Previous studies have established a role for N-methyl-D-aspartate receptor (NMDAR) containing the GluN2B subunit in efficient learning behavior on a variety of tasks. Recent findings have suggested that NMDAR on GABAergic interneurons may underlie the modulation of striatal function necessary to balance efficient action with cortical excitatory input. Here we investigated how loss of GluN2B-containing NMDAR on GABAergic interneurons altered corticostriatal-mediated associative learning. Mutant mice (floxed-GluN2B×Ppp1r2-Cre) were generated to produce loss of GluN2B on forebrain interneurons and phenotyped on a touchscreen-based pairwise visual learning paradigm. We found that the mutants showed normal performance during Pavlovian and instrumental pretraining, but were significantly impaired on a discrimination learning task. Detailed analysis of the microstructure of discrimination performance revealed reduced win→stay behavior in the mutants. These results further support the role of NMDAR, and GluN2B in particular, on modulation of striatal function necessary for efficient choice behavior and suggest that NMDAR on interneurons may play a critical role in associative learning.
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http://dx.doi.org/10.1097/WNR.0000000000000373 | DOI Listing |
Toxics
December 2024
Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
Methamphetamine (METH) abuse disrupts the homeostasis of neurotransmitter (NT) metabolism, contributing to a wide range of neurological and psychological disorders. However, the specific effects of METH on NT metabolism, particularly for the tryptophan (TRP) and tyrosine (TYR) metabolic pathways, remain poorly understood. In this study, serum samples from 78 METH abusers and 79 healthy controls were analyzed using Ultra-High-Performance Liquid Chromatography with Tandem Mass Spectrometry (UHPLC-MS/MS).
View Article and Find Full Text PDFChildren (Basel)
December 2024
Department of Community Health & Epidemiology, Dalhousie University, Halifax, NS B3H 1V7, Canada.
Purpose: Is machine learning (ML) superior to the traditionally used logistic regression (LR) in prediction of neurodevelopmental outcomes in preterm infants?
Objectives: To develop and internally validate a ML model to predict neurodevelopmental impairment (NDI) in very preterm infants (<31 weeks) at 36 months corrected age, using clinical predictors.
Methods: A retrospective cohort of very preterm infants (2330 weeks) born between January 2004 and December 2016 in Nova Scotia, Canada. Survivors with neurodevelopmental assessment at 36 months corrected age were included.
Nat Commun
January 2025
Biogen Inc, Cambridge, MA, USA.
Progressive supranuclear palsy (PSP) is a rare neurodegenerative disorder characterized by physical, cognitive, and behavioral impairments. The PSP Rating Scale (PSPRS) is a widely used and validated, clinical scale to monitor disease progression. Here we show the modification of PSPRS to improve clinical meaningfulness and sensitivity.
View Article and Find Full Text PDFJ Exerc Sci Fit
January 2025
Sports Medicine and Rehabilitation Center, Shanghai University of Sport, Shanghai, China.
Introduction: Alzheimer's disease (AD) involves neuroinflammation and amyloid plaque deposition, yet the role of amyloid-reactive immune response in neurodegeneration remains unclear. We investigate amyloid-reactive T cell levels in the Epidemiology of Mild Cognitive Impairment Study in Taiwan (EMCIT) and Taiwan Precision Medicine Initiative of Cognitive Impairment and Dementia (TPMIC) cohorts.
Method: Using diverse amyloid peptide formulations, we established a polyfunctionality assay for five T cell functions and compared mild cognitive impairment (MCI) patients to control subjects in both cohorts.
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