Brain–computer interfacing has been applied in a range of domains including rehabilitation, neuro-prosthetics, and neurofeedback. Neuroimaging techniques provide insight into the structural and functional aspects of the brain. There is a need to identify, map and understand the various structural areas of the brain together with their functionally active roles for the accurate and efficient design of a brain–computer interface. In this review, the functionally active areas of the brain are reviewed by analyzing the research available in the literature on brain–computer interfacing in conjunction with neuroimaging experiments. This review first provides an overview of various approaches of brain–computer interfacing and basic components in the BCI system and then discuss active functional areas of the brain being utilized in non-invasive brain–computer interfacing performed with hemodynamic signals and electrophysiological recording-based signals. This paper also discusses various challenges and limitations in BCI becoming accessible to a novice user, including security issues in the BCI system, effective ways to overcome those issues, and design implementations.

/pdf/functional-mapping-of-the-brain-for-brain-computer-3aw5tybl.pdf

Functional Mapping of the Brain for Brain–Computer Interfacing: A Review

Insomnia in healthcare workers has become a topic of concern in the health system. The high infectivity and longevity of the COVID-19 pandemic have resulted in great pressure and a high incidence of insomnia among healthcare workers. Insomnia among healthcare workers has a negative impact on high-quality healthcare services in addition to their health. Thus, it's necessary to explore insomnia's underlying mechanisms.The present research's aims were threefold: explored the association between social support, resilience, COVID-19 anxiety, and insomnia among healthcare workers during the pandemic, elucidated the underlying mechanism of insomnia, and offered recommendations for improving the health of these workers.A cross-sectional design was adopted. From May 20 to 30, 2022, 1038 healthcare workers were selected to fill out the Oslo 3-item Social Support Scale, the eight-item Athens Insomnia Scale, the Coronavirus Anxiety Scale, and the Brief Resilience Scale. Descriptive statistics and correlations were analyzed by SPSS 25.0. Mediation analysis was conducted by Mplus 8.3 using 5000 bootstrap samples.Of the participating 1038 healthcare workers, the prevalence of insomnia was 41.62% (432/1038). Significant associations were found involving insomnia, resilience, COVID-19 anxiety, and social support. Insomnia was directly affected by social support. Moreover, three indirect pathways explain how social support affected insomnia: resilience's mediating role, COVID-19 anxiety's mediating role, and the chain-mediation role of resilience and COVID-19 anxiety.The results validated our hypotheses and supported the opinion of Spielman et al. ‘s three-factor model of insomnia. Social support of healthcare workers has an indirect impact on insomnia in addition to its direct one via independent and chain-mediation effects of resilience and COVID-19 anxiety.

The mediating effect of resilience and COVID-19 anxiety on the relationship between social support and insomnia among healthcare workers: a cross-sectional study

Objective This study aims to construct and use natural language processing and other methods to analyze major depressive disorder (MDD) and radiology studies’ publications in the PubMed database to understand the historical growth, current state, and potential expansion trend. Methods All MDD radiology studies publications from January 2002 to January 2022 were downloaded from PubMed using R, a statistical computing language. R and the interpretive general-purpose programming language Python were used to extract publication dates, geographic information, and abstracts from each publication’s metadata for bibliometric analysis. The generative statistical algorithm “Latent Dirichlet allocation” (LDA) was applied to identify specific research focus and trends. The unsupervised Leuven algorithm was used to build a network to identify relationships between research focus. Results A total of 5,566 publications on MDD and radiology research were identified, and there is a rapid upward trend. The top-cited publications were 11,042, and the highly-cited publications focused on improving diagnostic performance and establishing imaging standards. Publications came from 76 countries, with the most from research institutions in the United States and China. Hospitals and radiology departments take the lead in research and have an advantage. The extensive field of study contains 12,058 Medical Subject Heading (MeSH) terms. Based on the LDA algorithm, three areas were identified that have become the focus of research in recent years, “Symptoms and treatment,” “Brain structure and imaging,” and “Comorbidities research.” Conclusion Latent Dirichlet allocation analysis methods can be well used to analyze many texts and discover recent research trends and focus. In the past 20 years, the research on MDD and radiology has focused on exploring MDD mechanisms, establishing standards, and constructing imaging methods. Recent research focuses are “Symptoms and sleep,” “Brain structure study,” and “functional connectivity.” New progress may be made in studies on MDD complications and the combination of brain structure and metabolism.

