06 Sep Varieties of Neural Circuits in the Cerebellum
In this post we explore the roles and varieties of neural circuits of the cerebellum in motor control and the maintenance of life-support systems. The layers of the cerebellum have different cell populations, and the types of cells have radically different forms. Three main points will be made today:
- the morphology of cells and layers in each part of the brain have unique circuitry that supports overall functions;
- human sensory processing, reasoning, and responses are too complex to be isolated to the cerebrum or even the brain;
- the structure of cybernetic models may be influenced by the physiology of the parts of the brain being modeled. For instance, robot motion coordination may model cerebellum form or function.
The reason this discussion is important, in my view, is that it shows how specialization occurs throughout all areas of the brain. This specialization enables and arises from structural structural uniqueness that differentiates the parts of the brain from one another, and optimally connects to other neuro and muscular systems to support life and activity.
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|cerebellum impulses||Pansky 1988|
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|Purkinje cells||Gluhbegovic 1980|
The cerebellum is divided into hemispheres with three lobes in each. The section between hemispheres is called the vermis. The lobes are flocculonodular, anterior and
posterior. The flocculonodular lobe manages equilibrium. The anterior lobe regulates muscle tone and receives impulses from muscles and tendons. The posterior lobe controls dexterity by mediating fine motor movements.
The cerebellum consists of white matter (lower right), surrounded by a thin layer or mantle of gray matter (represented by the red, blue and green areas in the illustration). Within the gray matter are three layers: an outer molecular layer, an inner granular layer, and a thin layer of large Purkinje cells between the two.
The white matter contains pairs of relay neurons that connect the cerebellum to other parts of the nervous system. The distribution of cells in the three layers and their known activities demonstrate task specialization.
There are five types of neurons in the cerebellum:
The figure at right shows the stratified layers of the cerebellum and the relative positions of the cells. I’m preparing additional posts to describe the morphologies and locations of these cells and explain how their circuitry works.
When you think of motor control, such as is provided by the cerebellum, and imagine machines that need motor control, you may think of machine tools that have computerized numerical control (CNC) devices. You may think of Systems Control and Data Acquisition (SCADA) systems. Or you may think of robots. All these are good examples of machines with brains whose functions may resemble the functions of the cerebellum. I want to look at what we know about the cerebellum in a broader context: What can we learn from the structure and processes in the cerebellum that could apply to any brain tasks?
When I have finished looking into the morphologies and locations of motor control system cells, it is my intent to build an ontology of unique brain functions, including life support and motor control, that may provide components of more intelligent computing approaches. This complexity appears to show how most artificial neural network models lack the complexity to mimic the specialization and complexity in the human brain. Fortunately, there is much we can learn from neural network learning algorithms that could significantly contribute to more capable mechanical brains.
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