Striatal response to negative feedback in a stop signal task operates as a multi-value learning signal

Benjamin J. Smith, Megan Lipsett, Danielle Cosme, Victoria A. Braun, Anastasia M. Browning O’Hagan, Elliot T. Berkman
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Abstract

Abstract Background and aim: We examined error-driven learning in fMRI activity of 217 subjects in a stop signal task to obtain a more robust characterization of the relation between behavioral measures of learning and corresponding neural learning signals than previously possible. Methods: The stop signal task is a two-alternative forced choice in which participants respond to an arrow by pressing a left or right button but must inhibit that response on 1 in 7 trials when cued by an auditory “stop signal.” We examined post-error learning by comparing brain activity (BOLD signal) and behavioral responses on trials preceded by successful (correct stop) vs. failed (failed stop) inhibition. Results: There was strong evidence of greater bilateral striatal activity in the period immediately following correct (vs. failed) stop trials (most evident in the putamen; peak MNI coordinates [-26 8 -2], 430 voxels, p < 0.001; [24 14 0], 527 voxels, p < 0.001). We measured median activity in the bilateral striatal cluster following every failed stop and correct stop trial and correlated it with learning signals for (a) probability and (b) latency of the stop signal. In a mixed-effects model predicting activity 5-10 s after the stop signal, both reaction time (RT) change (B = -0.05, t = 3.0, χ2 = 11.3, p < 0.001) and probability of stop trial change (B = 1.53, t = 6.0, χ2 = 43.0, p < 0.001) had significant within-subjects effects on median activity. In a similar mixed model predicting activity 1-5 s after the stop signal, only probability of stop trial change was predictive. Conclusions: A mixed-effects model indicates the striatal activity might be a learning signal that encodes reaction time change and the current expected probability of a stop trial occuring. This extends existing evidence that the striatum encodes a reward prediction error signal for learning within the stop signal task, and demonstrates for the first time that this signal seems to encode both change in stop signal probability and in stop signal delay.
在停止信号任务中,纹状体对负反馈的响应是一种多值学习信号
背景和目的:我们研究了217名受试者在停止信号任务中的fMRI活动中的错误驱动学习,以获得学习行为测量与相应神经学习信号之间关系的更强大的特征。方法:停止信号任务是一个两种选择的强迫选择,参与者通过按左键或右键来回应箭头,但当听到“停止信号”提示时,必须在七分之一的试验中抑制这种反应。我们通过比较成功(正确停止)和失败(失败停止)抑制之前的大脑活动(BOLD信号)和行为反应来检查错误后学习。结果:有强有力的证据表明,在正确(与失败)停止试验后的一段时间内,双侧纹状体活动更大(最明显的是壳核;峰值MNI坐标[-26 8 -2],430体素,p <0.001;[24 14 0], 527体素,p <0.001)。在每次失败的停止和正确的停止试验后,我们测量了双侧纹状体簇的中位数活动,并将其与学习信号(a)概率和(b)停止信号的潜伏期相关联。在预测停止信号后5 ~ 10 s活动的混合效应模型中,两种反应时间(RT)都发生了变化(B = -0.05, t = 3.0, χ2 = 11.3, p <0.001)和停止试验改变的概率(B = 1.53, t = 6.0, χ2 = 43.0, p <0.001)对中位活动有显著的受试者内效应。在预测停止信号后1-5秒活动的类似混合模型中,只有停止试验变化的概率是可预测的。结论:混合效应模型表明纹状体活动可能是一种学习信号,编码反应时间变化和当前停止试验发生的预期概率。这扩展了现有的证据,即纹状体在停止信号任务中为学习编码奖励预测错误信号,并首次证明该信号似乎编码了停止信号概率和停止信号延迟的变化。
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