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Nootropics are a group of medicinal substances purported to improve important cognitive functions such as learning, focus and memory. Many of these substances have demonstrated beneficial effects on cognitive performance and overall health. However, a thorough understanding of how these substances and their synergistic effects in the form of a supplement may benefit fundamental brain processes is currently lacking. In the current study, we will investigate the effects of a plant-based, nootropic supplement (https://uk.mindlabpro.com/) on perceptual decision-making and working memory in healthy adult participants.

Omar Khoja,1,* Bárbara Silva Passadouro,1,* Matthew Mulvey,2 Ioannis Delis,3 Sarah Astill,3 Ai Lyn Tan,1,4 Manoj Sivan1,4,5 1Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Leeds, UK; 2Academic Unit of Palliative Care, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK; 3School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK; 4NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK; 5COVID Rehabilitation Service, Leeds Community Healthcare NHS Trust, Leeds, UK*These authors contributed equally to this workCorrespondence: Manoj Sivan, Leeds Institute of Rheumatic and Musculoskeletal Medicine, University of Leeds, Floor D Martin Wing, Leeds General Infirmary, Leeds, LS1 3EX, UK, Tel +44 113 3922564, Email M.Sivan@leeds.ac.ukObjective: Musculoskeletal (MSK) pain is being increasingly reported by patients as one of the most common persistent symptoms in post-COVID-19 syndrome or Long COVID. However, there is a lack of understanding of its prevalence, characteristics, and underlying pathophysiological mechanisms. The objective of this review is to identify and describe the features and characteristics of MSK pain in Long COVID patients.Methods: The narrative review involved a literature search of the following online databases: MEDLINE (OVID), EMBASE (OVID), CINAHL, PsyclNFO, and Web of Science (December 2019 to February 2022). We included observational studies that investigated the prevalence, characteristics, risk factors and mechanisms of MSK pain in Long COVID. After screening and reviewing the initial literature search results, a total of 35 studies were included in this review.Results: The overall reported prevalence of MSK pain in Long COVID ranged widely from 0.3% to 65.2%. The pain has been reported to be localized to a particular region or generalized and widespread. No consistent pattern of progression of MSK pain symptoms over time was identified. Female gender and higher BMI could be potential risk factors for Long COVID MSK pain, but no clear association has been found with age and ethnicity. Different pathophysiological mechanisms have been hypothesized to contribute to MSK pain in Long COVID including increased production of proinflammatory cytokines, immune cell hyperactivation, direct viral entry of neurological and MSK system cells, and psychological factors.Conclusion: MSK pain is one of the most common symptoms in Long COVID. Most of the current literature on Long COVID focuses on reporting the prevalence of persistent MSK pain. Studies describing the pain characteristics are scarce. The precise mechanism of MSK pain in Long COVID is yet to be investigated. Future research must explore the characteristics, risk factors, natural progression, and underlying mechanisms of MSK pain in Long COVID.Keywords: post-COVID-19 syndrome, post-acute COVID-19, chronic pain

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We develop a novel methodology for the single-trial analysis of multichannel time-varying neuroimaging signals. We introduce the space-by-time M/EEG decomposition, based on Non-negative Matrix Factorization (NMF), which describes single-trial M/EEG signals using a set of non-negative spatial and temporal components that are linearly combined with signed scalar activation coefficients. We illustrate the effectiveness of the proposed approach on an EEG dataset recorded during the performance of a visual categorization task. Our method extracts three temporal and two spatial functional components achieving a compact yet full representation of the underlying structure, which validates and summarizes succinctly results from previous studies. Furthermore, we introduce a decoding analysis that allows determining the distinct functional role of each component and relating them to experimental conditions and task parameters. In particular, we demonstrate that the presented stimulus and the task difficulty of each trial can be reliably decoded using specific combinations of components from the identified space-by-time representation. When comparing with a sliding-window linear discriminant algorithm, we show that our approach yields more robust decoding performance across participants. Overall, our findings suggest that the proposed space-by-time decomposition is a meaningful low-dimensional representation that carries the relevant information of single-trial M/EEG signals.