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      Temporal and spectral EEG dynamics can be indicators of stealth placement

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          Abstract

          Stealth placement marketing, where consumers are unaware that they are being marketed to, attempts to reduce the audiences’ resistance to traditional persuasive advertising. It is a form of advertising that involves targeted exposure of brands or products incorporated in other works, usually with or without explicit reference to the brands or products. Brand placement can be presented in different visual and auditory forms in video programs. The present study proposed that different ‘representations’ (i.e., representable or non-representable) and ‘sounds’ (i.e., speech or musical sound) of brand placement can affect the viewers’ perception of the brand. Event-related potential results indicated significant differences in P1, N1, P2, N270, and P3. Further, event-related spectral perturbation results indicated significant differences in theta, alpha, beta, and gamma (30–100 Hz), in the right parietal, right occipital area, and limbic lobe. ‘Non-representable’ or ‘speech sound’ brand placement induced significant temporal and spectral EEG dynamics in viewers.

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          Most cited references109

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          Removing electroencephalographic artifacts by blind source separation.

          Eye movements, eye blinks, cardiac signals, muscle noise, and line noise present serious problems for electroencephalographic (EEG) interpretation and analysis when rejecting contaminated EEG segments results in an unacceptable data loss. Many methods have been proposed to remove artifacts from EEG recordings, especially those arising from eye movements and blinks. Often regression in the time or frequency domain is performed on parallel EEG and electrooculographic (EOG) recordings to derive parameters characterizing the appearance and spread of EOG artifacts in the EEG channels. Because EEG and ocular activity mix bidirectionally, regressing out eye artifacts inevitably involves subtracting relevant EEG signals from each record as well. Regression methods become even more problematic when a good regressing channel is not available for each artifact source, as in the case of muscle artifacts. Use of principal component analysis (PCA) has been proposed to remove eye artifacts from multichannel EEG. However, PCA cannot completely separate eye artifacts from brain signals, especially when they have comparable amplitudes. Here, we propose a new and generally applicable method for removing a wide variety of artifacts from EEG records based on blind source separation by independent component analysis (ICA). Our results on EEG data collected from normal and autistic subjects show that ICA can effectively detect, separate, and remove contamination from a wide variety of artifactual sources in EEG records with results comparing favorably with those obtained using regression and PCA methods. ICA can also be used to analyze blink-related brain activity.
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            Modulation of Oscillatory Neuronal Synchronization by Selective Visual Attention

            P. Fries (2001)
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              Electrophysiological correlates of feature analysis during visual search.

              Event-related brain potentials (ERPs) were recorded from normal young adults during visual search tasks in which the stimulus arrays contained either eight identical items (homogeneous arrays) or seven identical items and one deviant item (pop-out arrays). Four experiments were conducted in which different classes of stimulus arrays were designated targets and the remaining stimulus arrays were designated nontargets. In Experiments 1 and 2, both target and nontarget pop-out stimuli elicited an enhanced anterior N2 wave and a contralaterally larger posterior P1 wave, but Experiments 3 and 4 demonstrated that these components do not reflect fully automatic pop-out detection processes. In all four experiments, target pop-outs elicited enlarged anterior P2, posterior N2, occipital P3, and parietal P3 waves. The target-elicited posterior N2 wave contained a contralateral subcomponent (N2pc) that exhibited a focus over occipital cortex in maps of current source density. The overall pattern of results was consistent with guided search models in which preattentive stimulus information is used to guide attention to task-relevant stimuli.
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                Author and article information

                Contributors
                wyw@mail.ntust.edu.tw
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                14 June 2018
                14 June 2018
                2018
                : 8
                : 9117
                Affiliations
                [1 ]ISNI 0000 0000 9744 5137, GRID grid.45907.3f, Design Perceptual Awareness Lab (D:PAL), , National Taiwan University of Science and Technology (Taiwan Tech), ; Taipei, Taiwan
                [2 ]ISNI 0000 0000 9744 5137, GRID grid.45907.3f, The Department of Industrial and Commercial Design, , National Taiwan University of Science and Technology (Taiwan Tech), ; Taipei, Taiwan
                [3 ]ISNI 0000 0000 9744 5137, GRID grid.45907.3f, Taiwan Building Technology Center, , National Taiwan University of Science and Technology (Taiwan Tech), ; Taipei, Taiwan
                Article
                27294
                10.1038/s41598-018-27294-4
                6002479
                29904124
                d8a6e6b2-a331-4d90-bb4d-f61b03d2225c
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 2 January 2018
                : 18 May 2018
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