRS investigation: Episodic memory encoding in
the left dlPFC is influenced by early brand-placement
in television commercials
Pleun J. Strooper
Psychobiology, University of Amsterdam, Amsterdam, The Netherlands Neurensics, Amsterdam, The Netherlands
© 2020
A B S T R A C T
Using brain-based tools for marketing research is a consequence of uncertainties in conventional marketing research. Unfortunately, the popular neuro-imaging techniques, EEG and fMRI, still have limitations for neuroscientific (marketing) research. Consequently, a more affordable neuro-imaging technique with more possibilities should be found, this might be fNIRS. In the current explorative study, it is questioned if fNIRS can measure episodic memory encoding in the dlPFC and vmPFC. Also, it is investigated if episodic memory might be influenced by different types of brand-placement in television commercials. (HHb)-fluctuations elicited by an intra-item association task are measured. Enhanced dlPFC activity was observed, this might be a result of episodic memory encoding. A significant difference between the different types of brand-placement was only found in the left dlPFC. Therefore, it is suggested that early brand-brand-placement improves episodic memory encoding. Aspects that might have influenced the left dlPFC activity are brand-logo frequency and variations in emotional memory encoding.
Keywords:
Brand-association Brand-placement
Dorsolateral prefrontal cortex Episodic memory encoding fNIRS
Ventral medial prefrontal cortex
1. Introduction
The main goal for brands is selling their product or service to regular costumers and new customers. Therefore, regular customers need to be retained and new customers need to be recruited with effective marketing strategies. The difficulty here is understanding the general
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costumers’ buying behavior. While shopping costumers make impulsive perceptual decisions that are based on previous knowledge (Pisauro et al., 2017). Marketers try to predict these impulsive perceptual decisions by investigating their costumers’ previous brand-knowledge with questionnaires or service (Morin, 2011). However, these conventional marketing research might not always be reliable as a result of two aspects: firstly, people may often give a socially desired answer (Gittelman et al., 2015). Secondly, individuals might not be able to report their feelings because they are not aware of their unconscious cognitive processes (Marichamy & Sathiyavathi, 2014).
To provide a more consistent way for data-collection in marketing research, change is needed. Therefore, in 2002 a new promising field in the marketing research arose: neuromarketing. This entails operating brain-based tools for understanding consumer's brain and behavior and linking it to effective marketing strategies (Vecchiato et al., 2011). The methodologies that are used for collecting data in physiological changes and brain activity are facial coding, eye tracking, voice analysis, skin conductance, electroencephalography (EEG), and functional Magnetic Resonance Imaging (fMRI) (Morin, 2011). Especially the neuro-imaging techniques, EEG and fMRI, are popular. These techniques may aid in understanding the consumers’ brain and behavior and give insight into unconscious processes, like perceptual decision making. Eventually, this marketing research field helps us in understanding why some marketing strategies fail and some succeed (Marichamy & Sathiyavathi, 2014).
The popular neuro-imaging techniques, EEG and fMRI, have many benefits and limitations in finding the underlying processes of perceptual decision making. In the neuro-imaging technique EEG, behavioral responses are linked to electrical patterns in the brain. While thinking or moving, neurons in the brain interact with each other with ionic currents. These currents generate electrical signals over the entire brain. Electrodes, that are non-invasively placed on the scalp, can record these electrical signals in cortical brain areas (Yadava et al., 2017). These signals have multiple patterns of frequencies that are transformed into brainwaves (Marichamy & Sathiyavathi, 2014). Benefits of EEG are the low maintenance costs and the high temporal resolution, brainwaves can be recorded at small-time interval, some to 10 000 times per second (2004; Ohme et al., 2010). However, the main limitation of EEG is the low spatial resolution, only the cortical activity can be measured. Even with a high temporal resolution EEG method, just a squared centimeter per sub-millisecond can be measured (Nunez, 1995; Bai et al., 2007; He et al., 1999; Dale et al., 2000; Babiloni et al., 2005). Due to low spatial resolution, it is only possible to measure an accumulation of electrical activity during perceptual decision making, not the exact location of the activity (O’Connel et al., 2012; Wyart et al., 2012; Kelly and O’Connel, 2013; Philiastides et al., 2014; Mostert et al., 2015).
In contrast to EEG, fMRI gives a precise representation of the neuronal activity in brain areas. An active brain area receives more oxygenated blood compared to an inactive area. Oxygen is transported in red blood cells, in particular, the chromophore hemoglobin. Distortions in the magnetic field of the fMRI scanner arise as a result of changes in the oxygen concentrations in the blood flow. These magnetic changes are detected by the fMRI scanner and called Blood Oxygen Level-Dependant (BOLD) responses (Huettel et al., 2008; McClure et al., 2004; Marichamy & Sathiyavathi, 2014). The spatial resolution is ten times higher compared to EEG measurements (Ariely and Berns, 2010; Morin, 2011), findings suggest a link between the BOLD responses and active brain areas. Between the neuronal activity and the changing BOLD signal there is a delay of a couple of seconds, causing a slow temporal resolution. BOLD-signals do not directly reflect the electrochemical signals, which is the case with EEG, they indirectly reflect the neuronal activity. Nonetheless, it is possible to localize the involved brain areas of perceptual decision making. Previous research suggests that the sensorimotor cortex and higher-level prefrontal areas are involved (Heekeren et al., 2004; Filimon et al., 2013, Tosoni et al., 2008; Noppeney et al., 2010; Liu and Pleskac, 2011). Despite the high spatial resolution and all the additional methodological benefits, fMRI-scanner has high maintenance costs (Kenning et al., 2007; Morin,
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2011). This is why many brands reject neuromarketing studies with the neuro-imaging technique fMRI.
