Adolescent functional network connectivity prospectively predicts adult anxiety symptoms related to perceived COVID-19 economic adversity.

BACKGROUND: Stressful events, such as the COVID-19 pandemic, are major contributors to anxiety and depression, but only a subset of individuals develop psychopathology. In a population-based sample (N = 174) with a high representation of marginalized individuals, this study examined adolescent functional network connectivity as a marker of susceptibility to anxiety and depression in the context of adverse experiences. METHODS: Data-driven network-based subgroups were identified using an unsupervised community detection algorithm within functional neural connectivity. Neuroimaging data collected during emotion processing (age 15) were extracted from a priori regions of interest linked to anxiety and depression. Symptoms were self-reported at ages 15, 17, and 21 (during COVID-19). During COVID-19, participants reported on pandemic-related economic adversity. Differences across subgroup networks were first examined, then subgroup membership and subgroup-adversity interaction were tested to predict change in symptoms over time. RESULTS: Two subgroups were identified: Subgroup A, characterized by relatively greater neural network variation (i.e., heterogeneity) and density with more connections involving the amygdala, subgenual cingulate, and ventral striatum; and the more homogenous Subgroup B, with more connections involving the insula and dorsal anterior cingulate. Accounting for initial symptoms, subgroup A individuals had greater increases in symptoms across time (ß = .138, p = .042), and this result remained after adjusting for additional covariates (ß = .194, p = .023). Furthermore, there was a subgroup-adversity interaction: compared with Subgroup B, Subgroup A reported greater anxiety during the pandemic in response to reported economic adversity (ß = .307, p = .006), and this remained after accounting for initial symptoms and many covariates (ß = .237, p = .021). CONCLUSIONS: A subgrouping algorithm identified young adults who were susceptible to adversity using their personalized functional network profiles derived from a priori brain regions. These results highlight potential prospective neural signatures involving heterogeneous emotion networks that predict individuals at the greatest risk for anxiety when experiencing adverse events.

The effect of acupuncture at the Yuji point on resting-state brain function in anxiety.

BACKGROUND: The COVID-19 epidemic has placed a lot of mental burdens on school students, causing anxiety. Clinically, it has been found that the Yuji point (LU10) can relieve anxiety by regulating Qi. METHODS: Thirty-six volunteers with anxiety disorders were divided into 3 groups, all of whom underwent 2 MRI examinations. The Yuji and nonacupoint groups received acupuncture between functional magnetic resonance imagings. We used the amplitude of low-frequency fluctuation to analyze regional brain activity, and seed-based functional connectivity (FC) to analyze changes in brain networks. RESULTS: After acupuncture, the LU10 was able to activate the frontal lobe, medial frontal gyrus, anterior cingulate gyrus, temporal lobe, hippocampus, etc in the left brain compared to the control group. The frontal lobe, medial frontal gyrus, cingulate gyrus, and anterior cingulate gyrus in the left brain were activated compared to those in the nonacupoint group. Compared with the control group, LU10 showed increased FC in the right parietal lobe, right precuneus, left temporal lobe, left superior temporal gyrus, and with cingulate gyrus. FC was enhanced among the hippocampus with the left temporal lobe and the superior temporal gyrus and reduced in the right lingual gyrus and right occipital lobe. CONCLUSION: Acupuncture at LU10s can regulate anxiety by upregulating or downregulating the relevant brain regions and networks. LU10s can be used to treat not only lung disorders but also related mental disorders.

Face processing in the infant brain after pandemic lockdown.

The role of visual experience in the development of face processing has long been debated. We present a new angle on this question through a serendipitous study that cannot easily be repeated. Infants viewed short blocks of faces during fMRI in a repetition suppression task. The same identity was presented multiple times in half of the blocks (repeat condition) and different identities were presented once each in the other half (novel condition). In adults, the fusiform face area (FFA) tends to show greater neural activity for novel versus repeat blocks in such designs, suggesting that it can distinguish same versus different face identities. As part of an ongoing study, we collected data before the COVID-19 pandemic and after an initial local lockdown was lifted. The resulting sample of 12 infants (9-24 months) divided equally into pre- and post-lockdown groups with matching ages and data quantity/quality. The groups had strikingly different FFA responses: pre-lockdown infants showed repetition suppression (novel > repeat), whereas post-lockdown infants showed the opposite (repeat > novel), often referred to as repetition enhancement. These findings provide speculative evidence that altered visual experience during the lockdown, or other correlated environmental changes, may have affected face processing in the infant brain.

Interdigitated Columnar Representation of Personal Space and Visual Space in Human Parietal Cortex.

