Social anxiety disorder (SAD) is associated with aberrant self-referential processing (SRP) such as increased self-focused attention. Aberrant SRP is one of the core features of SAD and is also related to therapeutic interventions. Understanding of the underlying neural correlates of SRP in SAD is important for identifying specific brain regions as treatment targets. We reviewed functional magnetic resonance imaging (fMRI) studies to clarify the neural correlates of SRP and their clinical implications for SAD. Task-based and resting fMRI studies have reported the cortical midline structures including the default mode network, theory of mind-related regions of the temporo-parietal junction and temporal pole, and the insula as significant neural correlates of aberrant SRP in SAD patients. Also, these neural correlates are related to clinical improvement on pharmacological and cognitive-behavioral treatments. Furthermore, these could be candidates for the development of novel SAD treatments. This review supports that neural correlates of SAD may be significant biomarkers for future pathophysiology based treatment.
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http://dx.doi.org/10.9758/cpn.2019.17.1.12 | DOI Listing |
Sci Rep
December 2024
Department of Civil Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Deep learning models are widely used for traffic forecasting on freeways due to their ability to learn complex temporal and spatial relationships. In particular, graph neural networks, which integrate graph theory into deep learning, have become popular for modeling traffic sensor networks. However, traditional graph convolutional networks (GCNs) face limitations in capturing long-range spatial correlations, which can hinder accurate long-term predictions.
View Article and Find Full Text PDFNat Commun
December 2024
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, US.
The correlational structure of brain activity dynamics in the absence of stimuli or behavior is often taken to reveal intrinsic properties of neural function. To test the limits of this assumption, we analyzed peripheral contributions to resting state activity measured by fMRI in unanesthetized, chemically immobilized male rats that emulate human neuroimaging conditions. We find that perturbation of somatosensory input channels modifies correlation strengths that relate somatosensory areas both to one another and to higher-order brain regions, despite the absence of ostensible stimuli or movements.
View Article and Find Full Text PDFJ Exerc Sci Fit
January 2025
Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, People's Republic of China.
Background: Basketball is an attractive sport required both cooperative and antagonistic motor skills. However, the neural mechanism of basketball proficiency remains unclear. This study aimed to examine the brain functional and structural substrates underlying varying levels of basketball capacity.
View Article and Find Full Text PDFHealth Inf Sci Syst
December 2025
School of Nursing, National Taipei University of Nursing and Health Sciences, No. 365, Ming-Te Road, Peitou District, Taipei, 112 Taiwan.
Background: Health risks associated with phthalate esters depend on exposure level, individual sensitivities, and other contributing factors.
Purpose: This study employed artificial intelligence algorithms while applying data mining techniques to identify correlations between phthalate esters [di(2-ethylhexyl) phthalate, DEHP], lifestyle factors, and disease outcomes.
Methods: We conducted exploratory analysis using demographic and laboratory data collected from the Taiwan Biobank.
J Neuroeng Rehabil
December 2024
The School of Information Science and Technology, Dalian Maritime University, Dalian, 116026, China.
Background: Simultaneous and proportional control (SPC) based on surface electromyographic (sEMG) signals has emerged as a research hotspot in the field of human-machine interaction (HMI). However, the existing continuous motion estimation methods mostly have an average Pearson coefficient (CC) of less than 0.85, while high-precision methods suffer from the problem of long inference time (> 200 ms) and can only estimate SPC of less than 15 hand movements, which limits their applications in HMI.
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