Open
Description
To normalize sum of CaP weights to same sum as CaD or not?
- for 25 cyc bins, renorm factor is 0.9843 -- not enough by itself to allow CaPScale = 1 to work -- CaPScale ~ 0.95 is generally beneficial
- in lvis, CaPScale with 25 bins, CapScale = 0.95 fails. .96 works. Thus, better to not renormalize, use .95 for this sim.
- lvis fails with bins = 10 -- and most sims are worse with 10, but bgdorsal definitely benefits from 10 cycle bins.
- thus, need to be able to use both 10 and 25 bins and select between them for different projections..
- bins are recorded at the neuron level so actually need to select this at the neuron level.
- need to investigate more about what makes bgdorsal tick with this, in light of updated params, and what makes lvis fail..
Key point: need to use 10 cycle bins always and integrate over them to get 20,30 cycle windows -- can do weighting to get graded effective bin size.. Integration param is per synapse so we can figure out where it matters.
Metadata
Metadata
Assignees
Labels
No labels