Results 31 to 40 of about 144,480 (50)
IntroductionIn cognitive behavioral experiments, we often asked participants to make judgments within a deadline. However, the most common instruction of “do the task quickly and accurately” does not highlight the importance of the balance between being ...
Haijian Li +4 more
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Identification of early influences on cognitive decline is of paramount importance in order to stem the impacts of decrements in cognitive functioning and to potentially intervene.
Lisa M James +3 more
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BackgroundAge-related decline in cognitive function is often linked to changed prefrontal cortex (PFC) activity and heart rate variability (HRV). Mild cognitive impairment (MCI), a transitional stage between normal aging and dementia, might have further ...
Pei-Hsin Ku +5 more
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Follicle-stimulating hormone induces depression-like phenotype by affecting synaptic function
Depression is one of the most common affective disorders in people’s life. Women are susceptibility to depression during puberty, peripartum and menopause transition, when they are suffering from sex hormone fluctuation.
Liqin Huang +13 more
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The early detection of cognitive decline in older adults is crucial for preventing dementia. This mini-review focuses on electroencephalography (EEG) markers of early dementia-related precursors, including subjective cognitive decline, subjective memory ...
Mutsuhide Tanaka +2 more
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Pigeons have natural advantages in robotics research, including a wide range of activities, low energy consumption, good concealment performance, strong long-distance weight bearing and continuous flight ability, excellent navigation, and spatial ...
Mengmeng Li +5 more
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Transcranial Sonography Characteristics of Cerebellar Neurodegenerative Ataxias
Cerebellar neurodegenerative ataxias are a group of disorders affecting the cerebellum and its pathways with different neurological structures. Transcranial sonography (TCS) has been used for the evaluation of brain parenchymal structures in various ...
Olivera Tamaš +7 more
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Unsupervised Multivariate Feature-Based Adaptive Clustering Analysis of Epileptic EEG Signals
Supervised classification algorithms for processing epileptic EEG signals rely heavily on the label information of the data, and existing supervised methods cannot effectively solve the problem of analyzing unlabeled epileptic EEG signals.
Yuxiao Du, Gaoming Li, Min Wu, Feng Chen
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Human Recognition: The Utilization of Face, Voice, Name and Interactions—An Extended Editorial
The many stimulating contributions to this Special Issue of Brain Science focused on some basic issues of particular interest in current research, with emphasis on human recognition using faces, voices, and names [...]
Guido Gainotti
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The study of complex process models often encounters challenges in terms of comprehensibility. This paper explores using modularization as a strategy to mitigate such challenges, notably the reduction in complexity.
Julia Baß +3 more
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