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Biological Psychiatry: CNNI Archival Report Functional Brain Connectivity Prior to the COVID-19 Outbreak Moderates the Effects of Coping and Perceived Stress on Mental Health Changes: A First Year of COVID-19 Pandemic Follow-up Study María Cabello-Toscano, Lídia Vaqué-Alcázar, Gabriele Cattaneo, Javier Solana-Sánchez, Ivet Bayes-Marin, Kilian Abellaneda-Pérez, Dídac Macià-Bros, Lídia Mulet-Pons, Cristina Portellano-Ortiz, Miquel Angel Fullana, Laura Oleaga, Sofía González, Nuria Bargalló, Jose M. Tormos, Alvaro Pascual-Leone, and David Bartrés-Faz ABSTRACT BACKGROUND: The COVID-19 pandemic provides a unique opportunity to investigate the psychological impact of a global major adverse situation. Our aim was to examine, in a longitudinal prospective study, the demographic, psychological, and neurobiological factors associated with interindividual differences in resilience to the mental health impact of the pandemic. METHODS: We included 2023 healthy participants (age: 54.32 6 7.18 years, 65.69% female) from the Barcelona Brain Health Initiative cohort. A linear mixed model was used to characterize the change in anxiety and depression symptoms based on data collected both pre-pandemic and during the pandemic. During the pandemic, psychological variables assessing individual differences in perceived stress and coping strategies were obtained. In addition, in a subsample (n = 433, age 53.02 6 7.04 years, 46.88% female) with pre-pandemic resting-state functional magnetic resonance imaging available, the system segregation of networks was calculated. Multivariate linear models were fitted to test associations between COVID-19–related changes in mental health and demographics, psychological features, and brain network status. RESULTS: The whole sample showed a general increase in anxiety and depressive symptoms after the pandemic onset, and both age and sex were independent predictors. Coping strategies attenuated the impact of perceived stress on mental health. The system segregation of the frontoparietal control and default mode networks were found to modulate the impact of perceived stress on mental health. CONCLUSIONS: Preventive strategies targeting the promotion of mental health at the individual level during similar adverse events in the future should consider intervening on sociodemographic and psychological factors as well as their interplay with neurobiological substrates. https://doi.org/10.1016/j.bpsc.2022.08.005 The COVID-19 pandemic has resulted in an unprecedented anxiety and depressive symptoms have been observed, which impact, with more than 400 million people affected and 6 are higher than the usual incidence rate observed in the gen- million deaths worldwide by mid-March 2022 (https://www. eral population [e.g., (2,3)]. Nonetheless, many of the initial worldometers.info/coronavirus/?utm_campaign=homeAdvegas1). studies investigating mental health effects of the COVID-19 From its inception, this pandemic has been highlighted as a pandemic have been cross-sectional and have lacked com- health and societal threat, not only owing to the direct negative parable pre-pandemic baseline data. These methodological effects of SARS-CoV-2 infection but also because of the long- constraints limit the interpretation of findings; in fact, other term restrictions imposed by governments and authorities studies challenge the assumption that the effect of the attempting to prevent or limit the spread of the virus. General pandemic on mental health can be described as a significant confinements and quarantines, along with other protective overall negative impact on anxiety and depressive symptoms measures, closure of businesses, and limitation of social in- (4,5). There also remains inconsistency among studies with teractions, can be expected to result in multiple psychological preoutbreak data, with some studies reporting significant in- sequelae (1). Accordingly, overall rates of around 30% in creases in psychological distress (6,7) and others highlighting SEE COMMENTARY ON PAGE 133 200 ª 2022 Society of Biological Psychiatry. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Biological Psychiatry: Cognitive Neuroscience and Neuroimaging February 2023; 8:200–209 www.sobp.org/BPCNNI ISSN: 2451-9022 Biological Psychiatry: COVID-19: Neural Networks and Mental Health CNNI general null effects (4). Other research has highlighted the high and that both sociodemographic and psychological factors prevalence of individuals showing resilient outcomes, and in would influence this change in anxiety and depression general, the need to consider different, even opposite, trajec- symptoms. We also predicted that basal connectivity status tories across groups of individuals (8,9). of particular resilience-related networks, such as those Resilience is a broad term that generally refers to the involving frontal, limbic, cingulate, or DMN areas, would in- interindividual differences with regard to the ability to resist fluence the degree of pandemic-related change in psycho- the impact of an illness or stress (10). Hence, in the context of logical distress experienced by our cohort. this study, resilience can be defined as the lack of anxiety or depression during the COVID-19 pandemic. Psychological variables, such as coping abilities, are defined as behaviors to METHODS AND MATERIALS protect