The site of the Media Sphera Publishers contains materials intended solely for healthcare professionals.
By closing this message, you confirm that you are a certified medical professional or a student of a medical educational institution.

Login
EN
+7 (495) 482-4118
+7 (495) 482-4329
+8 800 250-18-12
  • (toll-free number for subscriptions)
    Mon-Fri from 10 a.m. to 6 p.m.

  • © 1998-2026
+7 (495) 482-43-29
EN
All journals
Journal
Year
Year
Search result: 0

Kremneva E.I.

Research Center of Neurology

Sinitsyn D.O.

Research Center of Neurology

Dobrynina L.A.

Research Center of Neurology

Suslina A.D.

Research Center of Neurology

Krotenkova M.V.

Research Center of Neurology

Resting state functional MRI in neurology and psychiatry

Authors:

Kremneva E.I., Sinitsyn D.O., Dobrynina L.A., Suslina A.D., Krotenkova M.V.

More about the authors

Journal: S.S. Korsakov Journal of Neurology and Psychiatry. 2022;122(2): 5‑14

DOI: 10.17116/jnevro20221220215

Read: 8877 times

Download PDF (RU)
Contact the author
Table of contents

RESTING STATE FUNCTIONAL MRI IN NEUROLOGY AND PSYCHIATRY
RESTING STATE FUNCTIONAL MRI IN NEUROLOGY AND PSYCHIATRY

To cite this article:

Kremneva EI, Sinitsyn DO, Dobrynina LA, Suslina AD, Krotenkova MV. Resting state functional MRI in neurology and psychiatry. S.S. Korsakov Journal of Neurology and Psychiatry. 2022;122(2):5‑14. (In Russ.)
https://doi.org/10.17116/jnevro20221220215

Подписка 2026 Журнал неврологии и психиатрии им. С.С. Корсакова (S.S. Korsakov Journal of Neurology and Psychiatry)
МСФ на ЯМ
Использование инфографики авторами научных работ
Close metadata
Recommended articles:
Open-access data­bases in anesthesiology and inte­nsive care: a systematic review and guidelines. Russian Journal of Anesthesiology and Reanimatology. 2025;(4):61-71
Abstract:

Resting state functional magnetic resonance imaging (fMRI) is a neuroimaging technique based on analyzing spontaneous, low frequency fluctuations in the activity of brain areas by measuring by their MRI signal to investigate the functional architecture of the brain during rest. The use of resting state fMRI opens up possibilities for assessing brain functional relationships in both normal conditions and in different CNS pathologies in order to clarify the disturbed mechanisms of brain functioning and develop approaches for therapeutic non-invasive neuromodulation. Understanding the acquisition of data, the features of their preprocessing and analysis is very important for clinicians who use resting state fMRI in their studies, since it is neurologists, psychiatrists, and neurosurgeons who set research tasks and are the final consumers of the results. The article details the methodological features of obtaining and analyzing resting state fMRI data, the advantages and disadvantages of the method. The article is intended for a wide range of specialists using this method in their work or planning to include it in their research.

Keywords:

resting-state functional magnetic resonance tomography
functional connectivity
data analysis

Authors:

Kremneva E.I.

Research Center of Neurology

Sinitsyn D.O.

Research Center of Neurology

Dobrynina L.A.

Research Center of Neurology

Suslina A.D.

Research Center of Neurology

Krotenkova M.V.

Research Center of Neurology

Received:

15.04.2021

Accepted:

29.04.2021

Close metadata

References:

