{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T12:13:30Z","timestamp":1788783210944,"version":"build-2803163510"},"reference-count":75,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T00:00:00Z","timestamp":1781740800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:00:00Z","timestamp":1788739200000},"content-version":"vor","delay-in-days":81,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"National Science Foundation","award":["IIS-2053498"],"award-info":[{"award-number":["IIS-2053498"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-026-57442-0","type":"journal-article","created":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T10:33:45Z","timestamp":1781778825000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Decoding concealed information using multimodal neurophysiological signals"],"prefix":"10.1038","volume":"16","author":[{"given":"Sruthi","family":"Sundharram","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Santosh","family":"Kottasamu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Krishna","family":"Ika","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramana","family":"Vinjamuri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,18]]},"reference":[{"key":"57442_CR1","volume-title":"Detecting Concealed Information and Deception: Recent Developments","year":"2018","unstructured":"Rosenfeld, J. P. (ed.) Detecting Concealed Information and Deception: Recent Developments (Elsevier \/ Academic Press, London \/ New York, 2018)."},{"key":"57442_CR2","doi-asserted-by":"publisher","unstructured":"Honts, C. R. The psychophysiological detection of deception. In The detection of deception in forensic contexts, 103\u2013123, https:\/\/doi.org\/10.1017\/CBO9780511490071.005 (Cambridge University Press) (2004).","DOI":"10.1017\/CBO9780511490071.005"},{"key":"57442_CR3","doi-asserted-by":"publisher","first-page":"782","DOI":"10.1037\/0033-2909.84.4.782","volume":"84","author":"JA Podlesny","year":"1977","unstructured":"Podlesny, J. A. & Raskin, D. C. Physiological measures and the detection of deception. Psychological bulletin 84, 782. https:\/\/doi.org\/10.1037\/0033-2909.84.4.782 (1977).","journal-title":"Psychological bulletin"},{"key":"57442_CR4","unstructured":"Ben-Shakhar, G. & Furedy, J.\u00a0J. Theories and applications in the detection of deception: A psychophysiological and international perspective (Springer Science & Business Media) (2012)."},{"key":"57442_CR5","doi-asserted-by":"publisher","unstructured":"Lykken, D.\u00a0T. The gsr in the detection of guilt. journal of Applied Psychology 43, 385, https:\/\/doi.org\/10.1037\/h0046060 (1959).","DOI":"10.1037\/h0046060"},{"key":"57442_CR6","doi-asserted-by":"publisher","first-page":"396","DOI":"10.1111\/j.1469-8986.1990.tb02333.x","volume":"27","author":"J Polich","year":"1990","unstructured":"Polich, J. & Kok, A. P300, probability, and interstimulus interval. Psychophysiology 27, 396\u2013403. https:\/\/doi.org\/10.1111\/j.1469-8986.1990.tb02333.x (1990).","journal-title":"Psychophysiology"},{"key":"57442_CR7","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1111\/j.1469-8986.2004.00158.x","volume":"41","author":"JP Rosenfeld","year":"2004","unstructured":"Rosenfeld, J. P., Soskins, M., Bosh, G. & Ryan, A. Simple, effective countermeasures to p300-based tests of detection of concealed information. Psychophysiology 41, 205\u2013219. https:\/\/doi.org\/10.1111\/j.1469-8986.2004.00158.x (2004).","journal-title":"Psychophysiology"},{"key":"57442_CR8","doi-asserted-by":"crossref","unstructured":"Verschuere, B., Ben-Shakhar, G. & Meijer, E. Memory detection: Theory and application of the Concealed Information Test (Cambridge University Press, 2011).","DOI":"10.1017\/CBO9780511975196"},{"key":"57442_CR9","doi-asserted-by":"publisher","DOI":"10.1111\/psyp.13362","volume":"57","author":"JP Rosenfeld","year":"2020","unstructured":"Rosenfeld, J. P. P300 in detecting concealed information and deception: A review. Psychophysiology 57, e13362. https:\/\/doi.org\/10.1111\/psyp.13362 (2020).","journal-title":"Psychophysiology"},{"key":"57442_CR10","doi-asserted-by":"publisher","unstructured":"Simbolon, A.