Personal space (PS) is the space around the body that people prefer to maintain between themselves and unfamiliar others. Intrusion into personal space evokes discomfort and an urge to move away. Physiologic studies in nonhuman primates suggest that defensive responses to intruding stimuli involve the parietal cortex. We hypothesized that the spatial encoding of interpersonal distance is initially transformed from purely sensory to more egocentric mapping within human parietal cortex. This hypothesis was tested using 7 Tesla (7T) fMRI at high spatial resolution (1.1 mm isotropic), in seven subjects (four females, three males). In response to visual stimuli presented at a range of virtual distances, we found two categories of distance encoding in two corresponding radially-extending columns of activity within parietal cortex. One set of columns (P columns) responded selectively to moving and stationary face images presented at virtual distances that were nearer (but not farther) than each subject's behaviorally-defined personal space boundary. In most P columns, BOLD response amplitudes increased monotonically and nonlinearly with increasing virtual face proximity. In the remaining P columns, BOLD responses decreased with increasing proximity. A second set of parietal columns (D columns) responded selectively to disparity-based distance cues (near or far) in random dot stimuli, similar to disparity-selective columns described previously in occipital cortex. Critically, in parietal cortex, P columns were topographically interdigitated (nonoverlapping) with D columns. These results suggest that visual spatial information is transformed from visual to body-centered (or person-centered) dimensions in multiple local sites within human parietal cortex.SIGNIFICANCE STATEMENT Recent COVID-related social distancing practices highlight the need to better understand brain mechanisms which regulate "personal space" (PS), which is defined by the closest interpersonal distance that is comfortable for an individual. Using high spatial resolution brain imaging, we tested whether a map of external space is transformed from purely visual (3D-based) information to a more egocentric map (related to personal space) in human parietal cortex. We confirmed this transformation and further showed that it was mediated by two mutually segregated sets of columns: one which encoded interpersonal distance and another that encoded visual distance. These results suggest that the cortical transformation of sensory-centered to person-centered encoding of space near the body involves short-range communication across interdigitated columns within parietal cortex.

Enhanced resting-state EEG source functional connectivity within the default mode and reward-salience networks in internet gaming disorder.

BACKGROUND: The two key mechanisms affected by internet gaming disorder (IGD) are cognitive and reward processing. Despite their significance, little is known about neurophysiological features as determined using resting-state electroencephalography (EEG) source functional connectivity (FC). METHODS: We compared resting-state EEG source FC within the default mode network (DMN) and reward/salience network (RSN) between patients with IGD and healthy controls (HCs) to identify neurophysiological markers associated with cognitive and reward processing. A total of 158 young male adults (79 patients with IGD and 79 HCs) were included, and the source FC of the DMN and RSN in five spectral bands (delta, theta, alpha, beta, and gamma) were assessed. RESULTS: Patients with IGD showed increased theta, alpha, and beta connectivity within the DMN between the orbitofrontal cortex and parietal regions compared with HCs. In terms of RSN, patients with IGD exhibited elevated alpha and beta connectivity between the anterior cingulate gyrus and temporal regions compared with HCs. Furthermore, patients with IGD showed negative correlations between the severity of IGD symptoms and/or weekly gaming time and theta and alpha connectivity within the DMN and theta, alpha, and beta connectivity within the RSN. However, the duration of IGD was not associated with EEG source FC. CONCLUSIONS: Hyper-connectivities within the DMN and RSN may be considered potential state markers associated with symptom severity and gaming time in IGD.

Harmonized-Multinational qEEG norms (HarMNqEEG).

This paper extends frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qEEG nuisance variance. We ameliorate these weaknesses. (i) Create lifespan Riemannian multinational qEEG norms for cross-spectral tensors. These norms result from the HarMNqEEG project fostered by the Global Brain Consortium. We calculate the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 subjects. Instead of raw data, only anonymized metadata and EEG cross-spectral tensors were shared. After visual and automatic quality control, developmental equations for the mean and standard deviation of qEEG traditional and Riemannian DPs were calculated using additive mixed-effects models. We demonstrate qEEG "batch effects" and provide methods to calculate harmonized z-scores. (ii) We also show that harmonized Riemannian norms produce z-scores with increased diagnostic accuracy predicting brain dysfunction produced by malnutrition in the first year of life and detecting COVID induced brain dysfunction. (iii) We offer open code and data to calculate different individual z-scores from the HarMNqEEG dataset. These results contribute to developing bias-free, low-cost neuroimaging technologies applicable in various health settings.

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.