Therefore, a new affordable neuro-imaging technique is required for localizing the mechanism behind perceptual choices. This technique might be functional near-infrared spectroscopy (fNIRS). This non-invasive technique measures metabolic changes in the blood flow due to fluctuations of the chromophores, oxyhemoglobin (O2Hb) and deoxyhemoglobin (HHb). The near-infrared light is absorbed by the two chromophores, the remaining light is received and analyzed. Because the chromophores have different absorption spectra, two laser-lights with different wavelengths are used (Heinzel et al., 2012). An fNIRS device contains light transmitters and receivers, that can be placed on the human skull. This neuro-imaging technique is similar to fMRI, but instead of magnetic changes, concentration changes of the chromophores are examined by the fNIRS device (Pinti et al., 2018). These fluctuations of chromophores reflect an indirect estimation of the neural activity in a brain area (Harrison and Hardley, 2019). If a brain area is metabolic active, it will demand oxygen, as a result, the (O2Hb)-concentration increases and the deoxyhemoglobin (HHb)-concentration decreases. The measured concentration changes of the chromophores are equivalent to fMRI BOLD-responses (Fishburn et al., 2014). However, the (HHb)- and (O2Hb)concentration changes result in a higher temporal resolution, compared to fMRI. fNIRS has sampling rates up to 100 Hz, while fMRI has sampling rates up to 0.5 Hz (Harrison & Hardley, 2019). Besides results of fMRI and fNIRS can be compared (Köchel et al., 2011; Steinbrink et al., 2006), it seems that a higher correlation is found between BOLD and the changed (HHb) concentration, compared to the changed (O2Hb) concentration (Kleinschmidt et al., 1996; Toronov et al., 2001; Kallen et al., 2002; Boas et al., 2003; Chen et al., 2003). If fNIRS would be used in neuro-scientific (marketing) research, it would have many possibilities compared to EEG and fMRI. Starting with the low maintenance costs, around USD 100 000 depending, whereas an MRI scanner costs significantly more. As mentioned above, fNIRS has a higher temporal resolution compared to fMRI (Harrison & Hardley, 2019). Furthermore, the spatial resolution of fNIRS is dependent on the source-detector distance. If the transmitter-receiver distance is approximately 3 cm, an optical penetration depth can be reached (Hoshi, 2003; Köchel et al., 2011). Usually, the penetration depth is half of the distance between source and detector (Patil et al., 2011; Ferrari & Quaresima, 2012; Pinti et al., 2018). However, the penetration depth depends on NIR light intensity, the measured head region (Ferrari & Quaresima, 2012), and the age of the subject (Tan et al., 2016). Age differences cause different (HHb)-concentration measurements. In elderly subjects (μ = 73 years, σ = 3) a decreased (HHb) concentration was found relative to the younger subjects (μ = 35 years, σ = 9) (Kallen et al., 2002). Despite the low spatial resolution, an fNIRS device can be used to measure activity in the dlPFC during a realistic grocery shopping scenario (Krampe et al., 2018). Using fNIRS in natural environments is achievable because it is robust to motion artifacts, and a wireless connection can be used (Arenth et al., 2007; Pinti et al., 2018). Altogether, fNIRS might be the new affordable neuroscientific (marketing) technique for localizing the mechanism behind perceptual decision making.
Due to uncertainties in conventional marketing research, a new field in marketing research has emerged: neuromarketing. Unconscious processes that might reflect perceptual decision-making processes, can be investigated with neuroimaging techniques. Compared to conventional marketing research, neuroscientific (marketing) research is more reliable. However, only fMRI localize brain areas that are linked to perceptual decision-making. Unfortunately, fMRI studies have high maintenance costs. As a result, many brands reject neuromarketing-studies with fMRI as the neuroimaging technique. Therefore, an affordable neuro-imaging technique that can localize the perceptual decision-making mechanism has to be found. In the current study, an explorative experiment is executed to investigate if fNIRS could be an affordable neuro-imaging technique to localize the perceptual decision-making mechanism.
The most basal function of marketing research is enhancing the brand-associations through evaluative conditioning (Allen and Janiszewski 1989; Allen and Madden 1985; Bierley et al., 1985;
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Kellaris and Cox 1989; Kim et al., 1998). While watching an advertisement or television commercial feelings and thoughts are evoked, these must be associated with the brand. If a brand-logo is presented, the earlier perceived feelings and thoughts should be evoked spontaneously. Previous research suggests, that brand-association might be encoded in the episodic memory (Koll et al., 2010). The prefrontal cortex (PFC) plays a crucial role in encoding and retrieving of episodic memories (Badre and Wagner, 2007, Balconi, 2012, Blumenfeld and Ranganath, 2007; Kirchhoff et al., 2000, Ranganath, 2010). Encoding is perceiving and storing an event. Retrieval is the specific recall of an event at a later moment (Tulving, 1984). Previous research suggests that the ventromedial (vm)PFC (Gais et al., 2007; Takashima et al., 2007; 2006; Sterpenich et al., 2009) and dorsolateral (dl)PFC are involved in episodic memory encoding. The dlPFC is linked to episodic memory through working memory manipulations. The dlPFC supports encoding associations between elements via working memory, called associative memory. Suggesting that activation in de dlPFC, in particular, the left dlPFC, is related to forming associations between items (Ranganath, 2010; Blumenfeld and Ranganath, 2006, 2007; Schaeffer et al., 2014; Murray and Ranganath, 2007; Addis and McAndrews, 2006; Rossi et al., 2001; Rossi et al., 2006; Rossi et al., 2011; Sandrini et al., 2003; Manenti et al., 2011; Grafman et al., 1994, Gagnon et al., 2011). Brand-placement plays an essential role in the association forming between the brand-logo and the television commercial (Reijmersdal, 2009; Romaniuk, 2009). It is defined as “the compensated inclusion of brands or brand identifiers through audio and/or visual means within media programming” (Karrh, 1998). However, there is some disagreement which type of brand-placement is linked to a successful association between brand-logos and television commercials. Some studies say it is more effective to place a brand logo at the beginning of the commercial. This directly associates the brand-logo to the television commercial (Baker et al., 2004). Other