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Wang C, Yi X, Li H, Ke N, Lei Z, Fu G, Lin XA. Memory detection with concurrent behavioral, autonomic, and neuroimaging measures in a mock crime. Psychophysiology 2024:e14701. [PMID: 39392401 DOI: 10.1111/psyp.14701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Revised: 09/07/2024] [Accepted: 09/19/2024] [Indexed: 10/12/2024]
Abstract
Concealed information test (CIT) has been utilized for long to perform single measurements. The combination of multiple measures outperforms single measures because of the diverse cognitive processes they reflect and the reduction in random errors facilitated by multiple measures. To further explore the performance of the CIT with multiple measurements, 57 participants were recruited and randomly assigned into guilty and innocent groups. Subsequently, simultaneously recorded reaction time (RT), skin conductance responses (SCRs), heart rate (HR), and neuroimaging data were collected from functional near-infrared spectroscopy (fNIRS) to detect participants' concealed information in a standard CIT. The results demonstrated that all indicators including RT (area under the curve (AUC) = 0.87), SCRs (AUC = 0.79), HR (AUC = 0.78), and fNIRS (channel 8, AUC = 0.85) could differentiate guilty and innocent groups. Importantly, the use of multiple indicators achieved higher detection efficiency (AUC = 0.96) compared to the use of any single indicator. These results illustrate the effectiveness and feasibility of integrating multiple indicators for concealed information detection in CIT.
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Affiliation(s)
- Chongxiang Wang
- Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou, China
- Department of Psychology, Hangzhou Normal University, Hangzhou, China
- Department of Psychological and Cognitive Sciences, Tsinghua University, Beijing, China
| | - Xingyu Yi
- Department of Psychology, Hangzhou Normal University, Hangzhou, China
| | - Hongrui Li
- Department of Psychology, Hangzhou Normal University, Hangzhou, China
| | - Ni Ke
- Department of Psychology, Hangzhou Normal University, Hangzhou, China
| | - Zhili Lei
- Department of Psychology, Hangzhou Normal University, Hangzhou, China
| | - Genyue Fu
- Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou, China
- Department of Psychology, Hangzhou Normal University, Hangzhou, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, China
| | - Xiaohong Allison Lin
- Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou, China
- Department of Psychology, Hangzhou Normal University, Hangzhou, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, China
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Chen Y, Fazli S, Wallraven C. An EEG Dataset of Neural Signatures in a Competitive Two-Player Game Encouraging Deceptive Behavior. Sci Data 2024; 11:389. [PMID: 38627400 PMCID: PMC11021485 DOI: 10.1038/s41597-024-03234-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/05/2024] [Indexed: 04/19/2024] Open
Abstract
Studying deception is vital for understanding decision-making and social dynamics. Recent EEG research has deepened insights into the brain mechanisms behind deception. Standard methods in this field often rely on memory, are vulnerable to countermeasures, yield false positives, and lack real-world relevance. Here, we present a comprehensive dataset from an EEG-monitored competitive, two-player card game designed to elicit authentic deception behavior. Our extensive dataset contains EEG data from 12 pairs (N = 24 participants with role switching), controlled for age, gender, and risk-taking, with detailed labels and annotations. The dataset combines standard event-related potential and microstate analyses with state-of-the-art decoding approaches of four scenarios: spontaneous/instructed truth-telling and lying. This demonstrates game-based methods' efficacy in studying deception and sets a benchmark for future research. Overall, our dataset represents a unique resource with applications in cognitive neuroscience and related fields for studying deception, competitive behavior, decision-making, inter-brain synchrony, and benchmarking of decoding frameworks in a difficult, high-level cognitive task.
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Affiliation(s)
- Yiyu Chen
- Department of Artificial Intelligence, Korea University, Seoul, 02841, South Korea
| | - Siamac Fazli
- Department of Computer Science, Nazarbayev University, Astana, 010000, Kazakhstan
| | - Christian Wallraven
- Department of Artificial Intelligence, Korea University, Seoul, 02841, South Korea.
- Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, South Korea.
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Mecacci G, Haselager P. Identifying Criteria for the Evaluation of the Implications of Brain Reading for Mental Privacy. SCIENCE AND ENGINEERING ETHICS 2019; 25:443-461. [PMID: 29247306 PMCID: PMC6450833 DOI: 10.1007/s11948-017-0003-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2017] [Accepted: 11/03/2017] [Indexed: 05/29/2023]
Abstract
Contemporary brain reading technologies promise to provide the possibility to decode and interpret mental states and processes. Brain reading could have numerous societally relevant implications. In particular, the private character of mind might be affected, generating ethical and legal concerns. This paper aims at equipping ethicists and policy makers with conceptual tools to support an evaluation of the potential applicability and the implications of current and near future brain reading technology. We start with clarifying the concepts of mind reading and brain reading, and the different kinds of mental states that could in principle be read. Subsequently, we devise an evaluative framework that is composed of five criteria-accuracy, reliability, informativity, concealability and enforceability-aimed at enabling a clearer estimation of the degree to which brain reading might be realistically deployed in contexts where mental privacy could be at stake. While accuracy and reliability capture how well a certain method can access mental content, informativity indicates the relevance the obtainable data have for practical purposes. Concealability and enforceability are particularly important for the evaluation of concerns about potential violations of mental privacy and civil rights. The former concerns the degree with which a brain reading method can be concealed from an individual's perception or awareness. The latter regards the extent to which a method can be used against somebody's will. With the help of these criteria, stakeholders can orient themselves in the rapidly developing field of brain reading.
