8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Neuronal Correlates of Product Feature Attractiveness

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Decision-making is the process of selecting a logical choice from among the available options and happens as a complex process in the human brain. It is based on information processing and cost-analysis; it involves psychological factors, specifically, emotions. In addition to cost factors personal preferences have significant influence on decision making. For marketing purposes, it is interesting to know how these emotions are related to product acquisition decision and how to improve these products according to the user's preferences. For our proof-of-concept study, we use magneto- and electro-encephalography (MEG, EEG) to evaluate the very early reactions in the brain related to the emotions. Recordings from these methods are comprehensive sources of information to investigate neural processes of the human brain with good spatial- and excellent temporal resolution. Those characteristics make these methods suitable to examine the neurologic process that gives origin to human behavior and specifically, decision making. Literature describes some neuronal correlates for individual preferences, like asymmetrical distribution of frequency specific activity in frontal and prefrontal areas, which are associated with emotional processing. Such correlates could be used to objectively evaluate the pleasantness of product appearance and branding (i.e., logo), thus avoiding subjective bias. This study evaluates the effects of different product features on brain activity and whether these methods could potentially be used for marketing and product design. We analyzed the influence of color and fit of sports shirts, as well as a brand logo on the brain activity, specifically in frontal asymmetric activation. Measurements were performed using MEG and EEG with 10 healthy subjects. Images of t-shirts with different characteristics were presented on a screen. We recorded the subjective evaluation by asking for a positive, negative or neutral rating. The results showed significantly different responses between positively and negatively rated shirts. While the influence of the presence of a logo was present in behavioral data, but not in the neurocognitive data, the influence of shirt fit and color could be reconstructed in both data sets. This method may enable evaluation of subjective product preference.

          Related collections

          Most cited references38

          • Record: found
          • Abstract: not found
          • Article: not found

          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain.

            We describe almost entirely automated procedures for estimation of global, voxel, and cluster-level statistics to test the null hypothesis of zero neuroanatomical difference between two groups of structural magnetic resonance imaging (MRI) data. Theoretical distributions under the null hypothesis are available for 1) global tissue class volumes; 2) standardized linear model [analysis of variance (ANOVA and ANCOVA)] coefficients estimated at each voxel; and 3) an area of spatially connected clusters generated by applying an arbitrary threshold to a two-dimensional (2-D) map of normal statistics at voxel level. We describe novel methods for economically ascertaining probability distributions under the null hypothesis, with fewer assumptions, by permutation of the observed data. Nominal Type I error control by permutation testing is generally excellent; whereas theoretical distributions may be over conservative. Permutation has the additional advantage that it can be used to test any statistic of interest, such as the sum of suprathreshold voxel statistics in a cluster (or cluster mass), regardless of its theoretical tractability under the null hypothesis. These issues are illustrated by application to MRI data acquired from 18 adolescents with hyperkinetic disorder and 16 control subjects matched for age and gender.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Permutation Methods: A Basis for Exact Inference

                Bookmark

                Author and article information

                Contributors
                Journal
                Front Behav Neurosci
                Front Behav Neurosci
                Front. Behav. Neurosci.
                Frontiers in Behavioral Neuroscience
                Frontiers Media S.A.
                1662-5153
                17 July 2018
                2018
                : 12
                : 147
                Affiliations
                [1] 1Division of Sports and Exercise Medicine, Department of Sport Science and Sport, Friedrich-Alexander-Universität Erlangen-Nuremberg , Erlangen, Germany
                [2] 2Department of Neurosurgery, University of Halle , Halle, Germany
                [3] 3Department of Neurosurgery, University Hospital Erlangen , Erlangen, Germany
                Author notes

                Edited by: Bahar Güntekin, School of International Medicine, Istanbul Medipol University, Turkey

                Reviewed by: Maria Elide Vanutelli, Università degli Studi di Milano, Italy; Thomas Zoëga Ramsøy, Neurons Inc., Denmark

                *Correspondence: Franziska Schoen franziska.schoen@ 123456fau.de
                Article
                10.3389/fnbeh.2018.00147
                6059068
                30072882
                ab077048-d518-4d0e-af3b-84cdf948a1d7
                Copyright © 2018 Schoen, Lochmann, Prell, Herfurth and Rampp.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 05 March 2018
                : 26 June 2018
                Page count
                Figures: 6, Tables: 4, Equations: 0, References: 41, Pages: 13, Words: 7792
                Categories
                Neuroscience
                Original Research

                Neurosciences
                magnetoencephalography,electroencephalography,neurology,brain activity,attractiveness,emotion

                Comments

                Comment on this article