A Proposed Brain-, Spine-, and Mental- Health Screening Methodology (NEUROSCREEN) for Healthcare Systems: Position of the Society for Brain Mapping and Therapeutics.

The COVID-19 pandemic has accelerated neurological, mental health disorders, and neurocognitive issues. However, there is a lack of inexpensive and efficient brain evaluation and screening systems. As a result, a considerable fraction of patients with neurocognitive or psychobehavioral predicaments either do not get timely diagnosed or fail to receive personalized treatment plans. This is especially true in the elderly populations, wherein only 16% of seniors say they receive regular cognitive evaluations. Therefore, there is a great need for development of an optimized clinical brain screening workflow methodology like what is already in existence for prostate and breast exams. Such a methodology should be designed to facilitate objective early detection and cost-effective treatment of such disorders. In this paper we have reviewed the existing clinical protocols, recent technological advances and suggested reliable clinical workflows for brain screening. Such protocols range from questionnaires and smartphone apps to multi-modality brain mapping and advanced imaging where applicable. To that end, the Society for Brain Mapping and Therapeutics (SBMT) proposes the Brain, Spine and Mental Health Screening (NEUROSCREEN) as a multi-faceted approach. Beside other assessment tools, NEUROSCREEN employs smartphone guided cognitive assessments and quantitative electroencephalography (qEEG) as well as potential genetic testing for cognitive decline risk as inexpensive and effective screening tools to facilitate objective diagnosis, monitor disease progression, and guide personalized treatment interventions. Operationalizing NEUROSCREEN is expected to result in reduced healthcare costs and improving quality of life at national and later, global scales.

Ventromedial prefrontal cortex activity differentiates sick from healthy faces: Associations with inflammatory responses and disease avoidance motivation.

BACKGROUND: Humans are able to discern the health status of others using olfactory and visual cues, and subsequently shift behavior to make infection less likely. However, little is known about how this process occurs. The present study examined the neural regions involved in differentiating healthy from sick individuals using visual cues. METHODS: While undergoing a functional magnetic resonance imaging scan, participants (N = 42) viewed facial photos of 30 individuals (targets) who had been injected with an inflammatory challenge--low-dose endotoxin (i.e., sick) or placebo (i.e., healthy), and rated how much they liked each face. We examined regions implicated in processing either threat (amygdala, anterior insula) or cues that signal safety (ventromedial prefrontal cortex [VMPFC]), and how this activity related to their liking of targets and cytokine levels (interleukin-6, tumor necrosis factor-α) exhibited by the targets. RESULTS: Photos of sick faces were rated as less likeable compared to healthy faces, and the least liked faces were those individuals with the greatest inflammatory response. While threat-related regions were not significantly active in response to viewing sick faces, the VMPFC was more active in response to viewing healthy (vs. sick) faces. Follow-up analyses revealed that participants tended to have lower VMPFC activity when viewing the least liked faces and the faces of those with the greatest inflammatory response. CONCLUSIONS: This work builds on prior work implicating the VMPFC in signaling the presence of safe, non-threatening visual stimuli, and suggests the VMPFC may be sensitive to cues signaling relative safety in the context of pathogen threats.

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.

Brain reactivity to humorous films is affected by insomnia.

STUDY OBJECTIVES: Emotional reactivity to negative stimuli has been investigated in insomnia, but little is known about emotional reactivity to positive stimuli and its neural representation. METHODS: We used 3 Tesla functional magnetic resonance imaging (fMRI) to determine neural reactivity during the presentation of standardized short, 10- to 40-seconds, humorous films in patients with insomnia (n = 20, 18 females, aged 27.7 +/- 8.6 years) and age-matched individuals without insomnia (n = 20, 19 females, aged 26.7 +/- 7.0 years) and assessed humor ratings through a visual analog scale. Seed-based functional connectivity was analyzed for the left and right amygdalas (lAMYG and rAMYG, respectively) networks: group-level mixed-effects analysis (FLAME; FMRIB Software Library [FSL]) was used to compare amygdala connectivity maps between groups. RESULTS: fMRI seed-based analysis of the amygdala revealed stronger neural reactivity in patients with insomnia than in controls in several brain network clusters within the reward brain network, without humor rating differences between groups (p = 0.6). For lAMYG connectivity, cluster maxima were in the left caudate (Z = 3.88), left putamen (Z = 3.79), and left anterior cingulate gyrus (Z = 4.11), whereas for rAMYG connectivity, cluster maxima were in the left caudate (Z = 4.05), right insula (Z = 3.83), and left anterior cingulate gyrus (Z = 4.29). Cluster maxima of the rAMYG network were correlated with hyperarousal scores in patients with insomnia only. CONCLUSIONS: The presentation of humorous films leads to increased brain activity in the neural reward network for patients with insomnia compared with controls, related to hyperarousal features in patients with insomnia, in the absence of humor rating group differences. These novel findings may benefit insomnia treatment interventions. CLINICAL TRIAL: The Sleepless Brain: Neuroimaging Support for a Differential Diagnosis of Insomnia (SOMNET). ClinicalTrials.gov identifier: NCT02821234; https://clinicaltrials.gov/ct2/show/NCT02821234.