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Affiliation(s)
- Giulio Mecacci
- Donders Institute for Brain, Cognition and Behaviour, Montessorilaan 3, 6525 HR Nijmegen, The Netherlands
| | - Pim Haselager
- Donders Institute for Brain, Cognition and Behaviour, Montessorilaan 3, 6525 HR Nijmegen, The Netherlands
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Hsu CW, Begliomini C, Dall'Acqua T, Ganis G. The effect of mental countermeasures on neuroimaging-based concealed information tests. Hum Brain Mapp 2019; 40:2899-2916. [PMID: 30864277 DOI: 10.1002/hbm.24567] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2018] [Revised: 02/24/2019] [Accepted: 02/26/2019] [Indexed: 11/05/2022] Open
Abstract
During the last decade and a half, functional magnetic resonance imaging (fMRI) has been used to determine whether it is possible to detect concealed knowledge by examining brain activation patterns, with mixed results. Concealed information tests rely on the logic that a familiar item (probe) elicits a stronger response than unfamiliar, but otherwise comparable items (irrelevants). Previous work has shown that physical countermeasures can artificially modulate neural responses in concealed information tests, decreasing the accuracy of these methods. However, the question remains as to whether purely mental countermeasures, which are much more difficult to detect than physical ones, can also be effective. An fMRI study was conducted to address this question by assessing the effect of attentional countermeasures on the accuracy of the classification between knowledge and no-knowledge cases using both univariate and multivariate analyses. Results replicate previous work and show reliable group activation differences between the probe and the irrelevants in fronto-parietal networks. Critically, classification accuracy was generally reduced by the mental countermeasures, but only significantly so with region of interest analyses (both univariate and multivariate). For whole-brain analyses, classification accuracy was relatively low, but it was not significantly reduced by the countermeasures. These results indicate that mental countermeasure need to be addressed before these paradigms can be used in applied settings and that methods to defeat countermeasures, or at least to detect their use, need to be developed. HIGHLIGHTS: FMRI-based concealed information tests are vulnerable to mental countermeasures Measures based on regions of interest are affected by mental countermeasures Whole-brain analyses may be more robust than region of interest ones Methods to detect mental countermeasure use are needed for forensic applications.
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Affiliation(s)
- Chun-Wei Hsu
- School of Psychology and Cognition Institute, University of Plymouth, Plymouth, UK
| | - Chiara Begliomini
- Department of General Psychology, University of Padova, Padova, Italy.,Cognitive Neuroscience Center, University of Padova, Padova, Italy
| | | | - Giorgio Ganis
- School of Psychology and Cognition Institute, University of Plymouth, Plymouth, UK
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Hebart MN, Baker CI. Deconstructing multivariate decoding for the study of brain function. Neuroimage 2018; 180:4-18. [PMID: 28782682 PMCID: PMC5797513 DOI: 10.1016/j.neuroimage.2017.08.005] [Citation(s) in RCA: 138] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2017] [Revised: 07/28/2017] [Accepted: 08/01/2017] [Indexed: 12/24/2022] Open
Abstract
Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the study of brain function was firmly embedded in a statistical philosophy grounded on univariate methods of data analysis. In this way, multivariate decoding for brain interpretation grew out of two established frameworks: multivariate decoding for predictions in real-world applications, and classical univariate analysis based on the study and interpretation of brain activation. We argue that this led to two confusions, one reflecting a mixture of multivariate decoding for prediction or interpretation, and the other a mixture of the conceptual and statistical philosophies underlying multivariate decoding and classical univariate analysis. Here we attempt to systematically disambiguate multivariate decoding for the study of brain function from the frameworks it grew out of. After elaborating these confusions and their consequences, we describe six, often unappreciated, differences between classical univariate analysis and multivariate decoding. We then focus on how the common interpretation of what is signal and noise changes in multivariate decoding. Finally, we use four examples to illustrate where these confusions may impact the interpretation of neuroimaging data. We conclude with a discussion of potential strategies to help resolve these confusions in interpreting multivariate decoding results, including the potential departure from multivariate decoding methods for the study of brain function.