  1. Ogawa S, Menon RS, Kim SG, Ugurbil K. On the characteristics of functional magnetic resonance imaging of the brain. Annu Rev Biophys Biomol Struct. 1998;27:447-474.  https://doi.org/10.1146/annurev.biophys.27.1.447
  2. Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med. 1995;34(4):537-541.  https://doi.org/10.1002/mrm.1910340409
  3. Castellanos FX, Di Martino A, Craddock RC, et al. Clinical applications of the functional connectome. Neuroimage. 2013;80:527-540.  https://doi.org/10.1016/j.neuroimage.2013.04.083
  4. Van Dijk KR, Hedden T, Venkataraman A, et al. Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization. J Neurophysiol. 2010;103(1):297-321.  https://doi.org/10.1152/jn.00783.2009
  5. Smith SM, Beckmann CF, Andersson J, et al. Resting-state fMRI in the Human Connectome Project. Neuroimage. 2013;80:144-168.  https://doi.org/10.1016/j.neuroimage.2013.05.039
  6. Smitha KA, Akhil Raja K, Arun KM, et al. Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks. Neuroradiol J. 2017;30(4):305-317.  https://doi.org/10.1177/1971400917697342
  7. Huettel, Scott A., Allen W. Song, Gregory McCarthy. Functional magnetic resonance imaging. Vol. 1. Sunderland, MA: Sinauer Associates; 2004.
  8. Janine B, Smith St M., Beckmann ChF. An introduction to resting state fMRI functional connectivity. Oxford University Press, 2017.
  9. Jenkinson, Mark, and Michael Chappell. Introduction to neuroimaging analysis. Oxford University Press, 2018.
  10. Bulte D, Wartolowska K. Monitoring cardiac and respiratory physiology during FMRI. Neuroimage. 2017;154:81-91.  https://doi.org/10.1016/j.neuroimage.2016.12.001
  11. Cole DM, Smith SM, Beckmann CF. Advances and pitfalls in the analysis and interpretation of resting-state FMRI data. Front Syst Neurosci. 2010;4:8.  https://doi.org/10.3389/fnsys.2010.00008
  12. Friston KJ. Functional and effective connectivity: a review. Brain Connect. 2011;1(1):13-36.  https://doi.org/10.1089/brain.2011.0008
  13. Piradov MA, Suponeva NA, Seliversov YuA, et al. The Opportunities of modern imaging methods in the study of spontaneous brain activity in resting state. Nevrologicheskiy Zhurnal. 2016;21(1):4-12. (In Russ.). https://doi.org/10.18821/1560-9545-2016-21-1-4-12
  14. Bukkieva TA, Chegina DS, Efimtsev AYu, et al. Resting state functional MRI. General issues and clinical application. REJR. 2019;9(2):150-170. (In Russ.). https://doi.org/10.21569/2222-7415-2019-9-2-150-170
  15. Fox MD, Greicius M. Clinical applications of resting state functional connectivity. Front Syst Neurosci. 2010;4:19.  https://doi.org/10.3389/fnsys.2010.00019
  16. van den Heuvel MP, Hulshoff Pol HE. Exploring the brain network: a review on resting-state fMRI functional connectivity. Eur Neuropsychopharmacol. 2010;20(8):519-534.  https://doi.org/10.1016/j.euroneuro.2010.03.008
  17. Nieto-Castanon A. Handbook of functional connectivity magnetic resonance imaging methods in CONN. Hilbert-Press, Boston, MA; 2020.
  18. Martuzzi R, Ramani R, Qiu M, et al. A whole-brain voxel based measure of intrinsic connectivity contrast reveals local changes in tissue connectivity with anesthetic without a priori assumptions on thresholds or regions of interest. Neuroimage. 2011;58(4):1044-1050. https://doi.org/10.1016/j.neuroimage.2011.06.075
  19. Zang Y, Jiang T, Lu Y, He Y, Tian L. Regional homogeneity approach to fMRI data analysis. Neuroimage. 2004;22(1):394-400.  https://doi.org/10.1016/j.neuroimage.2003.12.030
  20. Yang H, Long XY, Yang Y, et al. Amplitude of low frequency fluctuation within visual areas revealed by resting-state functional MRI. Neuroimage. 2007;36(1):144-152.  https://doi.org/10.1016/j.neuroimage.2007.01.054
  21. Zou QH, Zhu CZ, Yang Y, et al. An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF. J Neurosci Methods. 2008;172(1):137-141.  https://doi.org/10.1016/j.jneumeth.2008.04.012
  22. Kiviniemi V, Kantola JH, Jauhiainen J, Hyvärinen A, Tervonen O. Independent component analysis of nondeterministic fMRI signal sources. Neuroimage. 2003;19(2 Pt 1):253-260.  https://doi.org/10.1016/s1053-8119(03)00097-1
  23. Seliverstov YuA, Seliverstova EV, Konovalov RN, Krotenkova MV, Illarioshkin SN. Resting-state fMRI: possibilities and future of the method. Bjulleten’ Nacional’nogo Obshhestva po Izucheniju Bolezni Parkinsona i Rasstrojstv Dvizhenij. 2014;1:16-19. (In Russ.).
  24. Seliverstova EV, Seliverstov YuA, Konovalov RN, Illarioshkin SN. Resting-state fMRI; new possibilities for studying physiology and pathology of the brain. Ann Kiln Eksperim Nevrol. 2013;7(46):39-43. (In Russ.).
  25. Chenji S, Jha S, Lee D, et al. Investigating Default Mode and Sensorimotor Network Connectivity in Amyotrophic Lateral Sclerosis. PLoS One. 2016;11(6):e0157443. https://doi.org/10.1371/journal.pone.0157443
  26. Shen W, Tu Y, Gollub RL, et al. Visual network alterations in brain functional connectivity in chronic low back pain: A resting state functional connectivity and machine learning study. Neuroimage Clin. 2019;22:101775. https://doi.org/10.1016/j.nicl.2019.101775
