New Psychometric Evidence of the Life Satisfaction Scale in Older Adults: An Exploratory Graph Analysis Approach.

The objective of the present study was to analyze the psychometric properties of a life satisfaction scale in older Peruvian adults using an exploratory graph analysis (EGA) approach. A total of 407 older adults aged between 60 and 95 years (M = 69.5; SD = 6.7) from three comprehensive elderly care centers (CIAMs) in Lima, Peru, were recruited. A non-probabilistic convenience sampling was used. The Satisfaction with Life Scale (SWLS) was analyzed using EGA with the Gaussian GLASSO model to assess its dimensionality and structural consistency. The relationship with other variables was analyzed using scales such as the GAD-7 and PHQ-9. The network structure of the SWLS indicates a single dimension. Additionally, network loadings (nodes) were examined, showing high values (>0.35) for most items except item 1, which had a moderate loading (>0.25). Structural reliability showed that a single dimension was identified 100% of the time. The post hoc CFA considering the unidimensional network structure obtained through EGA showed satisfactory fit (χ2/df = 3.48, CFI = 0.96, TLI = 0.92, SRMR = 0.02, RMSEA = 0.07 [90% CI 0.05, 0.08]). Finally, internal consistency reliability was acceptable (ω = 0.92). The SWLS measure is robust and consistent. These findings are a valuable reference for advancing research on aging in Peru, as they provide a practical, valid, and reliable measure.

The rubber hand illusion questionnaire: An exploratory graph analysis of ownership, referral of touch, and control statements.

The rubber hand illusion is a well-known experiment that allows manipulation of one's own body experience. The original questionnaire gauges both the illusion experience and unforeseen experiences acting as control statements. In particular, two statements pertain to the referral of touch originating from the rubber hand (RoT), and one concerns the feeling of ownership of the rubber hand (SoO). Despite its prominence, the rubber hand illusion questionnaire has not undergone thorough examination of its psychometric properties. The literature reveals a tendency to use RoT and SoO statements interchangeably. In this study, we employed Exploratory Graph Analysis to explore the item structure and compared the correlation between SoO and RoT items in various conditions. While SoO and RoT are closely linked, our findings suggest potential separation. SoO and RoT statements consistently correlate, yet hints emerge that RoT might represent a distinct facet of the illusion. Correlations diminish beyond the perihand space, indicating a nuanced relationship. Additionally, moderate relationships between control statements and those measuring the illusion suggest that even control statements are modulated by the illusion experience. This study underscores the need for further exploration into the psychometric properties of body illusion questionnaires, prompting reflections on the interpretation in light of these results.

A Network Analytic Approach to Dissociation: New Insights from Clinical Data.

The transdiagnostic construct of dissociation, characterized by a disintegration of specific psychological functions such as consciousness, memory, identity, perception, body representation, and behavior, remains elusive to a unified conceptualization. Specifically, its dimensionality is a matter of ongoing controversy. Empirical approaches applying factor analyses to the Dissociative Experiences Scale (DES) have yielded inconsistent findings. This study adopts a novel methodological approach, utilizing Exploratory Graph Analysis (EGA) to address this issue. In a sample of 668 day-hospital patients undergoing psychotherapy for a variety of mental disorders, a Gaussian graphical model was estimated for the 28 items of the DES. Additionally, the stability of the results was ensured by bootstrap procedures. While both the original EGA and the bootstrap EGA suggested four dimensions, the structural consistency of this solution was low due to an instability of 12 items. After excluding 10 of these unstable items, re-analyses again revealed a four-factor structure, but boot EGA indicated that one factor had unsatisfactory structural consistency due to the multidimensionality of its two items. Upon removing these, our final network consisted of 16 items mapping onto 3 dimensions. Our study, using data from a diagnostically heterogeneous sample, replicates and extends previous findings on the dimensionality of dissociation as captured by the DES. The three dimensions identified correspond to segregated processes, derealization/depersonalization, and absorption. This solution aligns with a bipartite model of dissociation with two broader categories referring to either altered states of consciousness (often named detachment) or to non-integrated mental modules (labeled as compartmentalization).

