Structure of Neural Nets

[TERU]

>Real (biological) neural networks have very complex computational structure.
>Ask any computational neuroscientist.  Connectionist networks will
>need complex structure to solve hard problems.  There is also a
>significant amount of genetically determined structure in real neural
>systems.  We will also have to pre-structure artificial systems, to
>bootstrap the subsequent learning.
>
>Nigel Goddard

Surely biological neural nets have complex structure: several types of
neurons, synapses, neurotransmitters, ion-channels, distinct layers, nuclei,
commissures, etc. I agree that the artificial neural nets need these structural
complexity to solve real-world problems. Certainly research activities are
pointing to that direction. The benefit of layered structure has already
been well-known. Modular structure is interesting so that it expands the net's
heterogeneous structure while maintaining rather uniform structure in a layer
within a module. Each module may be treated and controlled as a unit at another
level. Another step, for example, will be to somehow build functionally
different types of neurons in the net.

I will appreciate comments and pointers concerning these issues of
hierarchy, modularity and neuron-types in neural nets biological or artificial.

- Teru Homma