Abstract
In the current study, we used topological data analysis of fMRI data for exploring neurophysiological mechanisms underlying the execution of deceptive actions. We used the results of the analysis of psychophysiological interactions (PPI) of fMRI data, obtained during an earlier experiment where subjects were required to mislead an opponent through sequential execution of deceptive and honest claims. A connectivity matrix based on PPI analysis was processed with the methods of algebraic topology. With this approach, we confirmed our previous findings that the increase in local activity and psychophysiological interactions of the left caudate nucleus is associated with the execution of deceptive actions. It is also in line with our hypothesis that involvement of the left caudate nucleus in brain processing of deception reflects the process of activation of error detection mechanism. In contrast to this finding, the right caudate nucleus was most frequently observed in the selected cliques associated with honest actions in comparison with deceptive ones. This observation points to possible differential role of left and right caudate nuclei in processing deceptive and honest actions, so it can be further investigated in future research. Topological analysis of higher-order organization of functional interactions revealed three cycles encompassing different sets of brain regions. Those regions are associated with executive control, error detection and sociocognitive processes, involvement of which in deception execution was hypothesized in previous studies. The fact of observation of such loops of functionally integrated brain regions demonstrates the possibility of parallel functioning of above-mentioned mechanisms and substantially extends the current view on neurobiological basics of deceptive behavior.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Abe, N., Greene, J.D., Kiehl, K.A.: Reduced engagement of the anterior cingulate cortex in the dishonest decision-making of incarcerated psychopaths. Soc. Cogn. Affect. Neurosci. 13(8), 797–807 (2018)
Abu-Akel, A., Shamay-Tsoory, S.: Neuroanatomical and neurochemical bases of theory of mind. Neuropsychologia 49(11), 2971–2984 (2011)
Bassett, D.S., Zurn, P., Gold, J.I.: On the nature and use of models in network neuroscience. Nat. Rev. Neurosci. 19(9), 566–578 (2018). https://www.nature.com/articles/s41583-018-0038-8
Bechtereva, N., Gretchin, V.: Physiological foundations of mental activity. In: International review of neurobiology, vol. 11, pp. 329–352. Elsevier (1969)
Bubenik, P.: Statistical topological data analysis using persistence landscapes. J. Mach. Learn. Res. 16(1), 77–102 (2015)
Cisler, J.M., Bush, K., Steele, J.S.: A comparison of statistical methods for detecting context-modulated functional connectivity in fMRI. Neuroimage 84, 1042–1052 (2014)
Debey, E., Ridderinkhof, R.K., De Houwer, J., De Schryver, M., Verschuere, B.: Suppressing the truth as a mechanism of deception: delta plots reveal the role of response inhibition in lying. Conscious. Cogn. 37, 148–159 (2015)
Di, X., Reynolds, R.C., Biswal, B.B.: Imperfect (de)convolution may introduce spurious psychophysiological interactions and how to avoid it. Hum. Brain Mapp. 38(4), 1723–1740 (2017)
Ding, X.P., Wu, S.J., Liu, J., Fu, G., Lee, K.: Functional neural networks of honesty and dishonesty in children: evidence from graph theory analysis. Sci. Rep. 7(1), 12085 (2017)
Gao, J.F., Yang, Y., Huang, W.T., Lin, P., Ge, S., Zheng, H.M., Gu, L.Y., Zhou, H., Li, C.H., Rao, N.N.: Exploring time-and frequency-dependent functional connectivity and brain networks during deception with single-trial event-related potentials. Sci. Rep. 6, 37065 (2016)
Gitelman, D.R., Penny, W.D., Ashburner, J., Friston, K.J.: Modeling regional and psychophysiologic interactions in fMRI: the importance of hemodynamic deconvolution. Neuroimage 19(1), 200–207 (2003)
Giusti, C., Ghrist, R., Bassett, D.S.: Two’s company, three (or more) is a simplex. J. Comput. Neurosci. 41(1), 1–14 (2016). https://doi.org/10.1007/s10827-016-0608-6
Havel, P., Braun, B., Rau, S., Tonn, J.C., Fesl, G., Brückmann, H., Ilmberger, J.: Reproducibility of activation in four motor paradigms. J. Neurol. 253(4), 471–476 (2006)
Kireev, M., Korotkov, A., Medvedeva, N., Masharipov, R., Medvedev, S.: Deceptive but not honest manipulative actions are associated with increased interaction between middle and inferior frontal gyri. Front. Neurosci. 11, 482 (2017). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5583606/