studies say that presenting the brand-logo during the closing of a television commercial will result in a stronger association between brand-logo and television commercials. Withholding the brand will make the consumer more curious and focused, which will result in more efficient episodic memory encoding (Menon and Soman, 2002). However, both hypotheses are based on conventional marketing research. A neuroscientific method could aid in understanding what type of brand-placement results in an enhanced brand-association in the episodic memory. The question arises if fNIRS can measure episodic memory encoding in the dlPFC and vmPFC. Besides, it is examined if episodic memory can be influenced by different types of brand-placement in television commercials. In the future, findings might be used by brands to improve their television commercials. This explorative fNIRS study aims to investigate the possibility if episodic memory encoding can be measured in the dlPFC and vmPFC. It is hypothesized that episodic memory encoding results in enhanced activity in the dlPFC and vmPFC
Each participant is connected to fNIRS-equipment while performing an intra-item association task. In the first part, 25 different logos are presented followed by two priming words. The participant has to state which word fits better with each logo; repetition is included. After this, the participant has to pay attention to the corresponding TV commercials that are viewed. The third part is equal to the first part, the only difference is the order of the brand-logos. To answer the research-question a selection of television commercials is made that have late brand-placement or early and late brand-brand-placement. During the analysis, fNIRS data of the post-part minus the pre-part is examined for all conditions. It is expected that a distinction between the different types of placement can be made. Television commercials with early brand-placement show enhanced episodic memory encoding in the dlPFC and vmPFC as a result of episodic memory encoding.
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2. Material and methods 2.1. Subjects
In this fNIRS study, a total of 106 subjects (age range 18-30 and 50-62 years, μ = 24.96 years, σ = 10.22) participated. All subjects received monetary compensation for participating in the study. Inclusion criteria were normal or corrected to normal vision and Dutch as their first language. Subjects with noisy fNIRS data were excluded. Only the fNIRS data of version 1, 4 and 5 was used (see 2.5.1. pre-analysis, table 1: Selected television commercials), the subjects of version 2, 3, and 6 were excluded. A total of 26 subjects (age range 19-23 and 54-58, μ = 26.69 years, σ = 12.81) with data for further analysis remained. In previous research, it is suggested that age can influence the penetration depth (Kallen et al., 2002; Tan et al., 2016), so the four outliers in the age range from 54-58 years were removed. For statistical data analysis the data of 22 participants was used (age range 19-23, μ = 21.36 years, σ = 1.09; distribution versions = version 1: 8 subjects; version 4: 7 subjects; version 5: 7 subjects).
2.2. Stimuli
2.2.1. TV Commercials
2.2.1.1. All television commercials
A total of 150 television commercials were selected by Neurensics. The selection was based on different awards or brain activity (See Appendix A: 75 ‘Effies’ with a combination of brand and behavior categories; 25 'Gouden Loeki's', 25 'Loden Leeuwen' and 25 No Emotional Response). ‘Effies’ is one of the most pretentious awards within the marketing and advertising industry worldwide. Only brands with the most effective marketing strategies win this award. Effies have multiple categories, however for this intra-item association task only the behavioral and brand categories are selected. ‘Gouden Loeki' is a dutch television price for the best television commercial of that year. 'Loden Leeuw' is a dutch television price for the most irritating television commercial of that year. The Dutch population determines by voting who wins the 'Gouden Loeki' and 'Loden Leeuw'. The last television commercial category, No Emotional Response, is based on brain activity. In an fMRI study of Neurensics, many television commercials were tested for their emotional response. A selection of 25 television commercials with the most neutral response were chosen.
2.2.1.2. Selected television commercials
To answer the research question a distinction was made between three conditions (See Table 1: Selected Television Commercials). For the first condition, brand-logos from the control condition are used. For the second condition, a selection was made of TV commercials that only show their logo during closing (in the last seven seconds). For the last condition, a selection was made of television commercials that show their brand-logo during onset (in the first five seconds) and during closing (in the last seven seconds). These selected television commercials are based on annotations of three different people, who annotated the time if a logo was present in a television commercial.
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Table 1. Selected television commercials
Award/ Brain activity Version Control
Loden Leeuw 1 Specsavers: Shouldve Gone To (2014)
5 Lidl: Gerard Joling (2014)
5 EyeloveBrillen: Rene Froger (2018)
1 HoyHoy: Makeover Aart (2013)
4 Volkswagen: Volkswagen Hond (2013)
4 Zalando: Naakt-recreatie (2011)
1 Essent: Brand (2018)
4 Bonprix: Café (2013)
Late brand-placement
Gouden Loekie 1 Bol: Takelauto (2011)
5 Heineken: Der Rudi (2002)
Effies Brand 5 Jumbo: Moestuin (2014)
Effies Behavior 5 Unox: Knaks Kinderfeestje (2012)
4 Tele2: Omdat Het Kan (2015)
4 Nuon: Zonnepanelen Huren (2018)
No Emotional Response 1 Marktplaats: SpontaneVerkopen (2013)
4 ABNAmro: IntroductieTekst (2015)
Early and late brand-placement
Gouden Loekie 1 Blijdorp: Olli (2013)
5 Bol: Flappie (2014)
Effies Brand 1 Hema: Rompertje (2009)
5 Beter Bed: Edith Bosch (2015)
Effies Behavior 1 Philips: Airfryer (2014)
4 Essent: ZekerDalen (2013)
5 Independer: Vergelijken (2013)
4 Clipper: Many Reasons To Love (2016)
No Emotional Response 1 De Bijenkorf: Vogel (2017)
4 Airbnb: Belong Anywhere (2015)
2.2.2. Brand logos
For each television commercial, a corresponding brand logo was used. The brand-logo was identical to the one that was presented in the television commercial. To capture the association between the brand-logo and television commercial in this intra-item task, the brain activity is only measured in the brands pre and post part (see figure 1). As control, brand-logos without corresponding television commercial were added. In order to check if the episodic memory is influenced by television commercials.
