Resting-state neural networks in cognitive decline in patients with vascular encephalopathy
- Authors: Fokin V.F.1, Ponomareva N.V.1, Konovalov R.N.1, Krotenkova M.V.1, Medvedev R.B.1, Lagoda O.V.1, Tanashyan M.M.1
-
Affiliations:
- Research Center of Neurology
- Issue: Vol 14, No 4 (2020)
- Pages: 39-45
- Section: Original articles
- URL: https://ogarev-online.ru/2075-5473/article/view/124161
- DOI: https://doi.org/10.25692/ACEN.2020.4.5
- ID: 124161
Cite item
Full Text
Abstract
We evaluated the connectivity reorganization of resting-state neural networks in patients with cognitive decline secondary to vascular encephalopathy (VE). Quantitative cognitive functions were evaluated using the Montreal Cognitive Assessment (MoCA) scale and compared with the organization of resting-state neural networks recorded using functional magnetic resonance imaging (fMRI).
The aim of this work was to assess the relationship between various resting-state neural networks and cognitive function.
Materials and methods. The study involved 29 people with VE, divided into two groups: without cognitive decline (≥ 26 points on the MoCA) and with cognitive impairment (24–18 points on the MoCA). Connectivity between different brain regions was evaluated in all patients using resting-state fMRI, with SPM-12 and CONN18b software applications in Matlab.
Results and conclusion. Statistically significant differences in connectivity were found between groups in the dorsal attention network, visual network, and sensorimotor networks, as well as in the left parahippocampal cortex. New, negative connectivity was observed alongside cognitive decline, which, together with reduced connectivity in resting-state neural networks, can be considered an obligatory sign accompanying cognitive impairment in VE.
About the authors
Vitaliy F. Fokin
Research Center of Neurology
Author for correspondence.
Email: fvf@mail.ru
Russian Federation, Moscow
Natalia V. Ponomareva
Research Center of Neurology
Email: fvf@mail.ru
Russian Federation, Moscow
Rodion N. Konovalov
Research Center of Neurology
Email: fvf@mail.ru
Russian Federation, Moscow
Marina V. Krotenkova
Research Center of Neurology
Email: fvf@mail.ru
Russian Federation, Moscow
Roman B. Medvedev
Research Center of Neurology
Email: fvf@mail.ru
Russian Federation, Moscow
Olga V. Lagoda
Research Center of Neurology
Email: fvf@mail.ru
Russian Federation, Moscow
Marine M. Tanashyan
Research Center of Neurology
Email: fvf@mail.ru
Russian Federation, Moscow
References
- Suslina Z.A., Illarioshkin S.N., Piradov M.A. [Neurology and neuroscience - development prognosis]. Annaly klinicheskoy i eksperimental’noy nevrologii 2007; 1(1): 5–9. (In Russ.)
- Tanashyan M.M., Maksimova M.Yu., Domashenko M.A. [Encephalopathy]. In: Guide to medical appointments. Therapeutic guide. Moscow; 2015; 2: 1–25. (In Russ.)
- Yakhno N.N. [Cognitive disorders in a neurological clinic]. Nevrologicheskiy zhurnal 2006; 11(1): 4–12. (In Russ.)
- Piradov M.A., Suponeva N.A., Seliverstov Yu.A. et al. [Possibilities of modern methods of neuroimaging in the study of spontaneous activity of the brain at rest]. Nevrologicheskiy zhurnal 2016; 21(1): 4–12. doi: 10.18821/1560-9545-2016-21-1-4-12. (In Russ.)
- Fokin V.F., Ponomareva N.V., Konovalov R.N. et al. [Brain connectivity changes in patients with working memory impairments with chronic ischemic cerebrovascular disease]. Vestnik RGMU 2019; (5): 56–63. doi: 10.24075/vrgmu.2019.061. (In Russ.)
- Nasreddine Z.S, Phillips N.A, Bédirian V. et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc 2005; 53: 695–699. doi: 10.1111/j.1532-5415.2005.53221.x. PMID: 15817019.
- Borland E., Nägga R., Nilsson P.M. et al. The Montreal Cognitive Assessment: normative data from a large swedish population-based cohort. J Alzheimers Dis 2017; 59: 893–901. doi: 10.3233/JAD-170203. PMID: 28697562.
- Fokin V.F., Ponomareva N.V. [Technologies for the study of cerebral asymmetry]. In: M.A. Piradov, S.N. Illarioshkin, M.M. Tanashyan (eds.) Neurology of the XXI century: diagnostic, treatment and research technologies. A guide for doctors. Moscow; 2015; 3: 350–375. (In Russ.)
- Whitfield-Gabrieli S., Nieto-Castanon A. Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connect 2012; 2: 125–141. doi: 10.1089/brain.2012.0073. PMID: 22642651.
- Zhang H-Y., Wang S-J., Liu B. Resting brain connectivity: changes during the progress of Alzheimer Disease. Radiology 2010; 256: 598–606. doi: 10.1148/radiol.10091701. PMID: 20656843.
- Yamashita M., Yoshihara Y., Hashimoto R. et al. A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity. Elife 2018; 7: e38844. doi: 10.7554/eLife.38844. PMID: 30526859.
- Hafkemeijer А., Möller С., Dopper E.G.P. at al. A longitudinal study on resting state functional connectivity in behavioral variant Frontotemporal Dementia and Alzheimer's Disease. J Alzheimers Dis 2017; 55: 521–537. doi: 10.3233/JAD-150695. PMID: 27662284.
- Bukkiyeva T.A., Chegina D.S., Efimtsev A.Yu. et al. [Funktsional’naya MRT pokoya. Obshchiye voprosy i klinicheskoye primeneniye]. Rossiyskiy elektronnyy zhurnal luchshevoy diagnostiki 2019; 9(2): 150–170. doi: 10.21569/2222-7415- 2019-9-2-150-170. (In Russ.)
- Tsvetanov K.A., Henson R.N.A., Tyler L.K. et al. Extrinsic and intrinsic brain network connectivity maintains cognition across the lifespan despite accelerated decay of regional brain activation. J Neurosci 2016; 36: 3115–3126. doi: 10.1523/JNEUROSCI.2733-15.2016. PMID: 26985024.
- 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. doi: 10.1002/mrm.1910340409. PMID: 8524021.
- Sun Y., Qin L., Zhou Y. et al. Abnormal functional connectivity in patients with vascular cognitive impairment, no dementia: A resting-state functional magnetic resonance imaging study. Behav Brain Res 2011; 223: 388–394. doi: 10.1016/j.bbr.2011.05.006. PMID: 21605598.
- Seo S.W., Ahn J., Yoon U. et al. Cortical thinning in vascular mild cognitive impairment and vascular dementia of subcortical type. J Neuroimaging 2010; 20: 37–45. doi: 10.1111/j.1552-6569.2008.00293.x. PMID: 19220710.
- Yi L., Wang J., Jia L. et al. Structural and functional changes in subcortical vascular mild cognitive impairment: a combined voxel-based morphometry and resting-state fMRI study. PLoS One 2012; 7: e44758. doi: 10.1371/journal.pone.0044758. PMID: 23028606.
- Zheng W., Cui B., Han Y. et al. Disrupted regional cerebral blood flow, functional activity and connectivity in Alzheimer's Disease: a combined ASL perfusion and resting state fMRI study. Front Neurosci 2019; 13: 738. doi: 10.3389/fnins.2019.00738. PMID: 31396033.
Supplementary files