oneself by avoiding psychological harm from bad experiences (11) and have been shown to be strongly asso- Study Design and Participants ciated with resilience to life traumas (12). Moreover, the role of Study participants were part of the BBHI (Barcelona Brain distinct neurobiological substrates of resilience have been Health Initiative; https://bbhi.cat/en/), an ongoing longitudinal highlighted (13). Both neuroimaging (14,15) and neurophysi- cohort study investigating the determinants of brain and ological (16) studies in humans have revealed that the integ- mental health in healthy middle-aged and older adults. rity/functionality of specific brain networks are associated Recruitment started in 2017, when multiple initiatives (including with different response adaptations to major threatening life conferences, radio and television interviews, and social media events or during experimental investigations (17). Specifically, advertisements) took place to encourage participants to join numerous studies point out anatomical and functional impli- the study. The BBHI’s main inclusion criteria are the absence cations on resilience of different frontal (e.g., dorsolateral, of neurological, psychiatric, or unstable medical diagnoses and orbitofrontal) and limbic (e.g., amygdala, insula, or striatum) no cognitive impairment. The BBHI includes periodic cognitive, areas, midline structures integrated within the default mode medical, brain imaging, and biological assessments (26,27). network (DMN) (14), and the cingulate cortex (18–20). This study refers to a BBHI substudy aimed at investigating Concurrently, graph theory approaches for the study of brain mental health during the COVID-19 pandemic (10,28). connectivity enable the description of the dynamics of brain Data acquisition included a longitudinal design with mea- organization (21). More specifically, the effective functioning sures of anxiety and depression symptoms collected 2 times of the network seems to be supported by maintaining the before the pandemic outbreak (i.e., pre-pandemic) between separation of subnetworks while enabling integration be- 2018 and 2020 (average interval, 12.73 6 2.18 months) and 5 tween them. This harmony can be quantified by metrics such assessments separated on average by 3.04 6 2.29 months as system segregation (SyS), which summarizes the balance and covering the first year of the COVID-19 pandemic (i.e., between integration within and between networks in a single from March 2020 to March-April 2021) (Figure 1). The primary value (22). SyS variability has been studied specifically in the outcome measure for this study was symptoms of anxiety and context of aging, cognition (23), and resilience to neurode- depression as assessed with the Patient Health Questionnaire- generative disease (24), but it remains poorly explored in the 4 (PHQ-4) (see Questionnaires). Only participants who had context of mental health resilience. valid PHQ-4 measures obtained at least once pre-pandemic Altogether, these lines of evidence suggest that the and once during the pandemic were included (see interaction of an individual’s psychological resources (e.g., Questionnaires). Furthermore, because our focus was on coping strategies) with brain functional characteristics studying the impact of the COVID-19 pandemic on the healthy should predict individual differences in resilience versus population, we excluded all individuals who had scores sug- vulnerability to mental health outcomes in the face of a gesting a possible meaningful clinical status at any of the pre- sustained stressful situation (e.g., perceived stress during pandemic assessments (i.e., PHQ-4 scores equal to or above the COVID-19 pandemic). Therefore, taking advantage of 6) according to recommended cutoffs (29) (see BBHI vs whole longitudinal data collected starting 2 years pre-pandemic sample in the Supplement for more information on sample and during the first year of the pandemic on several occa- differences). For our main objective, only those participants sions, we first aimed to investigate whether a general change who had available baseline magnetic resonance imaging (MRI) in anxiety and depression symptoms could be observed in acquisitions before the outbreak that met the quality check our sample of healthy middle-aged individuals as well as to inspection requirements and had normative neuroradiological validate previous findings regarding the influence of principal reports (e.g., no brain tumor suspicions, stroke, or moderate to sociodemographic factors (i.e., age, sex, and education) severe white matter damage) were included. In addition, data (6,25). Second, we aimed to determine whether psychologi- from 7 participants were discarded because of outlier values in cal factors (perceived stress and coping strategies) the functional connectivity (FC) measures (see FC Measures). explained the change in anxiety and depressive symptoms. This led to a study sample of 2023 participants and 10,367 Finally, as our main goal, we were interested in elucidating observations and a subsample of 433 MRI-available in- whether the connectivity status of brain networks was able dividuals and 2358 observations (Figure S1). The study was to predict, either in an independent manner or by the inter- approved by the Unió Catalana d’Hospitals ethics committee action with the studied psychological factors, the change