INTENDeD – INTegration of EmotioNs During Decision-Making

Emotions are often contrasted with reason. However, the integration of emotional information into the decision-making processes can advantageously bias adaptive behavior selection. Miss-regulation of emotional information integration in cortical processing is a hallmark of psychiatric disorders with affect dysregulation. Our knowledge of the etiology and pathophysiology of these disorders is strongly limited by our understanding of the non-pathological neuronal circuits underlying emotional processing which makes targeted intervention methods scarce. 

We are therefore primarily interested in characterizing the non-pathological neuronal circuits underlying emotional processing, and more specifically in the information transfer between two hub regions: the basolateral complex of the amygdala (BLA) and the prefrontal cortex (PFC).
The BLA and PFC are implicated in valence assignment to environmental stimuli and the integration of this information in decision-making. Gaining insight into the long-range connectivity between them, as well as the integration of BLA information in the local PFC circuit in mice will therefore advance our understanding of emotional processing during decision-making. 

We hypothesize that the BLA can influence the PFC in a valence-specific manner leading to adaptive changes in action selection.
To test 
this we are investigating several interconnected questions:

  • How are the valence and value of an unconditioned stimulus, like a nutrient reward, represented in the BLA?
  • Is the BLA transmitting differential information to specific PFC subregions?
  • How is BLA information integrated into the local PFC circuit?
  • What is the role of the BLA during a two-alternative choice task?
  • How does BLA activity influence the PFC and decision-making in this task? 
 

We are investigating these questions with the long-term goal of gaining a detailed circuit- and cellular-level mechanistic understanding of the BLA on PFC processing and decision-making.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 844492