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

Kühn, Simone; Strelow, Enrique; Gallinat, Jürgen

doi:10.1016/j.neuroimage.2016.05.021

Cited by 89 publications

(94 citation statements)

References 38 publications

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“…Similarly, a study by Kühn et al (2016) suggests that brain activations measured by fMRI in one group of participants can predict consumer behavior in an independent sample. In this study, researchers first examined brain activations in a small sample of participants ( N = 18) while they viewed six different advertising posters for a single, new brand of chocolate bar.…”

Section: Discussionmentioning

confidence: 95%

Beyond Self-Report: A Review of Physiological and Neuroscientific Methods to Investigate Consumer Behavior

Bell

Vogt

Willemse³

et al. 2018

Front. Psychol.

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The current paper investigates the value and application of a range of physiological and neuroscientific techniques in applied marketing research and consumer science, highlighting new insights from research in social psychology and neuroscience. We review measures of sweat secretion, heart rate, facial muscle activity, eye movements, and electrical brain activity, using techniques including skin conductance, pupillometry, eyetracking, and magnetic brain imaging. For each measure, after a brief explanation of the underlying technique, we illustrate concepts and mechanisms that the measure allows researchers in marketing and consumer science to investigate, with a focus on consumer attitudes and behavior. By providing reviews on recent research that applied these methods in consumer science and relevant related fields, we also highlight methodological and theoretical strengths and limitations, with an emphasis on ecological validity. We argue that the inclusion of physiological and neuroscientific techniques can advance consumer research by providing insights into the often unconscious mechanisms underlying consumer behavior. Therefore, such technologies can help researchers and marketing practitioners understand the mechanisms of consumer behavior and improve predictions of consumer behavior.

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Section: Discussionmentioning

confidence: 95%

Beyond Self-Report: A Review of Physiological and Neuroscientific Methods to Investigate Consumer Behavior

Bell

Vogt

Willemse³

et al. 2018

Front. Psychol.

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show abstract

“…Nonetheless, implicit familiarity is more difficult to account for than explicit familiarity and therefore, should be addressed in further work (38). Furthermore, as in other neuroforecasting studies (24), future research might ideally forecast aggregate time allocation metrics collected after acquisition of brain data (although changes in the youtube.com interface have rendered these metrics less accessible). The cost-effectiveness of neuroforecasting applications may vary since tracking subcortical activity with FMRI is currently expensive and requires technical expertise.…”

Section: Discussionmentioning

confidence: 99%

“…If brain activity predicts time allocation in individuals, might it also forecast time allocation at the aggregate level in attention markets [here, "prediction" refers to predicting behavior within individuals, whereas "forecast" refers to predicting behavior across individuals but not necessarily across time (20)]? In laboratory samples, group NAcc activity can forecast music sales (21), microloan appeal success (22), advertisement efficacy (23), food purchases (24), news article popularity (25), and crowdfunding…”

mentioning

confidence: 99%

Brain activity forecasts video engagement in an internet attention market

Tong

Acikalin

Genevsky

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

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The growth of the internet has spawned new “attention markets,” in which people devote increasing amounts of time to consuming online content, but the neurobehavioral mechanisms that drive engagement in these markets have yet to be elucidated. We used functional MRI (FMRI) to examine whether individuals’ neural responses to videos could predict their choices to start and stop watching videos as well as whether group brain activity could forecast aggregate video view frequency and duration out of sample on the internet (i.e., onyoutube.com). Brain activity during video onset predicted individual choice in several regions (i.e., increased activity in the nucleus accumbens [NAcc] and medial prefrontal cortex [MPFC] as well as decreased activity in the anterior insula [AIns]). Group activity during video onset in only a subset of these regions, however, forecasted both aggregate view frequency and duration (i.e., increased NAcc and decreased AIns)—and did so above and beyond conventional measures. These findings extend neuroforecasting theory and tools by revealing that activity in brain regions implicated in anticipatory affect at the onset of video viewing (but not initial choice) can forecast time allocation out of sample in an internet attention market.

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“…It has, for example, been successfully used to study systems involved with sensory-motor functions (Biswal et al, 1995; Calvo-Merino et al, 2005), language (Woermann et al, 2003; Centeno et al, 2014), visuospatial orientation (Formisano et al, 2002; Rao and Singh, 2015), attention (Vuilleumier et al, 2001; Markett et al, 2014), memory (Machulda et al, 2003; Sidhu et al, 2015) affective processing (Kiehl et al, 2001; Shinkareva et al, 2014), working memory (Curtis and D'Esposito, 2003; Meyer et al, 2015), personality dimensions (Canli et al, 2001; Sampaio et al, 2013), decision-making (Bush et al, 2002; Soares et al, 2012), and executive function (Just et al, 2007; Di et al, 2014). Functional MRI has also been used as a tool in the study of topics as diverse as addiction behavior (Chase and Clark, 2010; Kober et al, 2016), neuromarketing (Ariely and Berns, 2010; Kuhn et al, 2016) and politics (Knutson et al, 2006), among others.…”

Section: Application Fieldsmentioning

confidence: 99%

A Hitchhiker's Guide to Functional Magnetic Resonance Imaging

et al. 2016

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Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular both with clinicians and researchers as they are capable of providing unique insights into brain functions. However, multiple technical considerations (ranging from specifics of paradigm design to imaging artifacts, complex protocol definition, and multitude of processing and methods of analysis, as well as intrinsic methodological limitations) must be considered and addressed in order to optimize fMRI analysis and to arrive at the most accurate and grounded interpretation of the data. In practice, the researcher/clinician must choose, from many available options, the most suitable software tool for each stage of the fMRI analysis pipeline. Herein we provide a straightforward guide designed to address, for each of the major stages, the techniques, and tools involved in the process. We have developed this guide both to help those new to the technique to overcome the most critical difficulties in its use, as well as to serve as a resource for the neuroimaging community.

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

Cited by 89 publications

References 38 publications

Beyond Self-Report: A Review of Physiological and Neuroscientific Methods to Investigate Consumer Behavior

Beyond Self-Report: A Review of Physiological and Neuroscientific Methods to Investigate Consumer Behavior

Brain activity forecasts video engagement in an internet attention market

A Hitchhiker's Guide to Functional Magnetic Resonance Imaging

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