Emotions are a fascinating aspect of our behavior and motivational drive. At the same time, they are notoriously difficult to assess and characterize, both quantitatively and qualitatively, especially in animal research models. As a result, researchers often overlook the internal state and effects of laboratory rodents during data collection despite testing most biological hypotheses on them. However, the current state of scientific knowledge is now sufficiently advanced to allow for a change in this paradigm.  

This Methods Collection will gather visual protocols focusing on new, refined methods of quantifying and interpreting animal emotion. The visualized experiments and concepts will exemplify the assessment of positive and negative effects in relation to fear, distress, social bond, reward or play, and context (physical or social enrichment). In particular, emotions of positive valence are underrepresented because they manifest subtly. Combinations of traditional measures and observations with new, AI-assisted methods can now unveil complex internal states and help shift the prism of negative valence through which emotions have been apprehended.  

Including these methods in neuroscientific procedures could represent a significant breakthrough in deepening our understanding of results and improving their interpretation for better translatability.