Representation in the Brain • 39(a) Oriented bar (b) Oriented moving bar (c) Short moving bar
● FIGURE 2.18 Three types of stimuli that Hubel and Wiesel (1959,
1965) found caused neurons in the cat cortex to respond. They found
neurons that responded to bars with a specifi c orientation, to bars
with a specifi c orientation that were moving in a particular direction,
and bars of a particular length that were moving in a particular
direction. Neurons that responded to these specifi c types of stimuli
were called feature detectors.Two researchers who played an important role in describing feature detectors
are David Hubel and Thorsten Wiesel, who began their careers at Johns Hopkins
University and then established a laboratory at Harvard, where they carried out
research on the visual system that earned them a Nobel Prize in 1981. Their tactic was
to monitor the signals generated by neurons in the cortex of cats and monkeys (see
Method: Recording From a Neuron, p. 28) and determine which visual stimuli caused
each neuron to fi re. Hubel and Wiesel found that each neuron fi red only to a specifi c
type of stimulation presented to a small area of the retina. ● Figure 2.18 shows some
of the stimuli that caused neurons in and near the visual receiving area to fi re (Hubel,
1982; Hubel & Wiesel, 1959, 1961, 1965).
This knowledge that neurons in the visual system fi re to specifi c types of stimuli
led researchers to propose that each of the thousands of neurons that fi re when we
look at a tree fi re to different features of the tree. Some neurons fi re to the vertically
oriented trunk, others to the variously oriented branches, and some to more complex
combinations of a number of features. We could, in fact, describe the fi ring of all of
these neurons together as creating a “chorus” of neural signals, with some neurons fi ring
vigorously (● Figure 2.19a), some slowly (Figure 2.19b), some steadily (Figures 2.19a
and b), some irregularly (Figure 2.19c), some in bursts (Figure 2.19d), and some little or
not at all (Figure 2.19e). What is important about this “neural chorus” is that it stands
for—or represents—the tree. Other objects in the environment create their own, unique
choruses of fi ring. Thus, we can describe the tree we are looking at or other stimuli in
the environment, such as the sound of a bird’s chirping or the smell of pine needles, as
each being represented by a particular pattern of fi ring in a number of neurons. The way
these patterns of neural fi ring represent environmental stimuli is called the neural code.
The discovery of feature detectors in the primary visual receiving area was the
fi rst step in determining the neural code. Further research in areas beyond the primary
receiving area revealed neurons that respond to stimuli that are more complex than
oriented lines. Many researchers, recording from neurons in the temporal lobe, found
neurons that responded to complex geometrical objects and some to that now familiar
stimulus—the face (● Figure 2.20). Because faces are such a common stimulus, and
because of the discovery of neurons sensitive to faces, we will now consider some ideas
about the neural code for faces.THE NEURAL CODE FOR FACES
How can a particular face be represented by the fi ring of neurons in the temporal cortex?
Although we will use faces as an example, our answer applies to all experiences, not just
to seeing faces. One possible way that faces could be represented is by specifi city coding—
the representation of a specifi c stimulus, such as a particular person’s face, by the fi ring
of very specifi cally tuned neurons that are specialized to respond just to that face. This● FIGURE 2.19 The types of
nerve fi ring patterns that would
be recorded from a few of the
feature detectors that respond
to the tree: (a) rapid, evenly
spaced fi ring; (b) slower, evenly
spaced fi ring; (c) irregular fi ring;
(d) bursts of fi ring; (e) little or
no fi ring. The overall pattern
of fi ring of these neurons, and
the many other neurons that
respond to the tree, are the
neural representation of the tree.
(b)
(a)
(c)
(d)
(e)
Receptive Fields
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