Several neurological diseases are accompanied by rhythmic oscillatory dysfunctions in various frequency ranges and disturbed cross-frequency relationships on regional, interregional, and whole brain levels. Knowledge of these disease-specific oscillopathies is important mainly in the context of deep brain stimulation (DBS) therapy. Electrophysiological biomarkers have been used as input signals for adaptive DBS (aDBS) as well as preoperative outcome predictors. As movement disorders, particularly Parkinson's disease (PD), are among the most frequent DBS indications, the current research of DBS is the most advanced in the movement disorders field. We reviewed the literature published mainly between 2010 and 2020 to identify the most important findings concerning the current evolution of electrophysiological biomarkers in DBS and to address future challenges for prospective research.
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http://dx.doi.org/10.1007/s00702-021-02381-5 | DOI Listing |
PLoS One
January 2025
Dept. of Psychiatry, Harvard Medical School, McLean Hospital, Belmont, Massachusetts, United States of America.
Opioid dependence is defined by an aversive withdrawal syndrome upon drug cessation that can motivate continued drug-taking, development of opioid use disorder, and precipitate relapse. An understudied but common opioid withdrawal symptom is disrupted sleep, reported as both insomnia and daytime sleepiness. Despite the prevalence and severity of sleep disturbances during opioid withdrawal, there is a gap in our understanding of their interactions.
View Article and Find Full Text PDFMed J Malaysia
January 2025
National University of Malaysia, Faculty of Medicine, Department of Medicine, Kuala Lumpur, Malaysia.
Introduction: Stroke is a major cause of morbidity and mortality worldwide. While electroencephalography (EEG) offers valuable data on post-stroke brain activity, qualitative EEG assessments may be misinterpreted. Therefore, we examined the potential of quantitative EEG (qEEG) to identify key band frequencies that could serve as potential electrophysiological biomarkers in stroke patients.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Second Department of Cardiology, Hippokration General Hospital, Aristotle University of Thessaloniki, 54642 Thessaloniki, Greece.
Atrial fibrosis is a hallmark of atrial cardiomyopathy and plays a pivotal role in the pathogenesis of atrial fibrillation (AF), contributing to its onset and progression. The mechanisms underlying atrial fibrosis are multifaceted, involving stretch-induced fibroblast activation, oxidative stress, inflammation, and coagulation pathways. Variations in fibrosis types-reactive and replacement fibrosis-are influenced by patient-specific factors such as age, sex, and comorbidities, complicating therapeutic approaches.
View Article and Find Full Text PDFJ Psychiatr Res
January 2025
Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry, Zürich, Lenggstrasse 31, P.O. Box 363, 8032, Zürich, Switzerland.
Repetitive transcranial magnetic stimulation (rTMS) is an established psychiatric procedure for patients suffering from treatment-resistant depression (TRD). Biomarker identification to predict rTMS outcomes may assist the clinician in optimizing treatment selection. In recent years, different electrophysiological markers, in particular electroencephalographic (EEG) markers, were shown to yield discriminative power between responders and non-responders to various TRD treatments.
View Article and Find Full Text PDFBiol Psychiatry Cogn Neurosci Neuroimaging
January 2025
School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou 511442, China; National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou 510006, China; Guangdong Province Key Laboratory of Biomedical Engineering, South China University of Technology, Guangzhou 510006, China; Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan. Electronic address:
Background: The detection of abnormal brain activity plays an important role in the early diagnosis and treatment of major depressive disorder (MDD). Recent studies have shown that the decomposition of the electroencephalography (EEG) spectrum into periodic and aperiodic components is useful for identifying the drivers of electrophysiologic abnormalities and avoiding individual differences.
Methods: This study aimed to elucidate the pathologic changes in individualized periodic and aperiodic activities and their relationships with the symptoms of MDD.
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