「欺瞞」這個社會現象無處不在，但使用功能性磁振造影(fMRI)技術探討各類型欺騙的研究，目前仍屬有限。部分的原因在於難以在fMRI中自然的誘發欺瞞，這個具有巨大個體差異，的行為。並且文獻中也看到不同的實驗情境，誘發欺瞞的程度也各不相同。在這個雙機同步功能性磁振造影研究中，招募了33對來自兩個地點(台南與台北)的受試者，兩人一同進行開寶箱的策略互動遊戲。互動遊戲中雙方會輪流擔任先手(建議)和後手(決定)猜測正確的寶箱。合作情境下，若後手成功猜中正確的寶箱，則兩人平分200元，從而促進彼此間的信任；相反的，在競爭情境若是後手成功猜中正確的寶箱，將獨得150元，從而促進了爾虞我詐。行為結果也反映了此種互動模式：在合作平分的情境下，先手幾乎總是誠實建議機率大的寶箱，而後手亦總是跟隨先手的建議; 而在贏者獨拿的競爭情境下，先手的說實話/說謊話，與後手的跟隨/不跟隨比率，皆各佔約50%。在fMRI結果中，本研究除了重現先前文獻整理出的三個相關神經網路(心智理論、執行控制與酬賞)外，另一個重要的發現是右側顳頂葉交界處(rTPJ，負責心智理論)與情緒經驗相關腦區(包含杏仁核、海馬旁回，與前扣帶迴)的功能性連結差異，與受試者在競爭情境中說謊的比率，呈現顯著的負相關。再者，透過加總數個在多元像素型態分析結果中，能團體顯著分類競爭情境下策略選擇的腦區，可將分類正確率提升至61%；而類似的情形在分類競爭與合作情境下說實話的策略腦區，分類正確率可提升至84.5%。最後，利用主成分分析將高維度的fMRI資料降維，在分類競爭情境下策略的使用只需要200個主成分，就能夠達到同樣的分類表現；而在競爭與合作情境下的說實話策略只需要10個主成分，表明前者團體結果分類表現較大的受到了個體差異的影響。總而言之，這些結果揭示了雙人社會互動下策略欺騙的大腦神經基礎。

Despite its ubiquity, deceiving as a social phenomenon is scarcely addressed with fMRI, partly due to the spontaneity and individual differences in cheating, and the contextual variability that fosters lying. In this hyperscanning fMRI study, the participant pairs (n=33) from two sites (two ends of Taiwan) joined an opening-treasure-chest (OTC) game, where the dyads took alternative turns as senders (to inform) and receivers (to decide) for guessing the right treasure chest. The cooperation condition was achieved by, upon successful guessing, splitting the $200 trial reward, thereby promoting mutual trust. The competition condition, in contrast, was done by, also upon winning, the latter receivers taking all the $150 reward, thereby encouraging strategic interactions. Behavioral results also mirrored this pattern: while senders guided and receivers followed both faithfully (near 100%) in the $200 condition, senders’ truth-telling/lying and receivers’ follow/unfollow rates both dropped to near chance in the $150 counterpart. For fMRI, the GLM contrasts reaffirmed the three documented sub-networks related to social deception: theory-of-mind (ToM), executive control, and reward processing. Another key finding was the negative correlations between the connectivity of right temporo-parietal junction (rTPJ, known as the ToM region) and emotion-related regions, including amygdala, parahippocampal gyrus, and rostral anterior cingulate (rACC), and senders’ lying rates. Furthermore, the Multi-Voxel Pattern Analysis (MVPA) over multiple searchlight-unearthed Region-Of-Interests (ROIs) in classifying either the “truth-telling vs. lying in $150” or the “truthful in $200 vs. truthful in $150” conditions achieved 61% and 84.5%, respectively. Lastly, principal component analysis (PCA) could reduce these high dimensional fMRI data in above-mentioned comparisons to the same level of accuracy with less than 200 or less than 10 components, respectively, suggesting that it may be due more to the individual difference in explaining the suboptimal results. To sum up, these results reveal the neural substrates underpinning the idiosyncratic social deceptions in dyadic interactions.

