The effect of deep brain stimulation in Parkinson's disease reflected in EEG microstates
Status PubMed-not-MEDLINE Jazyk angličtina Země Spojené státy americké Médium electronic
Typ dokumentu časopisecké články
Grantová podpora
NU21-04-00445
Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
NU21-04-00445
Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
NU21-04-00445
Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
NU21-04-00445
Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
NU21-04-00445
Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
NU21-04-00445
Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
LM2018129
Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
LM2018129
Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
LM2018129
Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
LM2018129
Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
LM2018129
Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
LM2018129
Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
PubMed
37069159
PubMed Central
PMC10110608
DOI
10.1038/s41531-023-00508-x
PII: 10.1038/s41531-023-00508-x
Knihovny.cz E-zdroje
- Publikační typ
- časopisecké články MeSH
Mechanisms of deep brain stimulation (DBS) on cortical networks were explored mainly by fMRI. Advanced analysis of high-density EEG is a source of additional information and may provide clinically useful biomarkers. The presented study evaluates EEG microstates in Parkinson's disease and the effect of DBS of the subthalamic nucleus (STN). The association between revealed spatiotemporal dynamics of brain networks and changes in oscillatory activity and clinical examination were assessed. Thirty-seven patients with Parkinson's disease treated by STN-DBS underwent two sessions (OFF and ON stimulation conditions) of resting-state EEG. EEG microstates were analyzed in patient recordings and in a matched healthy control dataset. Microstate parameters were then compared across groups and were correlated with clinical and neuropsychological scores. Of the five revealed microstates, two differed between Parkinson's disease patients and healthy controls. Another microstate differed between ON and OFF stimulation conditions in the patient group and restored parameters in the ON stimulation state toward to healthy values. The mean beta power of that microstate was the highest in patients during the OFF stimulation condition and the lowest in healthy controls; sources were localized mainly in the supplementary motor area. Changes in microstate parameters correlated with UPDRS and neuropsychological scores. Disease specific alterations in the spatiotemporal dynamics of large-scale brain networks can be described by EEG microstates. The approach can reveal changes reflecting the effect of DBS on PD motor symptoms as well as changes probably related to non-motor symptoms not influenced by DBS.
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Lozano AM, et al. Deep brain stimulation: current challenges and future directions. Nat. Rev. Neurol. 2019;15:148–160. doi: 10.1038/s41582-018-0128-2. PubMed DOI PMC
Habets JGV, et al. An update on adaptive deep brain stimulation in Parkinson’s disease. Mov. Disord. 2018;33:1834–1843. doi: 10.1002/mds.115. PubMed DOI PMC
Halje P, et al. Oscillations in cortico-basal ganglia circuits: implications for Parkinson’s disease and other neurologic and psychiatric conditions. J. Neurophysiol. 2019;122:203–231. doi: 10.1152/jn.00590.2018. PubMed DOI
Horn A, et al. Connectivity Predicts deep brain stimulation outcome in Parkinson disease. Ann. Neurol. 2017;82:67–78. doi: 10.1002/ana.24974. PubMed DOI PMC
Horn A, et al. Deep brain stimulation induced normalization of the human functional connectome in Parkinson’s disease. Brain. 2019;142:3129–3143. doi: 10.1093/brain/awz239. PubMed DOI
Kahan J, et al. Resting state functional MRI in Parkinson’s disease: the impact of deep brain stimulation on ‘effective’ connectivity. Brain. 2014;137:1130–1144. doi: 10.1093/brain/awu027. PubMed DOI PMC
Jech, R. & Mueller, K. Investigating network effects of DBS with fMRI. In Connectomic Deep Brain Stimulation 275–301 (Elsevier, 2022). 10.1016/B978-0-12-821861-7.00026-9.
