The impact of wearing a KN95 face mask on human brain function: evidence from resting state functional magnetic resonance imaging.

Background: Face masks are widely used in daily life because of the COVID-19 pandemic. The objective of this study was to explore the impact of wearing face masks on brain functions by using resting-state functional MRI (RS-fMRI). Methods: Scanning data from 15 healthy subjects (46.20 ± 6.67 years) were collected in this study. Each subject underwent RS-fMRI scans under two comparative conditions, wearing a KN95 mask and natural breathing (no mask). The amplitude of low frequency fluctuation (ALFF) and functional connectivity under the two conditions were analyzed and then compared using the paired t-test. Results: Compared with those of the no-mask condition, the ALFF activities when wearing masks were increased significantly in the right middle frontal gyrus, bilateral precuneus, right superior marginal gyrus, left inferior parietal gyrus, and left supplementary motor area and decreased significantly in the anterior cingulate gyrus, right fusiform gyrus, left superior temporal gyrus, bilateral lingual gyrus, and bilateral calcarine cortex (p < 0.05). Taking the posterior cingulate cortex area as a seed point, the correlations with the occipital cortex, prefrontal lobe, and motor sensory cortex were sensitive to wearing masks compared with not wearing masks (p < 0.05). Taking the medial prefrontal cortex region as a seed point, the functional connectivity with the bilateral temporal lobe, bilateral motor sensory cortex, and occipital lobe was influenced by wearing a KN95 mask (p < 0.05). Conclusion: This study demonstrated that wearing a KN95 face mask can cause short-term changes in human resting brain function. Both local neural activities and functional connectivity in brain regions were sensitive to mask wearing. However, the neural mechanism causing these changes and its impact on cognitive function still need further investigation.

Risk of insomnia during COVID-19: effects of depression and brain functional connectivity.

Normal sleepers may be at risk for insomnia during COVID-19. Identifying psychological factors and neural markers that predict their insomnia risk, as well as investigating possible courses of insomnia development, could lead to more precise targeted interventions for insomnia during similar public health emergencies. Insomnia severity index of 306 participants before and during COVID-19 were employed to determine the development of insomnia, while pre-COVID-19 psychometric and resting-state fMRI data were used to explore corresponding psychological and neural markers of insomnia development. Normal sleepers as a group reported a significant increase in insomnia symptoms after COVID-19 outbreak (F = 4.618, P = 0.0102, df = 2, 609.9). Depression was found to significantly contribute to worse insomnia (ß = 0.066, P = 0.024). Subsequent analysis found that functional connectivity between the precentral gyrus and middle/inferior temporal gyrus mediated the association between pre-COVID-19 depression and insomnia symptoms during COVID-19. Cluster analysis identified that postoutbreak insomnia symptoms followed 3 courses (lessened, slightly worsened, and developed into mild insomnia), and pre-COVID-19 depression symptoms and functional connectivities predicted these courses. Timely identification and treatment of at-risk individuals may help avoid the development of insomnia in the face of future health-care emergencies, such as those arising from COVID-19 variants.

Effects of hyperbaric oxygen therapy on functional and structural connectivity in post-COVID-19 condition patients: A randomized, sham-controlled trial.

