The ability to regulate one's mood state effectively is critical to emotional and physical health. Recent investigations have sought to delineate the neural mechanisms by which individuals regulate mood states and emotions, positing a critical role of a dorsal system that includes the dorsolateral prefrontal cortex and anterior cingulate. This study extended these efforts by examining the neural correlates of retrieving positive autobiographical memories while experiencing a negative mood state in a sample of healthy female adults. We demonstrated that mood-incongruent recall is associated with activation in ventrolateral and ventromedial prefrontal cortices (including orbitofrontal cortex and subgenual cingulate). These findings suggest that mood-incongruent recall differs from other affect regulation strategies by influencing mood through a ventral regulatory network.
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http://dx.doi.org/10.1097/WNR.0b013e3282f16db4 | DOI Listing |
Mol Psychiatry
January 2025
Siena Brain Investigation and Neuromodulation Lab, Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy.
Ketamine, a dissociative compound, shows promise in treating mood disorders, including treatment-resistant depression (TRD) and bipolar disorder (BD). Despite its therapeutic potential, the neurophysiological mechanisms underlying ketamine's effects are not fully understood. This study explored acute neurophysiological changes induced by subanesthetic doses of ketamine in BD patients with depression using electroencephalography (EEG) biomarkers.
View Article and Find Full Text PDFJ Clin Nurs
January 2025
School of Nursing, Jinan University, Guangzhou, Guangdong, China.
Aim: To develop a deep learning-based smart assessment model for pressure injury surface.
Design: Exploratory analysis study.
Methods: Pressure injury images from four Guangzhou hospitals were labelled and used to train a neural network model.
J Phys Chem B
January 2025
Single Molecule Analysis Group, Department of Chemistry, The University of Michigan, Ann Arbor, Michigan 48109, United States.
Single-molecule fluorescence resonance energy transfer (smFRET) has emerged as a pivotal technique for probing biomolecular dynamics over time at nanometer scales. Quantitative analyses of smFRET time traces remain challenging due to confounding factors such as low signal-to-noise ratios, photophysical effects such as bleaching and blinking, and the complexity of modeling the underlying biomolecular states and kinetics. The dynamic distance information shaping the smFRET trace powerfully uncovers even transient conformational changes in single biomolecules both at or far from equilibrium, relying on trace idealization to identify specific interconverting states.
View Article and Find Full Text PDFLangmuir
January 2025
Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, School of Energy and Power Engineering, Dalian University of Technology, Dalian 116023, P. R. China.
Interfacial tension () between CO and brine depends on chemical components in multiphase systems, intricately evolving with a change in temperature. In this study, we developed a convolutional neural network with a multibranch structure (MBCNN), which, in combination with a compiled data set containing measurement data of 1716 samples from 13 available literature sources at wide temperature and pressure ranges (273.15-473.
View Article and Find Full Text PDFNeuron
January 2025
Department of Vision & Cognition, Netherlands Institute for Neuroscience (KNAW), 1105 BA Amsterdam, the Netherlands; Department of Integrative Neurophysiology, VU University, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands; Department of Neurosurgery, Academic Medical Centre, Postbus 22660, 1100 DD Amsterdam, the Netherlands; Laboratory of Visual Brain Therapy, Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, 75012 Paris, France. Electronic address:
Visual neuroscience benefits from high-quality datasets with neuronal responses to many images. Several neuroimaging datasets have been published in recent years, but no comparable dataset with spiking activity exists. Here, we introduce the THINGS ventral stream spiking dataset (TVSD).
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