Younce JR, et al. Resting‐State Functional Connectivity Predicts STN DBS Clinical Response. Mov. Disord. 2021;36:662–671. doi: 10.1002/mds.28376. PubMed DOI PMC
Shen L, et al. Subthalamic Nucleus Deep Brain Stimulation Modulates 2 Distinct Neurocircuits. Ann. Neurol. 2020;88:1178–1193. doi: 10.1002/ana.25906. PubMed DOI PMC
Michel, C. M., Koenig, T. & Brandeis, D. Electrical Neuroimaging. Electrical Neuroimaging (Cambridge University Press, 2009). 10.1017/CBO9780511596889
Giannicola G, et al. The effects of levodopa and ongoing deep brain stimulation on subthalamic beta oscillations in Parkinson’s disease. Exp. Neurol. 2010;226:120–127. doi: 10.1016/j.expneurol.2010.08.011. PubMed DOI
Bočková M, et al. Suboptimal response to STN-DBS in Parkinson’s disease can be identified via reaction times in a motor cognitive paradigm. J. Neural Transm. 2020;127:1579–1588. doi: 10.1007/s00702-020-02254-3. PubMed DOI
Hirschmann J, et al. A direct relationship between oscillatory subthalamic nucleus–cortex coupling and rest tremor in Parkinson’s disease. Brain. 2013;136:3659–3670. doi: 10.1093/brain/awt271. PubMed DOI
Bočková M, et al. Cortical network organization reflects clinical response to subthalamic nucleus deep brain stimulation in Parkinson’s disease. Hum. Brain Mapp. 2021;42:5626–5635. doi: 10.1002/hbm.25642. PubMed DOI PMC
Michel CM, Koenig T. EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review. Neuroimage. 2018;180:577–593. doi: 10.1016/j.neuroimage.2017.11.062. PubMed DOI
Khanna A, Pascual-Leone A, Michel CM, Farzan F. Microstates in resting-state EEG: Current status and future directions. Neurosci. Biobehav. Rev. 2015;49:105–113. doi: 10.1016/j.neubiorev.2014.12.010. PubMed DOI PMC
Bréchet L, et al. Capturing the spatiotemporal dynamics of self-generated, task-initiated thoughts with EEG and fMRI. Neuroimage. 2019;194:82–92. doi: 10.1016/j.neuroimage.2019.03.029. PubMed DOI
Britz J, Van De Ville D, Michel CM. BOLD correlates of EEG topography reveal rapid resting-state network dynamics. Neuroimage. 2010;52:1162–1170. doi: 10.1016/j.neuroimage.2010.02.052. PubMed DOI
Rajkumar, R. et al. Comparison of EEG microstates with resting state fMRI and FDG-PET measures in the default mode network via simultaneously recorded trimodal (PET/MR/EEG) data. Hum. Brain Mapp. 1–12 (2018). 10.1002/hbm.24429 PubMed PMC
Custo A, et al. Electroencephalographic Resting-State Networks: Source Localization of Microstates. Brain Connect. 2017;7:671–682. doi: 10.1089/brain.2016.0476. PubMed DOI PMC
Lamoš M, Morávková I, Ondráček D, Bočková M, Rektorová I. Altered Spatiotemporal Dynamics of the Resting Brain in Mild Cognitive Impairment with Lewy Bodies. Mov. Disord. 2021;36:2435–2440. doi: 10.1002/mds.28741. PubMed DOI
Nishida K, et al. EEG microstates associated with salience and frontoparietal networks in frontotemporal dementia, schizophrenia and Alzheimer’s disease. Clin. Neurophysiol. 2013;124:1106–1114. doi: 10.1016/j.clinph.2013.01.005. PubMed DOI
Pal A, Behari M, Goyal V, Sharma R. Study of EEG microstates in Parkinson’s disease: a potential biomarker? Cogn. Neurodyn. 2021;15:463–471. doi: 10.1007/s11571-020-09643-0. PubMed DOI PMC
Schumacher J, et al. Dysfunctional brain dynamics and their origin in Lewy body dementia. Brain. 2019;142:1767–1782. doi: 10.1093/brain/awz069. PubMed DOI PMC
Sverak T, Albrechtova L, Lamos M, Rektorova I, Ustohal L. Intensive repetitive transcranial magnetic stimulation changes EEG microstates in schizophrenia: A pilot study. Schizophr. Res. 2018;193:451–452. doi: 10.1016/j.schres.2017.06.044. PubMed DOI
Koenig T, et al. A deviant EEG brain microstate in acute, neuroleptic-naive schizophrenics at rest. Eur. Arch. Psychiatry Clin. Neurosci. 1999;249:205–211. doi: 10.1007/s004060050088. PubMed DOI
Chu C, et al. Spatiotemporal EEG microstate analysis in drug-free patients with Parkinson’s disease. NeuroImage Clin. 2020;25:102132. doi: 10.1016/j.nicl.2019.102132. PubMed DOI PMC
Serrano JI, et al. EEG Microstates Change in Response to Increase in Dopaminergic Stimulation in Typical Parkinson’s Disease Patients. Front. Neurosci. 2018;12:1–9. doi: 10.3389/fnins.2018.00714. PubMed DOI PMC
Li Z, et al. Dysfunctional Brain Dynamics of Parkinson’s Disease and the Effect of Acute Deep Brain Stimulation. Front. Neurosci. 2021;15:1–11. PubMed PMC