/pdf/exploring-changes-in-depression-and-radiology-related-kxoeyt3v.pdf

Exploring changes in depression and radiology-related publications research focus: A bibliometrics and content analysis based on natural language processing

Background Intermittent energy restriction (IER) is an effective weight loss strategy. However, the accompanying changes in spontaneous neural activity are unclear, and the relationship among anthropometric measurements, biochemical indicators, and adipokines remains ambiguous. Methods Thirty-five obese adults were recruited and received a 2-month IER intervention. Data were collected from anthropometric measurements, blood samples, and resting-state functional magnetic resonance imaging at four time points. The regional homogeneity (ReHo) method was used to explore the effects of the IER intervention. The relationships between the ReHo values of altered brain regions and changes in anthropometric measurements, biochemical indicators, and adipokines (leptin and adiponectin) were analyzed. Results Results showed that IER significantly improved anthropometric measurements, biochemical indicators, and adipokine levels in the successful weight loss group. The IER intervention for weight loss was associated with a significant increase in ReHo in the bilateral lingual gyrus, left calcarine, and left postcentral gyrus and a significant decrease in the right middle temporal gyrus and right cerebellum (VIII). Follow-up analyses showed that the increase in ReHo values in the right LG had a significant positive correlation with a reduction in Three-factor Eating Questionnaire (TFEQ)-disinhibition and a significant negative correlation with an increase in TFEQ-cognitive control. Furthermore, the increase in ReHo values in the left calcarine had a significant positive correlation with the reduction in TFEQ-disinhibition. However, no significant difference in ReHo was observed in the failed weight loss group. Conclusion Our study provides objective evidence that the IER intervention reshaped the ReHo of some brain regions in obese individuals, accompanied with improved anthropometric measurements, biochemical indicators, and adipokines. These results illustrated that the IER intervention for weight loss may act by decreasing the motivational drive to eat, reducing reward responses to food cues, and repairing damaged food-related self-control processes. These findings enhance our understanding of the neurobiological basis of IER for weight loss in obesity. 

pdf/intermittent-energy-restriction-changes-the-regional-1qsfviff97.pdf

Intermittent energy restriction changes the regional homogeneity of the obese human brain

Background There is limited evidence on the link between gut microbiota (GM) and resting-state brain activity in patients with chronic insomnia (CI). This study aimed to explore the alterations in brain functional connectivity strength (FCS) in CI and the potential associations among altered FCS, GM composition, and neuropsychological performance indicators. Materials and methods Thirty CI patients and 34 age- and gender-matched healthy controls (HCs) were recruited. Each participant underwent resting-state functional magnetic resonance imaging (rs-fMRI) for the evaluation of brain FCS and was administered sleep-, mood-, and cognitive-related questionnaires for the evaluation of neuropsychological performance. Stool samples of CI patients were collected and subjected to 16S rDNA amplicon sequencing to assess the relative abundance (RA) of GM. Redundancy analysis or canonical correspondence analysis (RDA or CCA, respectively) was used to investigate the relationships between GM composition and neuropsychological performance indicators. Spearman correlation was further performed to analyze the associations among alterations in FCS, GM composition, and neuropsychological performance indicators. Results The CI group showed a reduction in FCS in the left superior parietal gyrus (SPG) compared to the HC group. The correlation analysis showed that the FCS in the left SPG was correlated with sleep efficiency and some specific bacterial genera. The results of CCA and RDA showed that 38.21% (RDA) and 24.62% (CCA) of the GM composition variation could be interpreted by neuropsychological performance indicators. Furthermore, we found complex relationships between Alloprevotella, specific members of the family Lachnospiraceae, Faecalicoccus, and the FCS alteration, and neuropsychological performance indicators. Conclusion The brain FCS alteration of patients with CI was related to their GM composition and neuropsychological performance indicators, and there was also an association to some extent between the latter two, suggesting a specific interaction pattern among the three aspects: brain FCS alteration, GM composition, and neuropsychological performance indicators.

