1. Modeling Cognition with Neural Networks
David Northmore
Attempt to make a bridge between the theories of cognitive science and brain mechanisms, thereby guiding us to look for those mechanisms in the brain.
Pointers enable one to keep track of 4-5 moving objects

2. Multiple Object Tracking Paradigm
We know about these pointers through research on MOT.
How to make a neural network, a parallel processor, with fixed architecture, select and latch onto one or a few moving targets

3. Modeling a pointer Moving stimuli Gain layers Pointer layer (+ 3 or 4)
Neuron-like elements that are excitatory (Green) or inhibitory (Red) connections.
Moving discs excite topographic points in gain layer.
Response of each green unit is restrained by feedback inhibition from a red unit
Gain units topgraphically activate Pointer layer.
Lateral inhibitory WTA connections in pointer layer ensures only one locus.
Feeds back to inhibitory units of gain layers, amplifying one locus.
Multiple Pointer layers similarly connected with Gain Layers.
Pointers are powerful (as in computer programs), but in different ways.
Direct eye movements
Selection of features
Conjunction of features
Serial operations
Save to working memory
Construct subjective “panorama”
Pointer layer
(+ 3 or 4)