\u00a0I., Turnip, A., Hutahaean, J., Siagian, Y. & Irawati, N. An experiment of lie detection based eeg-p300 classified by svm algorithm. In 2015 International Conference on Automation, Cognitive Science, Optics, Micro Electro-Mechanical System, and Information Technology (ICACOMIT), 68\u201371, https:\/\/doi.org\/10.1109\/ICACOMIT.2015.7440177 (IEEE, 2015).","DOI":"10.1109\/ICACOMIT.2015.7440177"},{"key":"57442_CR11","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.cmpb.2008.10.001","volume":"94","author":"V Abootalebi","year":"2009","unstructured":"Abootalebi, V., Moradi, M. H. & Khalilzadeh, M. A. A new approach for eeg feature extraction in p300-based lie detection. Computer methods and programs in biomedicine 94, 48\u201357. https:\/\/doi.org\/10.1016\/j.cmpb.2008.10.001 (2009).","journal-title":"Computer methods and programs in biomedicine"},{"key":"57442_CR12","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1016\/j.eswa.2016.01.024","volume":"53","author":"H Wang","year":"2016","unstructured":"Wang, H., Chang, W. & Zhang, C. Functional brain network and multichannel analysis for the p300-based brain computer interface system of lying detection. Expert Systems with Applications 53, 117\u2013128. https:\/\/doi.org\/10.1016\/j.eswa.2016.01.024 (2016).","journal-title":"Expert Systems with Applications"},{"key":"57442_CR13","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1037\/0021-9010.88.1.131","volume":"88","author":"G Ben-Shakhar","year":"2003","unstructured":"Ben-Shakhar, G. & Elaad, E. The validity of psychophysiological detection of information with the guilty knowledge test: A meta-analytic review. Journal of Applied Psychology 88, 131. https:\/\/doi.org\/10.1037\/0021-9010.88.1.131 (2003).","journal-title":"Journal of Applied Psychology"},{"key":"57442_CR14","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1111\/j.1469-8986.1977.tb02974.x","volume":"14","author":"G Ben-Shakhar","year":"1977","unstructured":"Ben-Shakhar, G. A further study of the dichotomization theory in detection of information. Psychophysiology 14, 408\u2013413. https:\/\/doi.org\/10.1111\/j.1469-8986.1977.tb02974.x (1977).","journal-title":"Psychophysiology"},{"key":"57442_CR15","doi-asserted-by":"publisher","first-page":"578","DOI":"10.1111\/j.1469-8986.1972.tb00767.x","volume":"9","author":"RJ Cutrow","year":"1972","unstructured":"Cutrow, R. J., Parks, A., Lucas, N. & Thomas, K. The objective use of multiple physiological indices in the detection of deception. Psychophysiology 9, 578\u2013588. https:\/\/doi.org\/10.1111\/j.1469-8986.1972.tb00767.x (1972).","journal-title":"Psychophysiology"},{"key":"57442_CR16","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1037\/h0044413","volume":"44","author":"DT Lykken","year":"1960","unstructured":"Lykken, D. T. The validity of the guilty knowledge technique: The effects of faking. Journal of Applied Psychology 44, 258. https:\/\/doi.org\/10.1037\/h0044413 (1960).","journal-title":"Journal of Applied Psychology"},{"key":"57442_CR17","unstructured":"Rosenfeld, J. P. Event-related potentials in the detection of deception, malingering, and false memories (Academic Press, 2002)."