- I think that most neural phenomenon can be modelled deterministically.
- However, it is often simpler to use some form of randomness.
- For instance, you can specify the size of LIF neurons, to get different
- You could more easily use in built random functions to get similar
- Using randomness can often improve performance. If neurons have the
same parameters and inputs, they behave exactly the same.
- With machine learning, randomness is often essential. (E.g. random
initial weights in MLPs.)
- The simplified (and very simplified) neural and synaptic models we
use can benefit substantially from randomness.