Files
memex/0_inbox/books/TWOW/html/54 The possibility of a subjective level of neurological organization.html

669 lines
334 KiB
HTML
Raw Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN">
<html>
<head>
<meta http-equiv="content-type" content="text/html; charset=utf-8">
<title>The possibility of a subjective level of neurological organization</title>
<meta name="generator" content="LibreOffice 4.2.8.2 (Linux)">
<meta name="author" content="Amr Gharbeia">
<meta name="created" content="20010831;20400000000000">
<meta name="changed" content="20150722;304611745158">
<style type="text/css">
<!--
@page { margin-right: 1.2cm; margin-top: 1.2cm; margin-bottom: 1.25cm }
p { text-indent: 1.27cm; margin-bottom: 0.25cm; direction: ltr; color: #99ccff; line-height: 120%; text-align: left; widows: 2; orphans: 2 }
p.western { font-family: "Arial", sans-serif; font-size: 10pt; so-language: en-US }
p.cjk { font-family: "Times New Roman", serif; font-size: 10pt }
p.ctl { font-family: "Simplified Arabic"; font-size: 10pt; so-language: ar-EG }
a:link { color: #0000ff }
-->
</style>
</head>
<body lang="en-GB" text="#99ccff" link="#0000ff" dir="ltr">
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt"><font color="#993366"><font face="Verdana, sans-serif"><b>T<img src="data:image/png;base64,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" name="TtsOtkCRS06_05" align="right" hspace="5" width="275" height="35" border="0">he
possibility of a subjective level of neurological organization. </b></font></font>The
functional representation of the subjective animal system of
representation makes it clear that any animals that happened to try
out such a behavior guidance system would be able to acquire an
entire range of new powers for controlling relevant conditions in a
long period of gradual evolution. They would, in other words, begin a
new stage of animal evolution, refining the inherent powers of
spatial imagination and adapting it to all available ecological
niches. But in order to conclude that such an evolutionary stage is
inevitable, it must be possible for a radical random variation to try
it out. There are good reasons to believe that it is possible, but in
the end, the most compelling case depends on seeing how these
functions are served by nervous mechanisms. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 2.54cm; margin-right: 1.27cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">It
may seem that any neural mechanism complex enough to realize this
functional description of the subjective animal system of
representation would be too complex to be tried out as a radical
random variation on the telesensory system by the multicellular
biological behavior guidance system. The functional diagram indicates
that it requires a higher level of neurological organization than
telesensory animals. But since the mechanism of embryological
development must get all its instructions from the structure of the
nucleus and the chromosomes it contains, such a higher level may seem
beyond the range of random variations being tried out, especially
considering that more complex neural connections are needed for
higher level systems to interact as an animal behavior guidance
system. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">This is the
same kind of problem that we faced in explaining the eukaryotic and
multicellular levels of biological organization. But there it
required a new kind of biological behavior guidance system, and here
a different kind of solution is required, for the same biological
behavior guidance system is responsible for all the levels of
neurological organization. The appropriate random variation must
somehow occur in the multicellular biological behavior guidance
system (the process of embryological development). </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 2.54cm; margin-right: 1.27cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">There
are at least three reasons for believing that such a random variation
is possible. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">First, one
reason was found in how deuterostome embryological development is
different from proterostome development. With the neural tube divided
into segments, the mechanism of embryological development can address
entire 2-D arrays of neurons and determine them, as a whole, to
migrate or send processes to other areas of the neural tube (or the
body), and to make topologically ordered connections with 2-D arrays
of neurons there. That means, as suggested earlier, that the units
from which deuterostome development constructs the nervous system are
already on a higher level of organization than in proterostome
development — not to mention that the connections among such units
can be made without interference with the development of other organs
in the body, since the neural tube itself is separate from the rest
of the body. </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">Second, it
is not necessary for the mechanism of embryological development to
prescribe all the neural connections involved in the subjective
animal system of representation, because the three basic systems are
laid out in such a way that most of the detailed connections they
require can be acquired from the world by learning. Since the power
of animal behavior comes from adapting it to spatial and
spatio-temporal aspects of the world, it is possible to internalize
the detailed structural causes of the brain mechanisms that serve
that function from experience with the world. The world already has a
spatial structure, and if the animal is protected and cared for
during the first part of its life, its interactions with the world
can internalize the structures needed to construct <i>local images
</i>and maps of <i>local images </i>that can be explored by covert
locomotion. Thus, much detailed structure can be supplied by the
contained form of reproductive causation mentioned above, in which
behavioral schemata evolve by reinforcement selection. This is the
role of nurture as well as nature in neurological development. </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">Third,
given how detailed neural connections can be internalized from the
structure of the world by experience, that is, learning, all that is
necessary is a random variation that would set up the basic structure
on a higher level of neurological organization within which those
detailed structures can be acquired. As it happens, there are two,
connected kinds of changes in the embryological development of the
non-mammalian vertebrate that do set up a higher level of
