#Matlab 2009 grid alpha update#
#Matlab 2009 grid alpha series#

In the current study, we asked whether somatosensory alpha activity is also modulated when expecting incoming distracting stimuli on the nonattended side. In previous work, we showed that contralateral somatosensory alpha activity decreases to facilitate processing of an anticipated target stimulus in a tactile discrimination task. It has been proposed that topвЂ“down modulation of oscillatory alpha band activity (8вЂ“14 Hz) serves to allocate resources to various regions, depending on task demands. However, if you need to interact with different points (or groups of points) individually - maybe you want to add a separate legend entry for each, maybe you want to be able to turn them on and off separately etc - using plot3 in a loop may be the best (though slow) solution.Effective processing of sensory input in daily life requires attentional selection and amplification of relevant input and, just as importantly, attenuation of irrelevant information. Why have these different functions? scatter3 allows you to plot points with different marker sizes, and colors under a single handle, while you'd need a loop and get a handle for each point using plot3, which is not only costly in terms of speed, but also in terms of memory. Compare with omitting the hold on, which makes plotting take longer, because axes are recalculated at every step. However, even if the axes limits started out differently, it wouldn't take many iterations for them to converge with these data.

#Matlab 2009 grid alpha update#

Which forces Matlab to update the figure at every iteration (and which is A LOT slower), you'll see that the axes limits don't change at all (since the default axes limits are 0 and 1). Recalculation of axes limits aren't an issue here. Furthermore, you're calling several functions often instead of just once and incur thus calls from the function overhead. The main difference between the time required to plot in a loop versus plotting in one go is that you add the handle to the plot as a child to the axes (have a look at the output of get(gca,'Children')), and you're thus growing a complicated array inside a loop, which we all know to be slow. If scatter3 was compiled as well, the speed difference would be small. The main difference between the time required to run scatter3 and plot3 comes from the fact that plot3 is compiled, while scatter3 is interpreted (as you'll see when you edit the functions). Plot3(1:3,, ) % Plot data for network 7-8 Here, the x-axis represents the iteration number and the y-axis represents each individual network: plot3(1:2,, ) % Plot data for network 4-5 It may be better to instead make a 3-D plot of the data, since it may be easier to interpret. Also, plotting lots of points in this way will get cluttered and it will be hard to see them all well. The problem: Although the plot looks kind of interesting, it's not very intuitive. Surface(X, Y, Z, 'EdgeColor', 'none') % Plot sphere Z = z.*c+data(i, 3) % New Z coordinates for sphere Y = y.*c+data(i, 2) % New Y coordinates for sphere X = x.*c+data(i, 1) % New X coordinates for sphere MAX_ERROR = 121 % Maximum expected errorД¬ = 0.5*data(i, 4)/MAX_ERROR % Scale factor for sphere I'll be using the sample data you added to the question (formatted as a 5-by-4 matrix with the columns containing the x, y, t, and e data): data = In this example, I'll plot a sphere at each point with a diameter that varies based on the error (a diameter of 1 equates to the maximum expected error). You could do this by changing the color or size of the point.

#Matlab 2009 grid alpha series#

In order to do this, you will have to plot a series of x,y,t points and somehow represent the error value e at each point. I can give you two suggestions: one is what you want, and one is what you should probably do instead. The type of plot you are trying to make may be difficult to visualize well.