With our review paper we want to inspire amygdala research by suggesting a unified narrative grounded in biological fundamentals (self-regulation) and a computational framework (Bayes). This, so called, active inference perspective would allow us to reframe different amygdala research topics that were previously fragmented:

1. Fear and Anxiety: Fear does not appear out of nowhere. Fundamentally, it is a concern about our safety. This means how safe and sound you feel at the moment influences your emotions. We see the amygdala as a mediator between interoception and exteroception. The central amygdala acts as a Bayesian regulator to inform affective states. It sends predictions to the basolateral amygdala, which allows efficient perception.

2. Danger Detection: How do we distinguish something dangerous, like a snake, from something harmless, like a rope? The context matters: if you are afraid of encountering snakes (e.g., because you are in the jungle) you are more likely to (mis)identify a snaky object as a snake. The situation would be different on a relaxing sailing cruise.

3. Fear Conditioning: Using exteroception the amygdala helps to predict deviations from optimal regulation (e.g., pain) before they happen. We call this a pro gamer move if you want to survive.

4. Actions: Some sensations feel better than others. Approach and avoidance actions can make more preferred expected sensations become reality. It's like magic. If it hurts in a bad way and you avoid it before it hurts, it does not hurt.

Sladky, R., Kargl, D., Haubensak, W., Lamm, C. (2024). An active inference perspective for the amygdala complex. Trends in Cognitive Sciences. 28, 223–236. https://doi.org/10.1016/j.tics.2023.11.004 

Click here for a link to the full text.