arXiv subjects

Irene Messina

Publications and source records attributed to Irene Messina.

4 recordsLinked to original sources

arXiv2025

Increased GM-WM in a prefrontal network and decreased GM in the insula and the precuneus are associated with reappraisal usage: A data fusion approach

Emotion regulation plays a crucial role in mental health, and difficulties in regulating emotions can contribute to psychological disorders. While reappraisal and suppression are well-studied strategies, the combined contributions of gray matter (GM) and white matter (WM) to these strategies remain unclear due to methodological limitations in previous studies. To address this, we applied a data fusion approach using Parallel Independent Component Analysis (Parallel ICA) to GM and WM MRI images from 165 individuals. Parallel ICA identified two networks associated with reappraisal usage. Network 1 included a large lateral and medial prefrontal cortical network, overlapping with the default mode network (DMN) and adjacent WM regions. Higher reappraisal frequency was associated with greater GM-WM density within this network, and this network was negatively correlated with perceived stress. Network 2 included the insula, precuneus, sub-gyral, and lingual gyri in its GM portion, showing a negative association with reappraisal usage. The WM portion, adjacent to regions of the central executive network (CEN), was positively associated with reappraisal usage. Regarding suppression, no significant network was associated with this strategy. This study provides new insights into individual differences in reappraisal use, showing a positive association between reappraisal frequency and increased gray and white matter concentration in a large frontal network, including regions of the frontal DMN and the CEN. Conversely, subcortical areas exhibited reduced gray and white concentration.

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arXiv2024

Resting-State fingerprints of Acceptance and Reappraisal. The role of Sensorimotor, Executive and Affective networks

Acceptance and Reappraisal are considered adaptive emotion regulation strategies. While previous studies have explored the neural underpinnings of these strategies using task based fMRI and sMRI, a gap exists in the literature concerning resting-state functional brain networks contributions to these abilities, especially for what concerns Acceptance. Another intriguing question is whether these strategies rely on similar or different neural mechanisms. Building on the well-known improved emotion regulation and increased cognitive flexibility of individuals who rely on acceptance, we expected to find decreased activity inside the Affective network and increased activity inside the Executive and Sensorimotor networks to be predicted of acceptance. We also expect that these networks may be associated at least in part with Reappraisal, indicating a common mechanism behind different strategies. To test these hypotheses, we conducted a functional connectivity analysis of resting-state data from 134 individuals (95 females). To assess acceptance and reappraisal abilities, we used the Cognitive Emotion Regulation Questionnaire (CERQ) and a group-ICA unsupervised machine learning approach to identify resting state networks. Subsequently, we conducted backward regression to predict acceptance and reappraisal abilities. As expected, results indicated that acceptance was predicted by decreased Affective, and increased Executive, and Sensorimotor networks, while reappraisal was predicted by an increase in the Sensorimotor network. Notably, these findings suggest both distinct and overlapping brain contributions to acceptance and reappraisal, with the Sensorimotor network potentially serving as a core common mechanism. These results not only align with previous findings but also expand upon them, demonstrating the complex interplay of cognitive, affective, and sensory abilities in emotion regulation.

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arXiv2023

The neural signature of inner peace: morphometric differences between high and low accepters

Acceptance is an adaptive emotion regulation strategy characterized by an open and non-judgmental attitude toward mental and sensory experiences. While a few studies have investigated the neural correlates of acceptance in task-based fMRI studies, a gap remains in the scientific literature in dispositional use of acceptance, and how this is sedimented at a structural level. Therefore, the aim of the present study is to investigate the neural and psychological differences between infrequent acceptance users (i.e., low accepters) and frequent users (i.e., high accepters). Another question is whether high and low accepters differ in personality traits and emotional intelligence. To this aim, we applied, for the first time, a data fusion unsupervised machine learning approach (mCCA-jICA) to the gray matter (GM) and white matter (WM) of high accepters (N = 50), and low accepters (N = 78) to possibly find joint GM-WM differences in both modalities. Our results show that two covarying GM-WM networks separate high from low accepters. The first network showed decreased GM-WM concentration in a fronto-temporal-parietal circuit largely overlapping with the Default Mode Network, while the second network showed increased GM-WM concentration in portions of the orbito-frontal, temporal, and parietal areas, related to a Central Executive Network. At the psychological level, the high accepters display higher openness to experience compared to low accepters. Overall, our findings suggest that high accepters compared to low accepters differ in neural and psychological mechanisms. These findings confirm and extend previous studies on the relevance of acceptance as a strategy associated with well-being.

q-bio.NC↗

arXiv2023

Understanding the neural architecture of emotion regulation by comparing two different strategies: A meta-analytic approach

In the emotion regulation literature, the amount of neuroimaging studies on cognitive reappraisal led the impression that the same top-down, control-related neural mechanisms characterize all emotion regulation strategies. However, top-down processes may coexist with more bottom-up and emotion-focused processes that partially bypass the recruitment of executive functions. A case in point is acceptance-based strategies. To better understand neural commonalities and differences behind different emotion regulation strategies, in the present study we applied a meta-analytic method to fMRI studies of task-related activity of reappraisal and acceptance. Results showed increased activity in left-inferior frontal gyrus and insula for both strategies, and decreased activity in the basal ganglia for reappraisal, and decreased activity in limbic regions for acceptance. These findings are discussed in the context of a model of common and specific neural mechanisms of emotion regulation that support and expand the previous dual-routes models. We suggest that emotion regulation may rely on a core inhibitory circuit, and on strategy-specific top-down and bottom-up processes distinct for different strategies.

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