Brain Stress Mapping in COVID-19 Survivors Using MR Spectroscopy: New Avenue of Mental Health Status Monitoring$.

Coronavirus (COVID-19) has emerged as a human catastrophe worldwide, and it has impacted human life more detrimentally than the combined effect of World Wars I and II. Various research studies reported that the disease is not confined to the respiratory system but also leads to neurological and neuropsychiatric disorders suggesting that the virus is potent to affect the central nervous system (CNS). Moreover, the damage to CNS may continue to rise even after the COVID-19 infection subsides which may further induce a long-term impact on the brain, resulting in cognitive impairment. Neuroimaging techniques is the ideal platform to detect and quantify pathological manifestations in the brain of COVID-19 survivors. In this context, a scheme based on structural, spectroscopic, and behavioral studies could be executed to monitor the gradual changes in the brain non-invasively due to COVID-19 which may further help in quantifying the impact of COVID-19 on the mental health of the survivors. Extensive research is required in this direction for identifying the mechanism and implications of COVID-19 in the brain. Cohort studies are urgently required for monitoring the effects of this pandemic on individuals of various subtypes longitudinally.

Dealing with uncertainty: A high-density EEG investigation on how intolerance of uncertainty affects emotional predictions.

Intolerance of uncertainty (IU) can influence emotional predictions, constructed by the brain (generation stage) to prearrange action (implementation stage), and update internal models according to incoming stimuli (updating stage). However, neurocomputational mechanisms by which IU affects emotional predictions are unclear. This high-density EEG study investigated if IU predicted event-related potentials (ERPs) and brain sources activity developing along the stages of emotional predictions, as a function of contextual uncertainty. Thirty-six undergraduates underwent a S1-S2 paradigm, with emotional faces and pictures as S1s and S2s, respectively. Contextual uncertainty was manipulated across three blocks, each with 100%, 75%, or 50% S1-S2 emotional congruency. ERPs, brain sources and their relationship with IU scores were analyzed for each stage. IU did not affect prediction generation. During prediction implementation, higher IU predicted larger Contingent Negative Variation in the 75% block, and lower left anterior cingulate cortex and supplementary motor area activations. During prediction updating, as IU increased P2 to positive S2s decreased, along with P2 and Late Positive Potential in the 75% block, and right orbito-frontal cortex activity to emotional S2s. IU was therefore associated with altered uncertainty assessment and heightened attention deployment during implementation, and to uncertainty avoidance, reduced attention to safety cues and disrupted access to emotion regulation strategies during prediction updating.

Special Report on the Impact of the COVID-19 Pandemic on Clinical EEG and Research and Consensus Recommendations for the Safe Use of EEG.

INTRODUCTION: The global COVID-19 pandemic has affected the economy, daily life, and mental/physical health. The latter includes the use of electroencephalography (EEG) in clinical practice and research. We report a survey of the impact of COVID-19 on the use of clinical EEG in practice and research in several countries, and the recommendations of an international panel of experts for the safe application of EEG during and after this pandemic. METHODS: Fifteen clinicians from 8 different countries and 25 researchers from 13 different countries reported the impact of COVID-19 on their EEG activities, the procedures implemented in response to the COVID-19 pandemic, and precautions planned or already implemented during the reopening of EEG activities. RESULTS: Of the 15 clinical centers responding, 11 reported a total stoppage of all EEG activities, while 4 reduced the number of tests per day. In research settings, all 25 laboratories reported a complete stoppage of activity, with 7 laboratories reopening to some extent since initial closure. In both settings, recommended precautions for restarting or continuing EEG recording included strict hygienic rules, social distance, and assessment for infection symptoms among staff and patients/participants. CONCLUSIONS: The COVID-19 pandemic interfered with the use of EEG recordings in clinical practice and even more in clinical research. We suggest updated best practices to allow safe EEG recordings in both research and clinical settings. The continued use of EEG is important in those with psychiatric diseases, particularly in times of social alarm such as the COVID-19 pandemic.