journal article·2026-01Open access

Efficiency Recalibrates Social‐Emotional Trade‐Offs Behind Partner Choice in Direct Reciprocity through Intention‐Specific Neural Bases

Rui Liao, Xintong Li, Xuqi Liu, Yu Nan, Xiaolin Zhou, Xiaoxue Gao

Advanced Science· Volume 13· Issue 5

Abstract

Abstract Direct reciprocity, in which beneficiaries return favors to benefactors, is a cornerstone of human cooperation. Previous empirical work addresses partner control—how individuals decide whether and how much to reciprocate—whereas the equally critical dimension of partner choice, deciding whom to reciprocate when aided by multiple benefactors, remains understudied. This gap is addressed by testing two determinants: social‐emotional motivations and reciprocal efficiency (the efficiency of reinforcing future relational capital). Combining an interpersonal task with fMRI multivariate neural expressions and representational similarity analysis, it is demonstrated that efficiency recalibrates choices between altruistic and strategic benefactors by shifting the neural balance between distinct social‐emotional concerns. When reciprocating to altruistic benefactors yielded higher efficiency, participants prioritized communal concerns (gratitude/guilt) represented in the ventromedial prefrontal cortex, whereas higher efficiency for strategic benefactors led them to prioritize obligation represented in the ventral striatum. General efficiency engaged the putamen, dorsomedial prefrontal, and orbitofrontal cortices; the inferior parietal lobe integrated efficiency‐driven recalibration. These findings suggest that efficiency does not merely optimize material outcomes but adaptively reweights social‐emotional concerns behind reciprocal partner choices, bridging economic models of rational choice with psychological theories of social emotions, offering insights into human cooperation and related practical applications.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Evolutionary Game Theory and Cooperation · Experimental Behavioral Economics Studies · Action Observation and Synchronization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention School of Psychology and Cognitive Science East China Normal University Shanghai 200062 China

School of Psychological and Cognitive Sciences Peking University Beijing 100871 China

Funding

National Natural Science Foundation of China · Fundamental Research Funds for the Central Universities

References (100+)