  27. Rosazza C, Minati L. Resting-state brain networks: literature review and clinical applications. Neurol Sci. 2011;32(5):773-785.  https://doi.org/10.1007/s10072-011-0636-y
  28. Luria AR. Higher cortical functions in man. 2nd ed. M.: Izd-vo MGU; 1980. (In Russ.).
  29. Diachek E, Blank I, Siegelman M, et al. The Domain-General Multiple Demand (MD) Network Does Not Support Core Aspects of Language Comprehension: A Large-Scale fMRI Investigation. J Neurosci. 2020;40(23):4536-4550. https://doi.org/10.1523/JNEUROSCI.2036-19.2020
  30. Duncan J. The structure of cognition: attentional episodes in mind and brain. Neuron. 2013;80(1):35-50.  https://doi.org/10.1016/j.neuron.2013.09.015
  31. Toga, Arthur W. Brain mapping: An encyclopedic reference. Academic Press. 2015;597-611. 
  32. Morozova SN, Kremneva EI, Gadzhieva ZSh, et al. Evaluation of fMRI counting task efficiency for normal brain functional connectivity analisys during executive function examination. Medicinskaja Vizualizacija. 2020;24(2):119-130. (In Russ.). https://doi.org//10.24835/1607-0763-2020-2-119-130
  33. Raichle ME, MacLeod AM, Snyder AZ, et al. A default mode of brain function. Proc Natl Acad Sci USA. 2001;98(2):676-682.  https://doi.org/10.1073/pnas.98.2.676
  34. Vossel S, Geng JJ, Fink GR. Dorsal and ventral attention systems: distinct neural circuits but collaborative roles. Neuroscientist. 2014;20(2):150-159.  https://doi.org/10.1177/1073858413494269
  35. Farahani FV, Karwowski W, Lighthall NR. Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review. Front Neurosci. 2019;13:585.  https://doi.org/10.3389/fnins.2019.00585
  36. Shen X, Tokoglu F, Papademetris X, Constable RT. Groupwise whole-brain parcellation from resting-state fMRI data for network node identification. Neuroimage. 2013;82:403-415.  https://doi.org/10.1016/j.neuroimage.2013.05.081
  37. Supekar K, Menon V, Rubin D, et al. Network analysis of intrinsic functional brain connectivity in Alzheimer’s disease. PLoS Comput Biol. 2008;4(6):e1000100. https://doi.org/10.1371/journal.pcbi.1000100
  38. Hafkemeijer A, Möller C, Dopper EG, et al. Resting state functional connectivity differences between behavioral variant frontotemporal dementia and Alzheimer’s disease. Front Hum Neurosci. 2015;9:474.  https://doi.org/10.3389/fnhum.2015.00474.
  39. Argyelan M, Ikuta T, DeRosse P, et al. Resting-state fMRI connectivity impairment in schizophrenia and bipolar disorder. Schizophr Bull. 2014;40(1):100-110.  https://doi.org/10.1093/schbul/sbt092
  40. Greicius M. Resting-state functional connectivity in neuropsychiatric disorders. Curr Opin Neurol. 2008;21(4):424-430.  https://doi.org/10.1097/WCO.0b013e328306f2c5
  41. Badhwar A, Tam A, Dansereau C, et al. Resting-state network dysfunction in Alzheimer’s disease: A systematic review and meta-analysis. Alzheimers Dement (Amst). 2017;8:73-85.  https://doi.org/10.1016/j.dadm.2017.03.00.
  42. Zhang D, Liu X, Chen J, et al. Widespread increase of functional connectivity in Parkinson’s disease with tremor: a resting-state FMRI study. Front Aging Neurosci. 2015;7:6.  https://doi.org/10.3389/fnagi.2015.00006.
  43. Smirnov AS, Sharaev MG, Melnikova-Pitskhelauri TV, et al. Resting state fMRI in pre-surgical brain mapping. Literature Review. 2018;(5):6-13. (In Russ.). https://doi.org/10.24835/1607-0763-2018-5-6-13
  44. Kumar VA, Heiba IM, Prabhu SS, et al. The role of resting-state functional MRI for clinical preoperative language mapping. Cancer Imaging. 2020;20(1):47.  https://doi.org/10.1186/s40644-020-00327-w
  45. Picchioni D, Duyn JH, Horovitz SG. Sleep and the functional connectome. Neuroimage. 2013;80:387-396.  https://doi.org/10.1016/j.neuroimage.2013.05.067
  46. Hutchison RM, Womelsdorf T, Allen EA, et al. Dynamic functional connectivity: promise, issues, and interpretations. Neuroimage. 2013;80:360-378.  https://doi.org/10.1016/j.neuroimage.2013.05.079
Contact the author
Email
Message
The publishing house "Media Sphere" does not provide treatment services, does not give recommendations on contacting medical institutions and specific specialists, on the prescription of medicines and dietary supplements.

Email Confirmation

An email was sent to test@gmail.com with a confirmation link. Follow the link from the letter to complete the registration on the site.

Email Confirmation

Contact us
If you have any questions, complaints or suggestions, please use this feedback form.
Email
Message
The publishing house "Media Sphere" does not provide treatment services, does not give recommendations on contacting medical institutions and specific specialists, on the prescription of medicines and dietary supplements.
Submit Application

You can become an author of one of our magazines, send a request and we will consider it in during the day.

Name
Phone
E-mail
Message
Login
Registration
E-mail
Password
Forgot Password?

Log in to the site using your account in one of the services

Password recovery
E-mail
Login
Register

We use cооkies to improve the performance of the site. By staying on our site, you agree to the terms of use of cооkies. To view our Privacy and Cookie Policy, please. click here.