},{"key":"57442_CR18","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1111\/j.1469-8986.2010.01050.x","volume":"48","author":"JB Meixner","year":"2011","unstructured":"Meixner, J. B. & Rosenfeld, J. P. A mock terrorism application of the p300-based concealed information test. Psychophysiology 48, 149\u2013154. https:\/\/doi.org\/10.1111\/j.1469-8986.2010.01050.x (2011).","journal-title":"Psychophysiology"},{"key":"57442_CR19","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1016\/j.procs.2018.10.392","volume":"143","author":"A Bablani","year":"2018","unstructured":"Bablani, A., Edla, D. R. & Dodia, S. Classification of eeg data using k-nearest neighbor approach for concealed information test. Procedia computer science 143, 242\u2013249. https:\/\/doi.org\/10.1016\/j.procs.2018.10.392 (2018).","journal-title":"Procedia computer science"},{"key":"57442_CR20","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1016\/j.ijpsycho.2009.12.007","volume":"75","author":"W Ambach","year":"2010","unstructured":"Ambach, W., Bursch, S., Stark, R. & Vaitl, D. A concealed information test with multimodal measurement. International Journal of Psychophysiology 75, 258\u2013267. https:\/\/doi.org\/10.1016\/j.ijpsycho.2009.12.007 (2010).","journal-title":"International Journal of Psychophysiology"},{"key":"57442_CR21","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.imu.2017.05.004","volume":"9","author":"ED Farahani","year":"2017","unstructured":"Farahani, E. D. & Moradi, M. H. Multimodal detection of concealed information using genetic-svm classifier with strict validation structure. Informatics in Medicine Unlocked 9, 58\u201367. https:\/\/doi.org\/10.1016\/j.imu.2017.05.004 (2017).","journal-title":"Informatics in Medicine Unlocked"},{"key":"57442_CR22","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1016\/j.ijpsycho.2009.12.007","volume":"45","author":"E Farahani","year":"2013","unstructured":"Farahani, E. & Moradi, M. A concealed information test with combination of erp recording and autonomic measurements. Neurophysiology 45, 223\u2013233. https:\/\/doi.org\/10.1016\/j.ijpsycho.2009.12.007 (2013).","journal-title":"Neurophysiology"},{"key":"57442_CR23","doi-asserted-by":"publisher","unstructured":"Gamer, M. Detecting concealed information using autonomic measures. Memory detection: Theory and application of the Concealed Information Test 27\u201345, https:\/\/doi.org\/10.1017\/CBO9780511975196.003 (2011).","DOI":"10.1017\/CBO9780511975196.003"},{"key":"57442_CR24","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1111\/j.1469-8986.1981.tb03040.x","volume":"18","author":"M Bradley","year":"1981","unstructured":"Bradley, M. & Janisse, M. P. Accuracy demonstrations, threat, and the detection of deception: Cardiovascular, electrodermal, and pupillary measures. Psychophysiology 18, 307\u2013315. https:\/\/doi.org\/10.1111\/j.1469-8986.1981.tb03040.x (1981).","journal-title":"Psychophysiology"},{"key":"57442_CR25","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1037\/0021-9010.81.3.273","volume":"81","author":"G Ben-Shakhar","year":"1996","unstructured":"Ben-Shakhar, G. & Dolev, K. Psychophysiological detection through the guilty knowledge technique: Effects of mental countermeasures. Journal of applied psychology 81, 273. https:\/\/doi.org\/10.1037\/0021-9010.81.3.273 (1996).","journal-title":"Journal of applied psychology"},{"key":"57442_CR26","doi-asserted-by":"publisher","first-page":"1182","DOI":"10.1007\/s10439-006-9143-3","volume":"34","author":"DA Pollina","year":"2006","unstructured":"Pollina, D. A. et al. Facial skin surface temperature changes during a \u201cconcealed information\u2019\u2019 test. Annals of biomedical Engineering 34, 1182\u20131189. https:\/\/doi.org\/10.1007\/s10439-006-9143-3 (2006).","journal-title":"Annals of biomedical Engineering"},{"key":"57442_CR27","doi-asserted-by":"publisher","first-page":"70","DOI":"10.3389\/fnhum.2013.00070","volume":"7","author":"KK Park","year":"2013","unstructured":"Park, K. K., Suk, H. W., Hwang, H. & Lee, J.