Empathic Accuracy and its Neural Correlates: A Convergence between Shared Representations and Mental State Attributions

Accurately understanding the internal states of others – what is called empathic accuracy (EA) – is a crucial skill for social coexistence. However, until recently, there were no robust experimental methods that allowed us to identify the neural substrates that support this ability based on objective data. The study conducted by Zaki et al. (2009) represents a breakthrough in this field by demonstrating, through functional neuroimaging (fMRI), that EA depends on activity in brain regions traditionally associated with both shared sensorimotor representations (SRs) and cognitive attributions of mental states (MSA).

The work uses a naturalistic paradigm in which participants watch videos of targets reporting emotional experiences and continuously evaluate the affective states of these targets. Empathic accuracy is then defined as the correlation between the observers’ assessments and the targets’ introspective reports. This methodology allows a direct link between observed neural activity and empathic accuracy, overcoming limitations of previous studies that only inferred mental states without access to the actual subjective experience of the targets.

The results show that accurate empathic judgments are associated with the coactivation of two distinct neural networks. The first is the mirror neuron system, especially the dorsal premotor cortex and the inferior parietal lobule, regions involved in the simulation of observed actions and emotions. The second network involves the superior temporal sulcus and the medial prefrontal cortex (dorsal and rostral), traditionally implicated in the inference of others’ mental states. The functional convergence of these two networks supports the notion that accurate empathy depends on both automatic simulation processes and contextualized cognitive inferences (Zaki et al., 2009).

Interestingly, regions often associated with affective empathy, such as the anterior insula, anterior cingulate cortex, and secondary somatosensory cortex, did not demonstrate a significant correlation with empathic accuracy in this study. This suggests that activation of these areas may be more related to the perception of intense somatoviscal states—such as pain or disgust—than to the interpretation of complex and naturalistic emotions, such as those expressed verbally in the videos used.

Another relevant finding was the absence of involvement of the temporoparietal gyrus (TPJ), a region implicated in the detection of false beliefs and in processes of reorientation of social attention. The authors hypothesize that, since there was no deception or misinformation in the reports of the targets, the function attributed to the TPJ was not required in this specific context.

The central implication of the study is that accurate empathy in realistic contexts requires the integration of different levels of social processing: embodied simulation of others’ states and context-based interpretive inference. This integrative view contrasts with reductionist approaches that prioritize only one of the pathways, and suggests a more holistic model of human empathic functioning.

In addition to the theoretical implications, the adopted methodology offers a promising path for clinical investigations, especially in populations with social deficits, such as individuals with autism spectrum disorders (ASD). Although some of these individuals perform well on simplified theory of mind tasks, they continue to have difficulties in real social interactions. The EA paradigm, by capturing nuances closer to everyday social demands, can contribute to a more ecological assessment of social cognition and the development of more effective interventions.

In summary, the study by Zaki et al. (2009) inaugurates a robust methodological approach to investigate empathic accuracy, while proposing a functionally integrated neural architecture for this ability. Accurate empathy does not appear to be an exclusive product of automatic simulation or deliberate inference, but emerges from the dynamic collaboration between both networks. A personal observation: while reading the article, I noticed that this integrative model intuitively aligns with the everyday experience of empathy – sometimes we feel with the other, sometimes we think about what the other feels – and perhaps the effectiveness of human empathy derives precisely from this functional plasticity.

Reference:

ZAKI, J.; WEBER, J.; BOLGER, N.; OCHSNER, K. The neural bases of empathic accuracy. Proceedings of the National Academy of Sciences, v. 106, n. 27, p. 11382–11387, 2009. DOI: 10.1073/pnas.0902666106.

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