neurological organization in the mammalian forebrain. </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 2.54cm; margin-right: 1.27cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">In
order to give this final argument for the possibility of the
subjective level of neurological organization, therefore, we must
consider the structure of the mammalian brain. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">Starting
with the functional diagram of the subjective animal behavior
guidance system, I will, first, simply identify the neural mechanisms
in the mammalian brain that are responsible for each of the
subsystems. This is to view the structure of the mammalian brain from
a rather high altitude. It affords a general impression of how the
mammalian brain works, and for those who are familiar with its
structure, it will be possible to see how it explains the functioning
of the mammalian brain. </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">Second, I
will explain how this functional explanation of the structure of the
mammalian brain would also explain the contained form of reproductive
causation by which behavioral schemata evolve in the individual brain
by reinforcement selection. </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">Finally, in
order to show how the subjective level of neurological organization
is possible, I will show how it could arise from two basic, yet
simple changes in the non-mammalian vertebrate brain. That will
involve a much more detailed description of how the functionally
identified systems are realized in the mammalian brain. </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt"><font face="Verdana, sans-serif">N<img src="data:image/png;base64,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" name="TtsOtkCRS06_06" align="right" hspace="5" width="250" height="25" border="0">eural
structure of the subsystems of the subjective animal behavior
guidance system. </font>In the diagram of the subjective animal
behavior guidance system, the systems that were previously defined
functionally are labeled by parts of the nervous mechanism that serve
their functions in the mammalian brain. (The functional diagram is
included for comparison.) The brain mechanisms involving the
neocortex are depicted as beveled buttons, while the thalamic nuclei
projecting to them are depicted as purple spheres. Notice that when
we look more closely at the detailed structure, the <i>behavior
generator </i>itself is a complete circuit of telesensory-level
nervous mechanisms. That is because there are two, distinct circuits
within the behavioral output system, one that supplies the behavioral
schemata and generates covert behavior and the other that also
generates overt behavior. (Covert behavior needs only the ventral
anterior thalamic nucleus, whereas both it and the ventral lateral
thalamic nucleus are involved in generating overt behavior.) The part
of the frontal neocortex that contains the behavior schemata and
where covert behavior is generate is labeled “Sch.”)</font></font></font></p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><img src="data:image/png;base64,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" name="SubAbgsDet" align="bottom" width="480" height="325" border="0"></font></p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: -2.86cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><img src="data:image/png;base64,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" name="SubAbgsDetN" align="bottom" width="574" height="400" border="0"></font></p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">This
key to the neurological interpretation of the functional diagram of
the subjective animal behavior guidance system may be enough for
those who are familiar with the structure of the mammalian brain to
see the functional diagram as an explanation of how the mammalian
brain works. But for those who are not familiar with the structure of
the mammalian brain and want a briefer, more intuitive way of seeing
how it realizes these functionally defined systems, the following
diagrams and brief explanations may suffice.</font></font></font></p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">In
the mammal, the entire animal behavior guidance system is located in
the forebrain, and its basic structure is composed of two main units,
the thalamus and the neocortex. The thalamus is at the end of a brain
stem, just rostral to the midbrain, hindbrain and spinal chord, and
it sends a massive projection to all parts the neocortex, which
encloses the rest of the forebrain. (A projection is a set the axons
from a 2-D array of neurons in one region to a 2-D array of neurons
in another region, taking full advantage of the chordates way of
constructing the nervous system in the neural tube.) The nuclei in
the thalamus send their projections mostly to different parts of the
brain (though the anterior temporal cortex receives none). There are
also projections back from the neocortex to thalamic nuclei by which
they interact in some way, but the main direction of influence is
from the thalamus to the neocortex. These thalamic projections are
2-D arrays of neurons in which the information conveyed by the firing
of any single neuron depends on the neuron's position in the 2-D
array as a whole, and the thalamus apparently has the function of
synchronizing the processing in all the parts of the neocortex. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">There
are three grand, distinct circuits of connections, each involving
many such 2-D arrays, that pass though the thalamus and the neocortex
back. That is, each circuit uses some part of the projection of many
2-D arrays from the thalamus to the neocortex, but each has a special
way by which the neocortex completes the circuit of multiple 2-D
projections by acting on those same thalamic nuclei (that is,
distinct from the connections by which the neocortex reacts to the
thalamus directly). Each such circuit is one of the three main
subsystems of the animal behavior guidance system, with the circuits
themselves on the subjective level of neurological organization. (See
diagram of the basic structure of the mammalian brain.) </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><img src="data:image/jpeg;base64,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" name="MamBParts" align="bottom" width="477" height="356" border="0"></font></p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">In
the framework of this basic diagram, we can see how each of the
functionally defined subsystems is realized by the mammalian brain.