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2.2.3. Priming words
In the brands pre part and brands post part, brand-logos were presented followed by two priming words. Three types of priming words were used: positive ('sympatiek' and 'betrouwbaar'), negative ('afstotelijk' and 'onoprecht') and neutral words ('herkenbaar' and 'nietszeggend') (Hermans et al., 1994).
2.3. Procedure (see figure 1)
2.3.1. Brands pre part
In this part, the associations between previous knowledge and brand-logo are recorded. In each version, 29 (25 corresponding to television commercial + 4 control) brand-logos are presented. A trial starts by viewing a brand-logo for 2 seconds, after this two priming words pop-up. Every brand-logo is repeated three times time with a different combination of priming words (positive-negative; positive-neutral; negative-neutral). When the priming words pop-up the subjects have to decide between the two priming words with a keypress (left (= keypress 'm') or right (= keypress 'z'). No keypress has to be done if the subject does not recognize the brand-logo or the priming words do not give an accurate description of the brand. After a keypress or a waiting time of 2,5 seconds, a blank screen is projected. This screen is projected until the entire trial is either 6, 7 or 8 seconds long (I.S.I. = ~7 seconds). After 25 trials a self-paced break is included. The total time for this part is approximately 10 minutes.
2.3.2. Television commercials
In this part, 25 corresponding TV commercials were viewed. The average of each TV commercial is 40 seconds long. After 5 commercials a self-paced break is included. In between the commercials, there is a pause of 8 seconds. The total time for this part is approximately 17 minutes.
Figure 1. Structure and timing of the intra-item association task. The intra-item association task is divided into three
parts. Starting with the Brands pre part: The association between the previous knowledge and the brand-logo is recorded here. Each logo is repeated three times with three different priming word combinations. In the second part television commercials are viewed. In the last part, the association of the television commercial with the brand-logo is recorded. This intra-item association task is programmed using EventIDE (Okazolab Ltd, Delft, The Netherlands).
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2.3.3. Brands post part
In this part, the association between the brand-logo and the television commercials were recorded. It is equivalent to the brands pre part, the only difference is the order of the brand logos, and priming words.
2.4. Data acquisition
2.4.1. fNIRS configurations
In table 2 the fNIRS compounds of the left and right dlPFC and vmPFC are summarized. The coordinates are based on The Principles of Neuroscience (p. 403; figures 18-9).
Table 2. fNIRS compounds per brain area
2.4.2. fNIRS equipment
A portable fNIRS system, the Brite 24 (Artinis; NIRx Medical Technologies, Elst, The Netherlands), performed the optical measurements during the intra-item association task. The (O2Hb)- and (HHb)-fluctuations were measured with two wavelengths, 760 nm, and 850nm. All data were collected at a sampling rate of 50 Hz. Ten near-infrared light transmitters (T1-T10) and eight near-infrared light receivers (R1-R8) were placed, in a radius of 30 mm from each other (see figure 2), in a neoprene cap (sizes: S – L). During the intra-item association task this cap, with transmitters and receivers, was placed on the scalp of the subject for fNIRS measurements. The right configuration is equal to the left configuration, except the numbers differ (right: T1-T5 + R1-R4; left: T6-T10 + R5-R8). The goal is finding episodic memory encoding in the dlPFC a vmPFC, so these compounds are examined (see Table 1: fNIRS compounds per brain area). Oxysoft software is used for fNIRS acquisition and experimental analysis (Artinis; NIRx Medical Technologies, Elst, The Netherlands, 2019).
Brain area The left hemisphere The right hemisphere
dlPFC Rx05-Tx06 Rx01-Tx01
Rx06-Tx06 Rx02-Tx01
vmPFC Rx07-Tx10 Rx03-Tx05
Rx08-Tx10 Rx04-Tx-05
Figure 2. Schematic configuration the left hemisphere with of the near-infrared light transmitters and receivers.
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2.5. Analysis
2.5.1. Pre-analysis: raw fNIRS data
The pre-analysis was done in Matlab (The Matworks, 2016). Raw fNIRS signals were smoothed by applying a 5th order cubic Savitzky-Golay (Orfanidis, 1996) filter with a frame length of 12 seconds. Next, the smoothed signal was filtered with a Chebyshev Type 1 lowpass filter (passband freq 2 Hz, stopband frequency 5 Hz, Passband ripple 1dB, stopband attenuation 20dB) (Chebyshev, 2020). For analysis, a stick model time-series was generated and convoluted with a canonical BOLD function.
2.5.2. Statistical analysis: Processed fNIRS data
The average fNIRS data in the pre and post part for all subjects in each condition are used for statistical analysis (see Table 2: Selected television commercials). The results of all the participants are filtered for motion and physiological changes, noisy fNIRS data is removed. For statistical analysis, the remaining fNIRS data is used. Only the HHb-fluctuations of the dlPFC and vmPFC compounds are used (See Table 1: fNIRS compounds per brain area). To check for a significant difference between the post and pre part, for each compound, a paired t-test is used. Before further analysis, fNIRS data of the average brands post-part minus fNIRS data of the average brands pre-part per subject and compound is calculated. This data is checked for the assumptions of an One-Way ANOVA, with a Shapiro-Wilk test and a Levene’s test. An One-Way ANOVA can be performed when the assumptions are not violated. To solve the counteraction problem between the different compounds the Modified Bonferonni Adjustments (Holm, 1979) can be used. The family-wise error rate is controlled by adjusting the rejection criteria of each hypothesis.
