I am Me:Brain systems integrate and segregate to establish a multidimensional sense of self

Humans experience a sense of self, which is proposed to emerge from the integration of intrinsic and extrinsic self-processing through the propagation of information across brain systems. Using a novel functional magnetic resonance imaging (fMRI) paradigm, we tested this hypothesis in a non-clinical sample by modulating the intrinsic and extrinsic self-relatedness of auditory action consequences in terms of identity and agency, respectively. In addition, the relevance of individual traits associated with altered self-experiences (e.g., psychosis-like experiences) was examined. The task-evoked fMRI results showed distinctive associations between the neural coding of identity and negative affect traits, and between agency and psychosis-like experiences. Most importantly, regarding the functional connectivity analysis, graph theoretical measures demonstrated that the simultaneous processing of identity and agency relies on the functional integration and segregation of default mode, sensorimotor, language, and executive brain networks. Finally, cross-network interactions mediated by executive and sensorimotor regions were negatively associated with psychosis-like experiences when the intrinsic and extrinsic self-relatedness of action consequences conflicted. These findings provide evidence that the self is a multidimensional phenomenon rooted in the functional interactions between large-scale neuronal networks. Such interactions may have particular relevance for self-experience alterations

Intrinsic Shapes of Empathy: Functional Brain Network Topology Encodes Intersubjective Experience and Awareness Traits

Trait empathy is an essential personality feature in the intricacy of typical social inclinations of individuals. Empathy is likely supported by multilevel neuronal network functioning, whereas local topological properties determine network integrity. In the present functional MRI study (N = 116), we aimed to trace empathic traits to the intrinsic brain network architecture. Empathy was conceived as composed of two dimensions within the concept of pre-reflective, intersubjective understanding. Vicarious experience consists of the tendency to resonate with the feelings of other individuals, whereas intuitive understanding refers to a natural awareness of others’ emotional states. Analyses of graph theoretical measures of centrality showed a relationship between the fronto-parietal network and psychometric measures of vicarious experience, whereas intuitive understanding was associated with sensorimotor and subcortical networks. Salience network regions could constitute hubs for information processing underlying both dimensions. The network properties related to empathy dimensions mainly concern inter-network information flow. Moreover, interaction effects implied several sex differences in the relationship between functional network organization and trait empathy. These results reveal that distinct intrinsic topological network features explain individual differences in separate dimensions of intersubjective understanding. The findings could help understand the impact of brain damage or stimulation through alterations of empathy-related network integrity

Comparison and combination of a hemodynamics/biomarkers-based model with simplified PESI score for prognostic stratification of acute pulmonary embolism: findings from a real world study