-H. A functional analysis of deception detection of a mock crime using infrared thermal imaging and the concealed information test. Frontiers in human neuroscience 7, 70. https:\/\/doi.org\/10.3389\/fnhum.2013.00070 (2013).","journal-title":"Frontiers in human neuroscience"},{"key":"57442_CR28","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1007\/s10979-010-9251-3","volume":"35","author":"L Warmelink","year":"2011","unstructured":"Warmelink, L. et al. Thermal imaging as a lie detection tool at airports. Law and human behavior 35, 40\u201348. https:\/\/doi.org\/10.1007\/s10979-010-9251-3 (2011).","journal-title":"Law and human behavior"},{"key":"57442_CR29","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.1912","volume":"10","author":"I Liu","year":"2024","unstructured":"Liu, I., Liu, F., Zhong, Q., Ma, F. & Ni, S. Your blush gives you away: Detecting hidden mental states with remote photoplethysmography and thermal imaging. PeerJ Computer Science 10, e1912. https:\/\/doi.org\/10.7717\/peerj-cs.1912 (2024).","journal-title":"PeerJ Computer Science"},{"key":"57442_CR30","doi-asserted-by":"publisher","unstructured":"Ambach, W. & Gamer, M. Physiological measures in the detection of deception and concealed information. In Detecting concealed information and deception, 3\u201333, https:\/\/doi.org\/10.1016\/B978-0-12-812729-2.00001-X (Elsevier, 2018).","DOI":"10.1016\/B978-0-12-812729-2.00001-X"},{"key":"57442_CR31","doi-asserted-by":"publisher","first-page":"879","DOI":"10.1111\/psyp.12239","volume":"51","author":"EH Meijer","year":"2014","unstructured":"Meijer, E. H., Selle, N. K., Elber, L. & Ben-Shakhar, G. Memory detection with the c oncealed i nformation t est: A meta analysis of skin conductance, respiration, heart rate, and p300 data. Psychophysiology 51, 879\u2013904. https:\/\/doi.org\/10.1111\/psyp.12239 (2014).","journal-title":"Psychophysiology"},{"key":"57442_CR32","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/T-AFFC.2011.15","volume":"3","author":"S Koelstra","year":"2011","unstructured":"Koelstra, S. et al. Deap: A database for emotion analysis; using physiological signals. IEEE transactions on affective computing 3, 18\u201331. https:\/\/doi.org\/10.1109\/T-AFFC.2011.15 (2011).","journal-title":"IEEE transactions on affective computing"},{"key":"57442_CR33","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/9\/4\/045008","volume":"9","author":"A-M Brouwer","year":"2012","unstructured":"Brouwer, A.-M. et al. Estimating workload using eeg spectral power and erps in the n-back task. Journal of neural engineering 9, 045008. https:\/\/doi.org\/10.1088\/1741-2560\/9\/4\/045008 (2012).","journal-title":"Journal of neural engineering"},{"key":"57442_CR34","doi-asserted-by":"publisher","unstructured":"D\u2019mello, S.\u00a0K. & Kory, J. A review and meta-analysis of multimodal affect detection systems. ACM computing surveys (CSUR) 47, 1\u201336, https:\/\/doi.org\/10.1145\/2682899 (2015).","DOI":"10.1145\/2682899"},{"key":"57442_CR35","doi-asserted-by":"publisher","first-page":"2425","DOI":"10.1126\/science.1063736","volume":"293","author":"JV Haxby","year":"2001","unstructured":"Haxby, J. V. et al. Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science 293, 2425\u20132430. https:\/\/doi.org\/10.1126\/science.1063736 (2001).","journal-title":"Science"},{"key":"57442_CR36","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1016\/j.neuron.2015.05.025","volume":"87","author":"J-D Haynes","year":"2015","unstructured":"Haynes, J.-D. A primer on pattern-based approaches to fmri: Principles, pitfalls, and perspectives. Neuron 87, 257\u2013270. https:\/\/doi.org\/10.1016\/j.neuron.2015.05.025 (2015).","journal-title":"Neuron"},{"key":"57442_CR37","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/s11571-012-9192-2","volume":"6","author":"LA Farwell","year":"2012","unstructured":"Farwell, L. A. Brain fingerprinting: A comprehensive tutorial review of detection of concealed information with event-related brain potentials. Cognitive neurodynamics 6, 115\u2013154. https:\/\/doi.org\/10.1007\/s11571-012-9192-2 (2012).","journal-title":"Cognitive neurodynamics"},{"key":"57442_CR38","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1016\/j.physbeh.2018.01.002","volume":"186","author":"G