Abstract
Empathy—affective resonance with others’ sensory or emotional experiences—is hypothesized to be an important precursor to altruism. However, it is not known whether real-world altruists’ heightened empathy reflects true self-other mapping of multi-voxel neural response patterns. We investigated this relationship in adults who had engaged in extraordinarily costly real-world altruism: donating a kidney to a stranger. Altruists and controls completed fMRI testing while anticipating and experiencing pain, and watching as a stranger anticipated and experienced pain. Machine learning classifiers tested for shared representation between experienced and observed distress. Altruists exhibited more similar representations of experienced and observed fearful anticipation spontaneously and following an empathy prompt in anterior insula and anterior/middle cingulate cortex, respectively, suggesting heightened empathic proclivities and abilities for fear. During pain epochs, altruists were distinguished by spontaneous empathic responses in anterior insula, anterior/mid-cingulate cortex and supplementary motor area, but showed no difference from controls after the empathy prompt. These findings (1) link shared multi-voxel representations of the distress of self and others to real-world costly altruism, (2) reinforce distinctions between empathy for sensory states like pain and anticipatory affective states like fear, and (3) highlight the importance of differentiating between the proclivity and ability to empathize.
Highlights
Fewer than 350 Americans annually undergo surgery to donate a kidney to a stranger (Organ Procurement and Transplantation Network Data as of May, 2019)
Our first goal was to use multivariate cross-classification (MVCC)—a machine learning approach in which a classifier is trained to discriminate between neural responses in one context tested for its ability to discriminate between responses in a distinct context23—to examine the role of affective resonance in altruism
The present study used multivariate cross-classification to reveal greater similarity between real-world altruists’ neural representations of their own and others’ fearful anticipation and pain, indicating that individuals who engage in acts of costly altruism experience greater affective resonance with strangers’ distress
Summary
Fewer than 350 Americans annually undergo surgery to donate a kidney to a stranger (Organ Procurement and Transplantation Network Data as of May, 2019). Exhibit greater self-other overlap in AI during the fearful anticipation of pain, consistent with prior work linking altruism to increased sensitivity to others’ fear[3,21,22] It remains unknown whether these overlapping responses reflect more similar multi-voxel patterns, which would suggest true abstraction across experienced and observed distress and more directly index empathic affective resonance. Our first goal was to use multivariate cross-classification (MVCC)—a machine learning approach in which a classifier is trained to discriminate between neural responses in one context tested for its ability to discriminate between responses in a distinct context23—to examine the role of affective resonance in altruism We used this approach to assess the similarity of altruists’ experienced and observed (empathic) multi-voxel response patterns to both pain and fearful anticipation. Non-aversive control trials were included throughout each of the three runs
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