From survival in the wild to living in complex societies, brains seek to stay clear from danger while following up on opportunities. This is controlled by affective networks which associate environmental stimuli with threat or rewards, and initiate the corresponding defensive or appetitive responses, respectively.
In a circuit neuroscience initiative, we deconstruct how the brain computes such affective stimulus-behavior transformations at the neuronal network level. We have recently identified a cortico-limbic circuit module between amygdala, brainstem and insular cortex, which serves as model to study two key steps in this process (Grössl et al. 2018, Kargl et al. 2020): How does this network build affective models and integrates interoceptive intuition (gut feelings) to assign an affective value (salience (important) and valence (good or bad)) - to environmental stimuli? How, in turn, are these affective responses gated in space (object navigation) and time (impulse control) (Piszczek et al. 2022)?
In the long run, this research helps to explain how brains assign the world with emotions and controls its affective reactions to it.
Perhaps luckily so, individual brains interpret and react to the world differently. Some are more anxious, impulsive or dominant, others less. But what contributes to this diversity? To a large part, neuronal circuitry can be genetically programmed for certain behavioral bias, which manifests as a behavioral trait or psychiatric disease (e.g. stress disorders). One attractive model is that most of the genetic variance accumulates along specific sites in neuronal networks, biasing local computations, which in turn underly transitions between behavioral phenotypes. Indeed, genetic variance for a given psychiatric trait maps to specific subnetworks in the brain (Ganglberger et al. 2018).
We are currently adopting integrated workflows that bridge circuit neuroscience with neurogenetic data (Pfaff, Tabansky, and Haubensak 2019) to investigate how sets of genes might bias circuit activity and responding. In the long run, this will help to understand constraints and freedoms between genetic variance, circuit computation and affective traits ? processes that drive behavioral diversity in health and psychiatric conditions.