Duran","year":"2018","unstructured":"Duran, G., Tapiero, I. & Michael, G. A. Resting heart rate: A physiological predicator of lie detection ability. Physiology & behavior 186, 10\u201315. https:\/\/doi.org\/10.1016\/j.physbeh.2018.01.002 (2018).","journal-title":"Physiology & behavior"},{"key":"57442_CR39","first-page":"316","volume":"36","author":"LG Cook","year":"2019","unstructured":"Cook, L. G. & Mitschow, L. C. Beyond the polygraph: Deception detection and the autonomic nervous system. Federal Practitioner 36, 316 (2019).","journal-title":"Federal Practitioner"},{"key":"57442_CR40","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1037\/h0046624","volume":"55","author":"J Block","year":"1957","unstructured":"Block, J. A study of affective responsiveness in a lie-detection situation. The Journal of Abnormal and Social Psychology 55, 11. https:\/\/doi.org\/10.1037\/h0046624 (1957).","journal-title":"The Journal of Abnormal and Social Psychology"},{"key":"57442_CR41","unstructured":"Vrij, A. Detecting lies and deceit: Pitfalls and opportunities (Wiley, 2008)."},{"key":"57442_CR42","doi-asserted-by":"publisher","first-page":"8943","DOI":"10.1038\/s41598-025-92399-6","volume":"15","author":"G Joshi","year":"2025","unstructured":"Joshi, G. et al. Multimodal machine learning for deception detection using behavioral and physiological data. Scientific Reports 15, 8943. https:\/\/doi.org\/10.1038\/s41598-025-92399-6 (2025).","journal-title":"Scientific Reports"},{"key":"57442_CR43","doi-asserted-by":"publisher","first-page":"519","DOI":"10.3390\/brainsci15050519","volume":"15","author":"BN Taha","year":"2025","unstructured":"Taha, B. N., Baykara, M. & Alaku\u015f, T. B. Neurophysiological approaches to lie detection: A systematic review. Brain Sciences 15, 519. https:\/\/doi.org\/10.3390\/brainsci15050519 (2025).","journal-title":"Brain Sciences"},{"key":"57442_CR44","doi-asserted-by":"publisher","unstructured":"Javaid, H., Dilawari, A., Khan, U.\u00a0G. & Wajid, B. Eeg guided multimodal lie detection with audio-visual cues. In 2022 2nd International conference on artificial intelligence (ICAI), 71\u201378, https:\/\/doi.org\/10.1109\/ICAI55435.2022.9773469 (IEEE, 2022).","DOI":"10.1109\/ICAI55435.2022.9773469"},{"key":"57442_CR45","doi-asserted-by":"publisher","first-page":"3777","DOI":"10.1007\/s00521-019-04078-z","volume":"32","author":"N Saini","year":"2020","unstructured":"Saini, N., Bhardwaj, S. & Agarwal, R. Classification of eeg signals using hybrid combination of features for lie detection. Neural Computing and Applications 32, 3777\u20133787. https:\/\/doi.org\/10.1007\/s00521-019-04078-z (2020).","journal-title":"Neural Computing and Applications"},{"key":"57442_CR46","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4614-1126-0","author":"W Boucsein","year":"2012","unstructured":"Boucsein, W. et al. Electrodermal activity. Springer https:\/\/doi.org\/10.1007\/978-1-4614-1126-0 (2012).","journal-title":"Electrodermal activity. Springer"},{"key":"57442_CR47","doi-asserted-by":"publisher","first-page":"308","DOI":"10.1177\/107385840200800209","volume":"8","author":"HD Critchley","year":"2002","unstructured":"Critchley, H. D. Electrodermal responses: What happens in the brain. The Neuroscientist 8, 308\u2013313. https:\/\/doi.org\/10.1177\/107385840200800209 (2002).","journal-title":"The Neuroscientist"},{"key":"57442_CR48","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6579\/ac826d","volume":"43","author":"PH Charlton","year":"2022","unstructured":"Charlton, P. H. et al. Detecting beats in the photoplethysmogram: Benchmarking open-source algorithms. Physiological Measurement 43, 085007. https:\/\/doi.org\/10.1088\/1361-6579\/ac826d (2022).","journal-title":"Physiological Measurement"},{"key":"57442_CR49","doi-asserted-by":"publisher","first-page":"785","DOI":"10.1080\/09658211.2020.1849307","volume":"30","author":"LE