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Mental fatigue is a widely studied topic on account of its serious negative effects. But how the neural mechanism of task switching before and after mental fatigue remains a question. To this end, this study aims to use brain functional network features to explore the answer to this question. Specifically, task-state EEG signals were recorded from 20 participants. The tasks include a 400-s 2-back-task (2-BT), followed by a 6480-s of mental arithmetic task (MAT), and then a 400-s 2-BT. Network features and functional connections were extracted and analyzed based on the selected task switching states, referred to from Pre_2-BT to Pre_MAT before mental fatigue and from Post_MAT to Post_2-BT after mental fatigue. The results showed that mental fatigue has been successfully induced by long-term MAT based on the significant changes in network characteristics and the high classification accuracy of 98% obtained with Support Vector Machines (SVM) between Pre_2-BT and Post_2-BT. when the task switched from Pre_2-BT to Pre_MAT, delta and beta rhythms exhibited significant changes among all network features and the selected functional connections showed an enhanced trend. As for the task switched from Post_MAT to Post_2-BT, the network features and selected functional connectivity of beta rhythm were opposite to the trend of task switching before mental fatigue. Our findings provide new insights to understand the neural mechanism of the brain in the process of task switching and indicate that the network features and functional connections of beta rhythm can be used as neural markers for task switching before and after mental fatigue.
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http://dx.doi.org/10.3390/s22208036 | DOI Listing |
J Autism Dev Disord
September 2025
The Melbourne Clinic Neuropsychology Service, 130 Church St, Richmond, Melbourne, VIC, 3121, Australia.
Investigate the utility of a neuropsychological strengths-based approach to the assessment of Autism in adults; to determine the acceptability of the approach and feedback provided to clients; and gather information about improving the assessment process for future clients. The approach was grounded in a neurodiversity-positive framework, providing diagnosis-affirming care. Participants were inpatient clients of the neuropsychology service of a private adult, mental health treatment service.
View Article and Find Full Text PDFJ Nephrol
September 2025
Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, Health Psychology Section, King's College London, 5th Floor Bermondsey Wing, Guy's Campus, London Bridge, London, SE1 9RT, UK.
Background: Depression and anxiety are common in chronic kidney disease (CKD) and worsen clinical outcomes. Psycho-behavioural interventions offer a promising, non-pharmacological approach. However, most evidence comes from people with kidney failure with distinct treatment needs, limiting relevance to earlier stages of CKD, where timely support may enhance self-management and slow progression.
View Article and Find Full Text PDFFront Psychol
August 2025
Department of Neurology, Medical University of Graz, Graz, Austria.
Background: Cognitive impairment and psychological complaints are among the most common consequences for patients suffering from Post-Covid-19 condition (PCC). As there are limited training options available, this study examined a longitudinal tablet-based training program addressing cognitive and psychological symptoms.
Methods: Forty individuals aged between 36 and 71 years ( = 49.
Cureus
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School of Medicine, Universidad Central del Caribe, Bayamon, PRI.
Background Breast augmentation surgery (BAS) is one of the top cosmetic surgical procedures performed in the United States every year. There are various breast implant options, such as saline, silicone, smooth, and textured implants. Breast implant illness (BII) is a disorder associated with a wide array of symptoms presenting post breast implant surgery and is often associated with autoimmune disorders.
View Article and Find Full Text PDFAlpha Psychiatry
August 2025
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, 610036 Chengdu, Sichuan, China.
Objective: Physical aggression in schizophrenia patients carries significant societal implications. Previous studies on aggression prediction have primarily focused on hospitalized patients, overlooking specific rural community contexts in China. This study investigated multidimensional predictive factors to develop and validate a predictive model for predicting physical aggression in schizophrenia patients in rural communities in southwestern China.
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