Abe, N. (2011). How the brain shapes deception: an integrated review of the literature. Neuroscientist, 17(5), 560-574. doi:10.1177/1073858410393359

Abe, N., & Greene, J. D. (2014). Response to anticipated reward in the nucleus accumbens predicts behavior in an independent test of honesty. J Neurosci, 34(32), 10564-10572. doi:10.1523/JNEUROSCI.0217-14.2014

Abe, N., Okuda, J., Suzuki, M., Sasaki, H., Matsuda, T., Mori, E., . . . Fujii, T. (2008). Neural correlates of true memory, false memory, and deception. Cereb Cortex, 18(12), 2811-2819. doi:10.1093/cercor/bhn037

Bitsch, F., Berger, P., Nagels, A., Falkenberg, I., & Straube, B. (2018). The role of the right temporo-parietal junction in social decision-making. Hum Brain Mapp, 39(7), 3072-3085. doi:10.1002/hbm.24061

Chen, M., Zhang, T., Zhang, R., Wang, N., Yin, Q., Li, Y., . . . Li, X. (2020). Neural alignment during face-to-face spontaneous deception: Does gender make a difference? Hum Brain Mapp, 41(17), 4964-4981. doi:10.1002/hbm.25173

Chou, C. A., Kampa, K., Mehta, S. H., Tungaraza, R. F., Chaovalitwongse, W. A., & Grabowski, T. J. (2014). Voxel selection framework in multi-voxel pattern analysis of FMRI data for prediction of neural response to visual stimuli. IEEE Trans Med Imaging, 33(4), 925-934. doi:10.1109/TMI.2014.2298856

Cui, Q., Vanman, E. J., Wei, D., Yang, W., Jia, L., & Zhang, Q. (2014). Detection of deception based on fMRI activation patterns underlying the production of a deceptive response and receiving feedback about the success of the deception after a mock murder crime. Soc Cogn Affect Neurosci, 9(10), 1472-1480. doi:10.1093/scan/nst134

Cunningham, S. I., Tomasi, D., & Volkow, N. D. (2017). Structural and functional connectivity of the precuneus and thalamus to the default mode network. Hum Brain Mapp, 38(2), 938-956. doi:10.1002/hbm.23429

Czeszumski, A., Eustergerling, S., Lang, A., Menrath, D., Gerstenberger, M., Schuberth, S., . . . Konig, P. (2020). Hyperscanning: A Valid Method to Study Neural Inter-brain Underpinnings of Social Interaction. Front Hum Neurosci, 14, 39. doi:10.3389/fnhum.2020.00039

Davis, T., LaRocque, K. F., Mumford, J. A., Norman, K. A., Wagner, A. D., & Poldrack, R. A. (2014). What do differences between multi-voxel and univariate analysis mean? How subject-, voxel-, and trial-level variance impact fMRI analysis. Neuroimage, 97, 271-283. doi:10.1016/j.neuroimage.2014.04.037

Ding, X. P., Sai, L., Fu, G., Liu, J., & Lee, K. (2014). Neural correlates of second-order verbal deception: a functional near-infrared spectroscopy (fNIRS) study. Neuroimage, 87, 505-514. doi:10.1016/j.neuroimage.2013.10.023

Elliott, M. L., Knodt, A. R., Ireland, D., Morris, M. L., Poulton, R., Ramrakha, S., . . . Hariri, A. R. (2020). What Is the Test-Retest Reliability of Common Task-Functional MRI Measures? New Empirical Evidence and a Meta-Analysis. Psychol Sci, 31(7), 792-806. doi:10.1177/0956797620916786

Farah, M. J., Hutchinson, J. B., Phelps, E. A., & Wagner, A. D. (2014). Functional MRI-based lie detection: scientific and societal challenges. Nat Rev Neurosci, 15(2), 123-131. doi:10.1038/nrn3665

Ferrari, M., & Quaresima, V. (2012). A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application. Neuroimage, 63(2), 921-935. doi:10.1016/j.neuroimage.2012.03.049

Gamer, M., Bauermann, T., Stoeter, P., & Vossel, G. (2007). Covariations among fMRI, skin conductance, and behavioral data during processing of concealed information. Hum Brain Mapp, 28(12), 1287-1301. doi:10.1002/hbm.20343

Greene, J. D., & Paxton, J. M. (2010). Patterns of neural activity associated with honest and dishonest moral decisions. Proceedings of the National Academy of Sciences, 107(9), 4486-4486. doi:10.1073/pnas.1000505107

Hackel, L. M., Wills, J. A., & Van Bavel, J. J. (2020). Shifting prosocial intuitions: neurocognitive evidence for a value-based account of group-based cooperation. Soc Cogn Affect Neurosci, 15(4), 371-381. doi:10.1093/scan/nsaa055

Ito, A., Abe, N., Fujii, T., Hayashi, A., Ueno, A., Mugikura, S., . . . Mori, E. (2012). The contribution of the dorsolateral prefrontal cortex to the preparation for deception and truth-telling. Brain Res, 1464, 43-52. doi:10.1016/j.brainres.2012.05.004

Jiang, W., Liu, H., Zeng, L., Liao, J., Shen, H., Luo, A., . . . Wang, W. (2015). Decoding the processing of lying using functional connectivity MRI. Behav Brain Funct, 11, 1. doi:10.1186/s12993-014-0046-4

Jin, B., Strasburger, A., Laken, S. J., Kozel, F. A., Johnson, K. A., George, M. S., & Lu, X. (2009). Feature selection for fMRI-based deception detection. BMC Bioinformatics, 10 Suppl 9, S15. doi:10.1186/1471-2105-10-S9-S15

Kim, J., Yeon, J., Ryu, J., Park, J. Y., Chung, S. C., & Kim, S. P. (2017). Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception. Front Hum Neurosci, 11, 445. doi:10.3389/fnhum.2017.00445

Kriegeskorte, N., Goebel, R., & Bandettini, P. (2006). Information-based functional brain mapping. Proceedings of the National Academy of Sciences of the United States of America, 103, 3863-3868.