Paige","year":"2022","unstructured":"Paige, L. E., Wolf, J. M. & Gutchess, A. Evaluating heart rate variability as a predictor of the influence of lying on memory. Memory 30, 785\u2013795. https:\/\/doi.org\/10.1080\/09658211.2020.1849307 (2022).","journal-title":"Memory"},{"key":"57442_CR50","doi-asserted-by":"crossref","unstructured":"Pinheiro, N. Can ppg be used for hrv analysis? In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2945\u20132949 (IEEE, 2016).","DOI":"10.1109\/EMBC.2016.7591347"},{"key":"57442_CR51","first-page":"123","volume":"5","author":"\u015e Mirescu","year":"2012","unstructured":"Mirescu, \u015e & Harden, S. Photoplethysmography as a potential alternative to electrocardiography for recording heart rate intervals used in variability analysis. Journal of Medicine and Life 5, 123 (2012).","journal-title":"Journal of Medicine and Life"},{"key":"57442_CR52","doi-asserted-by":"publisher","first-page":"1015","DOI":"10.1109\/TIFS.2014.2317309","volume":"9","author":"BA Rajoub","year":"2014","unstructured":"Rajoub, B. A. & Zwiggelaar, R. Thermal facial analysis for deception detection. IEEE transactions on information forensics and security 9, 1015\u20131023. https:\/\/doi.org\/10.1109\/TIFS.2014.2317309 (2014).","journal-title":"IEEE transactions on information forensics and security"},{"key":"57442_CR53","doi-asserted-by":"publisher","unstructured":"van\u2019t Veer, A.\u00a0E., Gallucci, M., Stel, M. & Beest, I.\u00a0v. Unconscious deception detection measured by finger skin temperature and indirect veracity judgments\u2014results of a registered report. Frontiers in psychology 6, 672, https:\/\/doi.org\/10.3389\/fpsyg.2015.00672 (2015).","DOI":"10.3389\/fpsyg.2015.00672"},{"key":"57442_CR54","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1037\/h0023324","volume":"50","author":"S Kugelmass","year":"1966","unstructured":"Kugelmass, S. & Lieblich, I. Effects of realistic stress and procedural interference in experimental lie detection. Journal of Applied Psychology 50, 211. https:\/\/doi.org\/10.1037\/h0023324 (1966).","journal-title":"Journal of Applied Psychology"},{"key":"57442_CR55","doi-asserted-by":"crossref","unstructured":"Hosmer Jr, D.\u00a0W., Lemeshow, S. & Sturdivant, R.\u00a0X. Applied logistic regression (John Wiley & Sons, 2013).","DOI":"10.1002\/9781118548387"},{"key":"57442_CR56","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1007\/BF00994018","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes, C. & Vapnik, V. Support-vector networks. Machine learning 20, 273\u2013297. https:\/\/doi.org\/10.1007\/BF00994018 (1995).","journal-title":"Support-vector networks. Machine learning"},{"key":"57442_CR57","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L. Random forests. Machine learning 45, 5\u201332. https:\/\/doi.org\/10.1023\/A:1010933404324 (2001).","journal-title":"Random forests. Machine learning"},{"key":"57442_CR58","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1214\/aos\/1013203451","volume":"29","author":"JH Friedman","year":"2001","unstructured":"Friedman, J. H. Greedy function approximation: A gradient boosting machine. Annals of Statistics 29, 1189\u20131232. https:\/\/doi.org\/10.1214\/aos\/1013203451 (2001).","journal-title":"Annals of Statistics"},{"key":"57442_CR59","doi-asserted-by":"publisher","unstructured":"Chen, T. & Guestrin, C. Xgboost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 785\u2013794, https:\/\/doi.org\/10.1145\/2939672.2939785 (San Francisco, CA, USA, 2016).","DOI":"10.1145\/2939672.2939785"},{"key":"57442_CR60","doi-asserted-by":"publisher","unstructured":"Ke, G. et al. Lightgbm: A highly efficient gradient boosting decision tree. Advances in neural information processing systems 30, https:\/\/doi.org\/10.5555\/3294996.3295074 (2017).","DOI":"10.5555\/3294996.3295074"},{"key":"57442_CR61","unstructured":"Prokhorenkova, L., Gusev, G., Vorobev, A., Dorogush, A.