INTRODUCTION: Post-COVID-19 condition refers to a range of persisting physical, neurocognitive, and neuropsychological symptoms after SARS-CoV-2 infection. Abnormalities in brain connectivity were found in recovered patients compared to non-infected controls. This study aims to evaluate the effect of hyperbaric oxygen therapy (HBOT) on brain connectivity in post-COVID-19 patients. METHODS: In this randomized, sham-controlled, double-blind trial, 73 patients were randomized to receive 40 daily sessions of HBOT (n = 37) or sham treatment (n = 36). We examined pre- and post-treatment resting-state brain functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) scans to evaluate functional and structural connectivity changes, which were correlated to cognitive and psychological distress measures. RESULTS: The ROI-to-ROI analysis revealed decreased internetwork connectivity in the HBOT group which was negatively correlated to improvements in attention and executive function scores (p < 0.001). Significant group-by-time interactions were demonstrated in the right hippocampal resting state function connectivity (rsFC) in the medial prefrontal cortex (PFWE = 0.002). Seed-to-voxel analysis also revealed a negative correlation in the brief symptom inventory (BSI-18) score and in the rsFC between the amygdala seed, the angular gyrus, and the primary sensory motor area (PFWE = 0.012, 0.002). Positive correlations were found between the BSI-18 score and the left insular cortex seed and FPN (angular gyrus) (PFWE < 0.0001). Tractography based structural connectivity analysis showed a significant group-by-time interaction in the fractional anisotropy (FA) of left amygdala tracts (F = 7.81, P = 0.007). The efficacy measure had significant group-by-time interactions (F = 5.98, p = 0.017) in the amygdala circuit. CONCLUSIONS: This study indicates that HBOT improves disruptions in white matter tracts and alters the functional connectivity organization of neural pathways attributed to cognitive and emotional recovery in post-COVID-19 patients. This study also highlights the potential of structural and functional connectivity analysis as a promising treatment response monitoring tool.

Transfer Learning from Healthy to Unhealthy Patients for the Automated Classification of Functional Brain Networks in fMRI

Functional Magnetic Resonance Imaging (fMRI) is an essential tool for the pre-surgical planning of brain tumor removal, which allows the identification of functional brain networks to preserve the patient’s neurological functions. One fMRI technique used to identify the functional brain network is the resting-state-fMRI (rs-fMRI). This technique is not routinely available because of the necessity to have an expert reviewer who can manually identify each functional network. The lack of sufficient unhealthy data has so far hindered a data-driven approach based on machine learning tools for full automation of this clinical task. In this article, we investigate the possibility of such an approach via the transfer learning method from healthy control data to unhealthy patient data to boost the detection of functional brain networks in rs-fMRI data. The end-to-end deep learning model implemented in this article distinguishes seven principal functional brain networks using fMRI images. The best performance of a 75% correct recognition rate is obtained from the proposed deep learning architecture, which shows its superiority over other machine learning algorithms that were equally tested for this classification task. Based on this best reference model, we demonstrate the possibility of boosting the results of our algorithm with transfer learning from healthy patients to unhealthy patients. This application of the transfer learning technique opens interesting possibilities because healthy control subjects can be easily enrolled for fMRI data acquisition since it is non-invasive. Consequently, this process helps to compensate for the usual small cohort of unhealthy patient data. This transfer learning approach could be extended to other medical imaging modalities and pathology.

Altered brain regional homogeneity is associated with depressive symptoms in COVID-19.

BACKGROUND: COVID-19 is an infectious disease that has spread worldwide in 2020, causing a severe pandemic. In addition to respiratory symptoms, neuropsychiatric manifestations are commonly observed, including chronic fatigue, depression, and anxiety. The neural correlates of neuropsychiatric symptoms in COVID-19 are still largely unknown. METHODS: A total of 79 patients with COVID-19 (COV) and 17 healthy controls (HC) underwent 3 T functional magnetic resonance imaging at rest, as well as structural imaging. Regional homogeneity (ReHo) was calculated. We also measured depressive symptoms with the Patient Health Questionnaire (PHQ-9), anxiety using the General Anxiety Disorder 7-item scale, and fatigue with the Multidimension Fatigue Inventory. RESULTS: In comparison with HC, COV showed significantly higher depressive scores. Moreover, COV presented reduced ReHo in the left angular gyrus, the right superior/middle temporal gyrus and the left inferior temporal gyrus, and higher ReHo in the right hippocampus. No differences in gray matter were detected in these areas. Furthermore, we observed a negative correlation between ReHo in the left angular gyrus and PHQ-9 scores and a trend toward a positive correlation between ReHo in the right hippocampus and PHQ-9 scores. LIMITATIONS: Heterogeneity in the clinical presentation in COV, the different timing from the first positive molecular swab test to the MRI, and the cross-sectional design of the study limit the generalizability of our findings. CONCLUSIONS: Our results suggest that COVID-19 infection may contribute to depressive symptoms via a modulation of local functional connectivity in cortico-limbic circuits.

