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      Electrophysiological correlates of the interplay between low-level visual features and emotional content during word reading

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          Abstract

          Processing affectively charged visual stimuli typically results in increased amplitude of specific event-related potential (ERP) components. Low-level features similarly modulate electrophysiological responses, with amplitude changes proportional to variations in stimulus size and contrast. However, it remains unclear whether emotion-related amplifications during visual word processing are necessarily intertwined with changes in specific low-level features or, instead, may act independently. In this pre-registered electrophysiological study, we varied font size and contrast of neutral and negative words while participants were monitoring their semantic content. We examined ERP responses associated with early sensory and attentional processes as well as later stages of stimulus processing. Results showed amplitude modulations by low-level visual features early on following stimulus onset – i.e., P1 and N1 components –, while the LPP was independently modulated by these visual features. Independent effects of size and emotion were observed only at the level of the EPN. Here, larger EPN amplitudes for negative were observed only for small high contrast and large low contrast words. These results suggest that early increase in sensory processing at the EPN level for negative words is not automatic, but bound to specific combinations of low-level features, occurring presumably via attentional control processes.

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          Most cited references71

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          Attention and the detection of signals.

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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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              How to get statistically significant effects in any ERP experiment (and why you shouldn't).

              ERP experiments generate massive datasets, often containing thousands of values for each participant, even after averaging. The richness of these datasets can be very useful in testing sophisticated hypotheses, but this richness also creates many opportunities to obtain effects that are statistically significant but do not reflect true differences among groups or conditions (bogus effects). The purpose of this paper is to demonstrate how common and seemingly innocuous methods for quantifying and analyzing ERP effects can lead to very high rates of significant but bogus effects, with the likelihood of obtaining at least one such bogus effect exceeding 50% in many experiments. We focus on two specific problems: using the grand-averaged data to select the time windows and electrode sites for quantifying component amplitudes and latencies, and using one or more multifactor statistical analyses. Reanalyses of prior data and simulations of typical experimental designs are used to show how these problems can greatly increase the likelihood of significant but bogus results. Several strategies are described for avoiding these problems and for increasing the likelihood that significant effects actually reflect true differences among groups or conditions.
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                Author and article information

                Contributors
                sebastian.schindler@uni-bielefeld.de
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                15 August 2018
                15 August 2018
                2018
                : 8
                : 12228
                Affiliations
                [1 ]ISNI 0000 0001 2069 7798, GRID grid.5342.0, Department of Experimental-Clinical and Health Psychology, , Ghent University, ; Ghent, Belgium
                [2 ]ISNI 0000 0001 0944 9128, GRID grid.7491.b, Department of Psychology, , University of Bielefeld, ; Bielefeld, Germany
                [3 ]ISNI 0000 0001 2172 9288, GRID grid.5949.1, Institute of Medical Psychology and Systems Neuroscience, , University of Muenster, ; Muenster, Germany
                [4 ]Institute for Globally Distributed Open Research and Education (IGDORE), Ubud, Indonesia
                Author information
                http://orcid.org/0000-0002-7054-5431
                http://orcid.org/0000-0001-8065-6082
                Article
                30701
                10.1038/s41598-018-30701-5
                6093870
                30111849
                e6279710-e01e-45d1-9f79-738d8835194d
                © 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
                : 10 May 2018
                : 1 August 2018
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