Consider first the sensory input system. Visual input from the eyes
is relayed by the lateral geniculate nucleus (labeled &quot;LGN&quot;)
to the occipital (or striate) cortex where there are numerous copies
of the entire image from the retina of the eye. Auditory input is not
represented in the diagram, though it is handled in the same way,
with auditory images in the superior temporal lobe. The inferior
parietal neocortex is where the telesensory images are assembled as
the local image (using association fibers from the motor areas, or
<i>body image</i>, to supply information about the current bodily
condition, also not depicted). The activity of the inferior parietal
area in constructing the local image also depends on its interactions
with a thalamic nucleus called the &quot;pulvinar&quot; or (labeled
&quot;Pul.,&quot; which receives input from the superior colliculus
in the midbrain, the main visual image in the non-mammalian
vertebrate brain). </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><img src="data:image/png;base64,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" name="MamBSensIn" align="bottom" width="480" height="358" border="0"></font></p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">The
memory is what gives the sensory input system a complete circuit from
the thalamus through the neocortex back to the thalamus for another
projection to the neocortex. The memory circuit receives information
about the telesensory images and how they have been combined as the
<i>local image </i>in the anterior temporal neocortex where the
hippocampus is located. In fact, almost every region of neocortex
sends association fibers (or chains of association fibers) toward the
anterior temporal neocortex, where they are assembled for the
hippocampus (in an adjacent region, called the “entorhinal
cortex”). The hippocampus projects by way of the fornix to the
anterior nucleus of the thalamus, though many of its fibers pass
first to the mammillary body (located in the hypothalamus) which
relays them to the anterior nucleus. The anterior nucleus projects to
the entire cingulate gyrus, which is the extreme medial edge of
neocortex adjacent to both anterior and posterior regions of
neocortex. The cingulate neocortex has two way connections with
neurons in adjacent areas of neocortex. That completes the memory
circuit for the <i>local image </i>and its bundle of telesensory
images, since those images are affected by their own projection
through the memory circuit. And the function of this circuit is to
form memory groups of neurons throughout the neocortex that are
involved at some moment in the (synchronized) processing the image of
some local scene. That is, by strengthening the synapses among the
neurons involved throughout the neocortex, the whole group tends to
fire when some crucial group of them fires for some reason, recalling
the <i>local image.</i></font></font></font></p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><img src="data:image/png;base64,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" name="MamBMem" align="bottom" width="440" height="364" border="0"></font></p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">The
<i>behavior generator </i>for covert behavior receives the <i>local
image </i>(and its telesensory images) by way of the projection from
the entire posterior neocortex to the caudate nucleus of the corpus
striatum. That is the perception of the object in space that is used
to guide behavior. The corpus striatum also receives a projection
from the entire anterior neocortex, which includes both its
perception of its own body and the behavioral schemata contained in
the frontal neocortex. The corpus striatum can project to both the
ventral lateral and ventral anterior nuclei of the thalamus, but when
behavior is covert, the projection to the ventral lateral nucleus is
suppressed and only the ventral anterior nucleus is affected. The
ventral anterior nucleus projects to the entire frontal neocortex
(except for the motor neocortex itself and supplementary neocortex).