Changes in the Intranetwork and Internetwork Connectivity of the Default Mode Network and Olfactory Network in Patients with COVID-19 and Olfactory Dysfunction.

Olfactory dysfunction (OD) is a common symptom in coronavirus disease 2019 (COVID-19) patients. Moreover, many neurological manifestations have been reported in these patients, suggesting central nervous system involvement. The default mode network (DMN) is closely associated with olfactory processing. In this study, we investigated the internetwork and intranetwork connectivity of the DMN and the olfactory network (ON) in 13 healthy controls and 22 patients presenting with COVID-19-related OD using independent component analysis and region of interest functional magnetic resonance imaging (fMRI) analysis. There was a significant correlation between the butanol threshold test (BTT) and the intranetwork connectivity in ON. Meanwhile, the COVID-19 patients with OD showed significantly higher intranetwork connectivity in the DMN, as well as higher internetwork connectivity between ON and DMN. However, no significant difference was found between groups in the intranetwork connectivity within ON. We postulate that higher intranetwork functional connectivities compensate for the deficits in olfactory processing and general well-being in COVID-19 patients. Nevertheless, the compensation process in the ON may not be obvious at this stage. Our results suggest that resting-state fMRI is a potentially valuable tool to evaluate neurosensory dysfunction in COVID-19 patients.

No Alteration Between Intrinsic Connectivity Networks by a Pilot Study on Localized Exposure to the Fourth-Generation Wireless Communication Signals.

Neurophysiological effect of human exposure to radiofrequency signals has attracted considerable attention, which was claimed to have an association with a series of clinical symptoms. A few investigations have been conducted on alteration of brain functions, yet no known research focused on intrinsic connectivity networks, an attribute that may relate to some behavioral functions. To investigate the exposure effect on functional connectivity between intrinsic connectivity networks, we conducted experiments with seventeen participants experiencing localized head exposure to real and sham time-division long-term evolution signal for 30 min. The resting-state functional magnetic resonance imaging data were collected before and after exposure, respectively. Group-level independent component analysis was used to decompose networks of interest. Three states were clustered, which can reflect different cognitive conditions. Dynamic connectivity as well as conventional connectivity between networks per state were computed and followed by paired sample t-tests. Results showed that there was no statistical difference in static or dynamic functional network connectivity in both real and sham exposure conditions, and pointed out that the impact of short-term electromagnetic exposure was undetected at the ICNs level. The specific brain parcellations and metrics used in the study may lead to different results on brain modulation.

Sex difference in neural substrates underlying the association between trait self-control and overeating in the COVID-19 pandemic.

During the COVID-19 pandemic, people are at risk of developing disordered eating behaviors. The present study utilized resting-state functional magnetic resonance imaging (fMRI) to examine how trait self-control and its neural mechanisms predict overeating tendencies in young adults during the pandemic. Data on trait self-control, the amplitude of low-frequency fluctuation (ALFF), and resting-state functional connectivity (RSFC) were collected before COVID-19 (September 2019, T1), and data on overeating were collected during COVID-19 (February 2020, T2). Whole-brain regression analyses (N = 538) revealed that higher trait self-control was associated with higher ALFF in the right dorsolateral and ventrolateral prefrontal cortex (DLPFC, VLPFC) and the left anterior insula, and lower ALFF in the left fusiform gyrus and precuneus. With the DLPFC, fusiform gyrus and precuneus as seed regions, trait selfcontrol was associated with decreased connectivity of the orbitofrontal cortex, anterior cingulate cortex, temporal pole, and insula, and increased connectivity between the right VLPFC and anterior cerebellum. Longitudinal mediation models showed that trait self-control (T1) negatively predicted overeating (T2), and the mediating effects of the fusiform gyrus, DLPFC, and VLPFC were moderated by sex. The present study reveals that the brain networks for trait self-control are mainly involved in cognitive and executive control and incentive and emotional processing, demonstrating the longitudinal benefits of trait self-control in alleviating disordered eating behaviors during the pandemic. Sex differences in the neural substrates underlie this association. These finding may have implications of the interventions for behavioral maladjustment.

