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Decoding Salience: A Functional Magnetic Resonance Imaging Investigation of Reward and Contextual Unexpectedness in Memory Encoding and Retrieval.
Hum Brain Mapp
January 2025
Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University, Magdeburg, Germany.
The present study investigated the neuromodulatory substrates of salience processing and its impact on memory encoding and behaviour, with a specific focus on two distinct types of salience: reward and contextual unexpectedness. 46 Participants performed a novel task paradigm modulating these two aspects independently and allowing for investigating their distinct and interactive effects on memory encoding while undergoing high-resolution fMRI. By using advanced image processing techniques tailored to examine midbrain and brainstem nuclei with high precision, our study additionally aimed to elucidate differential activation patterns in subcortical nuclei in response to reward-associated and contextually unexpected stimuli, including distinct pathways involving in particular dopaminergic modulation.
View Article and Find Full Text PDFAcross a series of eight high-powered studies ( = 6,866), we develop a method for assessing impartial intergenerational beneficence, defined as intergenerational concern for all possible future generations. Across our studies, roughly 20% of participants displayed impartial intergenerational beneficence. Participants with impartial intergenerational beneficence expressed greater perceptions that future threats can be resolved, support for policies seeking to protect future generations of people, and a profound sense of responsibility for the long-term survival and prosperity of humanity.
View Article and Find Full Text PDFMachine learning analysis of factors affecting college students' academic performance.
Front Psychol
December 2024
Department of Science and Technology, Hebei Agricultural University, Huanghua, China.
This study aims to explore various key factors influencing the academic performance of college students, including metacognitive awareness, learning motivation, participation in learning, environmental factors, time management, and mental health. By employing the chi-square test to identify features closely related to academic performance, this paper discussed the main influencing factors and utilized machine learning models (such as LOG, SVC, RFC, XGBoost) for prediction. Experimental results indicate that the XGBoost model performs the best in terms of recall and accuracy, providing a robust prediction for academic performance.
View Article and Find Full Text PDFUnlabelled: While visual working memory (WM) is strongly associated with reductions in occipitoparietal 8-12 Hz alpha power, the role of 4-7 Hz frontal midline theta power is less clear, with both increases and decreases widely reported. Here, we test the hypothesis that this theta paradox can be explained by non-oscillatory, aperiodic neural activity dynamics. Because traditional time-frequency analyses of electroencephalopgraphy (EEG) data conflate oscillations and aperiodic activity, event-related changes in aperiodic activity can manifest as task-related changes in apparent oscillations, even when none are present.
View Article and Find Full Text PDFIn sensory and mid-level regions of the brain, stimulus information is often topographically organized; functional responses are arranged in maps according to features such as retinal coordinates, auditory pitch, and object animacy or size. However, such organization is typically measured during stimulus input, e.g.
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