Thus, when behavior is covert, the premotor neocortex and behavioral
schemata located in the frontal area are both also projected to the
anterior cingulate gyrus, and since the anterior cingulate neocortex
projects to the posterior neocortex and, indirectly, to the local
image, covert locomotion can call up images from memory in sequences,
as required for spatial imagination. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><img src="data:image/png;base64,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" name="MamBCovBeh" align="bottom" width="444" height="404" border="0"></font></p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">The
<i>body image </i>for overt behavior includes the motor neocortex,
supplementary motor neocortex and somatosensory neocortex, all of
which are organized somatotopically, like an image of the body. The
overt bodily image is the source of motor commands to all parts of
the body, but it is mediated by a projection (not depicted) from the
overt <i>body image </i>to the cerebellum and its projection back to
the motor neocortex by way of a part of the ventral lateral nucleus
of the thalamus. (The cerebellum evens out the gross motor commands
of the premotor and supplementary motor areas both spatially and
temporally so that the precise motor commands work together smoothly
in generating the prescribed behavior in the body as a whole.) This
overt <i>body image </i>located in the neocortex is also the source
of the input about bodily condition that is used to construct the
<i>local image.</i> Its projection (via association fibers) to the
inferior parietal neocortex is used to combine telesensory images as
the <i>local image </i>representing the spatial relations among
object in the current local scene relative to the body. Finally, the
overt <i>body image </i>also sends a projection to the anterior
cingulate neocortex, and since it projects to the posterior
cingulate, the overt <i>body image </i>provides the labels for
recording memory images according to the locomotion and turning that
are responsible for them. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><img src="data:image/png;base64,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" name="MamBOvBeh" align="bottom" width="482" height="360" border="0"></font></p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">When
behavior is being generated overtly, both parts of the circuits
through the corpus striatum are active. A behavioral schema in the
frontal neocortex is used to set up behavior in the premotor area,
and when the signal (from the centromedian nucleus of the thalamus)
to the putamen calls for the behavior to be generated overtly, the
schema is used to send motor commands to the body. (The centromedian
nucleus is in a position to tell when to generate behavior overtly,
because it is at the center of the thalamic nucleus receiving
processes from all its nuclei as the thalamus synchronizes processing
in all parts of the neocortex.) When behavior is overt, the anterior
cingulate gyrus receives input from both the overt and covert body
images, and thus, the labels attached to memory groups that are
formed when behavior is overt can be used to recall those images in
sequence as spatial imagination when behavior is covert. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><img src="data:image/png;base64,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" name="MamBOSys" align="bottom" width="481" height="416" border="0"></font></p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">All
the circuits combined are the subjective animal system of
representation. The auditory system (in the superior temporal
neocortex) and the tactile system (in the superior parietal
neocortex) are not depicted. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><img src="data:image/png;base64,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" name="MamBSubAsr" align="bottom" width="480" height="411" border="0"></font></p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">All
that is needed to complete the subjective animal behavior guidance
system is the goal selection system. It is also a complete circuit
through both the thalamus and the neocortex. The route from the
neocortex back to the thalamus so that a circuit can be completed is
provided in this case by the amygdala. Located in the anterior
temporal lobe, the amygdala receives the same information from
throughout the neocortex that the memory circuit receives by way of
the hippocampus, except that it passes through an ancient form of
cortex surrounding it (the piriform cortex). Thus, the amygdala is in
a position to attach desires to the objects (or read affective labels
already attached to objects) that are used by behavior schemata to
generate behavior in relation to them. The amygdala projects to the
dorsomedian nucleus of the thalamus, which projects in turn to the
whole frontal neocortex. A diffuse projection to most of the frontal
area is all that is needed to activate appropriate behavioral
schemata. A denser projection from the dorsomedian nucleus is
received by the orbitofrontal region, and it sends association fibers
(by way of the uncinate fasciculus) back to the piriform cortex
surrounding the amygdala. Thus, the goal selection circuit is able to
make sure that desires are attached to the right objects.</font></font></font></p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><img src="data:image/png;base64,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" name="MamBGoal" align="bottom" width="422" height="355" border="0"></font></p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt"><font face="Verdana, sans-serif">I<img src="data:image/png;base64,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" name="TtsOtkCRS06_07" align="right" hspace="5" width="250" height="25" border="0">nternalizing