/pdf/altered-functional-connectivity-strength-in-chronic-insomnia-77bv51ak.pdf

Altered functional connectivity strength in chronic insomnia associated with gut microbiota composition and sleep efficiency

Background Chronic insomnia disorder (CID) is considered a major public health problem worldwide. Therefore, innovative and effective technical methods for studying the pathogenesis and clinical comprehensive treatment of CID are urgently needed. Methods Real-time fMRI neurofeedback (rtfMRI-NF), a new intervention, was used to train 28 patients with CID to regulate their amygdala activity for three sessions in 6 weeks. Resting-state fMRI data were collected before and after training. Then, voxel-based degree centrality (DC) method was used to explore the effect of rtfMRI-NF training. For regions with altered DC, we determined the specific connections to other regions that most strongly contributed to altered functional networks based on DC. Furthermore, the relationships between the DC value of the altered regions and changes in clinical variables were determined. Results Patients with CID showed increased DC in the right postcentral gyrus, Rolandic operculum, insula, and superior parietal gyrus and decreased DC in the right supramarginal gyrus, inferior parietal gyrus, angular gyrus, middle occipital gyrus, and middle temporal gyrus. Seed-based functional connectivity analyses based on the altered DC regions showed more details about the altered functional networks. Clinical scores in Pittsburgh sleep quality index, insomnia severity index (ISI), Beck depression inventory, and Hamilton anxiety scale decreased. Furthermore, a remarkable positive correlation was found between the changed ISI score and DC values of the right insula. Conclusions This study confirmed that amygdala-based rtfMRI-NF training altered the intrinsic functional hubs, which reshaped the abnormal functional connections caused by insomnia and improved the sleep of patients with CID. These findings contribute to our understanding of the neurobiological mechanism of rtfMRI-NF in insomnia treatment. However, additional double-blinded controlled clinical trials with larger sample sizes need to be conducted to confirm the effect of rtfMRI-NF from this initial study.

/pdf/real-time-fmri-neurofeedback-training-changes-brain-degree-2mfkr45w.pdf

Real-Time fMRI Neurofeedback Training Changes Brain Degree Centrality and Improves Sleep in Chronic Insomnia Disorder: A Resting-State fMRI Study

Background Chronic insomnia disorder (CID) is a highly prevalent sleep disorder, which influences people's daily life and is even life threatening. However, whether the resting-state regional homogeneity (ReHo) of disrupted brain regions in CID can be reshaped to normal after treatment remains unclear. Methods A novel intervention real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) was used to train 28 CID patients to regulate the activity of the left amygdala for three sessions in 6 weeks. The ReHo methodology was adopted to explore its role on resting-state fMRI data, which were collected before and after training. Moreover, the relationships between changes of clinical variables and ReHo value of altered regions were determined. Results Results showed that the bilateral dorsal medial pre-frontal cortex, supplementary motor area (SMA), and left dorsal lateral pre-frontal cortex had decreased ReHo values, whereas the bilateral cerebellum anterior lobe (CAL) had increased ReHo values after training. Some clinical scores markedly decreased, including Pittsburgh Sleep Quality Index, Insomnia Severity Index, Beck Depression Inventory, and Hamilton Anxiety Scale (HAMA). Additionally, the ReHo values of the left CAL were positively correlated with the change in the Hamilton depression scale score, and a remarkable positive correlation was found between the ReHo values of the right SMA and the HAMA score. Conclusion Our study provided an objective evidence that amygdala-based rtfMRI-NF training could reshape abnormal ReHo and improve sleep in patients with CID. The improved ReHo in CID provides insights into the neurobiological mechanism for the effectiveness of this intervention. However, larger double-blinded sham-controlled trials are needed to confirm our results from this initial study.

Improved Regional Homogeneity in Chronic Insomnia Disorder After Amygdala-Based Real-Time fMRI Neurofeedback Training

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Real-Time fMRI Neurofeedback Training Changes Brain Degree Centrality and Improves Sleep in Chronic Insomnia Disorder: A Resting-State fMRI Study

Improved Regional Homogeneity in Chronic Insomnia Disorder After Amygdala-Based Real-Time fMRI Neurofeedback Training