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Affiliation(s)
- Martin N Hebart
- Section on Learning and Plasticity, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Chris I Baker
- Section on Learning and Plasticity, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
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Multi-voxel pattern classification differentiates personally experienced event memories from secondhand event knowledge. Neuroimage 2018; 176:110-123. [DOI: 10.1016/j.neuroimage.2018.04.024] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2017] [Revised: 03/25/2018] [Accepted: 04/10/2018] [Indexed: 02/03/2023] Open
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Lu Y, Rosenfeld JP, Deng X, Zhang E, Zheng H, Yan G, Ouyang D, Hayat SZ. Inferior detection of information from collaborative versus individual crimes based on a P300 Concealed Information Test. Psychophysiology 2017; 55. [DOI: 10.1111/psyp.13021] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Revised: 08/22/2017] [Accepted: 09/12/2017] [Indexed: 11/28/2022]
Affiliation(s)
- Yang Lu
- Department of Psychology, Faculty of Education; Hubei University; Wuhan China
| | - J. Peter Rosenfeld
- Department of Psychology; Institute for Neuroscience, Northwestern University; Evanston Illinois USA
| | - Xiaohong Deng
- Department of Psychology, Faculty of Education; Hubei University; Wuhan China
| | - Erhu Zhang
- Department of Psychology, Faculty of Education; Hubei University; Wuhan China
| | - Huihui Zheng
- Department of Psychology, Faculty of Education; Hubei University; Wuhan China
| | - Gejun Yan
- Department of Psychology, Faculty of Education; Hubei University; Wuhan China
| | - Dan Ouyang
- Department of Psychology, Faculty of Education; Hubei University; Wuhan China
| | - Saba Z. Hayat
- Department of Psychology, Faculty of Education; Hubei University; Wuhan China
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Ganis G, Bridges D, Hsu CW, Schendan HE. Is anterior N2 enhancement a reliable electrophysiological index of concealed information? Neuroimage 2016; 143:152-165. [PMID: 27570109 DOI: 10.1016/j.neuroimage.2016.08.042] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2016] [Revised: 08/17/2016] [Accepted: 08/19/2016] [Indexed: 10/21/2022] Open
Abstract
Concealed information tests (CITs) are used to determine whether an individual possesses information about an item of interest. Event-related potential (ERP) measures in CITs have focused almost exclusively on the P3b component, showing that this component is larger when lying about the item of interest (probe) than telling the truth about control items (irrelevants). Recent studies have begun to examine other ERP components, such as the anterior N2, with mixed results. A seminal CIT study found that visual probes elicit a larger anterior N2 than irrelevants (Gamer and Berti, 2010) and suggested that this component indexes cognitive control processes engaged when lying about probes. However, this study did not control for potential intrinsic differences among the stimuli: the same probe and irrelevants were used for all participants, and there was no control condition composed of uninformed participants. Here, first we show that the N2 effect found in the study by Gamer and Berti (2010) was in large part due to stimulus differences, as the effect observed in a concealed information condition was comparable to that found in two matched control conditions without any concealed information (Experiments 1 and 2). Next, we addressed the issue of the generality of the N2 findings by counterbalancing a new set of stimuli across participants and by using a control condition with uninformed participants (Experiment 3). Results show that the probe did not elicit a larger anterior N2 than the irrelevants under these controlled conditions. These findings suggest that caution should be taken in using the N2 as an index of concealed information in CITs. Furthermore, they are a reminder that results of CIT studies (not only with ERPs) performed without stimulus counterbalancing and suitable control conditions may be confounded by differential intrinsic properties of the stimuli employed.
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Affiliation(s)
- Giorgio Ganis
- School of Psychology, University of Plymouth, Plymouth, UK; Cognition Institute, University of Plymouth, Plymouth, UK; Department of Radiology, Harvard Medical School, Boston, MA 02115, USA; Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129, USA.
| | - David Bridges
- School of Psychology, University of Plymouth, Plymouth, UK; Cognition Institute, University of Plymouth, Plymouth, UK
| | - Chun-Wei Hsu
- School of Psychology, University of Plymouth, Plymouth, UK; Cognition Institute, University of Plymouth, Plymouth, UK
| | - Haline E Schendan
- School of Psychology, University of Plymouth, Plymouth, UK; Cognition Institute, University of Plymouth, Plymouth, UK
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Meijer EH, Verschuere B, Gamer M, Merckelbach H, Ben-Shakhar G. Deception detection with behavioral, autonomic, and neural measures: Conceptual and methodological considerations that warrant modesty. Psychophysiology 2016; 53:593-604. [DOI: 10.1111/psyp.12609] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Accepted: 12/18/2015] [Indexed: 10/22/2022]
Affiliation(s)
- Ewout H. Meijer
- Department of Clinical Psychological Science; Maastricht University; Maastricht The Netherlands
| | - Bruno Verschuere
- Department of Clinical Psychological Science; Maastricht University; Maastricht The Netherlands
- Department of Clinical Psychology; University of Amsterdam; Amsterdam The Netherlands
| | - Matthias Gamer
- Department of Psychology; University of Würzburg; Würzburg Germany
| | - Harald Merckelbach
- Department of Clinical Psychological Science; Maastricht University; Maastricht The Netherlands
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