the spatial structure of the world. </font>Even telesensory animals
internalize a map of their territory. But their map plays very
specific roles in generating complex, “hardwired” instinctive
routines in telesensory animals. However, much of what is hardwired
instinct in telesensory animals is learned by subjective animals from
the environment. That is partly what makes the subjective level of
neurological organization possible. As we have seen, what makes
learning so much more important in subjective animals is a form of
reproductive causation contained in individual brains with spatial
imagination by which behavioral schemata evolve by reinforcement
selection. (A similar mechanism has been described by <font color="#0000ff"><u><a href="/F:/Philosophy/Existentialism/The%20Wholeness%20Of%20the%20World/www.twow.net/ObjText/#Edelman">Edelman</a></u></font>,
1987, 1989, under the name of &quot;neural Darwinism&quot;.)</font></font></font></p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">The
basic structure of the forebrain systems is set up in mammals by the
biological behavior guidance system during embryological development,
including the circuits of 2-D arrays that constitute the basic
subsystems of the subjective animal behavior guidance system. But
more neurons are created than are needed, and many neurons can make
synapses more or less randomly with certain other neurons. The basic
circuits line up 2-D arrays so that sensory input is registered in a
way that can be used in generating behavior, and correspondingly, the
mechanisms of the <i>behavior generator </i>are set up to make use of
such sensory input in guiding behavior. But the specific neural
connections needed to analyze and store sensory input in the most
useful ways are lacking, and genetically prescribe behavior in
response to sensory input is little more than reflexes built into in
the behavioral output system and more or less random combinations of
them. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 2.54cm; margin-right: 1.27cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">Behavioral
schemata in the behavioral output system evolve by a contained form
of reproductive causation. As random variations on behavioral
schemata are tried out, there is a natural selection of those that
are successful in some way by a reinforcement that works through the
memory circuit. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">Though the
memory circuit is depicted in the functional diagram as the basic
structure of the sensory input system, it is realized in the brain in
such a way that it is able to work the same way on neurons throughout
the neocortex, including the behavioral schemata and <i>body image </i>in
the anterior as well as the <i>local image </i>in the posterior
neocortex. When some set of neurons is successful in some way, the
memory circuit ties those neurons together in a memory group. That
is, it instructs them to form synapses with one another so that if
any crucial group of those neurons fire, the whole group will fire
together. And with their synapses with one another strengthened, the
whole group is more likely to be included as parts of other random
variations on behavioral schemata. </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">Let us call
such groups of neurons, which may be in the same 2-D array or in many
different 2-D arrays, “memory groups.” Though the formation of
memory groups depends on the memory circuit, once they are formed,
they can be called up without any help from the memory circuit. The
newly formed synapses among the neurons will make them act as a group
when aroused by other neurons in the neocortex. </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">This
increase in their likelihood of firing together again as a group is a
form of natural selection of the group. It call it “reinforcement
selection,” because the criterion for forming memory groups is, in
mammals, the kind of desire satisfaction behaviorists were actually
referring to in talking about reinforcement. The memory circuit is an
ancient structure that includes the seat of desire, sometimes called
the “limbic system,” and thus, success in satisfying desire in
some way or other can easily be what triggers the formation of memory
groups. In the case of learning behavioral schemata, success can
easily be detected, for as we shall see, it is just success in
internalizing some aspect of the world. </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 2.54cm; margin-right: 1.27cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">Mechanisms
for identifying objects from the analysis of sensory input evolve in
a similar way in the sensory input system. At the beginning of this
phase of neurological development, groups of neurons respond to
sensory input more randomly, and the memory circuit internalizes
detailed structures that enable the sensory input system to recognize
objects in sensory input and discriminate among them. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">Telesensory
input in any modality, such as vision or hearing, is registered in
many different 2-D arrays. Those arrays may be determined to respond
to them in different ways by the biological behavior guidance system,
but the memory circuit, using built in criteria for success, can tie
neurons together that are regularly active in processing sensory
input in one way in one 2-D array with other neurons that are
regularly involved in processing the same input in another way in