in (approval references: CEIC 17/06 and CEI 18/07). Written psychological distress associated with the pandemic. We informed consent was obtained from all participants in hypothesized that we would be able to identify a significant accordance with the Code of Ethics of the World Medical change in psychological distress related to the pandemic Association (Declaration of Helsinki). Biological Psychiatry: Cognitive Neuroscience and Neuroimaging February 2023; 8:200–209 www.sobp.org/BPCNNI 201 Biological Psychiatry: CNNI COVID-19: Neural Networks and Mental Health Pre-COVID19 During-COVID19 PHQ-4 PSS Figure 1. Timeline study design showing baseline BRCS MRI (i.e., pre-pandemic) and during-pandemic points of OUTBREAK in Spain acquisition for the main outcome (i.e., Patient Health Questionnaire-4 [PHQ-4]), magnetic resonance im- aging (MRI), and psychological factors (perceived stress measured by the Perceived Stress Scale March M Mar ch A il May June h April J O t b October March-April r Ap rch rch-Ap [PSS] and coping strategies measured by the Brief 23-27th 5-10th 1-31st 1-7th 5-18th 15-5th Resilient Coping Scale [BRCS]). On the left and 2018 - early 2020 2020 2021 colored in purple are pre-pandemic data including 1 MRI acquisition and 2 online PHQ-4 measures ob- tained between 2018 and 2020 (average follow-up: 12.73 6 2.18 months). The beginning of the pandemic outbreak was defined according to the Spanish Government’s State of Emergency declaration on March 14, 2020. On the right and colored in green, 6 online questionnaires were administered during the first year of the COVID-19 pandemic (until March–April 2021). Each questionnaire was available for answering during the specified data periods shown. Questionnaires to generate a new variable termed PHQ-4 change (i.e., The main outcome was anxiety and depression symptoms change in anxiety and depression symptoms) where positive assessed with the PHQ-4, a valid ultra-brief tool consisting of 4 values meant PHQ-4 increases during compared with pre- Likert-type scale items for detecting both anxiety and pandemic observations (i.e., anxiety and depression symp- depressive disorders (29). Perceived stress was assessed with toms worsening). To analyze the associations between soci- the Perceived Stress Scale, a 14-item, 5-point Likert-type odemographic variables and PHQ-4 change, a linear scale including questions about feelings and thoughts during regression model was fitted in which PHQ-4 change was the the past month (30). The Brief Resilient Coping Scale is a 4- outcome and sex, age, and education were the predictor item, 5-point Likert-type scale used to estimate the tendency variables of interest. In addition, an analogous linear mixed- to effectively use coping strategies in flexible, committed ways effect model was fitted by including only pre-pandemic ob- to actively solve problems despite stressful circumstances servations. Then we fitted 3 linear regression models in which (31). For further details regarding the questionnaires, see the PHQ-4 change was the outcome and the predictors were Supplement. coping strategies, perceived stress, and their interaction. Finally, we fitted a set of linear regression models to predict FC Measures PHQ-4 change, in which SyS values from the 7 studied resting-state networks were included as independent vari- MRI data were acquired using a 3T Siemens scanner (Mag- ables. In this way, we tested whether there was a direct as- netom Prisma; Siemens Healthineers) with a 32-channel head coil at the Unitat d’Imatge per Ressonància Magnètica Institut sociation between any network SyS and PHQ-4 change and whether SyS measures modulated the effects of the psy- d’Investigacions Biomèdiques August Pi i Sunyer at Hospital Clínic de Barcelona, Barcelona, Spain. Resting-state functional chological factors (i.e., perceived stress and coping strate- gies) on the outcome. In addition, 2 analogous models were MRI scans were preprocessed, and then we quantified individual resting-state FC within and between resting-state networks as fitted to test for any association between SyS values and coping strategies or perceived stress, respectively. All these defined in the Schaefer-Yeo atlas of 100 nodes and 7 networks (32,33) (available at: https://github.com/ThomasYeoLab/CBIG/ models were adjusted for age, sex, socioeconomic status, employment situation during the pandemic, average pre- tree/master/stable_projects/brain_parcellation/Schaefer2018_ LocalGlobal for the calculation of the SyS metric (22). Here, SyS pandemic levels of anxiety and depression symptoms, and number of months between the last questionnaire adminis- values were considered as outliers when they were 3 standard deviations over or under the average (i.e., |z score| , 3, where tered before the pandemic and the first questionnaire administered during the pandemic. z score = [x 2 mean]/SD). As a result, 7 participants were excluded from the final sample. See the Supplement for further details regarding the acquisition parameters, preprocessing, and SyS. RESULTS Statistical Analyses Sample Demographics and Psychological All statistical analyses were written in R language (version Characteristics 3.6.2) (34) and run in RStudio (version 1.3.1093) (35). This study included a total sample of 2023 participants (age: To investigate the change in anxiety and depression 54.32 6 7.18 years, 65.69% female) and a subsample of 433 symptoms (i.e., PHQ-4 scores) along all the time points, a individuals with available MRI data (age: 53.02 6 7.04 years, linear mixed-effect model was first fitted for the whole sample 46.88% female) from the BBHI cohort (26,27). At baseline and using the lmer function from the lme4 R package (36). In this as per inclusion criteria, all the subjects presented normal to model, fixed and random effect coefficients were estimated mild symptomatology (i.e., PHQ-4 . 