Smokers show increased fear responses towards safety signals during fear generalization, independent from acute smoking.

Smoking is highly prevalent among patients with anxiety disorders. Previous studies suggest that smokers show altered fear learning as compared to non-smokers. To test the effect of acute smoking on fear learning and generalization, we conducted a fear learning experiment online. 202 healthy subjects learned to differentiate a danger and a safe cue on day 1 and were tested for generalization of threat responses 24 h later. To see if the timing of smoking impacts fear learning, we formed three smoker groups with manipulations of acute smoking and withdrawal at different time-points (each group: n = 46) and one non-smoker control group (n = 64). Smoking manipulations contained a 6 h withdrawal after fear learning, smoking directly before or after fear learning. We found no group differences between smoker manipulation groups for fear learning or generalization. However, we found differences in fear generalization between smokers and non-smokers. Smokers showed increased fear ratings towards the stimulus that has been learned as safe and higher US expectancy to stimuli similar to the safe stimulus, when compared to non-smokers. Smoking might constitute a risk factor for impaired discrimination between danger and safety and smoking restrictions could be an effective way to reduce the risks of development or maintenance of anxiety disorders.

Acquisition of threat responses are associated with elevated plasma concentration of endocannabinoids in male humans.

Endocannabinoids (eCBs) are involved in buffering threat and stress responses. Elevation of circulating eCBs in humans was reported to strengthen inhibition (i.e., extinction) of threat responses and to reduce effects of stressors. However, it remains unclear whether the acquisition of threat responses involves a physiological change in circulating eCBs. Here, we demonstrate in male human volunteers that the plasma concentration of the eCB N-arachidonoylethanolamine (AEA) and its metabolite arachidonic acid (AA) are increased during acquisition of threat responses. Furthermore, elevated responses to a learned threat cue (e.g., rating of fear) were associated with individual increases in plasma concentration of the eCB 2-arachidonoylglycerol (2-AG). In complementing these observations, we found individual increases in AEA associated with elevated neural responses during threat learning in the amygdala. Our results thereby suggest that physiological increases in circulating eCB levels are part of a response mechanism to learned threats.

Learning dynamics of electrophysiological brain signals during human fear conditioning.

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.