The Brain and Mind Institute, Western University, London, Ontario, Canada.
Department of Psychology, Western University, London, Ontario, Canada.
J Neurophysiol. 2020 Aug 1;124(2):610-622. doi: 10.1152/jn.00370.2020. Epub 2020 Jul 29.
Effort-based decision making is often modeled using subjective value, a function of reward discounted by effort. We asked whether EEG event-related potential (ERP) correlates of reward processing are also modulated by physical effort. Human participants performed a task in which they were required to accurately produce target levels of muscle activation to receive rewards. Quadriceps muscle activation was recorded with electromyography (EMG) during isometric knee extension. On a given trial, the target muscle activation required either low or high effort. The effort was determined probabilistically according to a binary choice, such that the responses were associated with 20% and 80% probability of high effort. This contingency could only be learned through experience, and it reversed periodically. Binary reinforcement feedback depended on accurately producing the target muscle activity. Participants adaptively avoided effort by switching responses more frequently after choices that resulted in hard effort. Feedback after participants' choices that revealed the resulting effort requirement did not elicit modulation of the feedback-related negativity/reward positivity (FRN/RP). However, the neural response to reinforcement outcome after effort production was increased by preceding physical effort. Source decomposition revealed separable early and late positive deflections contributing to the ERP. The main effect of reward outcome, characteristic of the FRN/RP, loaded onto the earlier component, whereas the reward × effort interaction was observed only in the later positivity, which resembled the P300. Thus, retrospective effort modulates reward processing. This may explain paradoxical behavioral findings whereby rewards requiring more effort to obtain can become more powerful reinforcers. Choices probabilistically determined the physical effort requirements for a subsequent task, and reward depended on task performance. Feedback revealing whether choices resulted in easy or hard effort did not elicit reinforcement learning signals. However, the neural responses to reinforcement were modulated by preceding effort. Thus, effort itself was not treated as loss or punishment, but it affected the responses to subsequent reinforcement outcomes. This may explain how effort can enhance the motivational effect of reward.
基于努力的决策通常使用主观价值来建模,主观价值是奖励与努力折扣的函数。我们想知道奖励处理的 EEG 事件相关电位 (ERP) 相关性是否也受到体力努力的调节。人类参与者执行一项任务,要求他们准确地产生肌肉激活的目标水平以获得奖励。在等长膝关节伸展期间,使用肌电图 (EMG) 记录股四头肌的激活。在给定的试验中,需要低或高努力才能达到目标肌肉激活。努力程度是根据二元选择来确定的概率,使得反应与高努力的 20%和 80%的概率相关联。这种偶然性只能通过经验来学习,并且它会周期性地反转。二元强化反馈取决于准确产生目标肌肉活动。参与者通过在导致高努力的选择后更频繁地切换反应来自适应地避免努力。在参与者的选择之后,反馈揭示了所需的努力要求,但并没有引起反馈相关负性/奖励正性 (FRN/RP) 的调制。然而,在产生努力之后,强化结果的神经反应会因先前的体力努力而增加。源分解揭示了早期和晚期正性偏转的可分离性,它们对 ERP 有贡献。奖励结果的主要效应,特征是 FRN/RP,加载到早期成分上,而奖励×努力的相互作用仅在后期正性中观察到,这类似于 P300。因此,回顾性努力调节奖励处理。这可能解释了奖励需要更多努力才能获得的矛盾行为发现,这些奖励可以成为更强大的强化物。选择概率确定了后续任务的体力努力要求,奖励取决于任务表现。反馈揭示了选择是否导致容易或困难的努力,但没有引起强化学习信号。然而,强化的神经反应受到先前努力的调节。因此,努力本身并不是损失或惩罚,而是会影响对后续强化结果的反应。这可能解释了为什么努力可以增强奖励的动机效应。