Abstract Cortex

Perhaps a better way of describing "General Cortex" is to describe it as "Abstract Cortex". Abstract as in computer programming -- a class that can be inherited, but not instantiated itself. All of the different cortical architectures across the brain are serving different functions, and so have slightly different properties. However, they all inherit (literally via evolution) many of their properties from abstract cortex, and then modify to suit their more specific needs.

Abstract cortex is the basis, and the rest of the cortical structures are variations of abstract cortex that are used to solve different problems. Biology has given us a giant tool kit of different cortical structures, which have been adapted to solve different problems. If we can figure out the rules that correspond to the alterations from abstract cortex and the consequences of these alterations on the final output, then we can design cortical structures for handling different types of data.

Evolution has figured out how to make many different variations of abstract cortex in a complementary manner to solve different problems. Vision is not going to be solved with a magic equation that is based on a single optimization, but rather setting up several cortical structures that pay attention to needed information in the visual world. Each of these structures may be driven by their own optimizations, but there will be a cortical structure that is designed to handle motion, one designed to handle faces, etc. To solve vision, there will have to be a lot of complementary cortices all designed to look at the world from different perspectives.

The differences in the cortical structures is partly set up by the type of information that they receive, which is definitely part of the whole process. Each cortical area should be able to handle oddities of the info that it gets, but will be set-up by evolution to transform the information it receives in a specific way. Most of this transformation is described by the general properties of abstract cortex -- i.e. some type of dimensionality reduction and classification. But other properties could emerge that give each cortical area special computational abilities.

Take as a possible (but this is hypothetical) that in MT there are neurons that are more sensitive to the timing of inputs on their dendrites. This makes them do strange computations when there is consistent motion signals -- i.e. if the inputs turn on in order towards the soma, the neuron fires at a higher rate, but if same inputs are turned on in opposite order the neuron fires at a lower rate, ala Bronco, Hausser. These alterations in the dendritic properties make the neurons non-linear with motion signals -- this creates a lot of extra entropy when there is motion in the firing rates of neurons in MT. This extra entropy is used by the abstract cortex algorithm to make useful classifications of motions, and these classifications are useful for the general problem of vision. Thus changes to cellular properties could enable MT to make new transformations of information, which are made useful by the abstract cortex algorithm. The rest of the brain can then use this new information, and if it is useful for survival then it will evolve.