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Introduction: We examined how abnormal prefrontal neurophysiology and changes in gamma-aminobutyric acid-ergic (GABAergic) neurotransmission contribute to behavioral impairments in disorders associated with frontotemporal lobar degeneration (FTLD).
Methods: We recorded magnetoencephalography during an adaptive visuomotor task from 11 people with behavioral-variant frontotemporal dementia, 11 with progressive supranuclear palsy, and 20 age-matched controls. We used tiagabine, a gamma-aminobutyric acid (GABA) re-uptake inhibitor, as a pharmacological probe to assess the role of GABA during motor-related beta power changes.
Results: Task impairments were associated with diminished movement-related beta power. Tiagabine facilitated partial recovery of behavioral impairments and neurophysiology, moderated by executive function, such that the greatest improvements were seen in those with higher cognitive scores. The right prefrontal cortex was revealed as a key site of drug interaction.
Discussion: Behavioral and neurophysiological deficits can be mitigated by enhancement of GABAergic neurotransmission. Clinical trials are warranted to test for enduring clinical benefits from this restorative-psychopharmacology strategy.
Highlights: Event-related beta power changes during movement can be altered by the GABA reuptake inhibitor, tiagabine. In people with behavioral-variant frontotemporal dementia and progressive supranuclear palsy, tiagabine enhanced beta modulation and concurrently improved task performance, dependent on baseline cognition, and diagnosis. The effects of the drug suggest a GABA-dependent beta-related mechanism that underlies adaptive motor control. Restoring selective deficits in neurotransmission is a potential means to improve behavioral symptoms in patients with dementia.
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http://dx.doi.org/10.1002/alz.14531 | DOI Listing |
Liver Int
October 2025
Division of Gastroenterology and Hepatology, Department of Medicine, The Institute for Bioelectronic Medicine, Feinstein Institutes for Medical Research & Cold Spring Harbor Laboratory, Northwell Health, Manhasset, New York, USA.
Background: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths, primarily due to late-stage diagnosis. In this multicenter study, our goal is to identify functional biomarkers that stratify the risk of HCC in patients with cirrhosis (CP) for early diagnosis.
Methods: Five thousand and eight serum proteins (Somascan) were analysed in Cohort A (477 CP, including 125 HCC).
Front Neurol
August 2025
The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Background: After stroke, upper limb dysfunction seriously affects patients' quality of life. The uncertain prognosis of patients poses a challenge for therapists in developing personalized rehabilitation programs. Electroencephalograph (EEG) power spectrum changes during rehabilitation training may have a predictive effect on the improvement of upper limb movement.
View Article and Find Full Text PDFSleep Adv
June 2025
Sleep and Performance Research Center, Washington State University, Spokane, WA, United States.
Study Objectives: There are large individual differences in the homeostatic response to sleep deprivation, as reflected in slow wave sleep (SWS) and electroencephalogram (EEG) spectral power, which have largely been left unexplained. Recent evidence suggests the possible involvement of the activity-regulated cytoskeleton-associated protein () gene. Here we assessed the effects of the "c.
View Article and Find Full Text PDFCNS Neurosci Ther
September 2025
School of Information and Communication Engineering, North University of China, Taiyuan, China.
Aims: Decoding the motor intention by electroencephalography to control external devices is an effective method of helping spinal cord injury (SCI) patients to regain motor function. Still, SCI patients have much lower accuracy in the decoding of motor intentions compared to healthy individuals, which severely hampers the clinical application. However, the underlying neural mechanisms are still unknown.
View Article and Find Full Text PDFInt Dent J
September 2025
Department of Periodontology, Oral Medicine and Oral Surgery, Institute for Dental and Craniofacial Sciences, Charité-University Medicine Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany; Department of Conservati
Introduction And Aims: Artificial intelligence (AI) is transforming dental care by enhancing diagnostic accuracy, efficiency, and patient experience. This study aimed to assess dental patients' acceptance, perceptions, and concerns regarding AI-powered diagnosis using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework through structural equation modelling (SEM).
Methods: A cross-sectional study was conducted among dental patients at King Saud University Dental Hospital, Riyadh.