Testing a theory of avoidance learning & overgeneralization in chronic pain

当我们触摸到一个热炉子或撞我们的脚对客厅的桌子，它伤害。虽然令人恼火， 现在，急性疼痛起着重要的作用。首先，它会立即引发防御反应， 防止或避免进一步的组织损伤。其次，它是一个强有力的教学信号，以确保我们 避免在未来犯同样的错误。这是一种适应性反应，如果疼痛感消退 当组织愈合时。然而，当疼痛持续超过3个月时， 大脑中错误解释这些教学信号的人可能会导致疼痛慢性化。类似于 即使在火被扑灭后，火警仍继续响起，大脑被认为是继续工作的。 预测它是在一个环境中的伤害和从事回避行为，即使在组织已经 好了重要的是，这些伤害信念被认为会转化为其他非伤害背景，导致一个 避免伤害的过度概括。 这种疼痛的伤害避免模型与最近的神经影像学发现很好地联系在一起，这些发现表明， 额-纹状体回路参与情境值的表征和强化学习， 慢性疼痛患者然而，这些相互作用的大脑系统有助于 慢性疼痛或其改善是未知的。 在这里，我们扩展了一个学习任务和计算模型，结合EEG来区分 在慢性疼痛患者中，（PFC驱动的）背景值估计与（BG驱动的）学习之间存在差异。 具体来说，我们检验了慢性疼痛患者的回避学习可能是由一种 过度强调从负面结果中学习，以及从一种伤害环境中过度概括 避免其他背景。我们假设，这可以额外观察到增加脑电图 慢性病人在伤害回避学习过程中的额叶theta波段功率。Theta波段的功率 先前示出为与上下文值和学习的表示协变，并且因此提供了一种 在整个任务中，有偏见的学习的重要读数。这项工作将为未来的 纵向研究，该任务将用于预测发生慢性疼痛的风险， 一种剧烈的疼痛状态

When we touch a hot stove or bang our foot against the living room table, it hurts. While irritating in the moment, acute pain serves an important purpose. First, it triggers an immediate defensive response to prevent or avoid further tissue damage. Second, it serves as a potent teaching signal to make sure we avoid making the same mistake in the future. This is an adaptive response if pain perception subsides when the tissue heals. However, when pain persists longer than 3 months, maladaptive learning processes in the brain that misinterpret these teaching signals may contribute to pain chronification. Analogous to a fire alarm that continues to ring even after the fire has been extinguished, the brain is thought to continue to predict that it is in a context of harm and engages in avoidance behavior even after the tissue has healed. Importantly these harm beliefs are thought to translate to other non-harm contexts, leading to an over-generalization of harm avoidance. This harm-avoidance model of pain ties in nicely with recent neuroimaging findings showing alterations in the fronto-striatal circuitry involved in the representation of context values and reinforcement learning in chronic pain Patients. However, the mechanism by which these interacting brain systems contribute to chronic pain or amelioration thereof is unknown. Here we expand a learning task and computational models in combination with EEG to differentiate between (PFC-driven) estimates of context values and (BG-driven) learning in chronic pain patients. Specifically, we test the hypothesis that avoidance learning in chronic pain patients may be driven by an overemphasis on learning from negative outcomes and an overgeneralization from one context of harm avoidance to other contexts. We hypothesize that this can be additionally observed in increased EEG frontal theta-band power in chronic patients during harm avoidance learning. Theta-band power has been previously shown to covary with the representation of context values and learning and thus provides an important read-out of biased learning throughout the task. This work will provide the basis for a future longitudinal research study where this task will be used to predict the risk of developing chronic pain after an acute pain state.