Biology subjects

Sicorello, M.

Publications and source records attributed to Sicorello, M..

4 recordsLinked to original sources

bioRxiv2025

The elusive neural signature of emotion regulation capabilities: evidence from a large-scale consortium

Cognitive reappraisal is a fundamental emotion regulation strategy for mental and physical well-being, but how its neural mechanisms relate to individual differences remains poorly understood. In a consortium effort analyzing 40 fMRI datasets (N=2,175), we examined the relationship between neural activation during reappraisal tasks and three core individual difference indices of reappraisal capabilities: (1) trait questionnaires, (2) task-based affective ratings, and (3) amygdala down-regulation. Strikingly, there was no shared overlap across these three common indices. Only a very weak correlation emerged between amygdala down-regulation and task-based affective ratings. Whole-brain analyses revealed no reliable neural associations with trait questionnaires, and associations with task-based affective ratings fell outside canonical emotion regulation networks (e.g., prefrontal circuitry). Moreover, amygdala down-regulation, often interpreted as a stable individual marker, was confounded by person-specific whole-brain responses -- a limitation extending to fMRI research beyond the emotion regulation domain. These findings challenge the assumption that an individuals prefrontal activity is a valid indicator of their reappraisal capabilities and suggest that common trait, behavioral, and neural measures might capture distinct facets of emotion regulation. More broadly, our results highlight concrete methodological challenges for fMRI research on individual differences, with implications extending beyond emotion regulation to the neuroscience of personality, psychopathology, and general well-being.

neuroscience↗

bioRxiv2025

The functional neurobiology of negative affective traits across regions, networks, signatures, and a machine learning multiverse

Understanding the neural basis of negative affective traits like neuroticism remains a critical challenge across psychology, neuroscience, and psychiatry. Here, we investigate which level of brain organization--regions, networks, or validated whole-brain machine-learning signatures--best explains negative affective traits in a community sample of 458 adults performing the two most widely used affective fMRI tasks, viewing emotional faces and scenes. Neuroticism could not be predicted from brain activity, with Bayesian evidence against all theory-guided neural measures. However, preregistered whole-brain models successfully decoded vulnerability to stress, a lower-level facet of neuroticism, with results replicating in a hold-out sample. The neural stress vulnerability pattern demonstrated good psychometric properties and indicated that negative affective traits are best represented by distributed whole-brain patterns related to domain-general stimulation rather than localized activity. Together with results from a comprehensive multiverse analysis across 14 traits and 1,176 models-- available for exploration in an online app--the findings speak against simplistic neurobiological theories of negative affective traits, highlight a striking gap between predicting individual differences (r<.35) and within-person emotional states (r=.88), and underscore the importance of aligning psychological constructs with neural measures at the appropriate level of granularity.

neuroscience↗

bioRxiv2022

The DNA methylation landscape of the human oxytocin receptor gene (OXTR): Recommendations for future research

The oxytocin receptor gene (OXTR) is of interest when investigating the effects of early adversity on DNA methylation. However, there is heterogeneity regarding the selection of the most promising CpG sites to target for analyses. The goal of this study was to determine functionally relevant clusters of CpG sites within the OXTR CpG island in 113 mother-infant dyads, with 58 of the mothers having experienced childhood maltreatment (CM). OXTR DNA methylation and gene expression was analyzed in peripheral/umbilical blood mononuclear cells. Different complexity reduction approaches were used to reduce the 188 CpG sites into clusters of co-methylated sites. Furthermore, associations between OXTR DNA methylation (cluster- and site-specific level) and OXTR gene expression and CM were investigated. Results showed that, first, CpG sections differed strongly regarding their statistical utility for research of individual differences in DNA methylation. Second, cluster analyses and Partial Least Squares (PLS) suggested two clusters consisting of intron1/exon2 and the protein-coding region of exon 3, respectively, as most strongly associated with outcome measures. Third, cross-validated PLS regression explained 7% of variance in CM, with low cross-validated variance explained for the prediction of gene expression. Fourth, very high mother-child correspondence was observed in correlation patterns within the identified clusters, but only modest correspondence outside these clusters. This study characterized the DNA methylation landscape of the OXTR CpG island by highlighting clusters of CpG sites that show desirable statistical properties and predictive value. We provide a Companion Web Application to guide future studies in their choice of CpG sites.

molecular biology↗

bioRxiv2021

Survey on Open Science Practices in Functional Neuroimaging

Replicability and reproducibility of scientific findings is paramount for sustainable progress in neuroscience. Preregistration of the hypotheses and methods of an empirical study before analysis, the sharing of primary research data, and compliance with data standards such as the Brain Imaging Data Structure (BIDS), are considered effective practices to secure progress and to substantiate quality of research. We investigated the current level of adoption of open science practices in neuroimaging and the difficulties that prevent researchers from using them. Email invitations to participate in the survey were sent to addresses received through a PubMed search of human functional magnetic resonance imaging studies between 2010 and 2020. 283 persons completed the questionnaire. Although half of the participants were experienced with preregistration, the willingness to preregister studies in the future was modest. The majority of participants had experience with the sharing of primary neuroimaging data. Most of the participants were interested in implementing a standardized data structure such as BIDS in their labs. Based on demographic variables, we compared participants on seven subscales, which had been generated through factor analysis. It was found that experienced researchers at lower career level had higher fear of being transparent, researchers with residence in the EU had a higher need for data governance, and researchers at medical faculties as compared to other university faculties reported a higher need for data governance and a more unsupportive environment. The results suggest growing adoption of open science practices but also highlight a number of important impediments.

scientific communication and education↗