Spiking Neural Network Simulation: Measuring and Classifying Bump Attractor States
0: As you suggested, use a temporal filter to get a smoothed rate representation
1.a: Clean up each frame by using (e.g.) a morphological opening then closing step
1.b: Locate the centres of bumps, perhaps using non-maximum suppression.
1.c: Choose a reasonable activity threshold for neurons to still be "inside" the bump: Maybe 80% of the distance between zero and the activity at the bump-centre.
1.d: Assign neurons to bumps by finding connected regions around the bump centres.
2, 2: Once you have the neurons assigned to bumps, this is just simple stats
4: Track bumps between frames by assigning nearest bump centres across frames. Apply some uniqueness criterion to detect bumps appearing and disappearing.
5: This is also easy once you have the bumps tracked.