Validation and structural exploration of the Chinese version of the Body Talk Scale.

The Body Talk Scale (BTS) measures both negative body talk (including fat talk and muscle talk) and positive body talk across genders. In this study, we translated it into Chinese and assessed its structure, reliability and validity among mainland Chinese residents. Item analyses indicated that no item deletion was necessary for this study, and both exploratory factor analysis (n = 1853) and exploratory graph analysis (n = 1583) supported the three-factor structure of the original scale. Confirmatory factor analysis showed that the scale had a good model fit with CFI= 0.95, GFI= 0.93, TLI= 0.94, and RMSEA= 0.079(90 %CI [0.075, 0.084]). The results also showed that the Chinese version of the BTS had adequate criterion-related validity，internal consistency and six-week test-retest reliability. Meanwhile, the scale has good measurement invariance with respect to gender and can be tested for gender differences. In conclusion, the BTS showed sufficient psychometric properties in a Chinese sample, making it a valid instrument for studying body talk and health status in Chinese populations.

Using exploratory graph analysis (EGA) in validating the structure of the Perth alexithymia questionnaire in Iranians with chronic pain.

Background: Chronic pain's influence on emotional well-being can be significant. It may evoke feelings of despair, frustration, nervousness, and melancholy in individuals, which often manifest as reactions to enduring pain and disruptions in their daily lives. In this study, we seek to perform Bootstrap Exploratory Graph Analysis (EGA) on the Persian Version of the Perth Alexithymia Questionnaire (PAQ) in a cohort of people with chronic pain. Methods: The research concentrated on the population of individuals encountering chronic pain within Tehran province from 2022 to 2023. Ultimately, the analysis comprised information from 234 male participants (with a mean age of 30.59, SD = 6.84) and 307 female participants (with a mean age of 30.16, SD = 6.65). After data collection, statistical analysis was conducted using the EGAnet2.0.4 package in R.4.3.2 software. Results: The outcome of bootstrapped EGA unveiled a two-dimensional configuration of the PAQ comprising Factor 1 denoted as negative difficulty in describing and identifying feelings (N-DDIF) and Factor 2 characterized as general-externally orientated thinking (GEOT), representing robust structural integrity and item consistency (all items have stabilities > 0.70). Conclusion: These findings endorse the validity of the PAQ, as evidenced by its confirmation in a broader sample using a novel methodology consistent with existing literature on two-factor decentering models.

A strategy to detect metabolic changes induced by exposure to chemicals from large sets of condition-specific metabolic models computed with enumeration techniques.

BACKGROUND: The growing abundance of in vitro omics data, coupled with the necessity to reduce animal testing in the safety assessment of chemical compounds and even eliminate it in the evaluation of cosmetics, highlights the need for adequate computational methodologies. Data from omics technologies allow the exploration of a wide range of biological processes, therefore providing a better understanding of mechanisms of action (MoA) related to chemical exposure in biological systems. However, the analysis of these large datasets remains difficult due to the complexity of modulations spanning multiple biological processes. RESULTS: To address this, we propose a strategy to reduce information overload by computing, based on transcriptomics data, a comprehensive metabolic sub-network reflecting the metabolic impact of a chemical. The proposed strategy integrates transcriptomic data to a genome scale metabolic network through enumeration of condition-specific metabolic models hence translating transcriptomics data into reaction activity probabilities. Based on these results, a graph algorithm is applied to retrieve user readable sub-networks reflecting the possible metabolic MoA (mMoA) of chemicals. This strategy has been implemented as a three-step workflow. The first step consists in building cell condition-specific models reflecting the metabolic impact of each exposure condition while taking into account the diversity of possible optimal solutions with a partial enumeration algorithm. In a second step, we address the challenge of analyzing thousands of enumerated condition-specific networks by computing differentially activated reactions (DARs) between the two sets of enumerated possible condition-specific models. Finally, in the third step, DARs are grouped into clusters of functionally interconnected metabolic reactions, representing possible mMoA, using the distance-based clustering and subnetwork extraction method. The first part of the workflow was exemplified on eight molecules selected for their known human hepatotoxic outcomes associated with specific MoAs well described in the literature and for which we retrieved primary human hepatocytes transcriptomic data in Open TG-GATEs. Then, we further applied this strategy to more precisely model and visualize associated mMoA for two of these eight molecules (amiodarone and valproic acid). The approach proved to go beyond gene-based analysis by identifying mMoA when few genes are significantly differentially expressed (2 differentially expressed genes (DEGs) for amiodarone), bringing additional information from the network topology, or when very large number of genes were differentially expressed (5709 DEGs for valproic acid). In both cases, the results of our strategy well fitted evidence from the literature regarding known MoA. Beyond these confirmations, the workflow highlighted potential other unexplored mMoA. CONCLUSION: The proposed strategy allows toxicology experts to decipher which part of cellular metabolism is expected to be affected by the exposition to a given chemical. The approach originality resides in the combination of different metabolic modelling approaches (constraint based and graph modelling). The application to two model molecules shows the strong potential of the approach for interpretation and visual mining of complex omics in vitro data. The presented strategy is freely available as a python module ( https://pypi.org/project/manamodeller/ ) and jupyter notebooks ( https://github.com/LouisonF/MANA ).

