Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom.
Elife. 2019 Jul 25;8:e44838. doi: 10.7554/eLife.44838.
Risk derives from the variation of rewards and governs economic decisions, yet how the brain calculates risk from the frequency of experienced events, rather than from explicit risk-descriptive cues, remains unclear. Here, we investigated whether neurons in dorsolateral prefrontal cortex process risk derived from reward experience. Monkeys performed in a probabilistic choice task in which the statistical variance of experienced rewards evolved continually. During these choices, prefrontal neurons signaled the reward-variance associated with specific objects ('object risk') or actions ('action risk'). Crucially, risk was not derived from explicit, risk-descriptive cues but calculated internally from the variance of recently experienced rewards. Support-vector-machine decoding demonstrated accurate neuronal risk discrimination. Within trials, neuronal signals transitioned from experienced reward to risk (risk updating) and from risk to upcoming choice (choice computation). Thus, prefrontal neurons encode the statistical variance of recently experienced rewards, complying with formal decision variables of object risk and action risk.
风险源于回报的变化，并支配着经济决策，但大脑如何根据经历事件的频率而不是明确的风险描述线索来计算风险，目前仍不清楚。在这里，我们研究了背外侧前额叶皮层中的神经元是否处理源自奖励体验的风险。猴子在一个概率选择任务中执行，其中经验奖励的统计方差不断演变。在这些选择中，前额叶神经元会对特定物体（“物体风险”）或动作（“动作风险”）的相关奖励方差进行信号传递。至关重要的是，风险不是源自明确的、描述性的风险线索，而是从最近经历的奖励方差中内部计算得出的。支持向量机解码证明了神经元风险的准确区分。在试验内，神经元信号从经历的奖励转变为风险（风险更新），再从风险转变为即将到来的选择（选择计算）。因此，前额叶神经元编码了最近经历奖励的统计方差，符合物体风险和动作风险的正式决策变量。