6 within a range of 0–12) for a binary variable indicating whether each observation before the pandemic outbreak. Regarding psychological fac- belonged to pre-pandemic assessments or to assessments tors of vulnerability (i.e., perceived stress) and those associ- made during the pandemic (i.e., COVID-19 period) to quantify ated with mechanisms of resilience (i.e., coping strategies), pandemic-related PHQ-4 general and individual changes, both samples mostly presented medium to high coping and respectively. The individual effect coefficients were extracted low to moderate stress profiles (Table 1). 202 Biological Psychiatry: Cognitive Neuroscience and Neuroimaging February 2023; 8:200–209 www.sobp.org/BPCNNI Biological Psychiatry: COVID-19: Neural Networks and Mental Health CNNI Table 1. Sample Characteristics Changes in Anxiety and Depressive Symptoms: Age Whole Sample, MRI Subsample, and Sex Effects Characteristic N = 2023 n = 433 A linear mixed-effect model on the total sample showed that Age, Years 54.32 6 7.18 53.02 6 7.04 PHQ-4 scores increased during the pandemic compared with Sex pre-pandemic (during the pandemic . pre-pandemic: b = Female 1329 (65.69%) 203 (46.88%) 0.229, t = 7.428, p , .001) (Figure 2). The random effect co- Male 694 (34.31%) 230 (53.12%) efficients estimated for each individual were used to compute Educational Levela the PHQ-4 change variable (Figure S2). PHQ-4 change was Primary 67 (3.31%) 12 (2.77%) negatively associated with age (b = 20.006, t = 24.084, p , Secondary 436 (21.55%) 104 (24.02%) .001) (see Figure S3A) but not with educational level (b = 0.034, t = 1.683, p = .092). This model (adjusted R2 [a-R2] = 0.278) Higher 1520 (75.14%) 317 (73.21%) also revealed that female individuals had higher PHQ-4 change Socioeconomic Statusb,c values than males (b = 0.141, t = 6.622, p , .001) (Figure S3B). Low 51 (2.53%) 10 (2.31%) In addition, we did not find any interaction between age and Low2middle 374 (18.54%) 83 (19.17%) sex associated with our outcome (a-R2 = 0.278; age 3 sex Middle2high 1198 (59.40%) 234 (54.04%) interaction; b = 20.004, t = 21.225, p = .221). Finally, High 394 (19.53%) 106 (24.48%) considering only baseline data, we found that female (females Employment During the Pandemicd . males; b = 0.261, t = 4.299, p , .001) and younger in- Employed 1123 (55.51%) 266 (61.43%) dividuals (age: b= 20.158, t = 24.338, p , .001) had higher Unemployed 900 (44.49%) 167 (38.57%) pre-pandemic PHQ-4 values. Anxiety and Depressione The results of repeating these analyses for the MRI sub- Pre-pandemic sample (n = 433) can be found in the Supplement. Normal2mild, 0–5 2023 (100%) 433 (100%) Moderate2severe, 6–12 0 (0.00%) 0 (0.00%) Changes in Effects of Perceived Stress and Coping During the pandemic Strategies on Anxiety and Depressive Symptoms Normal2mild, 0–5 1818 (89.87%) 400 (92.38%) In the total sample, we fitted 3 different linear models. The first Moderate2severe, 6–12 205 (10.13%) 33 (7.62%) model (a-R2 = 0.337) showed a negative association between Coping Strategiesc,e coping strategies and PHQ-4 change (b = 20.069, Low, 4–13 371 (18.70%) 60 (13.92%) t = 214.147, p , .001), and the second model (a-R2 = 0.421) showed a positive association between perceived stress and Medium, 14–16 1106 (55.75%) 226 (52.44%) PHQ-4 change (b = 0.036, t = 19.241, p , .001). Finally, the High, 17–20 507 (25.55%) 145 (33.64%) third model (a-R2 = 0.447) revealed that the change was Perceived Stressc,e significantly described by an interaction between perceived Low, 0–13 465 (30.80%) 128 (38.65%) stress and coping strategies (b = 20.003, t = 24.370, p , .001) Moderate, 14–26 928 (61.46%) 188 (55.29%) (Figure 3A). In the latter analysis, the direct effect of perceived High, 27–40 117 (7.75%) 24 (7.06%) stress on PHQ-4 was reduced but maintained (b = 0.075, t = Continuous variables are described by mean 6 SD values, while 7.085, p , .001), while the direct effect of coping strategies on categorical variables are described by the absolute number of anxiety and depressive symptoms change disappeared (b = individuals and its corresponding percentage (%) within the sample. 