Neurosensory Rehabilitation and Olfactory Network Recovery in Covid-19-related Olfactory Dysfunction.

Non-conductive olfactory dysfunction (OD) is an important extra-pulmonary manifestation of coronavirus disease 2019 (COVID-19). Olfactory bulb (OB) volume loss and olfactory network functional connectivity (FC) defects were identified in two patients suffering from prolonged COVID-19-related OD. One patient received olfactory treatment (OT) by the combination of oral vitamin A and smell training via the novel electronic portable aromatic rehabilitation (EPAR) diffusers. After four-weeks of OT, clinical recuperation of smell was correlated with interval increase of bilateral OB volumes [right: 22.5 mm3 to 49.5 mm3 (120%), left: 37.5 mm3 to 42 mm3 (12%)] and improvement of mean olfactory FC [0.09 to 0.15 (66.6%)].

Cerebral Regional Homogeneity Alternation of Pregnant Women With Antenatal Depression During the Pandemic.

Purpose: The COVID-19 epidemic has been a threat to the health of people all over the world. Various precautions during COVID-19 in China have kept a large number of people in isolation, and this has inconvenienced and placed enormous stress on pregnant women. Pregnant women are more likely to suffer from antenatal depression (ANDP) with social isolation or low social support. This research aims to investigate the neurobiological mechanisms underlying ANDP, which impedes early detection and intervention in this disorder. Methods: A total of 43 singleton pregnant women who experienced isolation were recruited, including 21 treatment-naïve ANDP patients and 22 healthy pregnant women (HPW). To explore the intrinsic cerebral activity alternations in ANDP using resting-state functional MRI (rsfMRI), we assessed the local regional homogeneity (ReHo) differences in two groups using the voxel-based whole-brain analysis. The correlation between the regional functional abnormalities and clinical variables in ANDP patients was also examined. Results: Compared with HPW, ANDP patients showed decreased ReHo in the left dorsolateral prefrontal cortex, right insular and the cluster coving the right ventral temporal cortex (VTC), amygdala (AMG), and hippocampus (HIP). The Edinburgh Postnatal Depression Scale (EPDS) scores of ANDP patients negatively correlated with the ReHo in the right VTC, AMG, and HIP. Conclusion: Elucidating the neurobiological features of ANDP patients during COVID-19 is crucial for evolving adequate methods for early diagnosis, precaution, and intervention in a future epidemic.

Functional Connectome Prediction of Anxiety Related to the COVID-19 Pandemic.

OBJECTIVE: Increased anxiety in response to the COVID-19 pandemic has been widely noted. The purpose of this study was to test whether the prepandemic functional connectome predicted individual anxiety induced by the pandemic. METHODS: Anxiety scores from healthy undergraduate students were collected during the severe and remission periods of the pandemic (first survey, February 22-28, 2020, N=589; second survey, April 24 to May 1, 2020, N=486). Brain imaging data and baseline (daily) anxiety ratings were acquired before the pandemic. The predictive performance of the functional connectome on individual anxiety was examined using machine learning and was validated in two external undergraduate student samples (N=149 and N=474). The clinical relevance of the findings was further explored by applying the connectome-based neuromarkers of pandemic-related anxiety to distinguish between individuals with specific mental disorders and matched healthy control subjects (generalized anxiety disorder, N=43; major depression, N=536; schizophrenia, N=72). RESULTS: Anxiety scores increased from the prepandemic baseline to the severe stage of the pandemic and remained high in the remission stage. The prepandemic functional connectome predicted pandemic-related anxiety and generalized to the external sample but showed poor performance for predicting daily anxiety. The connectome-based neuromarkers of pandemic-related anxiety further distinguished between participants with generalized anxiety and healthy control subjects but were not useful for diagnostic classification in major depression and schizophrenia. CONCLUSIONS: These findings demonstrate the feasibility of using the functional connectome to predict individual anxiety induced by major stressful events (e.g., the current global health crisis), which advances our understanding of the neurobiological basis of anxiety susceptibility and may have implications for developing targeted psychological and clinical interventions that promote the reduction of stress and anxiety.