Wednesday 26 July 2017

Pondering P6

In the list of points in my previous post was point P6

p6. Current models start with random sets of connections to neurons. This seems odd. Wouldn't a more efficient starting point be to add neurons with connections matching patterns as they occur during network development.

I've played around with a couple of small models that attempt to place nodes (neuron models) to recognise patterns that occur at an occurrence rate above that expected in a random input signal. It has showed some promise and I shall probably take it further given time.

The implementation so far uses an array of nodes that keep track of occurrence rates of sets of inputs, but these are not weighted connection nodes like the normal neuron modelled nodes in a neural net, they are generated by occurring pattern within a domain of inputs and then produce an output when that pattern occurs a set level above chance. The output from these nodes can then be used by other nodes to find combinations of patterns that occur above chance and to place neuron nodes and connections in places where pattern recognition should occur.

Where as nodes in a neural net have some basis in neuroscience, I could not see a basis for this new type of node until I did some further reading. I was taught that neurons where the data processors in the brain, held in place by glial cells that form the scaffolding for the cortex. However these cells also play a role in directing the placement and connection of new neurons and connections. Maybe these cells could be performing the process that my pattern tracking nodes are doing.

Of particular interest are Astrocytes and Radial glia.

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