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Dobrynina LA, Gadzhieva ZS, Dobrushina OR, Morozova SN, Kremneva EI, Volik AV, Krotenkova MV. [Identifying the neurostimulation target for treatment of cognitive impairment in aging and early cerebral small vessel disease]. Zh Nevrol Psikhiatr Im S S Korsakova 2024; 124:34-41. [PMID: 38529861 DOI: 10.17116/jnevro202412403134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
OBJECTIVE To develop individualized approaches to the use of neuromodulation as a non-pharmacological treatment of cognitive impairment (CI) based on the assessment of compensatory brain reserves in functional MRI (fMRI). MATERIAL AND METHODS Twenty-one adults over 45 years of age, representing a continuum from healthy norm to mild cognitive impairment due to aging and early cerebral small vessel disease, were studied. All participants underwent fMRI while performing two executive tasks - a modified Stroop task and selective counting. To assess the ability to compensate for CI in real life, functional activation and connectivity were analyzed using the BRIEF-MoCA score as a covariate, which is the difference in ratings between the Behavior Rating Inventory of Executive Function (BRIEF) and the Montreal Cognitive Assessment Scale (MoCA). RESULTS Both fMRI tasks were associated with activation of areas of the frontoparietal control network, as well as supplementary motor area (SMA) and the pre-SMA, the lateral premotor cortex, and the cerebellum. An increase in pre- SMA connectivity was observed during the tasks. The BRIEF-MoCA score correlated firstly with connectivity of the left dorsolateral prefrontal cortex (DLPFC) and secondly with involvement of the occipital cortex during the counting task. CONCLUSIONS The developed technique allows identification of the functionally relevant target within the left DLPFC in patients with CI in aging and early cerebral microangiopathy.
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Affiliation(s)
| | | | | | | | | | - A V Volik
- Research Center of Neurology, Moscow, Russia
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Sinitsyn DO, Poydasheva AG, Bakulin IS, Legostaeva LA, Iazeva EG, Sergeev DV, Sergeeva AN, Kremneva EI, Morozova SN, Lagoda DY, Casarotto S, Comanducci A, Ryabinkina YV, Suponeva NA, Piradov MA. Detecting the Potential for Consciousness in Unresponsive Patients Using the Perturbational Complexity Index. Brain Sci 2020; 10:E917. [PMID: 33260944 PMCID: PMC7760168 DOI: 10.3390/brainsci10120917] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 11/24/2020] [Accepted: 11/24/2020] [Indexed: 12/26/2022] Open
Abstract
The difficulties of behavioral evaluation of prolonged disorders of consciousness (DOC) motivate the development of brain-based diagnostic approaches. The perturbational complexity index (PCI), which measures the complexity of electroencephalographic (EEG) responses to transcranial magnetic stimulation (TMS), showed a remarkable sensitivity in detecting minimal signs of consciousness in previous studies. Here, we tested the reliability of PCI in an independently collected sample of 24 severely brain-injured patients, including 11 unresponsive wakefulness syndrome (UWS), 12 minimally conscious state (MCS) patients, and 1 emergence from MCS patient. We found that the individual maximum PCI value across stimulation sites fell within the consciousness range (i.e., was higher than PCI*, which is an empirical cutoff previously validated on a benchmark population) in 11 MCS patients, yielding a sensitivity of 92% that surpassed qualitative evaluation of resting EEG. Most UWS patients (n = 7, 64%) showed a slow and stereotypical TMS-EEG response, associated with low-complexity PCI values (i.e., ≤PCI*). Four UWS patients (36%) provided high-complexity PCI values, which might suggest a covert capacity for consciousness. In conclusion, this study successfully replicated the performance of PCI in discriminating between UWS and MCS patients, further motivating the application of TMS-EEG in the workflow of DOC evaluation.