Assessment of psychometric performance for the Chinese version of the Brief Inventory of Perceived Stress integrating exploratory graph analysis and confirmatory factor analysis.

OBJECTIVE: This study was to evaluate measurement properties of the Chinese version of the Brief Inventory of Perceived Stress (BIPS-C) and confirm possible solutions for measuring the constructs underlying perceived stress. METHODS: A total of 1356 community residents enrolled and were randomly split into two halves. The first half was used to explore the underlying constructs of the BIPS-C by exploratory graph analysis (EGA) and the second half was used to compare and confirm the constructs by confirmatory factor analysis (CFA). RESULTS: The EGA identified a one-factor model of the BIPS-C with an accuracy of 99.3%. One-factor, three-factor, second-order, and bifactor models were compared by CFAs. The bifactor model with one general and three specific factors was found to be the most adequate [comparative fit index (CFI) = 0.990; Tucker-Lewis index (TLI) = 0.979; root mean square error of approximation (RMSEA) = 0.058] and was superior to the other models. The related bifactor indices showed a stronger existence of the general factor. The bifactor model of the BIPS-C also showed adequate internal consistency with McDonald's omega and omega subscales ranging from moderate to strong (0.677-0.869). CONCLUSION: The BIPS-C demonstrates sufficient measurement properties for assessing general perceived stress.

Hippocampal hub failure is linked to long-term memory impairment in anti-NMDA-receptor encephalitis: insights from structural connectome graph theoretical network analysis.

BACKGROUND: Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is characterized by distinct structural and functional brain alterations, predominantly affecting the medial temporal lobes and the hippocampus. Structural connectome analysis with graph-based investigations of network properties allows for an in-depth characterization of global and local network changes and their relationship with clinical deficits in NMDAR encephalitis. METHODS: Structural networks from 61 NMDAR encephalitis patients in the post-acute stage (median time from acute hospital discharge: 18 months) and 61 age- and sex-matched healthy controls (HC) were analyzed using diffusion-weighted imaging (DWI)-based probabilistic anatomically constrained tractography and volumetry of a selection of subcortical and white matter brain volumes was performed. We calculated global, modular, and nodal graph measures with special focus on default-mode network, medial temporal lobe, and hippocampus. Pathologically altered metrics were investigated regarding their potential association with clinical course, disease severity, and cognitive outcome. RESULTS: Patients with NMDAR encephalitis showed regular global graph metrics, but bilateral reductions of hippocampal node strength (left: p = 0.049; right: p = 0.013) and increased node strength of right precuneus (p = 0.013) compared to HC. Betweenness centrality was decreased for left-sided entorhinal cortex (p = 0.042) and left caudal middle frontal gyrus (p = 0.037). Correlation analyses showed a significant association between reduced left hippocampal node strength and verbal long-term memory impairment (p = 0.021). We found decreased left (p = 0.013) and right (p = 0.001) hippocampal volumes that were associated with hippocampal node strength (left p = 0.009; right p < 0.001). CONCLUSIONS: Focal network property changes of the medial temporal lobes indicate hippocampal hub failure that is associated with memory impairment in NMDAR encephalitis at the post-acute stage, while global structural network properties remain unaltered. Graph theory analysis provides new pathophysiological insight into structural network changes and their association with persistent cognitive deficits in NMDAR encephalitis.

