A Day of Neurons

A typical day for me in the Gong Lab consists of me helping my mentor, Emily, with her project on how visual manipulations in virtual reality affect the firing pattern of place cells in mice. This project has been ongoing for a couple of months, and the data collection of the mice running through different conditions in the virtual reality set-up has already been completed.

What I am doing now is selecting through a list of computer generated masks and determining which circled areas are neurons and which are just arbitrary areas of fluorescence. This is necessary because the algorithm that is used to circle the potential neurons is not always accurate and may outline a group of pixels that does not represent a singular neuron. For example, the outline might circle two neurons, the space between two neurons, only part of the neuron, part of a neighboring neuron, etc. What I have learned from this particular task is that science is a slow process and that while looking at neurons firing on a computer screen may seem like a repetitive and mundane job, it is just as important towards the final results as any other step in the research project. 

Additionally, Emily is starting to train new mice, so I am getting some more hands-on experience with the mice and with the wet lab aspect of research by helping with the water restriction process. This process consists of giving a small amount of water to each mouse only once a day and recording the mouse’s percent weight loss. This water restriction process is necessary because in the experimental and training period, the mice are given water as positive reinforcement to reward their behavior.

In my free time at the lab, I am also working on improving my MatLab skills by practicing with some problem sets. These problems focus on the areas of MatLab that are important for the coding of the video processing program that we are currently using to select through the potential neurons. Once I have mastered the MatLab skills in these specific areas, I will be able to better understand how the computer is generating the masks around the areas of fluorescence and hopefully be able to use this deeper understanding to make more accurate neuron selections.

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