\u00a0V. & Gulin, A. Catboost: unbiased boosting with categorical features. In Advances in Neural Information Processing Systems (NeurIPS), 6638\u20136648 (2018)."},{"key":"57442_CR62","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/aab2f2","volume":"15","author":"F Lotte","year":"2018","unstructured":"Lotte, F., Congedo, M., L\u00e9cuyer, A., Lamarche, F. & Arnaldi, B. A review of classification algorithms for eeg-based brain\u2013computer interfaces: A 10 year update. Journal of Neural Engineering 15, 031005. https:\/\/doi.org\/10.1088\/1741-2552\/aab2f2 (2018).","journal-title":"Journal of Neural Engineering"},{"key":"57442_CR63","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1186\/s13634-015-0251-9","volume":"2015","author":"T Alotaiby","year":"2015","unstructured":"Alotaiby, T., El-Samie, F. E. A., Alshebeili, S. A. & Ahmad, I. A review of channel selection algorithms for eeg signal processing. EURASIP Journal on Advances in Signal Processing 2015, 66. https:\/\/doi.org\/10.1186\/s13634-015-0251-9 (2015).","journal-title":"EURASIP Journal on Advances in Signal Processing"},{"key":"57442_CR64","doi-asserted-by":"publisher","unstructured":"Blankertz, B., Lemm, S., Treder, M., Haufe, S. & M\u00fcller, K.-R. Single-trial analysis and classification of erp components\u2014a tutorial. In NeuroImage, 814\u2013825, https:\/\/doi.org\/10.1016\/j.neuroimage.2010.06.048 (Elsevier, 2011).","DOI":"10.1016\/j.neuroimage.2010.06.048"},{"key":"57442_CR65","doi-asserted-by":"publisher","unstructured":"Bashivan, P., Rish, I., Yeasin, M. & Codella, N. Learning representations from eeg with deep recurrent-convolutional neural networks. arXiv preprint arXiv:1511.06448https:\/\/doi.org\/10.48550\/arXiv.1511.06448 (2015).","DOI":"10.48550\/arXiv.1511.06448"},{"key":"57442_CR66","doi-asserted-by":"publisher","first-page":"1434753","DOI":"10.3389\/fmede.2024.1434753","volume":"2","author":"D Pei","year":"2024","unstructured":"Pei, D., Tirumala, S., Tun, K. T., Ajendla, A. & Vinjamuri, R. Identifying neurophysiological correlates of stress. Frontiers in Medical Engineering 2, 1434753. https:\/\/doi.org\/10.3389\/fmede.2024.1434753 (2024).","journal-title":"Frontiers in Medical Engineering"},{"key":"57442_CR67","doi-asserted-by":"publisher","first-page":"1002","DOI":"10.1111\/j.1469-8986.2010.01024.x","volume":"47","author":"JP Rosenfeld","year":"2010","unstructured":"Rosenfeld, J. P. & Labkovsky, E. New p300-based protocol to detect concealed information: Resistance to mental countermeasures against only half the irrelevant stimuli and a possible erp indicator of countermeasures. Psychophysiology 47, 1002\u20131010. https:\/\/doi.org\/10.1111\/j.1469-8986.2010.01024.x (2010).","journal-title":"Psychophysiology"},{"key":"57442_CR68","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.ijpsycho.2020.08.003","volume":"157","author":"L Sai","year":"2020","unstructured":"Sai, L. et al. Feedback does not influence the recognition-related p300 in a novel concealed information test while feedback-evoked p300 shows promising diagnostic accuracy. International Journal of Psychophysiology 157, 32\u201341. https:\/\/doi.org\/10.1016\/j.ijpsycho.2020.08.003 (2020).","journal-title":"International Journal of Psychophysiology"},{"key":"57442_CR69","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1016\/S0896-6273(00)80526-7","volume":"21","author":"K Grill-Spector","year":"1998","unstructured":"Grill-Spector, K., Kushnir, T., Edelman, S., Itzchak, Y. & Malach, R. Cue-invariant activation in object-related areas of the human occipital lobe. Neuron 21, 191\u2013202. https:\/\/doi.org\/10.1016\/S0896-6273(00)80526-7 (1998).","journal-title":"Neuron"},{"key":"57442_CR70","doi-asserted-by":"publisher","first-page":"4302","DOI":"10.1523\/JNEUROSCI.17-11-04302.1997","volume":"17","author":"N Kanwisher","year":"1997","unstructured":"Kanwisher, N., McDermott, J. & Chun, M. M. The