3. Results
Results of the paired t-test between the pre and post (HHb)-compounds are summarized in Table 3. Significant difference was only found in the dlPFC for all conditions, and no significant difference was found in the vmPFC. So, only the fNIRS data of the dlPFC was used for further analysis. The assumptions for an One Way ANOVA were checked for all dlPFC fNIRS compounds and none were violated (Rx01-Tx01: [Shapiro-Wilks test: p-value = 0.4927; Levene’s test: df = 2, F-value = 0.4162, p-value = 0.6613]; Rx02-Tx01: [Shapiro-Wilks test: p-value = 0.1717; Levene’s test: df = 2, F-value = 2.4974, p-value = 0.09042]; Rx05-Tx06: [Shapiro-Wilks test: p-value = 0 0.429; Levene’s test: df = 2, F-value = 1.5693, p-value = 0.2162]; Rx06-Tx06: [Shapiro-Wilks test: p-value = 0.3377; Levene’s test: df = 2, F-value = 1.3229, p-value = 0.2737]). After performing an One-Way ANOVA for all the dlPFC fNIRS compounds, only a significant difference was found in the Rx06-Tx06 component (Rx01-Tx01: [df=1, χ2 = 3.31, F-value = 3.1, p-value = 0.0831]; Rx02-Tx01: [df=1, χ2 = 1.45, F-value = 0.981, p-value = 0.326]; Rx05-Tx06: [df=1, χ2 = 9.841, F-value = 3.969, p-value = 0.0506]; Rx06-Tx06: [df=1, χ2 = 19.785, F-value = 10.4, p-value = 0.00199*]). (See figure 3 for the data visualization).
Table 3. The paired t-test results (per brain area/ compound/ condition)
Brain area fNIRS compounds Control Late Early and late
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* = p < 0.05 Post-Hoc analysis is performed with the Modified Bonferroni Adjustments (Holm, 1979), results are summarized in Table 4. This Holm procedure controls the family-wise error rate and reevaluates the rejection criteria for each individual hypothesis. Still, significant difference is found in fNIRS Rx1-Tx1 compounds after the adjustments.
Table 4. The adjusted rejection criteria
fNIRS compounds ANOVA Modified Bonferroni Adjustments
Rx06-Tx06 0.00199* 0.0125 Rx05-Tx06 0.05060 0.0167 Rx01-Tx01 0.08310 0.0250 Rx02-Tx01 0.32600 0.0500 Rx02-Tx01 0.3818 0.0179* 0.5823 Rx05-Tx06 0.1270 0.7810 0.2089 Rx06-Tx06 0.0183* 0.7626 0.0413* vmPFC Rx03-Tx05 0.6906 0.4359 0.9572 Rx04-Tx05 0.6356 0.9486 0.9334 Rx07-Tx10 0.8514 0.5878 0.3104 Rx08-Tx10 0.6308 0.2495 0.1727
Figure 3. Cluster bar chart of the average changed concentrations in the left and right dlPFC. An enhanced
(HHb)-concentration change is shown in the left dlPFC for early and late brand-placement, although an enhanced (HHb) (HHb)-concentration change in the right dlPFC is shown for late brand-placement. However, only a significant difference is found for the Rx06-Tx06 compound in the left dlPFC (df=1, χ2 = 19.785, F-value = 10.4, p-value = 0.00199*). Error bars with the standard error are included (Rx05-Tx06: both = 0,07247207, closing = 0,10326227, control = 0,11271156; Rx06-Tx06: both = 0,06663037, closing = 0,09238798, control = 0,094747; Rx01-Tx01: both = 0,09944968, closing = 0,05971315; control = 0,07077247; Rx02-Tx01: both = 0,09823299, closing = 0,0595494, control = 0,05574503). Y-ax: average changed (HHb) concentration.
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4. Discussion
This explorative fNIRS study aimed to investigate the possibility if episodic memory encoding can be measured in the dlPFC and vmPFC. It was hypothesized that enhanced activity for both areas, as a result of episodic memory encoding. Enhanced activity in the dlPFC was observed, this might be a result of episodic memory encoding. fNIRS data of the vmPFC was excluded because no significant difference was found after performing a paired t-test. Further analysis into the dlPFC showed significant differences in the left dlPFC after performing an One-Way ANOVA. Identical results were found after performing the Modified Bonferonni Adjustment. After visualizing the dlPFC data, hemispheric asymmetry was found. The left dlPFC showed enhanced activity for the early and late brand-placement condition, while the right dlPFC showed enhanced activity for the late brand-placement condition.
Previous research suggests that the ventromedial (vm)PFC (Takashima et al., 2007; 2006; Sterpenich et al., 2009) and the dorsolateral (dl)PFC (Murray and Ranganath, 2007; Qin et al., 2007; Addis & McAndrews, 2006; Ranganath, 2010; Schaeffer et al., 2014) are both involved in episodic memory encoding. However, in the current study, only a significant difference was found in the left dlPFC. This might be a consequence of the crucial role of the dlPFC, and especially the left dlPFC, in creating association between items (Rossi et al., 2001; Rossi et al., 2006; Rossi et al., 2011; Sandrini et al., 2003; Manenti et al., 2011; Grafman et al., 1994, Gagnon et al., 2011). Despite the findings of hemispheric asymmetry in the dlPFC, it is assumed that the left dlPFC gives an accurate representation of episodic memory encoding. Therefore, this explorative fNIRS study suggests that early brand-placement improves episodic memory encoding.