Kühn AA, Kupsch A, Schneider G-H, Brown P. Reduction in subthalamic 8-35 Hz oscillatory activity correlates with clinical improvement in Parkinson’s disease. Eur. J. Neurosci. 2006;23:1956–1960. doi: 10.1111/j.1460-9568.2006.04717.x. PubMed DOI
Brown, P. Bad oscillations in Parkinson’s disease. In Parkinson’s Disease and Related Disorders 27–30 (Springer Vienna, 2006). 10.1007/978-3-211-45295-0_6. PubMed
Cagnan H, Denison T, McIntyre C, Brown P. Emerging technologies for improved deep brain stimulation. Nat. Biotechnol. 2019;37:1024–1033. doi: 10.1038/s41587-019-0244-6. PubMed DOI PMC
Bočková M, Rektor I. Electrophysiological biomarkers for deep brain stimulation outcomes in movement disorders: state of the art and future challenges. J. Neural Transm. 2021;128:1169–1175. doi: 10.1007/s00702-021-02381-5. PubMed DOI
Telkes I, et al. Local field potentials of subthalamic nucleus contain electrophysiological footprints of motor subtypes of Parkinson’s disease. Proc. Natl Acad. Sci. U. S. A. 2018;115:E8567–E8576. doi: 10.1073/pnas.1810589115. PubMed DOI PMC
Bouthour W, et al. Biomarkers for closed-loop deep brain stimulation in Parkinson disease and beyond. Nat. Rev. Neurol. 2019;15:343–352. doi: 10.1038/s41582-019-0166-4. PubMed DOI
Little S, et al. Adaptive deep brain stimulation in advanced Parkinson disease. Ann. Neurol. 2013;74:449–457. doi: 10.1002/ana.23951. PubMed DOI PMC
Little S, et al. Bilateral adaptive deep brain stimulation is effective in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry. 2016;87:717–721. doi: 10.1136/jnnp-2015-310972. PubMed DOI PMC
Rosa M, et al. Adaptive deep brain stimulation in a freely moving parkinsonian patient. Mov. Disord. 2015;30:1003–1005. doi: 10.1002/mds.26241. PubMed DOI PMC
Bočková M, Rektor I. Impairment of brain functions in Parkinson’s disease reflected by alterations in neural connectivity in EEG studies: A viewpoint. Clin. Neurophysiol. 2019;130:239–247. doi: 10.1016/j.clinph.2018.11.013. PubMed DOI
Geraedts VJ, et al. Preoperative Electroencephalography-Based Machine Learning Predicts Cognitive Deterioration After Subthalamic Deep Brain Stimulation. Mov. Disord. 2021;36:2324–2334. doi: 10.1002/mds.28661. PubMed DOI PMC
Bréchet L, Brunet D, Perogamvros L, Tononi G, Michel CM. EEG microstates of dreams. Sci. Rep. 2020;10:17069. doi: 10.1038/s41598-020-74075-z. PubMed DOI PMC
Oswal A, et al. Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson’s disease. Brain. 2016;139:1482–1496. doi: 10.1093/brain/aww048. PubMed DOI PMC
Kikuchi M, et al. Native EEG and treatment effects in neuroleptic-naïve schizophrenic patients: Time and frequency domain approaches. Schizophr. Res. 2007;97:163–172. doi: 10.1016/j.schres.2007.07.012. PubMed DOI
Aron AR, Behrens TE, Smith S, Frank MJ, Poldrack RA. Triangulating a Cognitive Control Network Using Diffusion-Weighted Magnetic Resonance Imaging (MRI) and Functional MRI. J. Neurosci. 2007;27:3743–3752. doi: 10.1523/JNEUROSCI.0519-07.2007. PubMed DOI PMC
Litvak V, et al. Resting oscillatory cortico-subthalamic connectivity in patients with Parkinson’s disease. Brain. 2011;134:359–374. doi: 10.1093/brain/awq332. PubMed DOI
Brown P. Oscillatory nature of human basal ganglia activity: Relationship to the pathophysiology of Parkinson’s disease. Mov. Disord. 2003;18:357–363. doi: 10.1002/mds.10358. PubMed DOI
Eusebio A, et al. Deep brain stimulation can suppress pathological synchronisation in parkinsonian patients. J. Neurol. Neurosurg. Psychiatry. 2011;82:569–573. doi: 10.1136/jnnp.2010.217489. PubMed DOI PMC
Whitmer D, et al. High frequency deep brain stimulation attenuates subthalamic and cortical rhythms in Parkinson’s disease. Front. Hum. Neurosci. 2012;6:1–18. doi: 10.3389/fnhum.2012.00155. PubMed DOI PMC
Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods. 2004;134:9–21. doi: 10.1016/j.jneumeth.2003.10.009. PubMed DOI
Brunet D, Murray MM, Michel CM. Spatiotemporal analysis of multichannel EEG: CARTOOL. Comput. Intell. Neurosci. 2011;2011:813870. doi: 10.1155/2011/813870. PubMed DOI PMC
Michel CM, Brunet D. EEG Source Imaging: A Practical Review of the Analysis Steps. Front. Neurol. 2019;10:1–18. doi: 10.3389/fneur.2019.00325. PubMed DOI PMC
Seeber M, et al. Subcortical electrophysiological activity is detectable with high-density EEG source imaging. Nat. Commun. 2019;10:753. doi: 10.1038/s41467-019-08725-w. PubMed DOI PMC