The Network Structure of Cognitive Impairment: From Subjective Cognitive Decline to Alzheimer's Disease.

It was proposed that a reorganization of the relationships between cognitive functions occurs in dementia, a vision that surpasses the idea of a mere decline of specific domains. The complexity of cognitive structure, as assessed by neuropsychological tests, can be captured by exploratory graph analysis (EGA). EGA was applied to the neuropsychological assessment of people (humans) with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer's disease (AD; total N = 638). Both sexes were included. In AD, memory scores detach from the other cognitive functions, and memory subdomains reduce their reciprocal relation. SCD showed a pattern of segregated neuropsychological domains, and MCI showed a noisy and less stable pattern. Results suggest that AD drives a reorganization of cognitive functions toward a less-fractionated architecture compared with preclinical conditions. Cognitive functions show a reorganization that goes beyond the performance decline. Results also have clinical implications in test interpretations and usage.

Exploring the factor structure of a Chinese version of the CORE-OM: insights from network approach and bifactor modeling.

OBJECTIVE: The Clinical Outcomes in Routine Evaluation (CORE-OM) is a measure of clinical outcomes that has been widely used in mental health research. Nevertheless, the exploration of the factor structure of the CORE-OM yields diverse results. This study aims to explore the factor structure with an innovative method known as exploratory graph analysis (EGA) and supplemented with bifactor modeling. METHOD: A Chinese version of the CORE-OM was administrated to a total of 1361 clinical college students. We first examined the factor structure of the CORE-OM using EGA, and then compared the model derived by EGA with other models using CFA to find the most reasonable model. RESULTS: The result of EGA indicated a four-factor model of CORE-OM. The CFA further suggested a bifactor model with a four-factor structure combined with a general factor. The bifactor modeling suggested a significant proportion of shared variance among the variables was attributed to the general factor. The four-factor bifactor model exhibited a satisfactory fit to the data. CONCLUSION: The results confirm the robustness and parsimonious nature of a four-factor bifactor model for the Chinese version of CORE-OM. It is suitable for measuring intrapersonal psychological distress, positive emotions, interpersonal problems, and risk-related issues among the Chinese population.

Where Top-Down Meets Bottom-Up: Cell-Type Specific Connectivity Map of the Whisker System.

Sensorimotor computation integrates bottom-up world state information with top-down knowledge and task goals to form action plans. In the rodent whisker system, a prime model of active sensing, evidence shows neuromodulatory neurotransmitters shape whisker control, affecting whisking frequency and amplitude. Since neuromodulatory neurotransmitters are mostly released from subcortical nuclei and have long-range projections that reach the rest of the central nervous system, mapping the circuits of top-down neuromodulatory control of sensorimotor nuclei will help to systematically address the mechanisms of active sensing. Therefore, we developed a neuroinformatic target discovery pipeline to mine the Allen Institute's Mouse Brain Connectivity Atlas. Using network connectivity analysis, we identified new putative connections along the whisker system and anatomically confirmed the existence of 42 previously unknown monosynaptic connections. Using this data, we updated the sensorimotor connectivity map of the mouse whisker system and developed the first cell-type-specific map of the network. The map includes 157 projections across 18 principal nuclei of the whisker system and neuromodulatory neurotransmitter-releasing. Performing a graph network analysis of this connectome, we identified cell-type specific hubs, sources, and sinks, provided anatomical evidence for monosynaptic inhibitory projections into all stages of the ascending pathway, and showed that neuromodulatory projections improve network-wide connectivity. These results argue that beyond the modulatory chemical contributions to information processing and transfer in the whisker system, the circuit connectivity features of the neuromodulatory networks position them as nodes of sensory and motor integration.