Further, the fNIRS finding in the left dlPFC might be influenced by other effects than brand-placement. Starting with the brand-logo frequency. At the beginning of this research a selection of 150 television commercials was made by Neurensics (See Appendix A). To answer the research question only these television commercials were used. However, it was not possible to collect enough television commercials with early brand-placement. As an alternative, a selection was made of television commercials with early and late brand-placement. Resulting in a brand-logo frequency that is 2 times higher compared to television commercials with late brand-placement. Previous research suggests that brand-logo frequency in television commercials is linked to enhanced episodic memory encoding (Romaniuk, 2009; Martí-Parreño et al., 2017). Therefore, enhanced left dlPFC activity for television commercial with early and late brand-placement could be the result of a higher brand-logo frequency, and not influenced by brand-placement.
Another aspect that could have influenced the fNIRS findings in the left dlPFC is the differences in emotional responses caused by television commercials between and within subjects. Previous research suggests that the left dlPFC plays a role in emotional memory encoding (Balconi and Ferrari, 2012). The selected television commercials are based on awards and brain activity and not based on equal emotional responses, only the television commercials that might evoke an irritated response (“Loden Leeuw”) were excluded. As the emotional variances between television commercials were not taken into account, differences in emotional responses between and within subjects emerge. First the variances in emotional responses between subjects, as a result of individual differences in previous knowledge. Second the variances in emotional responses within a subject, as a result of differences in the emotional valences of television commercials. Unfortunately, these variances in emotional responses between and within subjects are not taken into account in this intra-item association task. It might be a possibility that the early and late condition contains more television commercials that enhance emotional memory encoding. Therefore, differences in emotional responses caused by television commercials might explain the enhanced activity in the left dlPFC.
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The dissimilar activation patterns in the left and right dlPFC might be a result of different types of memory processing in the two hemispheres. Hemispheric asymmetry is a common phenomenon in many unconscious processes in the brain, such as language (O’Regan & Serrien, 2018). It is possible that episodic memory encoding is one of these unconscious processes. While the left hemisphere often activates during analytical memory processing, like association forming
(
Blumenfeld & Ranganath, 2006). It is suggested that the right hemisphere is involved during the creative memory processing (Bowden & Jung-Beeman, 2003; Falcone & Loder, 1984). Enhanced activity in the right hemisphere is shown when individuals recognize themselves in information that has to be memorized (Mihov et al., 2010). Also, previous research suggests that familiar brands result in improved episodic memory encoding(
Martí-Parreño et al., 2017). The late brand-placement condition may contain more familiar brands (for the age range: 19-23 years), relative to the early and late brand-placement condition. This might explain enhanced activity in the right dlPFC.Furthermore, current findings need to be considered from the perspective of the low spatial resolution of fNIRS. In contrast to the spatial resolution of fMRI, it is still uncertain if the activity in the dlPFC and vmPFC are measured. Despite the detailed research for the coordinates of the dlPFC and vmPFC, it is still unknown if the chosen compounds are equal to the exact location in these brain areas. Future investigations might use an fMRI-fNIRS paradigm and replicate this intra-item association task. fMRI is integrated to determine if of the left dlPFC plays a role in episodic memory encoding. Besides, the effect of different types of brand-placement in episodic memory encoding could be examined. The procedure of the current study remains the same, only the selected television commercials, number of conditions and number of versions change. First, 24 television commercials without brand-logo are selected. For each television commercial, the brand is placed in the beginning (early); during closing (late); and early and late, eventually a total of (24 * 3 =) 72 television commercials are used for the task. Each type of brand-placements is assigned to one of the four versions. Every version contains the same 24 television commercials, the only difference is the type of brand-placement per television commercial. This is to ensure that brand-logo frequency and differences in emotional responses do not interfere with the results, in the hope to find similar results.
This explorative study suggests that fNIRS measured episodic memory encoding in the left dlPFC. This episodic memory encoding might be influenced by early brand-placement in television commercials. These findings might help future neuroscientific (marketing) research in three ways. First, the suggestion that early brand-placements improves episodic memory encoding, might be used for creating new effective television commercials for brands. Second, this intra-item association task might be used to assure the effectiveness of other television commercials. If enhanced activity in the left dlPFC is found, it might suggest a successful association between brand-logo and television commercials. At last, fNIRS might be an affordable neuro-imaging technique for measuring perceptual decision making and other unconscious processes in neuroscientific (marketing) research.
In short, fNIRS might be an affordable neuro-imaging technique for neuroscientific (marketing) research. This precise field might aid conventional marketing research in understanding the costumers’ buying behavior. Eventually, brands could act on how to retain and recruit costumers with effective marketing strategies.
P.J. STROOPER
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6. Appendix A.