Lisofsky, N., Kazzer, P., Heekeren, H. R., & Prehn, K. (2014). Investigating socio-cognitive processes in deception: a quantitative meta-analysis of neuroimaging studies. Neuropsychologia, 61, 113-122. doi:10.1016/j.neuropsychologia.2014.06.001

Marek, S., Tervo-Clemmens, B., Calabro, F. J., Montez, D. F., Kay, B. P., Hatoum, A. S., . . . Dosenbach, N. U. F. (2020). doi:10.1101/2020.08.21.257758

Montague, P. R., Berns, G. S., Cohen, J. D., McClure, S. M., Pagnoni, G., Dhamala, M., . . . Fisher, R. E. (2002). Hyperscanning: simultaneous fMRI during linked social interactions. Neuroimage, 16(4), 1159-1164. doi:10.1006/nimg.2002.1150

O'Reilly, J. X., Woolrich, M. W., Behrens, T. E., Smith, S. M., & Johansen-Berg, H. (2012). Tools of the trade: psychophysiological interactions and functional connectivity. Soc Cogn Affect Neurosci, 7(5), 604-609. doi:10.1093/scan/nss055

Olsson, A., Knapska, E., & Lindstrom, B. (2020). The neural and computational systems of social learning. Nat Rev Neurosci, 21(4), 197-212. doi:10.1038/s41583-020-0276-4

Pereira, F., & Botvinick, M. (2011). Information mapping with pattern classifiers: a comparative study. Neuroimage, 56(2), 476-496. doi:10.1016/j.neuroimage.2010.05.026

Pinti, P., Tachtsidis, I., Hamilton, A., Hirsch, J., Aichelburg, C., Gilbert, S., & Burgess, P. W. (2020). The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience. Ann N Y Acad Sci, 1464(1), 5-29. doi:10.1111/nyas.13948

Pornpattananangkul, N., Zhen, S., & Yu, R. (2018). Common and distinct neural correlates of self-serving and prosocial dishonesty. Hum Brain Mapp, 39(7), 3086-3103. doi:10.1002/hbm.24062

Premack, D., & Woodruff, G. (2010). Does the chimpanzee have a theory of mind? Behavioral and Brain Sciences, 1(4), 515-526. doi:10.1017/s0140525x00076512

Quaresima, V., & Ferrari, M. (2016). Functional Near-Infrared Spectroscopy (fNIRS) for Assessing Cerebral Cortex Function During Human Behavior in Natural/Social Situations: A Concise Review. Organizational Research Methods, 22(1), 46-68. doi:10.1177/1094428116658959

Redcay, E., & Schilbach, L. (2019). Using second-person neuroscience to elucidate the mechanisms of social interaction. Nat Rev Neurosci, 20(8), 495-505. doi:10.1038/s41583-019-0179-4

Saxe, R., & Kanwisher, N. (2003). People thinking about thinking peopleThe role of the temporo-parietal junction in “theory of mind”. Neuroimage, 19(4), 1835-1842. doi:10.1016/s1053-8119(03)00230-1

Saxe, R., & Wexler, A. (2005). Making sense of another mind: the role of the right temporo-parietal junction. Neuropsychologia, 43(10), 1391-1399. doi:10.1016/j.neuropsychologia.2005.02.013

Schurz, M., Radua, J., Aichhorn, M., Richlan, F., & Perner, J. (2014). Fractionating theory of mind: a meta-analysis of functional brain imaging studies. Neurosci Biobehav Rev, 42, 9-34. doi:10.1016/j.neubiorev.2014.01.009

Shaw, D. J., Czekoova, K., Stanek, R., Marecek, R., Urbanek, T., Spalek, J., . . . Brazdil, M. (2018). A dual-fMRI investigation of the iterated Ultimatum Game reveals that reciprocal behaviour is associated with neural alignment. Sci Rep, 8(1), 10896. doi:10.1038/s41598-018-29233-9

Sip, K. E., Roepstorff, A., McGregor, W., & Frith, C. D. (2008). Detecting deception: the scope and limits. Trends Cogn Sci, 12(2), 48-53. doi:10.1016/j.tics.2007.11.008