fusiform face area: A module in human extrastriate cortex specialized for face perception. Journal of Neuroscience 17, 4302\u20134311. https:\/\/doi.org\/10.1523\/JNEUROSCI.17-11-04302.1997 (1997).","journal-title":"Journal of Neuroscience"},{"key":"57442_CR71","doi-asserted-by":"publisher","first-page":"1680","DOI":"10.1093\/cercor\/bhl079","volume":"17","author":"R Epstein","year":"2007","unstructured":"Epstein, R. & Higgins, J. S. Differential parahippocampal and retrosplenial involvement in three types of visual scene recognition. Cerebral Cortex 17, 1680\u20131693. https:\/\/doi.org\/10.1093\/cercor\/bhl079 (2007).","journal-title":"Cerebral Cortex"},{"key":"57442_CR72","doi-asserted-by":"publisher","first-page":"2128","DOI":"10.1016\/j.clinph.2007.04.019","volume":"118","author":"J Polich","year":"2007","unstructured":"Polich, J. Updating p300: An integrative theory of p3a and p3b. Clinical Neurophysiology 118, 2128\u20132148. https:\/\/doi.org\/10.1016\/j.clinph.2007.04.019 (2007).","journal-title":"Clinical Neurophysiology"},{"key":"57442_CR73","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1016\/j.neubiorev.2011.11.009","volume":"36","author":"JF Thayer","year":"2012","unstructured":"Thayer, J. F., Ahs, F., Fredrikson, M., Sollers, J. J. I. & Wager, T. D. A meta-analysis of heart rate variability and neuroimaging studies: Implications for heart rate variability as a marker of stress and health. Neuroscience & Biobehavioral Reviews 36, 747\u2013756. https:\/\/doi.org\/10.1016\/j.neubiorev.2011.11.009 (2012).","journal-title":"Neuroscience & Biobehavioral Reviews"},{"key":"57442_CR74","doi-asserted-by":"publisher","first-page":"320","DOI":"10.1017\/S1355617700633054","volume":"6","author":"A Martin","year":"2000","unstructured":"Martin, A. Neural substrates of object identification: Functional magnetic resonance imaging evidence that category and visual attribute contribute to semantic knowledge. Journal of the International Neuropsychological Society 6, 320\u2013335. https:\/\/doi.org\/10.1017\/S1355617700633054 (2000).","journal-title":"Journal of the International Neuropsychological Society"},{"key":"57442_CR75","doi-asserted-by":"publisher","first-page":"627","DOI":"10.3390\/bs14080627","volume":"14","author":"JP Rosenfeld","year":"2024","unstructured":"Rosenfeld, J. P., Ben-Shakhar, G. & Meijer, E. Advances in concealed information testing: Eeg and psychophysiological markers of recognition. Behavioral Sciences 14, 627. https:\/\/doi.org\/10.3390\/bs14080627 (2024).","journal-title":"Behavioral Sciences"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-57442-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-57442-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-57442-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T12:05:14Z","timestamp":1788782714000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-57442-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,18]]},"references-count":75,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["57442"],"URL":"https:\/\/doi.org\/10.1038\/s41598-026-57442-0","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,18]]},"assertion":[{"value":"27 December 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 June 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 June 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.","order":1,"name":"Ethics","label":"Competing interest","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The studies involving humans were approved by the present study was conducted under IRB Approved Protocol at the University of Maryland Baltimore County (Protocol #408 \u2013 Selection of Optimal Control Signals for Human Machine Interfaces). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.","order":2,"name":"Ethics","label":"Ethical approval","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"27884"}}