Table 5. List of the television commercials used in the intra-item association task
Number Television commercial Award/ Brain activity Version Control for version:
1 TVC-AppieToday-BuikBillenBonus-77 Loden Leeuw 1 6
2 TVC-Zalando-2012-Virus-27 Loden Leeuw 1 6
3 TVC-NederlandseEnergieMaatschappij-2011-JohanDerksen-30 Loden Leeuw 1 6
4 TVC-Hak-2013-RonaldKoeman-32 Loden Leeuw 1 6
5 TVC-Blijdorp-2013-Olli-75 Gouden Loeki 1
6 TVC-Heineken-2009-WalkInFridge-31 Gouden Loeki 1
7 TVC-Bol-2011-Takelauto-25 Gouden Loeki 1
8 TVC-Volkswagen-2011-OudVrouwtje-45 Gouden Loeki 1
9 TVC-Eneco-2011-SamenGaanWeVoorDuurzaam-35 Effies brand 1
10 TVC-HertogJan-2016-Pilsener-24 Effies brand 1
11 TVC-Hema-2009-Rompertje-25 Effies brand 1
12 TVC-Robijn-2015-WasBijChantalJanzen-40 No Emotional Response 1
13 TVC-Philips-2014-Airfryer-25 Effies behavior 1
14 TVC-CentraalBeheer-2012-Woonverzekering-65 Effies behavior 1
15 TVC-Telfort-2013-Smartpakkers-44 Effies behavior 1
16 TVC-DubbelFris-2013-MeisjeVsJongen-30 Effies behavior 1
17 TVC-BelastingdienstDouane-ReizenApp-58 Effies behavior 1
18 TVC-Fietsenwinkel-OnlineKopen-30 Effies brand 1
19 TVC-ASN-2016-Gewoontegedrag-35 Effies brand 1
20 TVC-NOCNSF-ZoDoenWeDat-38 Effies brand 1
21 TVC-Beslist-2015-Winterjas-30 No Emotional Response 1
22 TVC-KPN-2015-Beeldbellen-45 No Emotional Response 1
23 TVC-Marktplaats-2013-SpontaneVerkopen-25 No Emotional Response 1
24 TVC-DeBijenkorf-2017-VogelPauw-30 No Emotional Response 1
25 TVC-Gamma-2015-Verfwinkel-30 No Emotional Response 1
P.J. STROOPER
27 TVC-Specsavers-ShouldveGoneTo-2014-30 Loden Leeuw 2 1
28 TVC-HoyHoy-2014-MakeoverAart-35 Loden Leeuw 2 1
29 TVC-Plus-2011-HollandsePrijsweken-40 Loden Leeuw 2 1
30 TVC-McDonalds-2018-CadeauKalender-30 Gouden Loeki 2
31 TVC-Gamma-2011-Lego-30 Gouden Loeki 2
32 TVC-Ditzo-2012-JohndeWolf-35 Gouden Loeki 2
33 TVC-KPN-2015-1eAppje-40 Gouden Loeki 2
34 TVC-CentraalBeheer-1989-Klok-46 Gouden Loeki 2
35 TVC-AlbertHeijn-2011-Appie-42 Effies brand 2
36 TVC-McDonalds-2014-Euroknaller-20 Effies behavior 2
37 TVC-Skoda-2014-SkodaExperiment-36 Effies behavior 2
38 TVC-IKEA-2016-Aandacht-60 Effies behavior 2
39 TVC-Eneco-2014-ToonOmruil-40 Effies behavior 2
40 TVC-OldAmsterdam-2015-Karakter-30 Effies behavior 2
41 TVC-Pickwick-2010-Dutchblend-30 Effies behavior 2
42 TVC-MasterCard-IgonedeJong-40 Effies behavior 2
43 TVC-OHRA-2017-Viervoeters-45 Effies brand 2
44 TVC-SNS-2015-Motorcross-30 Effies brand 2
45 TVC-Chocomel-2016-ZoVersZoOP-20 Effies brand 2
46 TVC-Wildlands-KindTijger-25 Effies brand 2
47 TVC-Nuon-2012-EdEnEduardOverMijnNUON-45 No Emotional Response 2
48 TVC-DeFriesland-2017-BetereWereld-60 No Emotional Response 2
49 TVC-FBTO-2016-SchadeApp-30 No Emotional Response 2
50 TVC-ING-2014-WatGaatHetWorden-30 No Emotional Response 2
51 TVC-MiljoenenSpel-2012-PatriciaPaay-30 Loden Leeuw 3 2
52 TVC-Robijn-HuizeGerschanowitz-40 Loden Leeuw 3 2
53 TVC-Pricewise-PaulHaenen-30 Loden Leeuw 3 2
54 TVC-Hunkemoller-2013-SylvieMeis-20 Loden Leeuw 3 2
55 TVC-Yarden-2017-AliB-40 Loden Leeuw 3
56 TVC-Bol-2010-Mummiepak-25 Gouden Loeki 3
57 TVC-Jumbo-2018-Kerst-70 Gouden Loeki 3
58 TVC-Calve-2010-Pietertje-41 Gouden Loeki 3
59 TVC-Brand-2009-HetBierWaarLimburgTrotsOpIs-40 Gouden Loeki 3
60 TVC-Defensie-2013-WerkenBijDefensieJeMoetHetMaarKunnen-35 Effies brand 3
61 TVC-DELA-2012-LeefVandaag-55 Effies brand 3
62 TVC-Heineken-TheHero-30 Effies brand 3
63 TVC-Opel-2013-ADAM-40 Effies brand 3
64 TVC-CentraalBeheer-2012-HetLaatsteBod-45 Effies behavior 3
65 TVC-TMobile-2013-AliBZonderAnsjovis-40 Effies behavior 3
66 TVC-Eneco-2012-Toon-32 Effies behavior 3
P.J. STROOPER
68 TVC-Ziggo-2013-WifiSpots-30 Effies behavior 3
69 TVC-Shell-AirMiles-34 Effies behavior 3
70 TVC-ABNAmro-2017-Spaarverslimmers-45 Effies behavior 3
71 TVC-Telfort-2012-LekkerLangBellen-48 Effies brand 3
72 TVC-Interpolis-2018-ThuisWacht-60 No Emotional Response 3
73 TVC-Knab-2015-AllesGeven-22 No Emotional Response 3
74 TVC-Tele2-2012-Bioscoop-35 No Emotional Response 3
