Neuromarketing: the hope and hype of neuroimaging in business

Correlated components of ongoing EEG point to emotionally laden attention - a possible marker of engagement?

Recent evidence from functional magnetic resonance imaging suggests that cortical hemodynamic responses coincide in different subjects experiencing a common naturalistic stimulus. Here we utilize neural responses in the electroencephalogram (EEG) evoked by multiple presentations of short film clips to index brain states marked by high levels of correlation within and across subjects. We formulate a novel signal decomposition method which extracts maximally correlated signal components from multiple EEG records. The resulting components capture correlations down to a one-second time resolution, thus revealing that peak correlations of neural activity across viewings can occur in remarkable correspondence with arousing moments of the film. Moreover, a significant reduction in neural correlation occurs upon a second viewing of the film or when the narrative is disrupted by presenting its scenes scrambled in time. We also probe oscillatory brain activity during periods of heightened correlation, and observe during such times a significant increase in the theta band for a frontal component and reductions in the alpha and beta frequency bands for parietal and occipital components. Low-resolution EEG tomography of these components suggests that the correlated neural activity is consistent with sources in the cingulate and orbitofrontal cortices. Put together, these results suggest that the observed synchrony reflects attention- and emotion-modulated cortical processing which may be decoded with high temporal resolution by extracting maximally correlated components of neural activity.

The rise of neuroskepticism

The increasing popularity of functional neuroimaging technologies in multiple disciplines has gained attention from within and outside the field of neuroscience. As the scope of research employing functional neuroimaging technologies broadens, there appears to also be a growing concern about the use of these technologies and the related social, ethical and legal issues. These concerns have been coined 'neuroskepticism'. First, we review how the term neuroskepticism has been previously used and defined. Second, we examine review and commentary articles published in journals with top impact factors, probing the presence and evolution of neuroskepticism within these articles. Results demonstrate a wide, but expected, range of issues associated with functional neuroimaging. It also appears that neuroskepticism is increasing as functional neuroimaging technologies gain popularity, which may indicate the presence of a classic Gartner Hype Cycle.

Own-gender imitation activates the brain's reward circuitry

Imitation is an important component of human social learning throughout life. Theoretical models and empirical data from anthropology and psychology suggest that people tend to imitate self-similar individuals, and that such imitation biases increase the adaptive value (e.g., self-relevance) of learned information. It is unclear, however, what neural mechanisms underlie people's tendency to imitate those similar to themselves. We focused on the own-gender imitation bias, a pervasive bias thought to be important for gender identity development. While undergoing fMRI, participants imitated own- and other-gender actors performing novel, meaningless hand signs; as control conditions, they also simply observed such actions and viewed still portraits of the same actors. Only the ventral and dorsal striatum, orbitofrontal cortex and amygdala were more active when imitating own- compared to other-gender individuals. A Bayesian analysis of the BrainMap neuroimaging database demonstrated that the striatal region preferentially activated by own-gender imitation is selectively activated by classical reward tasks in the literature. Taken together, these findings reveal a neurobiological mechanism associated with the own-gender imitation bias and demonstrate a novel role of reward-processing neural structures in social behavior.

Inferring mental states from neuroimaging data: from reverse inference to large-scale decoding

A common goal of neuroimaging research is to use imaging data to identify the mental processes that are engaged when a subject performs a mental task. The use of reasoning from activation to mental functions, known as "reverse inference," has been previously criticized on the basis that it does not take into account how selectively the area is activated by the mental process in question. In this Perspective, I outline the critique of informal reverse inference and describe a number of new developments that provide the ability to more formally test the predictive power of neuroimaging data.

Brain computer interfaces, a review

A brain-computer interface (BCI) is a hardware and software communications system that permits cerebral activity alone to control computers or external devices. The immediate goal of BCI research is to provide communications capabilities to severely disabled people who are totally paralyzed or 'locked in' by neurological neuromuscular disorders, such as amyotrophic lateral sclerosis, brain stem stroke, or spinal cord injury. Here, we review the state-of-the-art of BCIs, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface. We discuss their advantages, drawbacks, and latest advances, and we survey the numerous technologies reported in the scientific literature to design each step of a BCI. First, the review examines the neuroimaging modalities used in the signal acquisition step, each of which monitors a different functional brain activity such as electrical, magnetic or metabolic activity. Second, the review discusses different electrophysiological control signals that determine user intentions, which can be detected in brain activity. Third, the review includes some techniques used in the signal enhancement step to deal with the artifacts in the control signals and improve the performance. Fourth, the review studies some mathematic algorithms used in the feature extraction and classification steps which translate the information in the control signals into commands that operate a computer or other device. Finally, the review provides an overview of various BCI applications that control a range of devices.

"Can it read my mind?" - What do the public and experts think of the current (mis)uses of neuroimaging?