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Affiliation(s)
- Dmitry O. Sinitsyn
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.G.P.); (I.S.B.); (L.A.L.); (E.G.I.); (D.V.S.); (A.N.S.); (E.I.K.); (S.N.M.); (D.Y.L.); (Y.V.R.); (N.A.S.); (M.A.P.)
| | - Alexandra G. Poydasheva
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.G.P.); (I.S.B.); (L.A.L.); (E.G.I.); (D.V.S.); (A.N.S.); (E.I.K.); (S.N.M.); (D.Y.L.); (Y.V.R.); (N.A.S.); (M.A.P.)
| | - Ilya S. Bakulin
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.G.P.); (I.S.B.); (L.A.L.); (E.G.I.); (D.V.S.); (A.N.S.); (E.I.K.); (S.N.M.); (D.Y.L.); (Y.V.R.); (N.A.S.); (M.A.P.)
| | - Liudmila A. Legostaeva
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.G.P.); (I.S.B.); (L.A.L.); (E.G.I.); (D.V.S.); (A.N.S.); (E.I.K.); (S.N.M.); (D.Y.L.); (Y.V.R.); (N.A.S.); (M.A.P.)
| | - Elizaveta G. Iazeva
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.G.P.); (I.S.B.); (L.A.L.); (E.G.I.); (D.V.S.); (A.N.S.); (E.I.K.); (S.N.M.); (D.Y.L.); (Y.V.R.); (N.A.S.); (M.A.P.)
| | - Dmitry V. Sergeev
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.G.P.); (I.S.B.); (L.A.L.); (E.G.I.); (D.V.S.); (A.N.S.); (E.I.K.); (S.N.M.); (D.Y.L.); (Y.V.R.); (N.A.S.); (M.A.P.)
| | - Anastasia N. Sergeeva
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.G.P.); (I.S.B.); (L.A.L.); (E.G.I.); (D.V.S.); (A.N.S.); (E.I.K.); (S.N.M.); (D.Y.L.); (Y.V.R.); (N.A.S.); (M.A.P.)
| | - Elena I. Kremneva
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.G.P.); (I.S.B.); (L.A.L.); (E.G.I.); (D.V.S.); (A.N.S.); (E.I.K.); (S.N.M.); (D.Y.L.); (Y.V.R.); (N.A.S.); (M.A.P.)
| | - Sofya N. Morozova
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.G.P.); (I.S.B.); (L.A.L.); (E.G.I.); (D.V.S.); (A.N.S.); (E.I.K.); (S.N.M.); (D.Y.L.); (Y.V.R.); (N.A.S.); (M.A.P.)
| | - Dmitry Yu. Lagoda
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.G.P.); (I.S.B.); (L.A.L.); (E.G.I.); (D.V.S.); (A.N.S.); (E.I.K.); (S.N.M.); (D.Y.L.); (Y.V.R.); (N.A.S.); (M.A.P.)
| | - Silvia Casarotto
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, 20157 Milan, Italy;
| | | | - Yulia V. Ryabinkina
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.G.P.); (I.S.B.); (L.A.L.); (E.G.I.); (D.V.S.); (A.N.S.); (E.I.K.); (S.N.M.); (D.Y.L.); (Y.V.R.); (N.A.S.); (M.A.P.)
| | - Natalia A. Suponeva
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.G.P.); (I.S.B.); (L.A.L.); (E.G.I.); (D.V.S.); (A.N.S.); (E.I.K.); (S.N.M.); (D.Y.L.); (Y.V.R.); (N.A.S.); (M.A.P.)
| | - Michael A. Piradov
- Research Center of Neurology, Volokolamskoe Shosse, 80, Moscow 125367, Russia; (A.G.P.); (I.S.B.); (L.A.L.); (E.G.I.); (D.V.S.); (A.N.S.); (E.I.K.); (S.N.M.); (D.Y.L.); (Y.V.R.); (N.A.S.); (M.A.P.)
