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Objectives: The importance and popularity of peripheral nerve block procedures have increased in the treatment of migraine. Greater occipital nerve (GON) block is a commonly used peripheral nerve block method, and there are numerous researches on its use in migraine treatment.
Materials And Methods: A search of PubMed for English-language randomized controlled trials (RCT) and open studies on greater occipital nerve block between 1995 and 2018 was performed using greater occipital nerve, headache, and migraine as keywords.
Results: In total, 242 potentially relevant PubMed studies were found. A sum of 228 of them which were non-English articles and reviews, case reports, letters and meta-analyses were excluded. The remaining articles were reviewed, and 14 clinical trials, seven of which were randomized-controlled on greater occipital nerve block in migraine patients, were identified and reviewed.
Conclusions: Although clinicians commonly use greater occipital nerve block in migraine patients, the procedure has yet to be standardized. The present study reviewed the techniques, drugs and dosages, the frequency of administration, side effects, and efficacy of greater occipital nerve block in migraine patients.
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http://dx.doi.org/10.1177/0333102418821669 | DOI Listing |
Cereb Cortex
August 2025
Section of Brain Function Information, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi 444-8585, Japan.
This study aimed to identify brain activity modulations associated with different types of visual tracking using advanced functional magnetic resonance imaging techniques developed by the Human Connectome Project (HCP) consortium. Magnetic resonance imaging data were collected from 27 healthy volunteers using a 3-T scanner. During a single run, participants either fixated on a stationary visual target (fixation block) or tracked a smoothly moving or jumping target (smooth or saccadic tracking blocks), alternating across blocks.
View Article and Find Full Text PDFBrain Behav
September 2025
Radiology Department, Yantaishan Hospital, Yantai, Shandong, China.
Objective: To investigate the characteristics of brain structures in patients with noise-induced hearing loss (NIHL) using source-based morphometry (SBM) and to evaluate the correlation between abnormal brain regions and clinical data.
Methods: High-resolution 3D T1 structural images were acquired from 81 patients with NIHL and 74 age- and education level-matched healthy controls (HCs). The clinical data of all subjects were collected, including noise exposure time, monaural hearing threshold weighted values (MTWVs), Mini-Mental State Examination (MMSE), and Hamilton Anxiety Scale (HAMA) scores.
Front Sports Act Living
August 2025
Faculty of Physical Education, China West Normal University, Nanchong, China.
Understanding how athletes mentally simulate and anticipate actions provides key insights into experience-driven brain plasticity. While previous studies have investigated motor imagery and action anticipation separately, little is known about how their underlying neural mechanisms converge or diverge in expert performers. This study conducted a meta-analysis using activation likelihood estimation (ALE) and meta-analytic connectivity modeling (MACM) to compare brain activation patterns between athletes and non-athletes across both tasks.
View Article and Find Full Text PDFEpilepsy Behav
September 2025
Department of Neurology, Yale University, 333 Cedar Street, New Haven, CT 06520, United States. Electronic address:
Temporal lobe epilepsy (TLE) is frequently associated with language impairment. This meta-analysis quantitatively synthesized data from 12 functional neuroimaging studies, including 390 TLE patients and 356 healthy controls (age range: 8.1-70 years; 57.
View Article and Find Full Text PDFSignificant changes occur in brain structure and cognitive abilities during adolescence. Investigating their association can provide insight into brain-based cognitive development, yet previous studies were limited by narrow brain measures, small samples, and lacking focus on age-related variation. Here, we analyzed a large cohort (N = 8,534, age 9-15) from the Adolescent Brain Cognitive Development dataset.
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