75 TVC-BeslistNL-2015-Sportschoenen-30 No Emotional Response 3
76 TVC-Mentos-2017-SayHello-30 Loden Leeuw 4 3
77 TVC-VanishOxiAction-2013-Vlekkenverwijderaar-45 Loden Leeuw 4 3
78 TVC-Autodrop-2010-Vingerneus-30 Loden Leeuw 4 3
79 TVC-STRATO-2014-Internet-30 Loden Leeuw 4 3
80 TVC-Knorr-2014-WereldgerechtenBurritos-35 Gouden Loeki 4
81 TVC-KNGF-2014-Buddyhond-30 Gouden Loeki 4
82 TVC-Rolo-1996-Olifant-36 Gouden Loeki 4
83 TVC-CentraalBeheer-2016-Rapper-60 Gouden Loeki 4
84 TVC-TMobile-2011-AliBAltijdSamen-45 Effies brand 4
85 TVC-Andrelon-2014-OilAndCare-40 Effies behavior 4
86 TVC-Essent-2013-ZekerDalen-30 Effies behavior 4
87 TVC-Tele2-2015-OmdatHetKan-60 Effies behavior 4
88 TVC-Coop-SamenMaakJeVerschil-45 Effies brand 4
89 TVC-Telfort-2013-Mobiel-54 Effies brand 4
90 TVC-Rabobank-2016-HypotheekBinnen1Week-30 Effies behavior 4
91 TVC-PostNL-2012-Moeder-25 Effies behavior 4
92 TVC-Nuon-NuonZonnepanelenHuren-40 Effies behavior 4
93 TVC-Clipper-ManyReasons-20 Effies behavior 4
94 TVC-Anderzorg-2016-DeLeven-20 Effies brand 4
95 TVC-Hak-2015-IlseDeLange-40 Effies brand 4
96 TVC-Eneco-2013-Toon4JarigContract-40 Effies behavior 4
97 TVC-ABNAmro-2015-IntroductieTekst-50 No Emotional Response 4
98 TVC-Smint-2017-VIP-20 No Emotional Response 4
99 TVC-Airbnb-2015-BelongAnywhere-60 No Emotional Response 4
100 TVC-KarvanCevitam-2015-Go-30' No Emotional Response 4
101 TVC-Zalando-2011-Naaktrecreatie-37 Loden Leeuw 5 4
102 TVC-Volkswagen-2013-VolkswagenHond-51 Loden Leeuw 5 4
103 TVC-BecamFinancieringen-Bouwvakker-20 Loden Leeuw 5 4
104 TVC-Bonprix-2013-Cafe-30 Loden Leeuw 5 4
105 TVC-AlbertHeijn-2015-Afscheid-80 Gouden Loeki 5
106 TVC-Bol-2014-Flappie-30 Gouden Loeki 5
P.J. STROOPER
108 TVC-Heineken-2002-DerRudi-40 Gouden Loeki 5
109 TVC-Marktplaats-2015-GaErvoor-30 Effies brand 5
110 TVC-Jumbo-2014-Moestuin-55 Effies brand 5
111 TVC-Unox-2012-KnaksKinderfeestje-25 Effies behavior 5
112 TVC-BeterBed-EdithBosch-20 Effies brand 5
113 TVC-Independer-2013-Vergelijken-26 Effies behavior 5
114 TVC-Simyo-2014-Vriendendeal-44 Effies behavior 5
115 TVC-Essent-2013-ThermostaatVanEssent-30 Effies behavior 5
116 TVC-McDonalds-2017-Maestro-60 Effies behavior 5
117 TVC-CarNext-EveryDetailMatters-40 Effies behavior 5
118 TVC-Plus-AngryBirds-20 Effies behavior 5
119 TVC-Eneco-2014-HollandseWindorigami-70 Effies brand 5
120 TVC-Flexa-Kleurtester-20 Effies brand 5
121 TVC-Hak-2016-BonenHermandenBlijker-25 Effies behavior 5
122 TVC-TempoTeam-2015-TeamUp-20 No Emotional Response 5
123 TVC-Granditalia-2014-pastamaestro-26 No Emotional Response 5
124 TVC-Interpolis-2018-ThuismeesterAppREV-62 No Emotional Response 5
125 TVC-BeslistNL-2016-Angry-32 No Emotional Response 5
126 TVC-BakkerBart-2010-Krentenbolletjes-40 Loden Leeuw 6 5
127 TVC-Yarden-2015-AdelheidRoosen-40 Loden Leeuw 6 5
128 TVC-EyeloveBrillen-2018-ReneFroger Loden Leeuw 6 5
129 TVC-Lidl-2014-GerardJoling-45 Loden Leeuw 6 5
130 TVC-KleneDrop-2017-Krakers-20 Gouden Loeki 6
131 TVC-CentraalBeheer-2010-Muis-45 Gouden Loeki 6
132 TVC-Gamma-2013-Baby-35 Gouden Loeki 6
133 TVC-Fiat-1983-Uitlachen-30 Gouden Loeki 6
134 TVC-AmstelRadler-2015-AlcoholVrij-45 Effies brand 6
135 TVC-Ford-2017-WelcomeHome-60 Effies behavior 6
136 TVC-Mona-2010-MonaXLDaarWordJeBlijVan-35 Effies brand 6
137 TVC-HertogJan-Bastaard-25 Effies behavior 6
138 TVC-PostNL-2017-Lippenstiftkus-22 Effies behavior 6
139 TVC-Telfort-2012-AllesInEen-40 Effies behavior 6
140 TVC-Jumbo-2015-BoodschappenGratis-60 Effies brand 6
141 TVC-CentraalBeheer-2013-MeerVerzekerdDanUDenkt-52 Effies behavior 6
142 TVC-Eneco-2016-Toon-25 Effies behavior 6
143 TVC-Tele2-2016-HappyDance-50 Effies behavior 6
144 TVC-Robijn-2010-DoetDeWasBij-IlseDeLange-38 Effies brand 6
145 TVC-Videoland-OnDemand-30 Effies brand 6
146 TVC-Interpolis-FocusAutomodus-30 Effies brand 6
147 TVC-ABNAmro-2015-Thuis-45 No Emotional Response 6
P.J. STROOPER
149 TVC-Nuon-2017-LuisterenGeeftEnergie-30 No Emotional Response 6
