Stimulation weights

[JESUS CABRERA ALVAREZ]

Hello!

I have been looking through the code, but it is still confusing to me how stimulation weights work.  

I define a stimulus pattern for regions and I define "weight" as an array to select what regions to stimulate. But, what magnitude of weight to use? This would depend on what it means to the state variable that it influences.

 Following the code I found out that at some point it converts the weight into some kind of "distance":

def configure_space(self, distance):
"""
Stores the distance vector as an attribute of the spatiotemporal pattern
and uses it to generate the spatial pattern vector.

Depending on equations used and interpretation distance can be an actual
physical distance, on a surface, geodesic distance (along the surface)
away for some focal point, or a per node weighting...
"""
# Set the discrete representation of space.
self.space = distance
# Generate a discrete representation of the spatial pattern.
# The argument x represents a distance, or effective distance, for each node in the space.
self._spatial_pattern = numpy.sum(self.spatial.evaluate(self.space), axis=1)[:, numpy.newaxis]

(distance coming from weights)

def weight_array(self):
"""
Wrap weight List into a Numpy array, as it is requested by the simulator.
"""
return numpy.array(self.weight)[:, numpy.newaxis]

def configure_space(self, region_mapping=None):
"""
Do necessary preparations in order to use this stimulus.
NOTE: this was previously done in simulator configure_stimuli() method.
It no needs to be used in stimulus viewer also.
"""
if region_mapping is not None:
# TODO: smooth at surface region boundaries
distance = self.weight_array[region_mapping, :]
else:
distance = self.weight_array
super(StimuliRegion, self).configure_space(distance)

But I don't really understand this because the higher the weight the higher the influence on the signal. 

So, the question is: what does the weight do to the state variable in each timestep?

Thanks in advance!

Jesús Cabrera-Alvarez