Kireev, M., Korotkov, A., Medvedeva, N., Medvedev, S.: Possible role of an error detection mechanism in brain processing of deception: PET-fMRI study. Int. J. Psychophysiol. 90(3), 291–299 (2013)
Kireev, M., Medvedeva, N., Korotkov, A., Medvedev, S.: Functional interactions between the caudate nuclei and inferior frontal gyrus providing deliberate deception. Hum. Physiol. 41(1), 22–26 (2015)
Knyazeva, I., Poyda, A., Orlov, V., Verkhlyutov, V., Makarenko, N., Kozlov, S., Velichkovsky, B., Ushakov, V.: Resting state dynamic functional connectivity: network topology analysis. Biol. Inspired Cogn. Archit. 23, 43–53 (2018)
Lisofsky, N., Kazzer, P., Heekeren, H.R., Prehn, K.: Investigating socio-cognitive processes in deception: a quantitative meta-analysis of neuroimaging studies. Neuropsychologia 61, 113–122 (2014)
Luo, Q., Ma, Y., Bhatt, M.A., Montague, P.R., Feng, J.: The functional architecture of the brain underlies strategic deception in impression management. Front. Hum. Neurosci. 11, 513 (2017)
Mar, R.A.: The neural bases of social cognition and story comprehension. Annu. Rev. Psychol. 62, 103–134 (2011)
McLaren, D.G., Ries, M.L., Xu, G., Johnson, S.C.: A generalized form of context-dependent psychophysiological interactions (gPPI): a comparison to standard approaches. Neuroimage 61(4), 1277–1286 (2012). http://www.sciencedirect.com/science/article/pii/S1053811912003497
Newman, M.E.J.: Analysis of weighted networks. Phys. Rev. E 70, 056131 (2004). https://doi.org/10.1103/PhysRevE.70.056131
Oldfield, R.C.: The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9(1), 97–113 (1971)
Otter, N., Porter, M.A., Tillmann, U., Grindrod, P., Harrington, H.A.: A roadmap for the computation of persistent homology. EPJ Data Sci. 6(1), 17 (2017)
Saxe, R.: Theory of mind (neural basis). Encycl. Conscious. 2, 401–410 (2009)
Seitzman, B.A., Gratton, C., Marek, S., Raut, R.V., Dosenbach, N.U., Schlaggar, B.L., Petersen, S.E., Greene, D.J.: A set of functionally-defined brain regions with improved representation of the subcortex and cerebellum. bioRxiv p. 450452 (2018)
Sizemore, A.E., Giusti, C., Kahn, A., Vettel, J.M., Betzel, R.F., Bassett, D.S.: Cliques and cavities in the human connectome. J. Comput. Neurosci. 44(1), 115–145 (2018). https://doi.org/10.1007/s10827-017-0672-6
Sizemore, A.E., Phillips-Cremins, J.E., Ghrist, R., Bassett, D.S.: The importance of the whole: topological data analysis for the network neuroscientist. Netw. Neurosci. 3(3), 656–673 (2018). https://doi.org/10.1162/netn_a_00073
Tausz, A., Vejdemo-Johansson, M., Adams, H.: JavaPlex: a research software package for persistent (co)homology. In: Hong, H., Yap, C. (eds.) Proceedings of ICMS 2014. LNCS, vol. 8592, pp. 129–136 (2014). http://appliedtopology.github.io/javaplex/
Volz, K.G., Vogeley, K., Tittgemeyer, M., von Cramon, D.Y., Sutter, M.: The neural basis of deception in strategic interactions. Front. Behav. Neurosci. 9, 27 (2015)
Wang, Y., Ng, W.C., Ng, K.S., Yu, K., Wu, T., Li, X.: An electroencephalography network and connectivity analysis for deception in instructed lying tasks. PLoS One 10(2), e0116522 (2015)
Yin, L., Weber, B.: I lie, why don’t you: neural mechanisms of individual differences in self-serving lying. Hum. Brain Mapp. 40(4), 1101–1113 (2019)
Lin, X., Fu, G., Sai, L., Chen, H., Yang, J., Wang, M., Liu, Q., Yang, G., Zhang, J., Zhang, J., et al.: Mapping the small-world properties of brain networks in deception with functional near-infrared spectroscopy. Sci. Rep. 6, 25297 (2016)
Acknowledgments
We gratefully acknowledge financial support of Saint-Petersburg State University (project ID 35544669), N.P. Bechtereva Institute of the Human Brain of the Russian Academy of Sciences and financial support of Institute of Information and Computational Technologies (Grant AR05134227, Kazakhstan).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Knyazeva, I. et al. (2020). Topological Properties of Brain Networks Underlying Deception: fMRI Study of Psychophysiological Interactions. In: Cherifi, H., Gaito, S., Mendes, J., Moro, E., Rocha, L. (eds) Complex Networks and Their Applications VIII. COMPLEX NETWORKS 2019. Studies in Computational Intelligence, vol 882. Springer, Cham. https://doi.org/10.1007/978-3-030-36683-4_69
Download citation
DOI: https://doi.org/10.1007/978-3-030-36683-4_69
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-36682-7
Online ISBN: 978-3-030-36683-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)