research

Distinguishing between the sensory and emotional states of pain in animals has been extremely challenging, because traditional measurements of pain provide limited resolution. We use fast imaging, computation, and mathematics to overcome this problem. An innovation in our work is recording sub-second behaviors in freely behaving mice and analyzing the data with artificial intelligence (AI) to measure pain sensation and affect.  We couple AI with software development and statistical modeling to develop mouse “pain scales” . This technology allowed us to measure, in an automated and unbiased manner, pain sensation versus affect in the nonverbal mouse.  Now that we have the ability to objectively measure pain in mice, a new direction for our lab is to determine how the brain and genome control the biological basis of individual sensitivity to pain.

Social touch is critical to relational bonds. A hug from a relative or friend evokes strong feelings of reward. Despite this general appreciation, the question remains, “how is social touch rewarding?” Although the intact nervous system faithfully transmits information about rewarding touch from skin-to-brain at rapid speed, the molecular logic of how this process works remains unknown. Here, we are using mouse genetics to test for necessity and sufficiency of molecular classes of peripheral sensory neurons in promoting normal development, resilience, and the rewarding nature of social interactions. Ongoing studies are connecting the skin and brain in vivo, by manipulating peripheral circuits while recording neuronal activity across the brain to uncover molecular details of skin-to-brain circuitry for rewarding social touch.