98%
921
2 minutes
20
Ketamine produces antidepressant effects in patients with treatment-resistant depression, but its usefulness is limited by its psychotropic side effects. Ketamine is thought to act via NMDA receptors and HCN1 channels to produce brain oscillations that are related to these effects. Using human intracranial recordings, we found that ketamine produces gamma oscillations in prefrontal cortex and hippocampus, structures previously implicated in ketamine's antidepressant effects, and a 3 Hz oscillation in posteromedial cortex, previously proposed as a mechanism for its dissociative effects. We analyzed oscillatory changes after subsequent propofol administration, whose GABAergic activity antagonizes ketamine's NMDA-mediated disinhibition, alongside a shared HCN1 inhibitory effect, to identify dynamics attributable to NMDA-mediated disinhibition versus HCN1 inhibition. Our results suggest that ketamine engages different neural circuits in distinct frequency-dependent patterns of activity to produce its antidepressant and dissociative sensory effects. These insights may help guide the development of brain dynamic biomarkers and novel therapeutics for depression.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10060225 | PMC |
http://dx.doi.org/10.1038/s41467-023-37463-3 | DOI Listing |
Acta Neurochir (Wien)
September 2025
Department of Neurosurgery, Kurume University School of Medicine 67, Asahimachi Kurume City, Fukuoka, 830-0011, Japan.
We report a 64-year-old woman who developed symptomatic vasospasm on postoperative day 7 after clipping of an unruptured right middle cerebral artery (MCA) aneurysm. Imaging revealed right MCA vasospasm, which resolved with oral antiplatelets and intravenous vasodilators. She was discharged without neurological deficits.
View Article and Find Full Text PDFNeurosurg Rev
September 2025
Department of Neurosurgery, University Hospital of Ioannina, Ioannina, Greece.
Background: The aim of this review is to present the role of intraoperative flow cytometry (IFC) in the intracranial tumor surgery. This scoping review aims to summarize current evidence on the intraoperative use of IFC in patients with intracranial tumors.
Methods: A comprehensive literature search was conducted in the Medline, Cochrane and Scopus databases up to January 21, 2025.
Childs Nerv Syst
September 2025
Department of Neurosurgery, Division of Pediatric Neurosurgery, University of Alabama at Birmingham, Children's of Alabama, 1600 7TH Avenue South, Lowder 400, Birmingham, AL, 35233, USA.
Purpose: Diagnostic cerebral venograms are the gold standard for evaluating cerebral venous sinus stenosis (CVSS). Venous sinus stenting (VSS) and less commonly venous sinus angioplasty are emerging endovascular treatments in pediatric patients. This study examines the baseline intracranial venous pressures and postoperative endovascular outcomes in pediatric patients with CVSS.
View Article and Find Full Text PDFBrain Behav
September 2025
Department of neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Background: Cerebral venous thrombosis (CVT) is a stroke type that primarily affects young individuals, with various risk factors and complex mechanisms. It accounts for 0.5% to 3% of all stroke cases and can significantly impact daily activities and quality of life.
View Article and Find Full Text PDFBrain Behav
September 2025
Department of Neurosurgery, First Medical Center of the Chinese PLA General Hospital, Beijing, People's Republic of China.
Background: The gut microbiota plays a crucial role in the development of glioma. With the evolution of artificial intelligence technology, applying AI to analyze the vast amount of data from the gut microbiome indicates the potential that artificial intelligence and computational biology hold in transforming medical diagnostics and personalized medicine.
Methods: We conducted metagenomic sequencing on stool samples from 42 patients diagnosed with glioma after operation and 30 non-intracranial tumor patients and developed a Gradient Boosting Machine (GBM) machine learning model to predict the glioma patients based on the gut microbiome data.