0.001, t = 0.801, p = .423) (Figure 3B). BRCS, Brief Resilient Coping Scale; MRI, magnetic resonance imaging; The results of repeating these analyses for the MRI sub- PHQ-4, Patient Health Questionnaire-4; PSS, Perceived Stress Scale. a Primary educational level corresponds to general basic education sample (n = 433) were in accordance with those in the total or equivalent (8 years approximately), secondary corresponds to sample (see the Supplement). baccalaureate or equivalent (up to approximately 12 years), and higher corresponds to university degrees such as diploma, degree, Changes in Anxiety and Depression Symptoms as a Master, or Ph.D. (over 12 years). Function of Brain Network Status and Psychological b Socioeconomic status corresponds to the approximate range of the individuals’ monthly family income (low: ,1000; low-middle: 1000–2000; Factors middle-high: 2000–5000; high: .5000; all amounts in euros). Nonsignificant direct associations between mental health c Missing data are due to noncompletion of the questionnaires by change, coping strategies, and perceived stress and any of the participants. d SyS values were found (all p values . .05). However, we aimed An individual was considered as employed when answered so at all time points. to test whether SyS variables were able to modulate the e Psychological variables are described here as categories created perceived stress effect on PHQ-4 change or the modulatory according to available cutoffs regarding severity of anxiety and effect of coping strategies (i.e., PHQ-4 change w coping depressive symptomatology (i.e., PHQ-4), level of coping strategies strategies 3 perceived stress interaction). The first model (i.e., BRCS), and perceived stress (i.e., PSS). Note that this (a-R2 = 0.536) showed a significant interaction between the categorization was done under descriptive purposes, but these frontoparietal control network SyS (FPCN-SyS) (Figure 4A) and variables were used as continuous in this study. In addition, as anxiety and depression were assessed on multiple occasions in both perceived stress (b = 0.108, t = 2.446, p = .009) (Figure 4C) and periods (pre-pandemic and during the pandemic), a subject was between the DMN-SyS (DMN-SyS) (Figure 4B) and perceived considered to present moderate to severe symptomatology when stress (b = 20.096, t = 22.626, p = .015) (Figure 4D) to the scoring within this range at least once. described PHQ-4 change. These interactions show that higher Biological Psychiatry: Cognitive Neuroscience and Neuroimaging February 2023; 8:200–209 www.sobp.org/BPCNNI 203 Biological Psychiatry: CNNI COVID-19: Neural Networks and Mental Health even after accounting for the effects of coping strategies, it appears that these could be independent of each other. Finally, the second model (a-R2 = 0.539) showed a trend toward sig- nificance between the limbic network SyS variable and the coping strategies’ effect on the association between perceived stress and PHQ-4 (b = 20.024, t = 21.727, p = .085) in the sense that a higher limbic network SyS could be related to an increased effect of coping strategies as a psychological reg- ulatory mechanism (Figure S4). DISCUSSION This study found a general increase in anxiety and depressive symptoms during the COVID-19 pandemic in a healthy middle- aged population where age and sex were found as indepen- dent predictors. We identified that coping strategies attenu- ated the impact of perceived stress on mental health. Finally, to our knowledge, this is the first study to identify the modu- lation of the impact of perceived stress on anxious-depressive responses through baseline FPCN and DMN network con- nectivity balance. Our findings revealed a measurable COVID-19 impact on mental health among healthy middle-aged individuals, arguing against a complete lack of a general effects (4). However, only Figure 2. Average values of the Patient Health Questionnaire-4 (PHQ-4) approximately 10% of individuals were found to surpass the along time point measurements for the whole sample (N = 2023) showing suggested clinical cutoff scores at any time point during the ratings increases. Shadow areas above and below the average PHQ-4 line pandemic. This finding reflects lower estimates, consistent (i.e., thick line) represent standard errors. Abscissa axes indicate the timeline with recent reviews (36) ranging from 20% to .30% (2,3) and of observations in the study, which are grouped within pre-pandemic (i.e., also suggests the presence of an overall high proportion of from 2018 to early 2020) and during-pandemic observations (i.e., those from resilient outcomes (8,37,38). In addition, our results provide March 2020 to March–April 2021). The green line indicates the beginning of the lock-down (March 14, 2020 in Spain) and separates pre-pandemic and confirmatory evidence that female individuals experienced the during-pandemic observations. Black vertical dashed lines delimit 2020 and psychological impact of COVID-19 to a greater extent than 2021. Finally, in the upper part of the figure, the increase in PHQ-4 values at males, in accordance with a previous large population proba- points during the pandemic compared with pre-pandemic is indicated. bility study (6) and with former meta-analytical evidence (2). Furthermore, our study is in accordance with many previous reports indicating higher rates of psychological distress during FPCN-SyS levels enhanced the positive association between the pandemic among younger individuals (5,37). However, it perceived stress and PHQ-4 change. Conversely, higher levels should be noted that a recent review studying the impact of of DMN-SyS attenuated the association between perceived age on mental health changes during the pandemic (39) stress and PHQ-4 change (Figure 4E) similar to the modulation highlighted heterogeneous findings in the literature. In fact, by coping strategies, which remained significant in this model there are also reports indicating that rates of relevant mental (b = 20.003, t = 22.136, p = .033). Because these 2 neural health aspects such as loneliness increased progressively mechanisms (i.e., FPCN-SyS and DMN-SyS) were significant