Department of Psychology, Personality Psychology and Assessment, University of Marburg, 35032 Marburg, Germany; Department of Psychology, Clinical Psychology and Psychotherapy, University of Giessen, 35394 Giessen, Germany.
Department of Psychiatry and Psychotherapy, Translational Neuroimaging Marburg, University of Marburg, 35039 Marburg, Germany.
Neuroimage. 2021 Feb 1;226:117569. doi: 10.1016/j.neuroimage.2020.117569. Epub 2020 Nov 20.
Electrophysiological studies in rodents allow recording neural activity during threats with high temporal and spatial precision. Although fMRI has helped translate insights about the anatomy of underlying brain circuits to humans, the temporal dynamics of neural fear processes remain opaque and require EEG. To date, studies on electrophysiological brain signals in humans have helped to elucidate underlying perceptual and attentional processes, but have widely ignored how fear memory traces evolve over time. The low signal-to-noise ratio of EEG demands aggregations across high numbers of trials, which will wash out transient neurobiological processes that are induced by learning and prone to habituation. Here, our goal was to unravel the plasticity and temporal emergence of EEG responses during fear conditioning. To this end, we developed a new sequential-set fear conditioning paradigm that comprises three successive acquisition and extinction phases, each with a novel CS+/CS- set. Each set consists of two different neutral faces on different background colors which serve as CS+ and CS-, respectively. Thereby, this design provides sufficient trials for EEG analyses while tripling the relative amount of trials that tap into more transient neurobiological processes. Consistent with prior studies on ERP components, data-driven topographic EEG analyses revealed that ERP amplitudes were potentiated during time periods from 33-60 ms, 108-200 ms, and 468-820 ms indicating that fear conditioning prioritizes early sensory processing in the brain, but also facilitates neural responding during later attentional and evaluative stages. Importantly, averaging across the three CS+/CS- sets allowed us to probe the temporal evolution of neural processes: Responses during each of the three time windows gradually increased from early to late fear conditioning, while long-latency (460-730 ms) electrocortical responses diminished throughout fear extinction. Our novel paradigm demonstrates how short-, mid-, and long-latency EEG responses change during fear conditioning and extinction, findings that enlighten the learning curve of neurophysiological responses to threat in humans.
在啮齿动物中进行的电生理研究允许以高时间和空间精度记录威胁期间的神经活动。尽管 fMRI 有助于将有关潜在大脑回路解剖结构的见解转化为人类，但神经恐惧过程的时间动态仍然不透明，需要 EEG。迄今为止，对人类脑电生理信号的研究有助于阐明潜在的感知和注意力过程，但广泛忽略了恐惧记忆痕迹随时间如何演变。EEG 的低信噪比要求在大量试验中进行聚合，这将消除由学习引起的和易于习惯化的短暂神经生物学过程。在这里，我们的目标是阐明恐惧条件反射过程中 EEG 反应的可塑性和时间出现。为此，我们开发了一种新的顺序集恐惧条件反射范式，该范式包括三个连续的获得和消退阶段，每个阶段都有一个新的 CS+/CS-集。每个集由两个不同的中性面孔组成，分别位于不同的背景颜色上，分别用作 CS+和 CS-。因此，这种设计为 EEG 分析提供了足够的试验次数，同时将涉及更短暂神经生物学过程的试验次数增加了两倍。与关于 ERP 成分的先前研究一致，数据驱动的地形 EEG 分析表明，ERP 幅度在 33-60ms、108-200ms 和 468-820ms 的时间段内增强，这表明恐惧条件反射优先考虑大脑中的早期感觉处理，但也促进了后期注意力和评估阶段的神经反应。重要的是，在三个 CS+/CS-集上进行平均处理使我们能够探测神经过程的时间演变：在三个时间窗口中的每一个期间，反应逐渐从早期恐惧条件反射增加到晚期恐惧条件反射，而长潜伏期（460-730ms）的皮层电反应在整个恐惧消退过程中逐渐减少。我们的新范式展示了在恐惧条件反射和消退期间短、中和长潜伏期 EEG 反应如何变化，这些发现为人类对威胁的神经生理反应的学习曲线提供了启示。