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Kremneva EI, Legostaeva LA, Morozova SN, Sergeev DV, Sinitsyn DO, Iazeva EG, Suslin AS, Suponeva NA, Krotenkova MV, Piradov MA, Maximov II. Feasibility of Non-Gaussian Diffusion Metrics in Chronic Disorders of Consciousness. Brain Sci 2019; 9:brainsci9050123. [PMID: 31137909 PMCID: PMC6562474 DOI: 10.3390/brainsci9050123] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 05/23/2019] [Accepted: 05/23/2019] [Indexed: 01/06/2023] Open
Abstract
Diagnostic accuracy of different chronic disorders of consciousness (DOC) can be affected by the false negative errors in up to 40% cases. In the present study, we aimed to investigate the feasibility of a non-Gaussian diffusion approach in chronic DOC and to estimate a sensitivity of diffusion kurtosis imaging (DKI) metrics for the differentiation of vegetative state/unresponsive wakefulness syndrome (VS/UWS) and minimally conscious state (MCS) from a healthy brain state. We acquired diffusion MRI data from 18 patients in chronic DOC (11 VS/UWS, 7 MCS) and 14 healthy controls. A quantitative comparison of the diffusion metrics for grey (GM) and white (WM) matter between the controls and patient group showed a significant (p < 0.05) difference in supratentorial WM and GM for all evaluated diffusion metrics, as well as for brainstem, corpus callosum, and thalamus. An intra-subject VS/UWS and MCS group comparison showed only kurtosis metrics and fractional anisotropy differences using tract-based spatial statistics, owing mainly to macrostructural differences on most severely lesioned hemispheres. As a result, we demonstrated an ability of DKI metrics to localise and detect changes in both WM and GM and showed their capability in order to distinguish patients with a different level of consciousness.
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Affiliation(s)
- Elena I Kremneva
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | | | - Sofya N Morozova
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Dmitry V Sergeev
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Dmitry O Sinitsyn
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Elizaveta G Iazeva
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Aleksandr S Suslin
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Natalia A Suponeva
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Marina V Krotenkova
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Michael A Piradov
- Research Center of Neurology, 80 Volokolamskoe shosse, 125367 Moscow, Russia.
| | - Ivan I Maximov
- Department of Psychology, University of Oslo, Forskningsveien 3A, 0373 Oslo, Norway.
- Norwegian Centre for Mental Disorders Research (NORMENT), Norway and Institute of Clinical Medicine, University of Oslo, Oslo Universitetssykehus Bygg 48 Ullevål, 0317 Oslo, Norway.
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Dobrynina LA, Gadzhieva ZS, Morozova SN, Kremneva EI, Krotenkova MV, Kashina EM, Poddubskaya AA. [Executive functions: fMRI of healthy volunteers during Stroop test and the serial count test]. Zh Nevrol Psikhiatr Im S S Korsakova 2018; 118:64-71. [PMID: 30585607 DOI: 10.17116/jnevro201811811164] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
AIM To assess executive function in healthy adults using fMRI. MATERIAL AND METHODS An analysis of fMRI activation and functional connectivity during a serial count task (as a shifting function test) and color-word Stroop test (classical inhibition function test) was made for 12 healthy adults. RESULTS AND CONCLUSION The executive control network and salience network activation was comparable in both tasks. Nevertheless, there were differences between two tests in functional connectivity of the dorsolateral prefrontal cortex (DLPFC) and the supplementary motor area (SMA) with other brain regions, that can be explained by the differences in the regulatory mechanisms of task performance. Stroop test assumes its automatic performance, and control of program realization is performed mainly by executive-control network. The connectivity between the two DLPFCs with the lower parietal lobules and with each other and inhibition by SMA connectivity with only the right hemisphere regions support this notion. Serial count task excludes the process of monotonous learning, that was confirmed by widespread SMA connections in the absence of connectivity of the DLPFC with executive control network regions. This connectivity pattern allows assuming the leading role of SMA in certain brain regions choice and switching their activity for providing attention and executive control of cognitive operations shift during task performance. These findings allow us to consider the serial count task as the relevant fMRI test for executive functions with the special focus on set shifting, also in patients with executive function deficits. Furthermore, SMA region mapping with the serial count test paradigm could be considered as a potential target for navigated transcranial magnetic stimulation (nTMS) in these patients.