during successive pandemic months among older adults (40). Figure 3. Plots illustrating the associations found between the studied psychological factors (i.e., coping strategies and perceived stress) and psy- chological distress worsening (i.e., Patient Health Questionnaire-4 [PHQ-4] change). (A) Scatter and lines plot showing the association between PHQ-4 change (vertical axis) and perceived stress (hori- zontal axis) as modulated by coping strategies. Dots show individual observations of PHQ-4 change and perceived stress for 2 groups with low (in brown; i.e., below median) and high (in green; i.e., above median) coping strategies. Thick lines illustrate estimated slopes for the association between PHQ-4 change and perceived stress for extreme minimum and maximum levels of low (in brown) and high (in green) coping strategies. This difference between slopes was found to be significant as an interaction between coping strategies and perceived stress to predict PHQ-4 change. Shadow areas above and below the slope lines represent standard errors. (B) Schema of the associations between variables of psychological factors and psychological distress worsening. 204 Biological Psychiatry: Cognitive Neuroscience and Neuroimaging February 2023; 8:200–209 www.sobp.org/BPCNNI Biological Psychiatry: COVID-19: Neural Networks and Mental Health CNNI Figure 4. Representation of the modulatory effect of frontoparietal control network (FPCN) and default mode network (DMN) system segregation (SyS) values on the association between perceived stress and Patient Health Questionnaire-4 (PHQ-4) change. (A, B) Graphs representing within- and between- network connectivity taking part in the computation of FPCN and DMN-SyS values, respectively. Nodes in the graph represent studied regions of interest (ROIs) as defined by the Schaefer-Yeo atlas of 100 nodes and 7 networks. The nodes and edges in light orange illustrate ROIs and within-network connec- tivity of the studied network (i.e., FPCN or DMN), while those in gray refer to outside network ROIs and the connectivity between them and the studied network. These graphs were created with the BrainNet Viewer (http://www.nitrc.org/projects/bnv/). (C, D) Scatter and lines plot showing the association between PHQ-4 change (vertical axis) and perceived stress (horizontal axis), as modulated by values of SyS, from the FPCN in panel (C) and the DMN in panel (D). Dots show individual observations of PHQ-4 change and perceived stress for 2 groups with low (in brown; i.e., below median) and high (in green; i.e., over median) SyS values. Thick lines illustrate estimated slopes for the association be- tween PHQ-4 change and perceived stress for extreme minimum and maximum levels of low (in brown) and high (in green) SyS. This difference be- tween slopes was found significant as an interaction between each particular SyS variable and perceived stress to predict PHQ-4 change. Shadow areas above and below the slope lines represent standard errors. (E) Schema of the associations between perceived stress and psychological distress wors- ening, as regulated by FPCN-SyS, DMN-SyS, and coping strategies. In addition, it should be noted that our findings may not apply Notwithstanding the impressive amount of research related to particular aged populations, i.e., those with medical diag- to the psychological impact of the COVID-19 pandemic, few nosis for risk conditions, those of extreme ages, or those in reports have considered functional brain status characteristics specific situations (i.e., individuals who are institutionalized). as predictors of associated mental health outcomes (47–52). Our observation that people who experienced greater levels of We observed that areas conforming the FPCN (largely over- perceived stress exhibited increased levels of anxiety and lapping with the executive control network) should be depressive symptoms pre-pandemic compared with post- considered as relevant neurobiological indicators of individual pandemic outbreak is aligned with the stress-vulnerability differences in mental health outcomes during the COVID-19 models of psychopathology (41). Negative associations be- pandemic. This network connecting the prefrontal dorsolat- tween coping and anxiety and depressive symptoms also fit eral and the superior parietal cortices supports executive with the understanding of coping abilities as cognitive and functions, is central to adequate social navigating and behavioral strategies that individuals use to manage stressful achievement of long-term goals (53), and has been identified situations (42). Previous research has reported a positive with resilience processes (14,15,54). Prior research showed impact of coping behaviors on anxiety and depressive symp- that the FPCN and more specifically the dorsolateral prefrontal toms during the pandemic, both in the general population cortex orchestrate a regulatory role over other cortical and (5,43) and in specific risk groups (44,45). Hence, our findings subcortical regions related to cognitive emotion regulation confirm the relevance of coping behaviors and highlight the (55–57). Such aspects may therefore help explain the obser- fact that they may benefit mental health status primarily vation of a modulatory role of the FPCN on buffering the through an attenuation of the negative impact of perceived negative effects of perceived stress on the expression of stress (11,46). anxiety and depressive symptoms. