6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Banknote authenticity is signalled by rapid neural responses

      research-article
      ,
      Scientific Reports
      Nature Publishing Group UK
      Decision, Perception

      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

          Authenticating valuable objects is widely assumed to involve protracted scrutiny for detection of reproduction flaws. Yet, accurate authentication of banknotes is possible within one second of viewing, suggesting that rapid neural processes may underpin counterfeit detection. To investigate, we measured event-related brain potentials (ERPs) in response to briefly viewed genuine or forensically recovered counterfeit banknotes presented in a visual oddball counterfeit detection task. Three ERP components, P1, P3, and extended P3, were assessed for each combination of banknote type (genuine, counterfeit) and overt response (“real”, “fake”). P1 amplitude was greater for oddballs, demonstrating that the initial feedforward sweep of visual processing yields the essential information for differentiating genuine from counterfeit. A similar oddball effect was found for P3. The magnitude of this P3 effect was positively correlated with behavioural counterfeit sensitivity, although the corresponding correlation for P1 was not. For the extended P3, amplitude was greatest for correctly detected counterfeits and similarly small for missed counterfeits, incorrectly and correctly categorised genuine banknotes. These results show that authentication of complex stimuli involves a cascade of neural processes that unfolds in under a second, beginning with a very rapid sensory analysis, followed by a later decision stage requiring higher level processing.

          Related collections

          Most cited references39

          • 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

            EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis

            We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              The Psychophysics Toolbox

                Bookmark

                Author and article information

                Contributors
                j.raymond@bham.ac.uk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                8 February 2022
                8 February 2022
                2022
                : 12
                : 2076
                Affiliations
                GRID grid.6572.6, ISNI 0000 0004 1936 7486, School of Psychology, , University of Birmingham, ; Edgbaston, Birmingham, B15 2TT UK
                Article
                5972
                10.1038/s41598-022-05972-8
                8827094
                35136115
                facece24-c213-4666-b749-8ba124f6bd93
                © The Author(s) 2022

                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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 18 October 2021
                : 18 January 2022
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                decision,perception
                Uncategorized
                decision, perception

                Comments

                Comment on this article