2019
DOI: 10.3389/fpsyt.2019.00636
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Evaluative Observation in a Concealed Information Test

Abstract: The Concealed Information Test (CIT) is a valid method to detect hidden knowledge by means of psychophysiological measures. Concealing information is always a social behavior; yet, the role of social aspects has barely been investigated in recent CIT research favoring standardized, computer-based experiments. Evaluative observation is known to influence social behavior as well as physiological measures; examining the impact of evaluative observation on physiological responding in a CIT is the aim of this study… Show more

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“…It is The copyright holder for this preprint this version posted June 18, 2021. ; https://doi.org/10.1101/2021.06.18.448944 doi: bioRxiv preprint imaging (fMRI), and stimulus-evoked brain potentials from electroencephalography (EEG), have become popular tools to record the reaction of the brain to the stimuli in the CIT (Gamer, 2014;Ganis, 2014;Hu et al, 2011;Mameli et al, 2010;Zeki et al, 2004). Although it might be noted that a measurement that is simpler and costs less, for example, electrodermal activity rather than fMRI, could be more easily adopted in forensic applications (Furedy, 2009), the CIT has proven capable of detecting concealed information across a range of measures (Ambach et al, 2010(Ambach et al, , 2019.…”
Section: Introductionmentioning
confidence: 99%
“…It is The copyright holder for this preprint this version posted June 18, 2021. ; https://doi.org/10.1101/2021.06.18.448944 doi: bioRxiv preprint imaging (fMRI), and stimulus-evoked brain potentials from electroencephalography (EEG), have become popular tools to record the reaction of the brain to the stimuli in the CIT (Gamer, 2014;Ganis, 2014;Hu et al, 2011;Mameli et al, 2010;Zeki et al, 2004). Although it might be noted that a measurement that is simpler and costs less, for example, electrodermal activity rather than fMRI, could be more easily adopted in forensic applications (Furedy, 2009), the CIT has proven capable of detecting concealed information across a range of measures (Ambach et al, 2010(Ambach et al, , 2019.…”
Section: Introductionmentioning
confidence: 99%