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging February 2023; 8:200–209 www.sobp.org/BPCNNI 205 Biological Psychiatry: CNNI COVID-19: Neural Networks and Mental Health Our results also highlight the role of the DMN in attenuating of anxiety (66) and depressive symptoms (67,68). Notably, the the impact of perceived stress on change in anxiety and combination of such techniques with electroencephalography depressive symptoms. Abnormal DMN functionality (along with and/or functional MRI allows for modulation of the spatio- FPCN and salience network dysfunctions) is characteristic of temporal dynamics of specific brain networks in an individu- anxiety and depression disorders (58,59), including the fact alized manner (69–73). Furthermore, the brain responses that individual anatomic and functional differences within this evoked by stimulation may hold predictive value regarding circuit contribute to individual differences in psychological clinical and behavioral outcomes (74). Hence, such experi- resilience (14). The DMN is also involved in interindividual mentally controlled approaches could be integrated with variability in stress responsiveness (60) and may contribute to other factors to predict an individual’s risk of experiencing behavioral homeostasis in response to induced stressors (61). negative mental health impact in the event of unexpected and In our study, the effects of the DMN operated in an opposite sustained stressors (10). manner than the FPCN (i.e., higher SyS for the DMN and lower Our study is not without limitations. First, we used the PHQ- SyS for the FPCN attenuated the effect of high perceived 4 as the primary outcome measure to maximize the fact that stress), which may be related to the inverse FC changes be- we had assessments across all the time points (pre-pandemic tween the 2 networks during exposure to sustained stress (17). and during the pandemic) for this variable, but we acknowl- Here, beyond exclusively considering the role of brain network edge that it may entail constraints in terms of the sensitivity intrinsic connectivity as markers of vulnerability versus resil- and specificity of the mental health symptoms assessed. ience, our study stresses the need to interpret effects in the Second, the included sample exhibits particular characteris- context of a given individual’s psychological resources. In this tics, in part because of the recruitment method used, notably regard, we found a trend toward significance, suggesting that the fact that the sample is composed of individuals with high higher segregation of orbital (i.e., the ventromedial prefrontal interest in their own brain health, with an underrepresentation cortex) and temporal pole regions, constituting the limbic of low mental health rates and with a high educational level. network previously associated with cognitive reappraisal and Hence, even though the lack of effects for education in our resilience (62), could be related to greater protective effects of study aligns with previous reports (11), findings might have an individual’s coping capacities on final mental health out- differed if the sample had included a greater representation of comes. To our knowledge, previous publications in the field individuals with no or fewer educational qualifications (25). testing associations between mental health and brain network Third, many other variables including individual dispositional characteristics have mainly used metrics of internetwork or factors, health- and family-related issues, and environmental intranetwork FC (60). In this light, we based our analyses in a and cultural aspects possibly affecting the investigated graph theory–based metric able to capture the organizational outcome were not considered here [see Discussion in (75)]. In properties supporting brain function (22), a functional archi- this regard, the availability of pre-pandemic information tecture measure that has been used in other contexts to regarding perceived stress would have been useful to better characterize the neurobiological substrates of resilience (63). characterize the COVID-19–related impact on this variable of Taken together, these findings highlight the need to interest. Particularly, information about ethnicity and race was consider the study of resilience using a person-centered not included in our analyses because we did not collect in- approach wherein relevant contributing factors (psychologi- formation about ethnicity and because our population was cal, lifestyles, sociocultural, and neurodevelopmental as- homogeneous, mostly considering themselves Caucasian or pects) should ultimately be integrated and where effects of White (i.e., 94.39%). It should also be noted that owing to our neurobiological markers should be interpreted within this inclusion criteria, our results might not generalize to samples of context (10). Our results may have implications for enabling patients or those individuals exhibiting higher pre-pandemic preventive strategies not only for the current COVID-19 anxiety and depression scores. Finally, the analytical pandemic but also in the face of similar future events. First, approach was neither specifically designed to formally test for cognitive behavioral interventions to improve coping strate- changes across temporal pandemic stages nor