Research status and trends of enterprise safety culture: a knowledge graph analysis based on CiteSpace.

The cultivation of safety culture within enterprises has evolved into a pivotal facet of overall safety progress, drawing increased attention from a myriad of businesses. With a comprehensive examination of relevant literature, 635 documents from both domestic and international sources were selected as the subjects of analysis. The developmental trends, both domestically and internationally, follow a generally consistent pattern, resembling an inverted "V" shape. The initial phase witnessed gradual development, followed by a substantial and rapid growth phase in the mid-term. In the later phase, a decline is observed. This study utilizes the CiteSpace software for keyword clustering analysis, employing the Log Likelihood Ratio (LLR) algorithm with default parameters to delve into the themes within the specific research field of enterprise safety culture. It was observed that domestic research predominantly centers on the practical perspective of mitigating accidents through the establishment of enterprise safety culture, while international research places greater emphasis on theoretical considerations, specifically focusing on the impact of safety culture atmospheres within enterprises on employees.

Dreaming Characteristics in Non-Rapid Eye Movement Parasomnia and Idiopathic Rapid Eye Movement Sleep Behaviour Disorder: Similarities and Differences.

Background: Speech graph analysis (SGA) of dreams has recently shown promise as an objective and language-invariant diagnostic tool that can aid neuropsychiatric diagnosis. Whilst the notion that dreaming mentations reflect distinct physiologic processes is not new, such studies in patients with sleep disorders remain exceptionally scarce. Here, using SGA and other dream content analyses, we set to investigate structural and thematic differences in morning dream recalls of patients diagnosed with Non-Rapid Eye Movement Parasomnia (NREMP) and Idiopathic REM Sleep Behavior Disorder (iRBD). Methods: A retrospective cross-sectional study of morning dream recalls of iRBD and NREMP patients was undertaken. Traditional dream content analyses, such as Orlinsky and Hall and Van de Castle analyses, were initially conducted. Subsequently, SGA was performed in order to objectively quantify structural speech differences between the dream recalls of the two patient groups. Results: Comparable rate of morning recall of dreams in the sleep laboratory was recorded; 25% of iRBD and 18.35% of NREMP patients. Aggression in dreams was recorded by 28.57% iRBD versus 20.00% in NREMP group. iRBD patients were more likely to recall dreams (iRBD vs NREMP; P = 0.007), but they also had more white dreams, ie having a feeling of having dreamt, but with no memory of it. Visual and quantitative graph speech analyses of iRBD dreams suggested stable sequential structure, reflecting the linearity of the chronological narrative. Conversely, NREMP dream reports displayed more recursive, less stable systems, with significantly higher scores of graph connectivity measures. Conclusion: The findings of our exploratory study suggest that iRBD and NREMP patients may not only differ on what is recalled in their dreams but also, perhaps more strikingly, on how dreams are recalled. It is hoped that future SGA-led dream investigations of larger groups of patients will help discern distinct mechanistic underpinnings and any associated clinical implications.

Cognitive restraint, uncontrolled eating, and emotional eating. The Italian version of the Three Factor Eating Questionnaire-Revised 18 (TFEQ-R-18): a three-step validation study.

BACKGROUND: The Three Factor Eating Questionnaire-Revised 18 (TFEQ-R-18) is an extensively used questionnaire to measure three transdiagnostic features of eating behavior: cognitive restraint, uncontrolled eating, and emotional eating. OBJECTIVE: This research aims to investigate the psychometric properties of the Italian version of the TFEQ-R-18 in three large community samples. METHOD: Cross-sectional research designs were employed. In Study 1 (N = 537), an exploratory graph analysis (EGA) was used to examine item clustering within the TFEQ-R-18. In Study 2 (N = 645), a confirmatory factor analysis (CFA) was conducted to test its structural validity. In Study 3 (N = 346), a MANOVA was employed assessing mean differences across eating disorders (e.g., anorexia nervosa, bulimia nervosa, binge eating disorder). RESULTS: In Study 1, the EGA accurately identified the three original dimensions of the TFEQ-R-18. Study 2 showed that the Italian TFEQ-R-18 has good fit indexes (CFI = 0.989, RMSEA = 0.064; 90% CI [0.058, 0.070], SRMR = 0.062), and possesses robust psychometric properties. Study 3 reveals distinct, statistically significant differences among eating disorders. CONCLUSION: The TFEQ-R-18 proves to be a concise and precise tool for measuring transdiagnostic eating behaviors. Its applicability in the Italian context, supported by robust psychometric properties, suggests its utility for both research and clinical purposes. The findings affirm its potential to inform interventions aimed at enhancing psychological health. LEVEL OF EVIDENCE: Level V, descriptive study.

Dimensionality assessment in the presence of wording effects: A network psychometric and factorial approach.

This study proposes a procedure for substantive dimensionality estimation in the presence of wording effects, the inconsistent response to regular and reversed self-report items. The procedure developed consists of subtracting an approximate estimate of the wording effects variance from the sample correlation matrix and then estimating the substantive dimensionality on the residual correlation matrix. This is achieved by estimating a random intercept factor with unit loadings for all the regular and unrecoded reversed items. The accuracy of the procedure was evaluated through an extensive simulation study that manipulated nine relevant variables and employed the exploratory graph analysis (EGA) and parallel analysis (PA) retention methods. The results indicated that combining the proposed procedure with EGA or PA achieved high accuracy in estimating the substantive latent dimensionality, but that EGA was superior. Additionally, the present findings shed light on the complex ways that wording effects impact the dimensionality estimates when the response bias in the data is ignored. A tutorial on substantive dimensionality estimation with the R package EGAnet is offered, as well as practical guidelines for applied researchers.

New psychometric evidence from the Revised Mental Health Inventory (R-MHI-5) in Peruvian adolescents from a network psychometrics approach.

BACKGROUND: Mental health is an aspect that has been relegated in recent years, prioritizing physical health care. However, there are more and more mental problems and disorders worldwide. In this context, adolescents are considered at risk for developing psychological difficulties due to the important transition stage they are going through. Given this, an adequate measurement of mental health in the adolescent population is necessary. This research aims to evaluate the internal structure and estimate the reliability of the R-MHI-5. METHOD: The sample covered 662 adolescents (55.2% men and 44.7% women) aged 12 to 17 years (M = 14.5; SD = 1.6). RESULTS: Exploratory graph analysis revealed a two-dimensional structure encompassing well-being and psychological distress. Furthermore, confirmatory factor analysis results indicated that a model with two related factors demonstrated superior fit indices (CFI = 0.99; TLI = 0.99; SRMR = 0.04; RMSEA = 0.101) in comparison to a one-dimensional model (CFI = 0.85; TLI = 0.71; SRMR = 0.23; RMSEA = 0.451). Additionally, adequate values were found in the reliability of the dimensions. CONCLUSION: It is concluded that the R-MHI-5 is an instrument with robust psychometric evidence from the perspective of the EGA and CFA, providing adequate evidence of reliability and validity so that it can be used effectively in future research and prevention and intervention processes. Furthermore, our study is the first to provide psychometric evidence of the scale from a media approach in Peruvian adolescents.

Dyslexia, the Amsterdam Way.

The current aim is to illustrate our research on dyslexia conducted at the Developmental Psychology section of the Department of Psychology, University of Amsterdam, in collaboration with the nationwide IWAL institute for learning disabilities (now RID). The collaborative efforts are institutionalized in the Rudolf Berlin Center. The first series of studies aimed at furthering the understanding of dyslexia using a gamified tool based on an artificial script. Behavioral measures were augmented with diffusion modeling in one study, and indices derived from the electroencephalogram were used in others. Next, we illustrated a series of studies aiming to assess individuals who struggle with reading and spelling using similar research strategies. In one study, we used methodology derived from the machine learning literature. The third series of studies involved intervention targeting the phonics of language. These studies included a network analysis that is now rapidly gaining prominence in the psychopathology literature. Collectively, the studies demonstrate the importance of letter-speech sound mapping and word decoding in the acquisition of reading. It was demonstrated that focusing on these abilities may inform the prediction, classification, and intervention of reading difficulties and their neural underpinnings. A final section examined dyslexia, conceived as a neurobiological disorder. This analysis converged on the conclusion that recent developments in the psychopathology literature inspired by the focus on research domain criteria and network analysis might further the field by staying away from longstanding debates in the dyslexia literature (single vs. a multiple deficit, category vs. dimension, disorder vs. lack of skill).