Background: Prognostic stratification is of utmost importance for management of acute Pulmonary Embolism (PE) in clinical practice. Many prognostic models have been proposed, but which is the best prognosticator in real life remains unclear. The aim of our study was to compare and combine the predictive values of the hemodynamics/biomarkers based prognostic model proposed by European Society of Cardiology (ESC) in 2008 and simplified PESI score (sPESI).Methods: Data records of 452 patients discharged for acute PE from Internal Medicine wards of Tuscany (Italy) were analysed. The ESC model and sPESI were retrospectively calculated and compared by using Areas under Receiver Operating Characteristics (ROC) Curves (AUCs) and finally the combination of the two models was tested in hemodinamically stable patients. All cause and PE-related in-hospital mortality and fatal or major bleedings were the analyzed endpointsResults: All cause in-hospital mortality was 25% (16.6% PE related) in high risk, 8.7% (4.7%) in intermediate risk and 3.8% (1.2%) in low risk patients according to ESC model. All cause in-hospital mortality was 10.95% (5.75% PE related) in patients with sPESI score ≥1 and 0% (0%) in sPESI score 0. Predictive performance of sPESI was not significantly different compared with 2008 ESC model both for all cause (AUC sPESI 0.711, 95% CI: 0.661-0.758 versus ESC 0.619, 95% CI: 0.567-0.670, difference between AUCs 0.0916, p=0.084) and for PE-related mortality (AUC sPESI 0.764, 95% CI: 0.717-0.808 versus ESC 0.650, 95% CI: 0.598-0.700, difference between AUCs 0.114, p=0.11). Fatal or major bleedings occurred in 4.30% of high risk, 1.60% of intermediate risk and 2.50% of low risk patients according to 2008 ESC model, whereas these occurred in 1.80% of high risk and 1.45% of low risk patients according to sPESI, respectively. Predictive performance for fatal or major bleeding between two models was not significantly different (AUC sPESI 0.658, 95% CI: 0.606-0.707 versus ESC 0.512, 95% CI: 0.459-0.565, difference between AUCs 0.145, p=0.34). In hemodynamically stable patients, the combined endpoint in-hospital PE-related mortality and/or fatal or major bleeding (adverse events) occurred in 0% of patients with low risk ESC model and sPESI score 0, whilst it occurred in 5.5% of patients with low-risk ESC model but sPESI ≥1. In intermediate risk patients according to ESC model, adverse events occurred in 3.6% of patients with sPESI score 0 and 6.65% of patients with sPESI score ≥1.Conclusions: In real world, predictive performance of sPESI and the hemodynamic/biomarkers-based ESC model as prognosticator of in-hospital mortality and bleedings is similar. Combination of sPESI 0 with low risk ESC model may identify patients with very low risk of adverse events and candidate for early hospital discharge or home treatment.

Evolutionary Heritage Influences Amazon Tree Ecology

Lineages tend to retain ecological characteristics of their ancestors through time. However, for some traits, selection during evolutionary history may have also played a role in determining trait values. To address the relative importance of these processes requires large-scale quantification of traits and evolutionary relationships among species. The Amazonian tree flora comprises a high diversity of angiosperm lineages and species with widely differing life-history characteristics, providing an excellent system to investigate the combined influences of evolutionary heritage and selection in determining trait variation. We used trait data related to the major axes of life-history variation among tropical trees (e.g. growth and mortality rates) from 577 inventory plots in closed-canopy forest, mapped onto a phylogenetic hypothesis spanning more than 300 genera including all major angiosperm clades to test for evolutionary constraints on traits. We found significant phylogenetic signal (PS) for all traits, consistent with evolutionarily related genera having more similar characteristics than expected by chance. Although there is also evidence for repeated evolution of pioneer and shade tolerant life-history strategies within independent lineages, the existence of significant PS allows clearer predictions of the links between evolutionary diversity, ecosystem function and the response of tropical forests to global change

Hyperdominance in Amazonian Forest Carbon Cycling

While Amazonian forests are extraordinarily diverse, the abundance of trees is skewed strongly towards relatively few ‘hyperdominant’ species. In addition to their diversity, Amazonian trees are a key component of the global carbon cycle, assimilating and storing more carbon than any other ecosystem on Earth. Here we ask, using a unique data set of 530 forest plots, if the functions of storing and producing woody carbon are concentrated in a small number of tree species, whether the most abundant species also dominate carbon cycling, and whether dominant species are characterized by specific functional traits. We find that dominance of forest function is even more concentrated in a few species than is dominance of tree abundance, with only ≈1% of Amazon tree species responsible for 50% of carbon storage and productivity. Although those species that contribute most to biomass and productivity are often abundant, species maximum size is also influential, while the identity and ranking of dominant species varies by function and by region

The global abundance of tree palms

Aim Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location Tropical and subtropical moist forests. Time period Current. Major taxa studied Palms (Arecaceae). Methods We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co‐occurring non‐palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long‐term climate stability. Life‐form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non‐tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above‐ground biomass, but the magnitude and direction of the effect require additional work. Conclusions Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests

