On Intelligence by Blakeslee Sandra & Hawkins Jeff

Author:Blakeslee, Sandra & Hawkins, Jeff [Hawkins, Jeff]
Language: eng
Format: epub
Publisher: Macmillan
Published: 2010-03-31T22:00:00+00:00

WHAT A REGION OF CORTEX LOOKS LIKE

We are now going to turn our attention to an individual region of cortex, one of the boxes in figure 5. Figure 6 shows such a

Figure 6. Layers and columns in a region of cortex.

region of cortex in more detail. My goal is to show you how the cells in a region of cortex can learn and recall sequences of patterns, which is the most essential element for forming invariant representations and making predictions. We will start with a description of what a cortical region looks like, and how it is put together. Cortical regions vary greatly in size, the largest being the primary sensory areas. V1, for example, is roughly the size of a passport in terms of the space it occupies at the back of the brain. But as I argued earlier, it is actually composed of many smaller regions that might be the size of the letters on this page. For now, let’s assume that a typical cortical area is the size of a small coin.

Think of the six business cards I mentioned in chapter 3, where each card represents a different layer of cortical tissue. Why do we say there are layers? If you take our coin-size region of cortex and place it under a microscope, you’ll see that the density and shape of the cells vary as you move from top to bottom. These differences define the layers. The top, called layer 1, is the most distinct of the six layers. It has very few cells, consisting primarily of a mat of axons running parallel to the cortical surface. Layers 2 and 3 look similar. They contain many tightly packed pyramidal cells. Layer 4 has a type of star-shaped cell. Layer 5 has regular pyramidal cells as well as a class of extra-big pyramid-shaped cells. The bottom layer, layer 6, also has several types of unique neurons.

Visually we see horizontal layers, but most often scientists talk about columns of cells that run perpendicular to the layers. You can think of columns as being vertical “units” of cells that work together. (The term column invites much debate in the neuroscience community. Their size, function, and importance are disputed. For our purposes, though, you can think in general terms of a columnar architecture, which everyone agrees exists.) The layers within each column are connected via axons that run up and down, making synapses along the way. Columns do not stand out like neat little pillars with clear boundaries—nothing in the cortex is that simple—but their existence can be inferred from several lines of evidence.

One reason is that the vertically aligned cells in each column tend to become active for the same stimulus. If we looked closely at columns in V1, we’d find some that respond to line segments that tilt in one direction (/) and some that respond to line segments that tilt in another direction (\). The cells within each column are strongly connected, which is why the entire column responds to the same stimulus.

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