Reorganization of the brain’s default mode network in patients with Parkinson’s disease: resting-state fMRI-based analysis of individual components

Abstract

Resting-state functional magnetic resonance imaging (rs-fMRI) enables evaluation of low-frequency oscillations (0.01–0.1 Hz) of the BOLD-signal, which are related to changes in the hemodynamics parameters, thereby making possible to determine indirectly the spontaneous neuronal activity of various areas of the brain at rest . We conducted an rs-fMRI study in groups of healthy volunteers and patients with Parkinson’s disease (PD). Out of the spectrum of resting neural networks of the brain, the brain’s default mode network (DMN) was selected, and changes in the neuronal activity pattern of the network in PD patients were evaluated. Compared to the norm, PD was found to be characterized by a decrease in the activity of the right inferior parietal lobe (i.e. in the area incorporated into DMN and involved in visual-spatial perception) and, on the contrary, an increase in the spontaneous neuronal activity of DMN in the medial segments of the right superior frontal gyrus, right and left angular gyri, and anterosuperior and posteroinferior parts of the left and right precuneus. The detected changes in the neuronal activity, regarded as a manifestation of the neuroplasticity phenomenon,may potentially serve as biomarkers of a neurodegenerative process in PD.

About the authors

E. V. Seliverstova

Research Center of Neurology, Moscow

Author for correspondence.
Email: platonova@neurology.ru
Russian Federation

Yu. A. Seliverstov

Research Center of Neurology, Moscow

Email: platonova@neurology.ru
Russian Federation

R. N. Konovalov

Research Center of Neurology, Moscow

Email: platonova@neurology.ru
Russian Federation

M. V. Krotenkova

Research Center of Neurology, Moscow

Email: platonova@neurology.ru
Russian Federation

S. N. Illarioshkin

Research Center of Neurology, Moscow

Email: platonova@neurology.ru
Russian Federation

References

  1. Кремнева Е.И. Коновалов Р.Н., Кротенкова М.В. Функциональная магнитно-резонансная томография. Анн. клин. и эксперим.неврол. 2011; 1: 30–39.
  2. Селиверстова Е.В., Селиверстов Ю.А., Коновалов Р.Н., Иллариошкин С.Н. Функциональная магнитно-резонансная томография покоя: возможности метода и первый опыт применения в России. Анн. клин. и эксперим. неврол. 2013; 4: 39–44.
  3. Селиверстова Е.В., Селиверстов Ю.А., Коновалов Р.Н. и др. Опыт применения функциональной магнитно-резонансной томографии покоя в России. Здравоохранение Таджикистана 2014; 12: 146–149.
  4. Andrews-Hanna J.R., Snyder A.Z., Vincent J.L. et al. Disruption of large-scale brain systems in advanced aging. Neuron 2007; 56: 924–935.
  5. Beckmann C.F., DeLuca M., Devlin J.T., Smith S.M. Investigations into resting-state connectivity using independent component analysis. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 2005; 360: 1001–1013.
  6. Biswal B., Yetkin F.Z., Haughton V.M., Hyde J.S. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn. Reson. Med. 1995; 34: 537–541.
  7. Calhoun V.D., Adali T., Pearlson G.D., Pekar J.J. A method for making group inferences from functional MRI data using independent component analysis. Hum. Brain Mapp. 2001; 14: 140–151.
  8. Cordes D., Haughton V., Carew J.D. et al. Hierarchical clustering to measure connectivity in fMRI resting-state data. Magn. Reson. Imaging 2002; 20: 305–317.
  9. Cordes D., Haughton V.M., Arfanakis K. et al. Mapping functionally related regions of brain with functional connectivity MR imaging. Am. J. Neuroradiol. 2000; 21: 1636–1644.
  10. Davie C.A. A review of Parkinson’s disease. Br. Med. Bull. 2008; 86: 109–127.
  11. Doucet G., Naveau M., Petit L. et al. Brain activity at rest: a multiscale hierarchical functional organization. J. Neurophysiol. 2011; 105: 2753–2763.
  12. Fransson P. Spontaneous low-frequency BOLD signal fluctuations: an fMRI in-vestigation of the resting-state default mode of brain function hypothesis. Hum. Brain Mapp. 2005; 26: 15–29.
  13. Friston K.J., Frith C.D., Liddle P.F., Frackowiak R.S. Functional connectivity: the principal-component analysis of large (PET) data sets. J. Cereb. Blood Flow Metab. 1993; 13: 5–14.
  14. Greicius M.D., Krasnow B., Reiss A.L., Menon V. Functional connec-tivity in the resting brain: a network analysis of the default mode hypothesis. Proc. Natl. Acad. Sci. U. S. A. 2003; 100: 253–258.
  15. Gusnard D.A., Raichle M.E., Raichle M.E. Searching for a baseline: functional imaging and the resting human brain. Nat. Rev. Neurosci. 2001; 2: 685–694.
  16. Hawkes C.M. Diagnosis and treatment of Parkinson’s disease. Anosmia is a common finding. BMJ 1995; 310: 1668.
  17. Kahan J., Urner M., Moran R. et al. Resting state functional MRI in Parkinson’s disease: the impact of deep brain stimulation on ‘effective’ connectivity. Brain 2014; 137 (Pt 4): 1130–1144.
  18. Larson-Prior L.J., Zempel J.M., Nolan T.S. et al. Cortical network functional connectivity in the descent to sleep. Proc. Natl. Acad. Sci. U. S. A. 2009; 106: 4489–4494.
  19. Lee M.H., Smyser C.D., Shimony J.S. Resting-State fMRI: A Review of Methods and Clinical Applications. Am. J. Neuroradiol. 2013; 34: 1866–1872.
  20. Mason M.F., Norton M.I., Van Horn J.D. et al. Wandering minds: the default network and stimulus-independent thought. Science 2007;315: 393–395.
  21. McKeown M.J., Hansenz L.K., Sejnowski T.J. Independent component analysis of functional MRI: what is signal and what is noise? Cur.Opin. Neurobiol. 2003; 13: 620–629.
  22. Mutch W.J., Dingwall-Fordyce I., Downie A.W. et al. Parkinson’s disease in a Scottish City. BMJ 1986; 292: 534–536.
  23. Salvador R., Suckling J., Coleman M.R. et al. Neurophysiological architecture of functional magnetic resonance images of human brain.Cereb. Cortex 2005; 15: 1332–1342.
  24. Song M., Zhou Y., Li J. et al. Brain spontaneous functional connectivity and intelligence. Neuroimage 2008; 41: 1168–1176.
  25. Stone J.V. Independent component analysis: an introduction. Trends Cogn. Sci. 2002; 6: 59–64.
  26. Thirion B., Dodel S., Poline J.B. Detection of signal synchronizations
  27. in resting-state fMRI datasets. Neuroimage 2006; 29: 321–327.
  28. Van den Heuvel M.P., Mandl R.C., Hulshoff Pol H.E. Normalized cut group clus-tering of resting-state fMRI data. PLoS ONE 2008; 3: e2001.
  29. Van de Ven V.G., Formisano E., Prvulovic D. et al. Functional connectivity as revealed by spatial independent component analysis of fMRI measurements during rest. Hum. Brain Mapp. 2004; 22: 165–178.

Statistics

Views

Abstract: 1083

PDF (Russian): 575

Article Metrics

Metrics Loading ...

Dimensions

PlumX


Copyright (c) 2015 Seliverstova E.V., Seliverstov Y.A., Konovalov R.N., Krotenkova M.V., Illarioshkin S.N.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies