Skip to main content

Voxel-Wise Localization of Brain Activity While Comprehending Oral Russian-Language Stories

  • Conference paper
  • First Online:
Advances in Cognitive Research, Artificial Intelligence and Neuroinformatics (Intercognsci 2020)

Abstract

We have implemented neurosemantic analysis to identify voxel-wise representations of lexical items in brain’s reaction of native participants on Russian spoken narratives and these representations possible global asymmetries in the brain. Twenty-five subjects took part in this study. Five texts with personal life stories were presented as audio stimuli. Each story was 2 min long. Ultrafast MRI sequences (TR = 1000 ms) were used to scan brain activity. Scanning was performed on 3 T MRI (Siemens). Seven subjects were selected for further analysis following the control of their cognitive involvement into listening and the level of their registered brain activity. As in an earlier our study with these narratives, twelve lexical clusters were found, with different but coherent semantic fields: from time-and-space concepts to human actions and mental states. The individual semantic maps of each subject look similar in terms of their broad brain activity distribution. Clusters demonstrated nearly symmetrical localization. This fact implies that the left and right hemispheres are both involved in the neural representation of mental lexicon.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Ardila, A.: A proposed neurological interpretation of language evolution. Behav. Neurol. 2015, 872487 (2015). https://doi.org/10.1155/2015/872487

    Article  Google Scholar 

  2. Luria, A.R.: Language and brain: towards the basic problems of neurolinguistics. Brain Lang. 1, 1–14 (1974). https://doi.org/10.1016/0093-934X(74)90022-4

    Article  Google Scholar 

  3. Luria, A.R.: Basic Problems in Neurolinguistics. Mouton, The Hague (1976)

    Book  Google Scholar 

  4. Grabowski, T.J., Damasio, H., Tranel, D., Ponto, L.L.B., Hichwa, R.D., Damasio, A.R.: A role for left temporal pole in the retrieval of words for unique entities. Hum. Brain. Mapp. 13, 199–212 (2001). https://doi.org/10.1002/hbm.1033

    Article  Google Scholar 

  5. Damasio, H., Tranel, D., Grabowski, T., Adolphs, R., Damasio, A.: Neural systems behind word and concept retrieval. Cognition 92, 179–229 (2004). https://doi.org/10.1016/j.cognition.2002.07.001

    Article  Google Scholar 

  6. Binder, J.R., Desai, R.H., Graves, W.W., Conant, L.L.: Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cereb. Cortex 19, 2767–2796 (2009). https://doi.org/10.1093/cercor/bhp055

    Article  Google Scholar 

  7. Assaf, M., Calhoun, V.D., Kuzu, C.H., Kraut, M.A., Rivkin, P.R., Hart, J., Pearlson, G.D.: Neural correlates of the object-recall process in semantic memory. Psychiatry Res. Neuroimaging 147, 115–126 (2006). https://doi.org/10.1016/j.pscychresns.2006.01.002

    Article  Google Scholar 

  8. Huth, A.G., de Heer, W.A., Griffiths, T.L., Theunissen, F.E., Gallant, J.L.: Natural speech reveals the semantic maps that tile human cerebral cortex. Nature 532, 453–458 (2016). https://doi.org/10.1038/nature17637

    Article  Google Scholar 

  9. Caramazza, A., Shelton, J.R.: Domain-specific knowledge systems in the brain the animate-inanimate distinction. J. Cogn. Neurosci. 10, 1–34 (1998). https://doi.org/10.1162/089892998563752

    Article  Google Scholar 

  10. Mummery, C.J., Patterson, K., Hodges, J.R., Price, C.J.: Functional neuroanatomy of the semantic system: divisible by what? J. Cogn. Neurosci. 10, 766–777 (1998). https://doi.org/10.1162/089892998563059

    Article  Google Scholar 

  11. Velichkovsky, B.M., Zaidelman, L.Y., Kotov, A.A., Nosovets, Z.A., Ushakov, V.L., Zabotkina, V.I.: The nature of neurosemantic representation: Stimuli, meaning, and personal sense. Quest. Psychol. (Boпpocы пcиxoлo гии) 66(3), 132–146 (2020). (in Russian)

    Google Scholar 

  12. Velichkovsky, B.M., Zabotkina, V.I., Nosovets, Z.A., Kotov, A.A., Zaidelman, L.Y., Nosovets, Z.A., Kartashov, S.I., Korosteleva, A.N., Malakhov, D.G., Orlov, V.A., Zinina, A.A., Goldberg, E., Ushakov, V.L.: Towards semantic brain mapping methodology based on a multidimensional markup of continuous Russian-language texts. STM 12(2), 14–25 (2020). https://doi.org/10.17691/stm2020.12.2.02

