Skip to main content
Log in

Characteristics of fMRI Patterns during the Performance of Hand and Finger Movements of Different Complexity

  • Published:
Neurophysiology Aims and scope

We analyzed the topography and quantitative characteristics of changes in a blood oxygenation level-dependent (BOLD) signal accompanying movements of the fingers and hand performed by healthy humans. Three test movements characterized by different levels of complexity were united in an integrated paradigm of activation. We assumed that such a paradigm should promote the understanding of mechanisms of functioning of separate neuronal networks controlling motor functions and their grouping in scaling networks responsible for general control of motor activity by the CNS. Concurrently with the processes of activation of the sensorimotor network, we observed partial deactivation of certain nodi of the default-mode network (DMN) and formation of functional connectivities independent of the performance of the tasks. This confirms the statement on the heterogeneity of the DMN, whose different parts can be simultaneously desynchronized and can function in an offline mode. Analysis of the frequency spectrum of fluctuations of the BOLD signal allowed us to conclude that the sensorimotor network and DMN function simultaneously; however, each of them demonstrates direct (for the sensorimotor network) and inverse (for the DMN) correlation between changes in the BOLD signal and the successfulness of performance of the motor task.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. C. Stippich, B. Kress, H. Ochmann, et al., «Preoperative functional magnetic resonance tomography (FMRI) in patients with rolandic brain tumors: indication, investigation strategy, possibilities and limitations of clinical application,» Fortschr. Geb. Rontgenstr. Nuklearmed., 175, No. 8, 1042-1050 (2003).

  2. J. D. Allison, K. J. Meador, D. W. Loring, et al., “Functional MRI cerebral activation and deactivation during finger movement,” Neurology, 54, No. 1, 135 (2000).

  3. S. Ogawa, T. Lee, A. Kay, et al., “Brain magnetic resonance imaging with contrast dependent on blood oxygenation,” Proc. Natl. Acad. Sci. USA, 87, No. 24, 9868-9872 (1990).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. G. L. Shulman, J. A. Fiez, M. Corbetta, et al., “Common blood flow changes across visual tasks: II. Decreases in cerebral cortex,” J. Cogn. Neurosci., 9, No. 5, 648-663 (1997).

    Article  CAS  PubMed  Google Scholar 

  5. Motor Cortex in Voluntary Movements: a Distributed System for Distributed Functions, A. Riehle and E. Vaadia (eds.), CRC Press, Boca Raton (2005).

  6. Dysregulative Pathology of the Nervous System [in Russian], E. I. Gusev and G. N. Kryzhanovskii (eds.), “Med. Inform. Agenstvo,” Moscow (2009).

  7. M. E. Raichle, A. M. MacLeod, A. Z. Snyder, et al., “A default mode of brain function,” Proc. Natl. Acad. Sci. USA, 98, No. 2, 676-682 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. W. Gao, J. H. Gilmore, S. Alcauter, et al., «The dynamic reorganization of the default-mode network during a visual classification task,» Front. Syst. Neurosci., 7, 1-13 (2013).

    Article  CAS  Google Scholar 

  9. M. D. Greicius, B. Krasnow, A. L. Reiss, et al., “Functional connectivity in the resting brain: a network analysis of the default mode hypothesis,” Proc. Natl. Acad. Sci. USA, 100, No. 1, 253-258 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. A. R. Laird, S. B. Eickhoff, K. Li, et al., “Investigating the functional heterogeneity of the default mode network using coordinate-based meta-analytic modeling,” J. Neurosci., 29, No. 46, 14496-14505 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. K. J. Friston, A. P. Holmes, K. J. Worsley, et al., “Statistical parametric maps in functional imaging: a general linear approach,” Hum. Brain Mapp., 2, No. 4, 189-210 (1994).

    Article  Google Scholar 

  12. C. F. Beckmann and S. M. Smith, “Probabilistic independent component analysis for functional magnetic resonance imaging,” IEEE Trans. Med. Imaging, 23, No. 2, 137-152 (2004).

    Article  PubMed  Google Scholar 

  13. J. P. Kuhtz-Buschbeck, C. Mahnkopf, C. Holzknecht, et al., “Effector-independent representations of simple and complex imagined finger movements: a combined fMRI and TMS study,” Eur. J. Neurosci., 18, No. 12, 3375-3387 (2003).

    Article  CAS  PubMed  Google Scholar 

  14. Y. Liu, H. Shen, Z. Zhou, et al., “Sustained negative BOLD response in human fMRI finger tapping task,” PLoS One, 6, No. 8, e23839 (2011).

  15. M. Rijntjes, C. Dettmers, C. Bьchel, et al., “A blueprint for movement: functional and anatomical representations in the human motor system,” J. Neurosci., 19, No. 18, 8043-8048 (1999).

    CAS  PubMed  Google Scholar 

  16. P. Hlustэмk, A. Solodkin, R. P. Gullapalli, et al., “Functional lateralization of the human premotor cortex during sequential movements,” Brain Cogn., 49, No. 1, 54-62 (2002).

    Article  Google Scholar 

  17. N. Picard and P. L. Strick, “Motor areas of the medial wall: a review of their location and functional activation,” Cerebr. Cortex, 6, No. 3, 342-353 (1996).

    Article  CAS  Google Scholar 

  18. K. Sakai, O. Hikosaka, S. Miyauchi, et al., “Transition of brain activation from frontal to parietal areas in visuomotor sequence learning,” J. Neurosci., 18, No. 5, 1827-1840 (1998).

    CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to A. N. Omel’chenko or Z. Z Rozhkova.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Omel’chenko, A.N., Rozhkova, Z.Z. Characteristics of fMRI Patterns during the Performance of Hand and Finger Movements of Different Complexity. Neurophysiology 48, 23–30 (2016). https://doi.org/10.1007/s11062-016-9565-y

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11062-016-9565-y

Keywords

Navigation