Collaborations
science is more fun when you do it with friends
science is more fun when you do it with friends
Travis and I have been collaborating since 2014 to study how obesity and consumption of fatty, sugary foods affect extracellular matrix proteins and prefrontal cortical function. We’ve published several papers around this topic, some in outbred rats and some using my selectively bred obesity-prone and obesity-resistant model. Through this work we’ve found sex differences in high-fat and junk-food diet induced cortical plasticity. We are currently conducting studies to determine how these alterations affect value-based decision making mediated by the prefrontal cortex.
Stephanie and I have complementary interests in understanding how insulin influences synaptic transmission and plasticity; her group has been studying dopamine neurons in the ventral tegmental area, while my group studies the NAc. We are collaborating to develop an insulin sensor, akin to the GrabDA sensor, for use in vivo and ex vivo. This work is funded by a grant from Brain Canada.
Monica is a fly geneticist who studies taste and how consumption of sugar alters taste perception in flies and transcriptional regulation. We began a fruitful collaboration several years ago, and published a study in rats showing that prolonged sucrose consumption blunts primary taste nerve responses to sucrose, without altering taste bud morphology. In ongoing studies conducted in collaboration with Dr. Francesca Telese at UCSD we are using single nuclei RNA sequencing of NAc tissue to determine how prolonged sucrose consumption alters gene expression, with a focus on changes in transcriptional regulation.
My interest in careful examination of rodent behavior led me to collaborate with Dr. Bing Ye here at UM to develop and adapt “LabGym”, a machine-learning based approach to automated identification and quantification of complex animal behaviors that his lab developed, for use in studies of motivation in rodents. This approach is unique in that it does not use pose estimation, rather it classifies behaviors based on video examples provided by the experimenter. The software then provides quantitative metrics of the behaviors of interest. Bing and I organized a workshop to introduce and teach scientists about LabGym. I am continuing to work with his group to refine this approach for use in operant boxes and with complex rodent behavior.
https://github.com/umyelab/LabGym?tab=readme-ov-file