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Affiliation(s)
| | | | | | | | | | - E M Kashina
- Research Center of Neurology, Moscow, Russia
| | - A A Poddubskaya
- Research Center of Neurology, Moscow, Russia; Treatment and Rehabilitation Center, Moscow, Russia
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Sinitsyn DO, Legostaeva LA, Kremneva EI, Morozova SN, Poydasheva AG, Mochalova EG, Chervyakova OG, Ryabinkina JV, Suponeva NA, Piradov MA. Degrees of functional connectome abnormality in disorders of consciousness. Hum Brain Mapp 2018; 39:2929-2940. [PMID: 29575425 DOI: 10.1002/hbm.24050] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Revised: 03/06/2018] [Accepted: 03/08/2018] [Indexed: 12/26/2022] Open
Abstract
Understanding the neuronal basis of disorders of consciousness can help improve the accuracy of their diagnosis, indicate potential targets for therapeutic interventions, and provide insights into the organization of normal conscious information processing. Measurements of brain activity have been used to find associations of the levels of consciousness with brain complexity, topological features of functional connectomes, and disruption of resting-state networks. However, obtainment of a detailed picture of activity patterns underlying the vegetative state/unresponsive wakefulness syndrome and the minimally conscious state remains a work in progress. We here aimed at finding the aspects of fMRI-based functional connectivity that differentiate these states from each other and from the normal condition. A group of 22 patients was studied (9 minimally conscious state and 13 vegetative state/unresponsive wakefulness syndrome). Patients were shown to have reduced connectivity in most resting-state networks and disrupted patterns of relative connection strengths as compared to healthy subjects. Differences between the unresponsive wakefulness syndrome and the minimally conscious state were found in the patterns formed by a relatively small number of strongest positive correlations selected by thresholding. These differences were captured by measures of functional connectivity disruption that integrate area-specific abnormalities over the whole brain. The results suggest that the strong positive correlations between the functional activities of specific brain areas observed in healthy individuals may be critical for consciousness and be an important target of disruption in disorders of consciousness.
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Affiliation(s)
- Dmitry O Sinitsyn
- Research Center of Neurology, 80 Volokolamskoe shosse, Moscow, 125367, Russia
| | | | - Elena I Kremneva
- Research Center of Neurology, 80 Volokolamskoe shosse, Moscow, 125367, Russia
| | - Sofya N Morozova
- Research Center of Neurology, 80 Volokolamskoe shosse, Moscow, 125367, Russia
| | | | | | | | - Julia V Ryabinkina
- Research Center of Neurology, 80 Volokolamskoe shosse, Moscow, 125367, Russia
| | - Natalia A Suponeva
- Research Center of Neurology, 80 Volokolamskoe shosse, Moscow, 125367, Russia
| | - Michael A Piradov
- Research Center of Neurology, 80 Volokolamskoe shosse, Moscow, 125367, Russia
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Bryukhov VV, Krotenkova IA, Morozova SN, Krotenkova MV. [A current view on the MRI diagnosis of multiple sclerosis: an update of 2016 revised MRI criteria]. Zh Nevrol Psikhiatr Im S S Korsakova 2017; 117:66-73. [PMID: 28617364 DOI: 10.17116/jnevro20171172266-73] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Magnetic resonance imaging (MRI) is the primary method for confirming the clinical diagnosis of multiple sclerosis (MS). The article presents the current data on using MRI of the brain and spinal cord for diagnosis in suspected MS. Special attention is paid to the MRI criteria of McDonald and MAGNIMS for relapsing-remitting MS (RRMS) and primary-progressive MS (PPMS) in the latest revisions of 2010 and 2016. The information provided can help radiologists and neurologists to optimize the use of MRI in clinical practice for diagnosis of MS.
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Abstract
The use of magnetic resonance imaging (MRI) in patients with multiple sclerosis has markedly increased in recent years. The main task of the MRI studies after the diagnosis of multiple sclerosis is to assess the dynamics of MRI for determining disease progression and monitoring the efficacy of therapy. In this regard, it is very important to obtain the most identical baseline and follow-up MRI that is possible when a single standard protocol is used. This article presents the protocol of brain MRI and spinal cord MRI and interpretation of MRI studies in patients with multiple sclerosis.
