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Filename: drivers/Session_files_driver.php
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Function: require_once
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Function: strpos
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Function: insertAPISummary
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Filename: helpers/my_audit_helper.php
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In the present study, we characterized within- and cross-frequency power correlations from magnetoencephalography (MEG) data in order to understand how different brain regions cooperate as a network to maintain working memory representations with several features. The working memory items were composed of spatially arranged dots supposedly requiring both the dorsal and the ventral stream to be engaged during maintenance. Using a beamforming technique, we localized memory-dependent sources in the alpha, beta, and gamma bands. After the single-trial power values were extracted from these frequency bands with respect to each source, we calculated the correlations within- and cross-frequency bands. The following general picture emerged: gamma power in right superior temporal gyrus (STG) during working memory maintenance was correlated with numerous other sources in the alpha band in prefrontal, parietal, and posterior regions. In addition, the power correlations within the alpha band showed correlations across posterior-parietal-frontal regions. From these findings, we suggest that the STG dominated by gamma activity serves as a hub region for the network nodes responsible for the retention of the stimulus used in this study, which is likely to depend on both the "where-" and the "what-" visual system simultaneously. The present study demonstrates how oscillatory dynamics reflecting the interaction between cortical areas can be investigated by means of cross-frequency power correlations in source space. This methodological framework could be of general utility when studying functional network properties of the working brain.
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http://dx.doi.org/10.1089/brain.2011.0046 | DOI Listing |
Heliyon
December 2024
North China University of Water Resources and Electric Power, Zhengzhou, Henan, 450011, PR China.
In the domain of stock price prediction, the intricate interdependencies within multivariate time series data present significant challenges for accurate forecasting. This paper introduces a groundbreaking hybrid preprocessing technique to tackle this issue. By leveraging the Empirical Wavelet Transform (EWT), we adeptly extract both low-frequency and high-frequency components from the time series.
View Article and Find Full Text PDFHear Res
December 2024
Clinics of Otolaryngology, Hannover Medical School, Hearing Center Hannover (DHZ), Karl-Wiechert-Allee 3, 30625 Hannover, Germany; Institute of AudioNeuroTechnology (VIANNA) & Dept. of Experimental Otology, Hannover Medical School, Stadtfelddamm 34, 30625 Hannover, Germany. Electronic address:
Objective: We investigated auditory working-memory using behavioural measures and electroencephalography (EEG) in adult Cochlear Implant (CI) users with varying degrees of CI performance.
Methods: 24 adult CI listeners (age: M = 61.38, SD = 12.
BMC Psychol
December 2024
Department of Psychiatry, National Center for Mental Disorders, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
Background: Cognitive bias plays a crucial role in the onset and persistence of depression. Research has established a link between personality traits and cognitive bias; however, most of them focused on the general population, overlooking individuals with depression. We aim to explore the relationship between personality and cognitive bias in patients with major depressive disorder (MDD) and compare the results with healthy controls (HCs) to identify potential patterns.
View Article and Find Full Text PDFJ Phys Chem B
December 2024
Science and Technology on Aerospace Chemical Power Laboratory, Laboratory of Emergency Safety and Rescue Technology, Hubei Institute of Aerospace Chemotechnology, Xiangyang 441003, China.
Doped semiconductors are often used to improve photocatalytic efficiency and address the challenges of easy recombination of electron-hole pairs and poor photoluminescence. However, the reproducibility and complexity of experimental studies result in time-consuming and less cost-effective studies, and it is difficult to gain insights into the intrinsic properties of doped photocatalysts to control their performance. Introducing a machine learning approach, we constructed a photocatalytic model of transition-metal- and rare earth metal-ion-doped γ-BiMoO.
View Article and Find Full Text PDFMenopause
December 2024
From the University of Aarhus, Institute for Clinical Medicine, Aarhus, Denmark.
Objective: The aim of the study was to explore the correlation between short luteal phases and cycle irregularity in perimenopausal women.
Methods: In this feasibility pilot study, daily salivary-progesterone measurements from presumed perimenopausal women have been analyzed using the inne minilab-an at-home system for ovulation and cycle tracking. Data were collected between 2020 to August 2022 from 29 women from Germany and Austria from users over the age of 42 years.
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