    Article  Google Scholar 

  13. Zaidelman, L.Y., Nosovets, Z.A., Kotov, A.A., Ushakov, V.L., Zabotkina, V.I., Velichkovsky, B.M.: Russian-language neurosemantics: clusterizing of words meaning and sense from the oral narratives. Cogn. Syst. Res. 67, 60–65 (2021)

    Article  Google Scholar 

  14. Velichkovsky, B.M., Kotov, A.A., Zabotkina, V.I., Nosovets, Z.A., Goldberg, E., Zaidelman, L.Y.: Heteroglossia in Neurosemantics: The Case of a Word Cluster with Mentalist Content. In: Velichkovsky, B., et al. (eds.) Advances in Cognitive Research, Artificial Intelligence and Neuroinformatics. Advances in Intelligent Systems and Computing, vol. 1358, pp. 307–318 (2021)

    Google Scholar 

  15. Kutuzov A., Kuzmenko E.: WebVectors: a toolkit for building web interfaces for semantic vector models. In: Ignatov, D., et al. (ed.) AIST 2016. CCIS, vol. 661, pp. 155–161. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-52920-2

  16. Lyashevskaya, O.N., Sharov S.A.: Frequency Dictionary of the Modern Russian Language (The Russian National Corpus). Azbukovnik (2009)

    Google Scholar 

  17. SPM8 Software. https://www.fil.ion.ucl.ac.uk/spm/software/spm8

  18. Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., Joliot, M.: Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15, 273–289 (2002). https://doi.org/10.1006/nimg.2001.0978

    Article  Google Scholar 

  19. Price, C.J.: The anatomy of language: a review of 100 fMRI studies published in 2009. Ann. N.Y. Acad. Sci. 1191, 62–88 (2010). https://doi.org/10.1111/j.1749-6632.2010.05444.x

    Article  Google Scholar 

  20. Price, C.J.: A review and synthesis of the first 20 years of PET and fMRI studies of heard speech, spoken language and reading. Neuroimage 62, 816–847 (2012). https://doi.org/10.1016/j.neuroimage.2012.04.062

    Article  Google Scholar 

  21. Mariën, P., Engelborghs, S., Fabbro, F., De Deyn, P.P.: The lateralized linguistic cerebellum: a review and a new hypothesis. Brain Lang. 79, 580–600 (2001). https://doi.org/10.1006/brln.2001.2569

    Article  Google Scholar 

  22. Argyropoulos, G.P.D.: The cerebellum, internal models and prediction in ‘non-motor’ aspects of language: a critical review. Brain Lang. 161, 4–17 (2016). https://doi.org/10.1016/j.bandl.2015.08.003

    Article  Google Scholar 

  23. van den Hurka, J., Baelena, M.V., de Beecka, H.P.O.: Development of visual category selectivity in ventral visual cortex does not require visual experience. PNAS 114, 4501–4510 (2017). https://doi.org/10.1073/pnas.1612862114

    Article  Google Scholar 

  24. Jackendoff, R.: Meaning and the Lexicon. Oxford University Press, Oxford, UK (2010)

    Google Scholar 

  25. Jackendoff, R.. : Defence of theory. Cogn. Sci. 41(2), 185–212 (2017). https://doi.org/10.1111/cogs.12324

    Article  Google Scholar 

  26. Tononi, G., Boly, M., Massimini, M., Koch, C.: Integrated information theory: from consciousness to its physical substrate. Nat. Rev. Neurosci. 17, 450–461 (2016). https://doi.org/10.1038/nrn.2016.44

    Article  Google Scholar 

  27. Dehghani, M., Boghrati, R., Man, K., Hoover, J., Gimbel, S., Vaswani, A., Zevin, J., Immordino-Yang, M., Gordon, A., Damasio, A., Kaplan, J.: Decoding the neural representation of story meanings across languages. Hum. Brain. Mapp. 38, 6096–6106 (2017). https://doi.org/10.1002/hbm.23814

    Article  Google Scholar 

Download references

Acknowledgements

The study has been in part supported by the Russian Science Foundation, grant 17-78-30029.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zakhar Nosovets .

Editor information

Editors and Affiliations

Appendix

Appendix

Table 3. Number of active voxels for all the clusters and ratio of these voxels to the number of the best 10,000 voxels, represented in the same zone for each subject (L and R correspond to left and right hemispheres; percentages are given in parentheses)

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Nosovets, Z. et al. (2021). Voxel-Wise Localization of Brain Activity While Comprehending Oral Russian-Language Stories. In: Velichkovsky, B.M., Balaban, P.M., Ushakov, V.L. (eds) Advances in Cognitive Research, Artificial Intelligence and Neuroinformatics. Intercognsci 2020. Advances in Intelligent Systems and Computing, vol 1358. Springer, Cham. https://doi.org/10.1007/978-3-030-71637-0_35

Download citation

Publish with us

Policies and ethics