My thought is that you could define a new variable

diff(t) = num_on_sugar_side(t) - num_on_sugar_side(t-30s)

If the insects do not care about the sugar, then these counts should be randomly distributed, with the average change relating to the probability that a bug chooses to move over a 30s period. The counts should go up or down with equal probability (everything else being equal).

If the insects do care about the sugar, then these counts should be lopsided: i.e. they should be more likely to increase if bugs like sugar, and more likely to decrease otherwise.

If our null hypothesis is that the bugs don't care about sugar, then we aught to be able to test it here.

I might opt to use a non-parametric test because I'm not too sure about how this would be distributed. Maybe Wilcoxon Rank Sum? Perhaps someone who knows more about these things can jump in...

My thought is that you could define a new variable

diff(t) = num_on_sugar_side(t) - num_on_sugar_side(t-30s)

If the insects do not care about the sugar, then these counts should be randomly distributed, with the average change relating to the probability that a bug chooses to move over a 30s period. The counts should go up or down with equal probability (everything else being equal).

If the insects do care about the sugar, then these counts should be lopsided: i.e. they should be more likely to increase if bugs like sugar, and more likely to decrease otherwise.

If our null hypothesis is that the bugs don't care about sugar, then we aught to be able to test it here.

I might opt to use a non-parametric test because I'm not too sure about how this would be distributed. Maybe Wilcoxon Rank Sum? Perhaps someone who knows more about these things can jump in...