Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy - PubMed (original) (raw)

Meta-Analysis

Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy

Danilo Bzdok et al. Brain Struct Funct. 2012 Oct.

Abstract

Morally judicious behavior forms the fabric of human sociality. Here, we sought to investigate neural activity associated with different facets of moral thought. Previous research suggests that the cognitive and emotional sources of moral decisions might be closely related to theory of mind, an abstract-cognitive skill, and empathy, a rapid-emotional skill. That is, moral decisions are thought to crucially refer to other persons' representation of intentions and behavioral outcomes as well as (vicariously experienced) emotional states. We thus hypothesized that moral decisions might be implemented in brain areas engaged in 'theory of mind' and empathy. This assumption was tested by conducting a large-scale activation likelihood estimation (ALE) meta-analysis of neuroimaging studies, which assessed 2,607 peak coordinates from 247 experiments in 1,790 participants. The brain areas that were consistently involved in moral decisions showed more convergence with the ALE analysis targeting theory of mind versus empathy. More specifically, the neurotopographical overlap between morality and empathy disfavors a role of affective sharing during moral decisions. Ultimately, our results provide evidence that the neural network underlying moral decisions is probably domain-global and might be dissociable into cognitive and affective sub-systems.

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Figures

Fig. 1

Fig. 1

ALE meta-analysis of neuroimaging studies on moral cognition, theory of mind, and empathy. Significant meta-analysis results displayed on frontal, right, and left surface view as well as sagittal, coronal, and axial sections of the MNI single-subject template. Coordinates in MNI space. All results were significant at a cluster-forming threshold of p < 0.05 and an extent threshold of k = 10 voxels (to exclude presumably incidental results)

Fig. 2

Fig. 2

Conjunction analyses for topographical convergence across brain activity related to moral cognition and theory of mind (ToM) or empathy. Left panel overlapping activation patterns between the meta-analysis on moral cognition and the difference analysis between ToM and empathy (cluster-forming threshold: p < 0.05). Right bottom panel overlapping activation patterns between the meta-analysis on moral cognition and the difference analysis between empathy and ToM (cluster-forming threshold: p < 0.05). Right top panel sagittal and coronal slices of juxtaposed results from the meta-analyses on moral cognition (green) and empathy (red) to highlight similar convergence in the posterior cingulate cortex and amygdala (extent threshold: k = 10 voxels to exclude presumably incidental results). Coordinates in MNI space

Fig. 3

Fig. 3

Functional characterization of the core-network implicated in moral cognition, theory of mind (ToM), and empathy. Left neural network consistently activated across individual meta-analyses on moral cognition, ToM, and empathy (extent threshold: k = 10 voxels to exclude presumably incidental results). Images were rendered using Mango (multi-image analysis GUI, Research Imaging Institute, San Antonio, Texas, USA;

http://ric.uthscsa.edu/mango/

). Right functional characterization of the convergent network across all three tasks by BrainMap metadata. The purple bars denote the number of foci for that particular metadata class within the seed network. The grey bars represent the number of foci that would be expected to hit the particular seed network if all foci with the respective class were randomly distributed throughout the cerebral cortex. That is, the grey bars denote the by-chance frequency of that particular label given the size of the cluster. All shown taxonomic classes reached significance according to a binomial test (p < 0.05). Asterisks denote classes that survived the Bonferroni correction for multiple comparisons

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