Speer, S. P. H., Smidts, A., & Boksem, M. A. S. (2020). Cognitive control increases honesty in cheaters but cheating in those who are honest. Proc Natl Acad Sci U S A, 117(32), 19080-19091. doi:10.1073/pnas.2003480117

Spilakova, B., Shaw, D. J., Czekoova, K., & Brazdil, M. (2019). Dissecting social interaction: dual-fMRI reveals patterns of interpersonal brain-behavior relationships that dissociate among dimensions of social exchange. Soc Cogn Affect Neurosci, 14(2), 225-235. doi:10.1093/scan/nsz004

Sun, P., Ling, X., Zheng, L., Chen, J., Li, L., Liu, Z., . . . Guo, X. (2017). Modulation of financial deprivation on deception and its neural correlates. Exp Brain Res, 235(11), 3271-3277. doi:10.1007/s00221-017-5052-y

Suzuki, H., Misaki, M., Krueger, F., & Bodurka, J. (2015). Neural Responses to Truth Telling and Risk Propensity under Asymmetric Information. PLoS One, 10(9), e0137014. doi:10.1371/journal.pone.0137014

Tsoi, L., Dungan, J., Waytz, A., & Young, L. (2016). Distinct neural patterns of social cognition for cooperation versus competition. Neuroimage, 137, 86-96. doi:10.1016/j.neuroimage.2016.04.069

Utevsky, A. V., Smith, D. V., & Huettel, S. A. (2014). Precuneus is a functional core of the default-mode network. J Neurosci, 34(3), 932-940. doi:10.1523/JNEUROSCI.4227-13.2014

van den Heuvel, M. P., & Sporns, O. (2013). Network hubs in the human brain. Trends Cogn Sci, 17(12), 683-696. doi:10.1016/j.tics.2013.09.012

Vartanian, O., Kwantes, P. J., Mandel, D. R., Bouak, F., Nakashima, A., Smith, I., & Lam, Q. (2013). Right inferior frontal gyrus activation as a neural marker of successful lying. Front Hum Neurosci, 7, 616. doi:10.3389/fnhum.2013.00616

Volz, K. G., Vogeley, K., Tittgemeyer, M., von Cramon, D. Y., & Sutter, M. (2015). The neural basis of deception in strategic interactions. Front Behav Neurosci, 9, 27. doi:10.3389/fnbeh.2015.00027

Wang, Z., Wang, Y., Zhou, X., & Yu, R. (2020). Interpersonal brain synchronization under bluffing in strategic games. Soc Cogn Affect Neurosci, 15(12), 1326-1335. doi:10.1093/scan/nsaa154

Wu, D., Loke, I. C., Xu, F., & Lee, K. (2011). Neural correlates of evaluations of lying and truth-telling in different social contexts. Brain Res, 1389, 115-124. doi:10.1016/j.brainres.2011.02.084

Xie, H., Karipidis, II, Howell, A., Schreier, M., Sheau, K. E., Manchanda, M. K., . . . Saggar, M. (2020). Finding the neural correlates of collaboration using a three-person fMRI hyperscanning paradigm. Proc Natl Acad Sci U S A, 117(37), 23066-23072. doi:10.1073/pnas.1917407117

Yin, L., Hu, Y., Dynowski, D., Li, J., & Weber, B. (2017). The good lies: Altruistic goals modulate processing of deception in the anterior insula. Hum Brain Mapp, 38(7), 3675-3690. doi:10.1002/hbm.23623

Yin, L., Reuter, M., & Weber, B. (2016). Let the man choose what to do: Neural correlates of spontaneous lying and truth-telling. Brain Cogn, 102, 13-25. doi:10.1016/j.bandc.2015.11.007

Yin, L., & Weber, B. (2019). I lie, why don't you: Neural mechanisms of individual differences in self-serving lying. Hum Brain Mapp, 40(4), 1101-1113. doi:10.1002/hbm.24432

Zhang, M., Liu, T., Pelowski, M., & Yu, D. (2017). Gender difference in spontaneous deception: A hyperscanning study using functional near-infrared spectroscopy. Sci Rep, 7(1), 7508. doi:10.1038/s41598-017-06764-1

Zheltyakova, M., Kireev, M., Korotkov, A., & Medvedev, S. (2020). Neural mechanisms of deception in a social context: an fMRI replication study. Sci Rep, 10(1), 10713. doi:10.1038/s41598-020-67721-z

Zhu, L., Jenkins, A. C., Set, E., Scabini, D., Knight, R. T., Chiu, P. H., . . . Hsu, M. (2014). Damage to dorsolateral prefrontal cortex affects tradeoffs between honesty and self-interest. Nat Neurosci, 17(10), 1319-1321. doi:10.1038/nn.3798