ArticleCognitive, affective & behavioral neuroscience2020
Less is more: Morphometric and psychological differences between low and high reappraisers.
Article in Cognitive, affective & behavioral neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 25 citations in OpenAlex.
- Orbitofrontal cortex and amygdala as key regions for the classification of small animal phobia: A structural MRI machine learning study.Cognitive, affective & behavioral neuroscience · 2026Article
- The phobic brain: Morphometric features correctly classify individuals with small animal phobia.Psychophysiology · 2025Article
- Decoding reappraisal and suppression from neural circuits: A combined supervised and unsupervised machine learning approach.Cognitive, affective & behavioral neuroscience · 2023Article
- Perceiving visual negative stimuli in schizophrenia and bipolar disorder: Meta-analytic evidence of a common altered thalamic-parahippocampal-basal ganglia circuit.Neuroimage. Reports · 2023Article
- Abnormal Brain Circuits Characterize Borderline Personality and Mediate the Relationship between Childhood Traumas and Symptoms: A mCCA+jICA and Random Forest Approach.Sensors (Basel, Switzerland) · 2023Article
- Interpersonal emotion regulation questionnaire: psychometric properties of the Italian version and associations with psychopathology.Research in psychotherapy (Milano) · 2022Article
- Built to last: Theta and delta changes in resting-state EEG activity after regulating emotions.Brain and behavior · 2022Article
- Dissociating the role of dACC and dlPFC for emotion appraisal and mood regulation using cathodal tDCS.Cognitive, affective & behavioral neuroscience · 2022Article
- Emotion regulation and delusion-proneness relate to empathetic tendencies in a transdiagnostic sample.Frontiers in psychiatry · 2022Article
- Zhongyong Thinking Style and Resilience Capacity in Chinese Undergraduates: The Chain Mediating Role of Cognitive Reappraisal and Positive Affect.Frontiers in psychology · 2022Article
- Structural Features Related to Affective Instability Correctly Classify Patients With Borderline Personality Disorder. A Supervised Machine Learning Approach.Frontiers in psychiatry · 2022Article
- Structural Features Predict Sexual Trauma and Interpersonal Problems in Borderline Personality Disorder but Not in Controls: A Multi-Voxel Pattern Analysis.Frontiers in human neuroscience · 2022Article
- Structural and functional brain networks of individual differences in trait anger and anger control: An unsupervised machine learning study.The European journal of neuroscience · 2022Article
- Anxiety Regulation: From Affective Neuroscience to Clinical Practice.Brain sciences · 2020Review
- A Dual Route Model for Regulating Emotions: Comparing Models, Techniques and Biological Mechanisms.Frontiers in psychology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
Abstract
Emotion regulation plays a crucial role in an individual's well-being, as it is known that deficits in regulating emotions can lead to psychological and psychiatric disorders. Cognitive reappraisal is widely considered to be an adaptive and effective emotion-regulation strategy. People are more or less able to apply it, but it is still not clear how reappraisal affects brain structures and the psychological profile of individuals. In our study we thus aimed to explore the impact of applying reappraisal at both the neural and the psychological level. Source-based morphometry (SBM), a whole-brain multivariate method based on the Independent Component Analysis that extracts patterns of covariation of gray matter ("independent networks"), was applied to the MRI images of 37 participants. In order to enrich their psychological profiles, we measured their experienced affectivity (PANAS) and their empathic abilities (IRI). Based on the frequency of applying reappraisal (ERQ), participants were divided into low and high reappraisers (18 vs. 19). An independent source of gray matter emerged as being different between the groups: specifically, low reappraisers showed more gray matter volume concentration in a network including the frontal, temporal, and parietal regions as compared to high reappraisers. At the psychological level, low reappraisers reported a more strongly experienced negative affect, while no difference among reappraisers emerged with regard to empathic abilities. Capitalizing on a multivariate method for structural analysis that is innovative in this field, this study extends previous observations on individual differences in the ability to regulate emotions, and it describes a plausible impact of reappraisal on brain structures and affectivity.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.