29 Aug Black Boxes: Specialized Areas of the Brain

The Black Box

Black Box is a term used to describe a mechanical device that does something inside, but whose functions are not visible from the outside. Specialized areas of the brain may operate as black boxes. Activation flows in and activation flows out, and what happens inside may have no direct affect on other areas of the brain. For example, the cerebellum gets motor coordination instructions from the midbrain and sends control impulses to the muscles. The midbrain does not know whether or not the cerebellum will succeed in following the instructions, and the muscles do not know where the impulses originated.

There are some brain areas to which the black box analogy does not apply: those that have complex and continuous interaction with other areas of the brain. This is specifically true of the correlation centers. There is still too much we don’t know about the functional nature of consciousness and that of cognition to be able to fully defend this analogy. But from a modeling perspective I suggest that we stay with the idea until we find something technical that breaks it.

Neuromorphic Design

Computer system designers can make black box programs or functions. Web Services oriented architecture (SOA) is intended primarily to support integratability of capabilities built as black boxes. Such programs typically get data from some data source, process the data, then send it back or send it on. The data source need not know what happens to the data while it is in the black box. The data recipient, however, must know the format and content assumptions governing the output data from the black box.

In the brain, format is always the same (positive and negative electrical impulses). Content is determined by the area where the signals originated and where they heat up their destinations.

Understanding Context Cross-Reference
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Section 1 #13

Table of Context

Current object-oriented programming techniques and layered architectures come closer to the “black box” paradigm. Server farms, such as the thousands of inexpensive commodity servers used in data centers are fundamentally distributed, and in this way, more closely resemble the distributed structure of the brain than a single computer. Mainframe computers are probably among the least neuromorphic designs for mimicking brain tasks. In addition to service-oriented architecture are there other important computational paradigms from which we may profitably borrow? I am thinking that emerging standards for big data bear useful similarities. Ontology, as a model for representation, can serve as a parallelizable model for the inner structure of these black boxes and other mechanical brain models.

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