Modelling linearly the effect of the DANs on valence/speed and other metrics

on Thursday, October 13th, 2016 12:26 | by Christian Rohrsen

So this first picture shows graphically how I get the valences contributions for each of the dopaminergic clusters. On the Y-axis you see the lines I used for the modelling and on the x-axis the clusters. This is the expression pattern for all the drivers (split G4 and the dirtier G4s). I also made this expression pattern binary, to avoid the errors I could add by trying to estimate the expression intensity from the literature.


Here below are the results I obtained for one of the metrics. I wont explain to much here because the main result I see is that the results change drastically upon changes in the model. This tells me that there is something wrong there. Since making the expression table binary or weighted, or using a subset of the G4s used should not give me so random values for the dopaminergic clusters.


With this, I am quite stuck and do not know what to do next. Results seem not to show that much. Considering planning another experiment while there is time or continuing analyizing. Comments please!

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Category: neuronal activation, Operant reinforcment, Optogenetics

3 responses to “Modelling linearly the effect of the DANs on valence/speed and other metrics”

  1. I’m not sure I can comment all that much, as the output you show here, at least to me, looks quite different from the one we previously discussed. So I think you may have to explain a little more what you have changed since last time?

  2. Discussing this at labmeeting, we also found that having such hugely different scales made it difficult to compare the two versions of the model. In general, we didn’t think they results were so radically different from each other, but it’s hard to tell.

  3. We also found it weird that the last 3-5 clusters on the right in “all” have rather big values, while they seem to be zero for the lines from which “all” is supposed to be combined (i.e., dirty G4 and splitG4)?

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