Affiliation
MPI of Psychiatry - Group "Neurobiology of Stress Resilience"
Contact
Neurobiology of Stress
Kraepelinstr. 2
D-80804 Munich
Phone:
+49 (89) 30622 - 519
Fax:
+49 (89) 30622 - 610
Email:
mschmidt@psych.mpg.de
Website:
http://www.psych.mpg.de/1496026/schmidt_m
Website:
https://www.imprs-ls.de/index.php?option=com_zooprofiles&task=userProfile&user=4264&Itemid=21
Research Focus
Project Title: Deep phenotyping of stress-induced behavioral dynamics
Mentor: London Aman
Stress-related disorders such as anxiety and depression affect the quality of life of millions worldwide, and often arise from interaction between stress exposure and genetic predispositions. Despite the improvements basic stress research has made utilizing animal models of stress behavior, these are often capturing only snapshots of the continuous, changing behavior after a stressful experience.
We are searching for a highly motivated student to assist with an ongoing project looking into the true dynamics of stress-induced behavior in mice by analyzing 48-hour home-cage recordings after a stressful event. We focus on analyzing classical home cage behavior, like food intake, sleep patterns, or exploration, but more importantly, we look past this to deep-phenotyping using deep-learning based tracking algorithms to understand stress behavior over time. With information over the full circadian rhythm and behavioral syllables such as sniffing and hiding, we better highlight differences due to stress and biological sex to understand their role in disease prevalence.
To improve our understanding of the interaction between genetics and stress, we will utilize a mouse line with glutamatergic neurons lacking FKBP51, a stress-responsive molecular chaperone implicated in stress and psychiatric disorders. Our aim for our work is to aid the behavioral research field in encouraging a more ecologically-relevant, informed testing environment and more effective translation towards psychiatric disease treatments.
Note: day-to-day work for this project as an Amgen scholar will be more analytical than hands-on. You would mainly learn how to use machine-learning based programs to efficiently analyze animal behavior, how to optimize cutting-edge behavioral analysis techniques, and how to draw meaningful conclusions from data. You would still have the opportunity to learn and practice certain techniques in the lab, based on interest and capacity.
Necessary Skills:
- Familiarity with coding (python, etc.) or a motivation to learn
- Comfort / openness to working with mice if interested
- Working effectively in a team spirit
- Attention to detail & good organization
- Interest in propelling methods development
- Curiosity!