Week 5: Long-Term Depression

Mar 21, 2019

Anyone wondering why I haven’t posted about the results of the OKR data? I have to keep some secrets … and while we’re on that subject, make sure to attend my presentation (hint hint!). 🙂

Last week was completely full of experiments, and also included troubleshooting of a camera. More on that below.

We have four different treatments, and four experimental conditions with varying LTD functionality. Don’t remember what LTD was? The short explanation is that LTD is the opposite of making connections between neurons. The cerebellum comes pre-made with a lot of unnecessary connections, so LTD just has to break those connections that contribute to errors in performance.

In order to control for order effects, we randomize the order that each subject receives each treatment. We also wait at least three days between experiments (in reality, this is usually about a week) so that the subjects have ample time to forget all the training they had during the experiment (whether 1 Hz Gain Up or 1 Hz Gain Down, see last week’s post).

Here’s what my experiment randomization table looks like. I’ve labeled four treatments (A-D).


As you can see, all subjects (numbered 1-26 with some gaps) receive OKR training. Then each treatment is done at least four times a week with the exception of A in week 4 (which is a small mistake, but now cannot be corrected). Treatments are in a random order, and all are the same. This way, we can be sure that learning is from the treatment itself rather than due to order effects.

We have a camera in the Raymond Lab that is designed to look at eye movements by taking a video of the eye, and then match those eye movements to the signal made by movement of the magnet. This is called calibration — it calibrates the magnet signal to the actual eye movements, and produces a scaling factor, which tells us how many degrees of eye movement corresponds to how many volts in the signal we receive.

Because we are trying to create a new experimental rig downstairs, I have been helping troubleshoot the new camera for this rig. The camera has to be positioned very precisely relative to the eye during experiments, and because I have done many experiments, I have developed a knack for this. I also know the math behind how the camera calculates eye position based on the two images it receives (yes, it’s actually two cameras). If you want to know what it is, you can look at this paper.

Next week will be the last week of experiments!


7 Replies to “Week 5: Long-Term Depression”

  1. Harleen D. says:

    As the experiments come to an end, it’s nice that you’ve developed a knack for what you need to do to speed up the process!

  2. Jake I. says:

    Very interesting how the camera tracks the eye movements! What exactly do the movements of the eye tell you about the treatment/patient?

    1. Jaydev B. says:

      An increase in eye movement reflects an improvement in learning. If the sinusoidal fit (see Week 3) shows an increase in amplitude of eye movements, we can conclude that the mouse learned to increase its eye movements.

  3. Beryl Z. says:

    What do you plan on doing after the experiments end? Will you be able to reach a conclusion? Your research has been super interesting so far!

    1. Jaydev B. says:

      If the data show the effects we’re looking for, I still may be able to make a conclusion. But probably, I will need to redo them.

      One way or another, I’ll have a conclusion, and it will be good.

    2. Jaydev B. says:

      Thanks! Yours is great too! I love your miniature mouse limbs! And I can’t wait to see your Claymation! You should use that tiny hand to point at things like you used in your CRISPR video, that will mimic the shape of the mouse limbs.

  4. anuradhamurthy says:

    Wonderful to see the progress you have made and how much you have learned in the process. Thanks for giving me a glimpse into current lab research!

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