another 2-D array. Thereafter, when sensory input is recognized in
one 2-D array, such association fibers make it more likely that the
input will also be recognized in the other 2-D arrays. Thus,
processing in the various telesensory images work together to
disambiguate sensory input.</font></font></p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">At a later
stage of neurological development, when mechanisms for recognizing
objects of certain kinds have been established, this mechanism can
also be used to identify particular objects. Different objects of
similar kinds can be distinguished by tying a general memory group
together with additional neurons in various 2-D arrays that are
distinctive of it in a new memory group. </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">When new
sensory input causes patterns of neuronal firings in many different
2-D arrays of the sensory input system that conform to such a memory
group, the memory group is activated, and the sensory input system
settles into equilibrium. (Since these areas of neocortex are all
coordinated by the thalamus, such a settling into equilibrium may be
what causes the distinctive “gamma oscillations” that are
detected by EKGs when objects are recognized.) </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">For
our purposes, what is most relevant about this contained form of
reproductive causation is how the evolution of behavioral schemata
internalizes the spatial structure of the world as the structural
cause of spatial imagination. Though the behavioral schemata are
certain groups of neurons in the frontal neocortex that the <i>behavior
generator </i>uses to issue motor commands from the <i>body image,
</i>what evolves are neural connections throughout the neocortex,
because motor commands must be generated in relation to sensory
input. These groups of neurons are the “organisms” (or primary
structures) that evolve, because they are what go through
reproductive cycles and have both essential structural effects.
Random variations on them are naturally selected by success in
reproduction, though in this case reproduction occurs when they
generate overt behavior and it is reinforced through the memory
circuit. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 2.54cm; margin-right: 1.27cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">The
basic schema has the part-whole complexity required of an organism
that can evolve, since it is made up of motor commands to different
parts of the body as well as different sequences of such sets of
motor commands in time. Thus, many varieties of the basic schema are
possible. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 2.54cm; margin-right: 1.27cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">These
schemata also do both kind of work that are required for organisms to
evolve. Their non-reproductive work is the behavior they generate in
relation to sensory input when they are firing. And they reproduce
when the groups of neurons involved are signaled to strengthen and
extend their synapses, that is, are reinforced for working together
in the various circuits of 2-D arrays in a way that satisfies desire.
</font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 2.54cm; margin-right: 1.27cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">Thus,
behavioral schemata evolve gradually, starting off simple, uniform
and weak, and becoming complex, diverse and powerful. The ecological
niches to which they adapt are all the various situations in which
some special kind of behavior in response to sensory input is needed
to satisfy a desire, that is, are reinforced. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">Memory
groups for identifying the telesensory images for situations in which
behavior is reinforced are part of the selected behavioral schemata,
that is, like discriminative stimuli. But since it is a faculty of
spatial imagination, connections are also established between
telesensory images and behavior that work the other way, so that when
the behavior is generated covertly, telesensory images representing
its effects are called up from memory. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 2.54cm; margin-right: 1.27cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">In
order to construct even a local image, the telesensory input must be
registered in a way that indicates the bodily condition at the time,
such as the direction the head and eyes are pointing when visual
input is registered. That is a regular relationship in any given
local scene viewed from a certain location, and thus, the memory
circuit can establish their neural connections as a memory group. But
in order for them to serve as a <i>local image </i>that can be
recalled from memory, it must be possible for the <i>behavior
generator </i>to use the combination of telesensory images recorded
in memory as a <i>local image </i>to anticipate what telesensory
images will occur when it behaves in various way, and that is a
result of the evolution of behavioral schemata in the behavior
generator. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">Starting
with whatever behavioral schemata are built into the <i>behavior
generator </i>genetically, such as standing up, walking, focusing
eyes together on an object, behavioral schemata for more complex or
more precisely controlled behavior can be acquired by reinforcement
selection of random variations on them. But since telesensory images
are recorded in the <i>local image </i>according to the bodily
condition at the time, schemata for generating those bodily
conditions become labels for calling up those telesensory images in
