Sequential gains and losses during gambling feedback: Differential effects in time-frequency delta and theta measures.
Sequential gains and losses during gambling feedback: Differential effects in time-frequency delta and theta measures.
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DOI：
10.1111/psyp.13907
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发表时间：
2022-05
期刊：
影响因子：
3.7
通讯作者：
Bernat EM
中科院分区：
文献类型：
--
作者：
Bachman MD;Watts ATM;Collins P;Bernat EM
奖励反馈的一个关键方面是局部结果历史的影响-过去的选择和结果经验如何影响当前的行为和神经活动。然而，在这一领域的先前事件相关电位（ERP）工作一直存在争议。这项研究有助于这一领域的时间-频率措施，以更好地隔离组成过程。具体来说，我们确定θ和三角洲是如何不同的敏感性，当地的结果的历史。参与者完成了一个二元货币选择任务，而我们收集脑电图数据。他们不知道的是，试验结果被操纵成预先确定的序列，从一个到八个连续的收益或损失。按序列建立（序列的前2次试验）和延续（3-8次试验的延长序列）安排分析。在建立序列的过程中，增量活动对收益和损失的影响在第一次（变化）试验中几乎是相同的，仅在第二次试验中表现出明显的分歧。这种差异在整个延续期内不断扩大，因为三角洲活动持续增加，但随着多次损失而下降。相反，θ活性在变化试验中表现出最大的损失-增益差异，但对建立新序列不敏感。结果之间的差异θ活动随着序列的继续而减少，θ活动随着累积收益而增加，并且在损失时保持稳定。结果表明，增量增益和θ-损失信号在连续结果中相对稳定。此外，θ是最敏感的损失-增益差异的初始变化试验，而三角洲是更敏感的收益-损失的差异与序列的延续。
One critical aspect of reward-feedback is the impact of local outcome history – how past experiences with choices and outcomes influences current behavior and neural activity. Yet, prior event-related potential (ERP) work in this area has been contentious. This study contributes to this field by using time-frequency measures to better isolate constituent processes. Specifically, we identify how theta and delta are differentially sensitive to local outcome history. Participants completed a binary monetary choice task while we collected EEG data. Unbeknownst to them, trial outcomes were manipulated into pre-determined sequences, ranging from one to eight gains or losses in a row. Analyses were arranged by sequence establishment (first 2 trials of a sequence) and continuation (prolonged sequences of 3–8 trials). During the establishment of a sequence, delta activity to gains and losses were virtually identical on the first (change) trial, demonstrating marked divergence only on the second trial. This difference grew throughout the continuation period, as delta activity was sustained with accruing gains but declined with multiple losses. Theta activity, conversely, demonstrated a maximal loss-gain difference on the change trial but was insensitive to the establishment of a new sequence. Differential theta activity between outcomes decreased as sequences continued, with theta activity increasing over accruing gains and remaining stable over losses. Results indicate that delta-gain and theta-loss signals are relatively stable across sequential outcomes. Furthermore, theta is most sensitive to loss-gain differences on the initial change trial, while delta is more sensitive to gain-loss differences with the continuation of a sequence.
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