Testing the magnitude of correlations across experimental conditions

Comparisons between correlation coefficients are used to investigate data across multiple research fields, as they allow investigators to determine different degrees of correlation to independent variables. Such differences may be small, even with adequate sample size, but still scientifically relevant. To date, although much effort has gone into developing methods for estimating differences across correlation coefficients, adequate tools for variable sample sizes and correlational strengths have yet to be tested. The present study evaluated four different methods for detecting the difference between two correlations and tested the adequacy of each method using simulations with multiple data structures. These methods were Cohen's q, Fisher's method, linear mixed-effects models (LMEM), and an ad-hoc developed procedure that integrates bootstrap effect size estimation. Results showed that Fisher's method and the LMEM tended to reject the null hypothesis even in the presence of relevant differences between correlations and that Cohen's method was not sensitive to data structure. Bootstrap followed by effect size estimation resulted in a favorable, unbiased compromise for estimating quantitative differences between statistical associations and producing outputs that could be easily compared across studies

The State-Trait Sense of Self Inventory: A psychometric instrument to measure multiple features of self-experience

The sense of self refers to an individual's subjective awareness and perception of their own existence, individuality, and continuity over time. It plays a crucial role in shaping thoughts, emotions, behaviors, and interactions with others. Despite being a fundamental trait, the individual sense of self is harmonized with the surrounding environment and context, originating self-states which are seldom investigated. Furthermore, the self can be better understood through its constitutive aspects such as the sense of identity, encompassing self-referential processing, and the sense of agency, which is the feeling of controlling our actions and their consequences. In this paper, we present the first inventory (25 total items) to assess a multidimensional sense of self, built upon the study of two separate samples for its construction and its validation. We detected a unique self-trait factor encompassing agency and identity items, whereas the self-state exhibited a bifactorial structure with a high-order factor and three lower-order factors: state-identity, state-agency, and state-technology. The factors showed high reliability and high clinical relevance by predicting psychopathological variables and were also related with demographic variables such as occupation, gender, and education. The st-SoSI is a reliable instrument able to distinguish between self-trait and self-states, and at the same time to discriminate between identity, agency, and interactions with intruding technological devices

The evolving sense of agency: Context recency and quality modulate the interaction between prospective and retrospective processes

Humans acquire a sense of agency through their interactions with the world and their sensory consequences. Previous studies have highlighted stable agency-related phenomena like intentional binding, which depend on both prospective, context-dependent and retrospective, outcome-dependent processes. In the current study, we investigated the interaction between prospective and retrospective processes underlying the adaptation of an ongoing sense of agency. The results showed that prospective intentional binding developed during a temporal window of up to 20 prior events were independent of the nature of the ongoing event. By contrast, the characteristics of the ongoing event retrospectively influenced prospective intentional binding developed during a temporal window narrower than 6 prior events. These findings characterize the interaction between prospective and retrospective mechanisms as a fundamental process to continuously update the sense of agency through sensorimotor learning. High psychosis-like experience traits weakened this interaction, suggesting that reduced adaption to the context contribute to altered self-experience

The prospective sense of agency is rooted in local and global properties of intrinsic functional brain networks

The sense of agency (SoA) refers to a constitutional aspect of the self describing the extent to which individuals feel in control over their actions and consequences thereof. Although the SoA has been associated with mental health and well-being, it is still unknown how interindividual variability in the SoA is embedded in the intrinsic brain organization. We hypothesized that the prospective component of an implicit SoA is associated with brain networks related to SoA and sensorimotor predictions on multiple spatial scales. We replicated previous findings by showing a significant prospective SoA as indicated by intentional binding effects. Then, using task-free functional magnetic resonance imaging (fMRI) and graph analysis, we analyzed associations between intentional binding effects and the intrinsic brain organization at regional, modular, and whole-brain scales. The results showed that inter-modular connections of a fronto-parietal module including the premotor cortex, supramarginal gyrus, and dorsal precuneus are associated with individual differences in prospective intentional binding. Notably, prospective intentional binding effects were also related to global brain modularity within a specific structural resolution range. These findings suggest that an implicit SoA generated through sensorimotor predictions relies on the intrinsic organization of the brain connectome on both local and global scales