Show source-provided references
1. 10.1038/s41562-018-0385-510.1038/s41562-018-0385-5 ↗
2. 10.1146/annurev-psych-081920-04210610.1146/annurev-psych-081920-042106 ↗
3. 10.1126/science.113375510.1126/science.1133755 ↗
4. 10.1016/j.cub.2007.06.00410.1016/j.cub.2007.06.004 ↗
5. 10.1016/j.tics.2013.06.00310.1016/j.tics.2013.06.003 ↗
6. 10.1146/annurev-economics-080213-04131210.1146/annurev-economics-080213-041312 ↗
7. 10.1257/00028280577466973610.1257/000282805774669736 ↗
8. 10.1126/science.114299610.1126/science.1142996 ↗
9. 10.1038/nrn377610.1038/nrn3776 ↗
10. 10.1146/annurev.psych.121208.13164710.1146/annurev.psych.121208.131647 ↗
11. Dufwenberg M. · Homo Oecon.‐J. Behav. Inst. Econ. · 2001 · 18 · 19
12. 10.1146/annurev-psych-081420-11071810.1146/annurev-psych-081420-110718 ↗
13. 10.1257/jep.14.3.15910.1257/jep.14.3.159 ↗
14. 10.1016/S0022-5193(05)80072-410.1016/S0022-5193(05)80072-4 ↗
15. Fehr E. · SSRN Electron. J. · 2003
16. 10.1038/nature0241410.1038/nature02414 ↗
17. 10.1038/s41562-021-01114-810.1038/s41562-021-01114-8 ↗
18. 10.1038/s41562-018-0320-910.1038/s41562-018-0320-9 ↗
19. 10.1111/j.1751-9004.2012.00439.x10.1111/j.1751-9004.2012.00439.x ↗
20. 10.1038/nn157510.1038/nn1575 ↗
21. 10.1093/scan/nsp00910.1093/scan/nsp009 ↗
22. 10.1002/hbm.2345110.1002/hbm.23451 ↗
23. 10.3389/fnins.2012.0014810.3389/fnins.2012.00148 ↗
24. 10.1126/science.110806210.1126/science.1108062 ↗
25. 10.1016/B978-0-12-374176-9.00013-010.1016/B978-0-12-374176-9.00013-0 ↗
26. 10.1038/s41467-019-09161-610.1038/s41467-019-09161-6 ↗
27. 10.1086/69635610.1086/696356 ↗
28. 10.1007/BF0094141810.1007/BF00941418 ↗
29. 10.3724/SP.J.1042.2022.0235610.3724/SP.J.1042.2022.02356 ↗
30. 10.1371/journal.pone.012519310.1371/journal.pone.0125193 ↗
31. 10.1016/j.jtbi.2011.04.02310.1016/j.jtbi.2011.04.023 ↗
32. 10.1016/j.evolhumbehav.2013.02.00210.1016/j.evolhumbehav.2013.02.002 ↗
33. 10.1016/j.copsyc.2015.07.01210.1016/j.copsyc.2015.07.012 ↗
34. Martin J. · ResearchGate · 2019
35. 10.1007/BF0016705310.1007/BF00167053 ↗
36. Noë R. · 2013 · 131
37. 10.1016/j.evolhumbehav.2004.04.00210.1016/j.evolhumbehav.2004.04.002 ↗
38. 10.1016/j.jenvp.2020.10144110.1016/j.jenvp.2020.101441 ↗
39. 10.1098/rspb.2006.020910.1098/rspb.2006.0209 ↗
40. 10.1177/014616720629100610.1177/0146167206291006 ↗
41. 10.1098/rspb.1998.031210.1098/rspb.1998.0312 ↗
42. 10.1093/scan/nst16810.1093/scan/nst168 ↗
43. 10.1080/17470919.2017.137001010.1080/17470919.2017.1370010 ↗
44. 10.3389/fnhum.2019.0027110.3389/fnhum.2019.00271 ↗
45. 10.1017/S0140525X1100220210.1017/S0140525X11002202 ↗
46. 10.1017/S193029750000640910.1017/S1930297500006409 ↗
47. 10.1038/s41467-023-44286-910.1038/s41467-023-44286-9 ↗
48. 10.1007/s11031-006-9031-z10.1007/s11031-006-9031-z ↗
49. 10.2117/psysoc.2010.17910.2117/psysoc.2010.179 ↗
50. 10.1080/0269993050017229110.1080/02699930500172291 ↗
51. 10.1523/JNEUROSCI.2944-17.201810.1523/JNEUROSCI.2944-17.2018 ↗
52. 10.1037/emo000025810.1037/emo0000258 ↗
53. Elfers J. · 201610.1007/978-3-319-41030-2 ↗
54. 10.1037/1528-3542.8.3.42510.1037/1528-3542.8.3.425 ↗
55. 10.1037/0033-2909.115.2.24310.1037/0033-2909.115.2.243 ↗
56. 10.1037/bul000013310.1037/bul0000133 ↗
57. 10.1038/nature0413110.1038/nature04131 ↗
58. 10.1037/pspa000037510.1037/pspa0000375 ↗
59. 10.1093/scan/nst09010.1093/scan/nst090 ↗
60. 10.1016/j.neuroimage.2021.11863110.1016/j.neuroimage.2021.118631 ↗
61. 10.2307/209262310.2307/2092623 ↗
62. 10.1177/01902725070700020810.1177/019027250707000208 ↗
63. 10.1177/014616729319600310.1177/0146167293196003 ↗
64. Greenberg M. S. · 1980 · 310.1007/978-1-4613-3087-5_1 ↗
65. 10.1086/40675510.1086/406755 ↗
66. 10.1093/cercor/bhz32610.1093/cercor/bhz326 ↗
67. 10.1016/j.neuron.2011.02.05610.1016/j.neuron.2011.02.056 ↗
68. 10.1073/pnas.131857011110.1073/pnas.1318570111 ↗
69. 10.1111/j.1475-6811.2010.01273.x10.1111/j.1475-6811.2010.01273.x ↗
70. 10.1080/02699931.2011.56129710.1080/02699931.2011.561297 ↗
71. 10.1037/a002155710.1037/a0021557 ↗
72. 10.1111/evo.1237810.1111/evo.12378 ↗
73. 10.1111/j.1558-5646.2011.01479.x10.1111/j.1558-5646.2011.01479.x ↗
74. 10.1162/qjec.2009.124.4.181510.1162/qjec.2009.124.4.1815 ↗
75. 10.1145/2783258.278341010.1145/2783258.2783410 ↗
76. Cheng J. · 49
77. 10.1002/cd.3510.1002/cd.35 ↗
78. 10.1016/j.neuroimage.2016.09.05210.1016/j.neuroimage.2016.09.052 ↗
79. 10.1016/j.plrev.2023.05.00210.1016/j.plrev.2023.05.002 ↗
80. 10.1006/jtbi.2000.211110.1006/jtbi.2000.2111 ↗
81. Lin N. · 2017 · 310.4324/9781315129457-1 ↗
82. 10.1007/978-1-137-09971-6_910.1007/978-1-137-09971-6_9 ↗
83. 10.3389/fpsyg.2016.0046010.3389/fpsyg.2016.00460 ↗
84. 10.1257/aer.90.1.16610.1257/aer.90.1.166 ↗
85. 10.1016/S1574-0722(07)00059-510.1016/S1574-0722(07)00059-5 ↗
86. 10.1016/S1574-0722(07)00046-710.1016/S1574-0722(07)00046-7 ↗
87. 10.1007/s10683-011-9283-710.1007/s10683-011-9283-7 ↗
88. 10.3389/fpsyg.2016.0072810.3389/fpsyg.2016.00728 ↗
89. 10.1109/TEVC.2023.324453710.1109/TEVC.2023.3244537 ↗
90. 10.3389/fnins.2019.0088710.3389/fnins.2019.00887 ↗
91. 10.2307/223413310.2307/2234133 ↗
92. 10.2308/acch-1022910.2308/acch-10229 ↗
93. 10.1177/089976401877389910.1177/0899764018773899 ↗
94. 10.1038/s41586-019-1488-510.1038/s41586-019-1488-5 ↗
95. 10.1257/aer.90.4.98010.1257/aer.90.4.980 ↗
96. 10.1016/j.jebo.2003.11.01010.1016/j.jebo.2003.11.010 ↗
97. 10.1080/1479277914300005110.1080/14792779143000051 ↗
98. 10.1126/science.115365110.1126/science.1153651 ↗
99. 10.1257/000282804200274110.1257/0002828042002741 ↗
100. 10.1257/aer.96.5.191210.1257/aer.96.5.1912 ↗