Revealing complex functional topology brain network correspondences between humans and marmosets.

Functional correspondences are known to exist within the brains of both human and non-human primates however, our understanding of this phenomenon remains largely incomplete. The examination of the topological characteristics inherent in whole-brain functional connectivity bears immense promise in elucidating shared as well as distinctive patterns across different species. In this investigation, we applied topological graph analysis to brain networks and scrutinized the congruencies and disparities within the connectomes of human and marmoset monkey brains. The findings brought to light noteworthy similarities in functional connectivity patterns distributed across the entire brain, with a particular emphasis on the dorsal attention network, default mode network and visual network. Moreover, we discerned unique neural connections between humans and marmosets during both resting and task-oriented states. In essence, our study reveals a combination of shared and divergent functional brain connections underlying spontaneous and specific cognitive functions across these two species.

Altered Temporal Dynamics of Resting-State Functional Magnetic Resonance Imaging in Adolescent-Onset First-Episode Psychosis.

BACKGROUND: Dynamic functional connectivity (dFC) alterations have been reported in patients with adult-onset and chronic psychosis. We sought to examine whether such abnormalities were also observed in patients with first episode, adolescent-onset psychosis (AOP), in order to rule out potential effects of chronicity and protracted antipsychotic treatment exposure. AOP has been suggested to have less diagnostic specificity compared to psychosis with onset in adulthood and occurs during a period of neurodevelopmental changes in brain functional connections. STUDY DESIGN: Seventy-nine patients with first episode, AOP (36 patients with schizophrenia-spectrum disorder, SSD; and 43 with affective psychotic disorder, AF) and 54 healthy controls (HC), aged 10 to 17 years were included. Participants underwent clinical and cognitive assessments and resting-state functional magnetic resonance imaging. Graph-based measures were used to analyze temporal trajectories of dFC, which were compared between patients with SSD, AF, and HC. Within patients, we also tested associations between dFC parameters and clinical variables. STUDY RESULTS: Patients with SSD temporally visited the different connectivity states in a less efficient way (reduced global efficiency), visiting fewer nodes (larger temporal modularity, and increased immobility), with a reduction in the metabolic expenditure (cost and leap size), relative to AF and HC (effect sizes: Cohen's D, ranging 0.54 to.91). In youth with AF, these parameters did not differ compared to HC. Connectivity measures were not associated with clinical severity, intelligence, cannabis use, or dose of antipsychotic medication. CONCLUSIONS: dFC measures hold potential towards the development of brain-based biomarkers characterizing adolescent-onset SSD.

A network perspective on real-life threat, anxiety, and avoidance.

BACKGROUND: Anxiety, approach, and avoidance motivation crucially influence mental and physical health, especially when environments are stressful. The interplay between anxiety and behavioral motivation is modulated by multiple individual factors. This proof-of-concept study applies graph-theoretical network analysis to explore complex associations between self-reported trait anxiety, approach and avoidance motivation, situational anxiety, stress symptoms, perceived threat, perceived positive consequences of approach, and self-reported avoidance behavior in real-life threat situations. METHODS: A total of 436 participants who were matched on age and gender (218 psychotherapy patients, 218 online-recruited nonpatients) completed an online survey assessing these factors in response to the COVID-19 pandemic. RESULTS AND DISCUSSION: The resulting cross-sectional psychological network revealed a complex pattern with multiple positive (e.g., between trait anxiety, avoidance motivation, and avoidance behavior) and negative associations (e.g., between approach and avoidance motivation). The patient and online subsample networks did not differ significantly, however, descriptive differences may inform future research.