利他选择的神经计算模型及其意义。
A Neurocomputational Model of Altruistic Choice and Its Implications.
作者信息
Hutcherson Cendri A, Bushong Benjamin, Rangel Antonio
机构信息
Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125, USA; Department of Psychology, University of Toronto, Toronto, ON M1C 1A4, Canada.
Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125, USA; Department of Economics, Harvard University, Cambridge, MA 02138, USA.
出版信息
Neuron. 2015 Jul 15;87(2):451-62. doi: 10.1016/j.neuron.2015.06.031.
We propose a neurocomputational model of altruistic choice and test it using behavioral and fMRI data from a task in which subjects make choices between real monetary prizes for themselves and another. We show that a multi-attribute drift-diffusion model, in which choice results from accumulation of a relative value signal that linearly weights payoffs for self and other, captures key patterns of choice, reaction time, and neural response in ventral striatum, temporoparietal junction, and ventromedial prefrontal cortex. The model generates several novel insights into the nature of altruism. It explains when and why generous choices are slower or faster than selfish choices, and why they produce greater response in TPJ and vmPFC, without invoking competition between automatic and deliberative processes or reward value for generosity. It also predicts that when one's own payoffs are valued more than others', some generous acts may reflect mistakes rather than genuinely pro-social preferences.
我们提出了一个关于利他选择的神经计算模型，并使用行为数据和功能磁共振成像（fMRI）数据对其进行测试。该任务中，受试者要在给自己和他人的真实货币奖励之间做出选择。我们发现，一个多属性漂移扩散模型能够捕捉到选择、反应时间以及腹侧纹状体、颞顶联合区和腹内侧前额叶皮质神经反应的关键模式。在这个模型中，选择源于一个相对价值信号的积累，该信号对自己和他人的收益进行线性加权。该模型对利他主义的本质产生了一些新的见解。它解释了何时以及为何慷慨选择比自私选择更快或更慢，以及为何它们在颞顶联合区和腹内侧前额叶皮质产生更大的反应，而无需援引自动和深思熟虑过程之间的竞争或慷慨的奖励价值。它还预测，当一个人对自己的收益比他人的收益更看重时，一些慷慨行为可能反映的是错误而非真正的亲社会偏好。
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