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Morozova SN, Bryukhov VV, Trifonova OV, Kremneva EI, Krotenkova MV. [A DTI study of the spinal cord lesion in patients with multiple sclerosis during the follow-up after relapse]. Zh Nevrol Psikhiatr Im S S Korsakova 2016; 116:21-26. [PMID: 27070357 DOI: 10.17116/jnevro20161162221-26] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
UNLABELLED Spinal cord involvement is frequent in multiple sclerosis (MS) but the correlation between spinal cord damage on conventional MRI and clinical symptoms is not always obvious. Diffusion tensor imaging (DTI) is a sensitive technique for revealing tissue damage. OBJECTIVE to investigate spinal cord DTI changes in MS patients during the relapse and in the follow-up. MATERIAL AND METHODS Data were acquired from 25 patients with relapsing-remitting MS during the relapse characterized by unilateral light hand palsy, in three and twelve months after it. All patients underwent full neurological examination and MRI including conventional head and neck MRI and DTI of the brain and upper spinal cord in the sagittal plane. Twelve healthy subjects entered the control group. RESULTS AND CONCLUSION Spinal cord sagittal DTI provides a reliable information about significant changes in MS patients compared tothe control group both inside demyelinating lesions and in the normal appearing spinal cord. These differences are preserved both in 3 and 12 months after the relapse and together with clinical recovery create evidence of functional compensatory mechanisms development. A tendency towards DTI parameters normalization together with faster fine motor skills recovery in patients without the asymmetrical decrease in vibration sense shows an important role that afferentation plays in recovery after the relapse.
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Saenko IV, Morozova SN, Zmeykina EA, Konovalov RN, Chervyakov AV, Poydasheva AG, Chernikova LA, Suponeva NA, Piradov MA, Kozlovskaya IB. [Changes in the Functional Connectivity of Motor Zones in the Use of Multimodal Exoskeleton Complex "Regent" in the Neurorehabilitation of Post-Stroke Patients]. Fiziol Cheloveka 2016; 42:64-72. [PMID: 27188148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
The article discusses the effect of a course of treatment with the use of multimodal complex exoskeleton (MCE) "Regent" on the reorganization of cortical locomotor zones in 14 patients with post-stroke hemiparesis, mainly atthe chronic stage of the disease. Before the course of treatment, we identified specific areas of activation in the primary sensorimotor and supplementary motor areas and the inferior parietal lobules in both affected and healthy hemispheres by means of functional MRI (fMRI) with the use of special passive sensorimotor paradigms. After the course of treatment with MCE, we observed an improvement of temporal characteristics of walking; it was accompanied by a decrease in the activation zones of inferior parietal lobules, especially in the healthy hemisphere, and by a significant increase in the activation zone of primary sensorimotor and supplementary motor areas. The analysis of the functional connectivity of studied zones before and after the course of treatment with MCE showed significant changes in intra- and interhemispheric interactions.
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Krotenkova MV, Morozova SN, Briukhov VV, Zavalishin IA, Peresedova AV. [Criteria of withdrawal of first-line DMT and substitution for second-line drugs (treatment escalation) basing on MRI results]. Zh Nevrol Psikhiatr Im S S Korsakova 2015; 115:79-80. [PMID: 26081343 DOI: 10.17116/jnevro20151152279-80] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
- M V Krotenkova
- Research Center of Neurology, Russian Academy of Sciences, Moscow
| | - S N Morozova
- Research Center of Neurology, Russian Academy of Sciences, Moscow
| | - V V Briukhov
- Research Center of Neurology, Russian Academy of Sciences, Moscow
| | - I A Zavalishin
- Research Center of Neurology, Russian Academy of Sciences, Moscow
| | - A V Peresedova
- Research Center of Neurology, Russian Academy of Sciences, Moscow
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