designed to gies combined with stress reduction approaches (e.g., investigate group trajectories potentially contributing to longi- mindfulness-based stress reduction) may be of benefit, tudinal individual differences (37,38), which will be the matter particularly for individuals with high levels of perceived stress, of future investigations. female individuals, and younger individuals. Second, the In conclusion, leveraging data from a longitudinal pro- status of functional brain networks was shown to be a valu- spective study including a large sample of healthy middle-aged able predictor of the probability of response to psychological individuals and multiple data points spanning from 2 years interventions [see (63) for a meta-analysis] and can reveal prior to the SARS-CoV-2 outbreak until the end of the first year neural mechanistic effects of successful treatments (64,65). of the pandemic, we have been able to elucidate how basic Our observation that such functional features moderate the sociodemographic measures, psychological factors, and effect of psychological resources on mental health suggests neurobiological characteristics relate to a general measure of that a combined approach that uses brain imaging to monitor mental health impact. FPCN and DMN segregation/integration whether the effects of interventions are targeting such key status was found to modulate the influence of psychological circuits may be of particular interest. Finally, this approxi- factors, acting through distinct pathways, and conferring mation could also benefit from the use of approaches that interindividual differences in vulnerability versus resilience allow a direct modulation of brain network connectivity. Here, regarding the change in psychological distress associated with noninvasive brain stimulation may directly improve symptoms the COVID-19 pandemic. 206 Biological Psychiatry: Cognitive Neuroscience and Neuroimaging February 2023; 8:200–209 www.sobp.org/BPCNNI Biological Psychiatry: COVID-19: Neural Networks and Mental Health CNNI ACKNOWLEDGMENTS AND DISCLOSURES staff and general public – A systematic review and meta-analysis. Psychiatry Res 291:113190. This work was supported by a grant from the Agència de Gestió d’Ajuts 3. Salari N, Hosseinian-Far A, Jalali R, Vaisi-Raygani A, Rasoulpoor S, Universitaris I de Recerca (AGAUR) PANDÈMIES 2020 (Grant No. Mohammadi M, et al. (2020): Prevalence of stress, anxiety, 2020PANDE00043 [to DB-F]) and a grant from La Marató de TV3 depression among the general population during the COVID-19 MARATÓ 2020 COVID-19 (Grant No. 202129-31). It was supported in part pandemic: A systematic review and meta-analysis. Global Health by the Spanish Ministry of Science, Innovation and Universities (Grant No. 16:57. RTI2018-095181-B-C21 [to DB-F]) and an Institut Català de Recerca i 4. van der Velden PG, Contino C, Das M, van Loon P, Bosmans MWG Estudis Avançats (ICREA) Academia 2019 grant award (to DB-F). This (2020): Anxiety and depression symptoms, and lack of emotional research received partial funding from La Caixa Foundation (Grant No. LCF/ support among the general population before and during the COVID- PR/PR16/11110004) and from the Institut Guttmann and Fundació Abertis. 19 pandemic. A prospective national study on prevalence and risk LV-A was supported by a Margarita Salas postdoctoral fellowship. LM-P factors. J Affect Disord 277:540–548. was supported by a fellowship associated with the Ministerio de Ciencia e 5. Fullana MA, Littarelli SA (2021): Covid-19, anxiety, and anxiety-related Innovación/Fondo Europeo de Desarrollo Regional RTI2018-095181-B-C21 disorders. Eur Neuropsychopharmacol 51:87–89. grant (Grant No. PRE2019-089449 [to LV-A]). KA-P and IB-M were sup- 6. Pierce M, Hope H, Ford T, Hatch S, Hotopf M, John A, et al. (2020): ported by 2 postdoctoral fellowships related to PANDÈMIES 2020 (AGAUR) Mental health before and during the COVID-19 pandemic: A longitu- (Grant No. 2020PANDE00043 [to DB-F]). JMT was partly supported by dinal probability sample survey of the UK population. Lancet Psychi- AGAUR (Grant No. 2018 PROD 00172), Fundació Joan Ribas Araquistain, atry 7:883–892. and La Marató de TV3 Fundation (Grant No. 201735.10). This research was 7. Twenge JM, Joiner TE (2020): U.S. Census Bureau-assessed preva- also supported by the Government of Catalonia (Grant No. 2017SGR748). lence of anxiety and depressive symptoms in 2019 and during the We are indebted to the Magnetic Resonance Imaging Core Facility. In 2020 COVID-19 pandemic. Depress Anxiety 37:954–956. addition, we acknowledge support from the Spanish Ministry of Science and 8. Kimhi S, Eshel Y, Marciano H, Adini B, Bonanno GA (2021): Trajec- Innovation and State Research Agency through the Centro de Excelencia tories of depression and anxiety during COVID-19 associations with Severo Ochoa 2019-2023 Program (Grant No. CEX2018-000806-S) and religion, income, and economic difficulties. J Psychiatr Res 144:389– support from the Generalitat de Catalunya through the CERCA Program. 396. AP-L is listed as an inventor on several issued and pending patents on 9. Shevlin M, Butter S, McBride O, Murphy J, Gibson-Miller J, the real-time integration of noninvasive brain stimulation with electroen- Hartman TK, et al. (2021): Refuting the myth of a ‘tsunami’ of mental ill- cephalography and MRI. 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