This week we profile a recent publication in NeuroImage from Dr. Scott Murray and
Dr. Michael-Paul Schallmo (pictured).
Can you provide a brief overview of your lab’s current research focus?
I’ve just recently started a position as an Assistant Professor in the Department of Psychiatry and Behavioral Science at the University of Minnesota. My lab at UMN is focused on understanding how the brain processes visual information, and how this is disrupted in neural and psychiatric disorders. This includes work examining vision in people with psychosis and autism spectrum disorders. I use a variety of methods in this work including behavioral tests, functional MRI to measure neural responses, and MR spectroscopy to look at brain chemistry.
What is the significance of the findings in this publication?
Our paper shows how brain chemistry relates to neural responses, and ultimately to how people perceive visual motion. Using MR spectroscopy, we can measure an index of glutamate, which is a neurotransmitter that affects brain activity. We showed that the amount of glutamate in a particular part of the brain that processes visual motion (called area MT) is related to the strength of the fMRI response (an index of neural activity) in that area (more glutamate, larger fMRI response, indicating a bigger neural response). We also showed that the amount of glutamate in area MT correlates with how well people do in a test of visual motion perception (more glutamate, superior performance). Together, this suggests that having glutamate facilitates larger neural responses and better behavioral performance during motion perception.
What are the next steps for this research?
The next steps for this line of research include looking at the role of glutamate during visual processing in clinical disorders such as autism and psychosis. People with these disorders show differences in visual perception, and it may be that glutamate is involved in these abnormalities.
This research was funded by:
This work was supported by funding from the National Institutes of Health (F32 EY025121 to MPS, R01 MH106520 to SOM, T32 EY00703). This work applies tools developed under NIH grants R01 EB016089 and P41 EB015909; RAEE also receives support from these grants.