Emerging applications of neuroimaging outside medicine and science have received intense public exposure through the media. Media misrepresentations can create a gulf between public and scientific understanding of the capabilities of neuroimaging and raise false expectations. To determine the extent of this effect and determine public opinions on acceptable uses and the need for regulation, we designed an electronic survey to obtain anonymous opinions from as wide a range of members of the public and neuroimaging experts as possible. The surveys ran from 1^st June to 30 September 2010, asked 10 and 21 questions, respectively, about uses of neuroimaging outside traditional medical diagnosis, data storage, science communication and potential methods of regulation. We analysed the responses using descriptive statistics; 660 individuals responded to the public and 303 individuals responded to the expert survey. We found evidence of public skepticism about the use of neuroimaging for applications such as lie detection or to determine consumer preferences and considerable disquiet about use by employers or government and about how their data would be stored and used. While also somewhat skeptical about new applications of neuroimaging, experts grossly underestimated how often neuroimaging had been used as evidence in court. Although both the public and the experts rated highly the importance of a better informed public in limiting the inappropriate uses to which neuroimaging might be put, opinions differed on the need for, and mechanism of, actual regulation. Neuroscientists recognized the risks of inaccurate reporting of neuroimaging capabilities in the media but showed little motivation to engage with the public. The present study also emphasizes the need for better frameworks for scientific engagement with media and public education.

The cognitive neuroscience toolkit for the neuroeconomist: A functional overview

This article provides the beginning neuroeconomist with an introductory overview to the different methods used in human neuroscience. It describes basic strengths and weaknesses of each technique, points to examples of how each technique has been used in neuroeconomic studies, and provides key tutorial references that contain more detailed information. In addition to this overview, the article presents a framework that organizes human neuroscience methods functionally, according to whether they provide tests of the association between brain activity and cognition or behavior, or whether they test the necessity or the sufficiency of brain activity for cognition and behavior. This framework demonstrates the utility of a multi-method research approach, since converging evidence from tests of association, necessity and sufficiency provides the strongest inference regarding brain-behavior relationships. Set against this goal of converging evidence, human neuroscience studies in neuroeconomics currently rely far too heavily on methods that test association, most notably functional MRI.

The structure of the EU mediasphere

BACKGROUND

A trend towards automation of scientific research has recently resulted in what has been termed "data-driven inquiry" in various disciplines, including physics and biology. The automation of many tasks has been identified as a possible future also for the humanities and the social sciences, particularly in those disciplines concerned with the analysis of text, due to the recent availability of millions of books and news articles in digital format. In the social sciences, the analysis of news media is done largely by hand and in a hypothesis-driven fashion: the scholar needs to formulate a very specific assumption about the patterns that might be in the data, and then set out to verify if they are present or not.

METHODOLOGY/PRINCIPAL FINDINGS

In this study, we report what we think is the first large scale content-analysis of cross-linguistic text in the social sciences, by using various artificial intelligence techniques. We analyse 1.3 M news articles in 22 languages detecting a clear structure in the choice of stories covered by the various outlets. This is significantly affected by objective national, geographic, economic and cultural relations among outlets and countries, e.g., outlets from countries sharing strong economic ties are more likely to cover the same stories. We also show that the deviation from average content is significantly correlated with membership to the eurozone, as well as with the year of accession to the EU.

CONCLUSIONS/SIGNIFICANCE

While independently making a multitude of small editorial decisions, the leading media of the 27 EU countries, over a period of six months, shaped the contents of the EU mediasphere in a way that reflects its deep geographic, economic and cultural relations. Detecting these subtle signals in a statistically rigorous way would be out of the reach of traditional methods. This analysis demonstrates the power of the available methods for significant automation of media content analysis.

[Neuromarketing: When marketing meet neurosciences]

INTRODUCTION

The emergence of brain imaging in recent years has been accompanied by an alliance between neuroscientists and marketers. This collaboration gave birth to "neuromarketing", a new field that uses imaging techniques with the aim of resolving marketing issues.

STATE OF THE ART

Several studies have shown that pleasure felt at the sight of a product or after its consumption, is activated by a reward system involving ventral striatum. Since then, marketers seeking exploit this data and have found that some marketing actions can generate added satisfaction in a placebo-like manner. However, neuromarketing suffer from many limits that are a barrier to its development and its scope is restricted.

PERSPECTIVES

Through this article, we attempt to give an overview on neuromarketing and its neural correlates while provide a perspective toward the use of field for less commercial purposes.

CONCLUSION

The neuromarketing is a new field which efficiency is not proven. Its results must be interpreted with caution.

Defining neuromarketing: practices and professional challenges

Neuromarketing has recently generated controversies concerning the involvement of medical professionals, and many key questions remain-ones that have potentially important implications for the field of psychiatry. Conflicting definitions of neuromarketing have been proposed, and little is known about the actual practices of companies, physicians, and scientists involved in its practice. This article reviews the history of neuromarketing and uses an exploratory survey of neuromarketing Web sites to illustrate ethical issues raised by this new field. Neuromarketing, as currently practiced, is heterogeneous, as companies are offering a variety of technologies. Many companies employ academicians and professionals, but few list their clients or fees. Media coverage of neuromarketing appears disproportionately high compared to the paucity of peer-reviewed reports in the field. Companies may be making premature claims about the power of neuroscience to predict consumer behavior. Overall, neuromarketing has important implications for academic-industrial partnerships, the responsible conduct of research, and the public understanding of the brain. We explore these themes to uncover issues relevant to professional ethics, research, and policy. Of particular relevance to psychiatry, neuromarketing may be seen as an extension of the search for quantification and certainty in previously indefinite aspects of human behavior.