imagination. Thus, as behavioral schemata evolve, the subjective
animal learns the motor commands to use in moving its head and body
in order to make an object that appears to the right visual field
move to the center of the visual field. </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">Though
<i>local images </i>vary with the local scenes they represent, the
same behavioral schemata for calling up particular telesensory images
from them will work for them all, because bodily movements have
similar effects in all situations. The behavioral schema that evolves
for that function becomes, in effect, the structure for recording all
local images, and the covert behavior for generating bodily
conditions become labels for calling up the telesensory images in
different directions. Thus, the evolution of behavioral schemata
internalizes an aspect of the spatial structure of the world.</font></font></p>
<p lang="en-US" align="left" style="margin-left: 2.54cm; margin-right: 1.27cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">Once
the ability to construct and recall <i>local images </i>has been
acquired, much the same kind of process will internalize the
structural causes needed to link them in sequences as a map of its
territory (assuming that the cingulate gyrus contains a mechanism
that can link memory groups in sequences). Given that behavioral
schemata for locomotion and turning in relations to perception have
been acquired, the key to spatial imagination is recording and
recalling entire <i>local images </i>in a way that corresponds to
such behavior. </font></font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">Starting
from a certain local scene in the territory, the effects of
locomotion and turning on the <i>local images </i>encountered are
determined by the spatial structure of the actual world. Thus,
assuming that the memory for sequences of <i>local images </i>(in the
cingulate gyrus) receives input about its overt locomotion and
turning, its neural connections to the resulting changes in <i>local
images </i>become labels for recording and recalling <i>local images
</i>as a map of the territory. Using those behavioral schemata to
generate covert locomotion and turning in relation to a given <i>local
image </i>would, therefore, enable the subjective animal to explore
the map of its territory. </font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">Once again,
however, the same kinds of behavior, turning and locomotion, work
much the same way in any <i>local image </i>of the territory. Thus,
as these behavioral schemata evolve, the memory for sequencing <i>local
images </i>(and for shifting from one sequence to another when the
body turns in a different direction) acquires labels that are used
for every <i>local image.</i> That is a general understanding of the
structure of space in terms of the effects of motion, and it informs
even the local image, that is, enables the subjective animal to see
its telesensory input from objects in the local scene as spatial
relations that can change by motion. For example, as it learns to
register <i>local images </i>according to turning, it learns that
turning far enough brings it back to the same direction, and it can
come to see how it would have that effect even in the <i>local image.</i>
</font></font>
</p>
<p lang="en-US" align="left" style="margin-left: 1.27cm; margin-right: 2.54cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif"><font size="3" style="font-size: 12pt">The
capacity to acquire structural causes from the environment eases the
burden on the biological behavior guidance system to provide
structural causes, but once the basic structure of the mammals
higher level of neurological organization had been selected,
evolution by reproductive causation would provide the additional
structures needed to make this learning mechanism more efficient and
complete.</font></font></font></p>
<p lang="en-US" align="left" style="margin-left: 3.81cm; margin-right: 2.03cm; text-indent: 0cm; margin-top: 0.49cm; margin-bottom: 0.49cm; line-height: 100%; widows: 0; orphans: 0">
<font color="#000000"><font face="Times New Roman, serif">The
representation of the local scene is, in effect, a representation
with polar coordinates, whereas the memory map of all the salient
objects in the territory uses, in effect, Cartesian coordinates. This
translation between polar and Cartesian coordinates is mathematically
too complex to be provided genetically, but it can be acquired from
experience. As the mammal experiences the consequences of moving in
different directions from the local scene and finds the same objects
showing up as a result of different combinations of bodily movements,
behavior schemata for turning and moving in each direction evolve, so
that later they can be used by the <i>behavior generator </i>as
labels (in the anterior cingulate) to switch from one sequence of
local images to another in exploring its subjective map. The mammal
discovers, for example, the direction in which the body winds up
moving as a result of various combinations of bodily movements, such
as turning, backing up, rolling over, and the like, and so those
combinations become packaged as behavioral schemata, or possible
<i>intentions, </i>to move in certain ways in local scenes. They
provide the translation from the &quot;polar coordinates&quot; of the
local image to the Cartesian labels of the memory map. Only when a
young mammal has learned the effects of turning and locomotion in the
local scene is it able to start using the <i>memory</i> circuit to
construct its own 3 .D memory map of the territory.</font></font></p>
</body>
</html>