9/25/95
I Introduction:
Human nervous systems display an impressive roster of complex
capacities, including the following: perceiving, learning and
remembering, planning, deciding, performing actions, as well as the
capacities to be awake, fall asleep, dream, pay attention, and be
aware. Although neuroscience has advanced spectacularly in this
century, we still do not understand in satisfying detail how any
capacity in the list emerges from networks of neurons.[1] We do not completely understand how humans can be
conscious, but neither do we understand how they can walk, run, climb
trees or pole vault. Nor, when one stands back from it all, is
awareness intrinsically more mysterious than motor control. Balanced
against the disappointment that full understanding eludes us still, is
cautious optimism, based chiefly on the nature of the progress behind
us. For cognitive neuroscience has already passed well beyond what
skeptical philosophers once considered possible, and continuing
progress seems likely.
In assuming that neuroscience can reveal the physical mechanisms subserving psychological functions, I am assuming that it is indeed the brain that performs those functions -- that capacities of the humans mind are in fact capacities of the human brain. This assumption and its corollary rejection of Cartesian souls or spirits or "spooky stuff" existing separately from the brain is no whimsy. On the contrary, it is a highly probable hypothesis, based on evidence currently available from physics, chemistry, neuroscience and evolutionary biology. In saying that physicalism is an hypothesis, I mean to emphasize its status as an empirical matter. I do not assume that it is a question of conceptual analysis, a priori insight, or religious faith, though I appreciate that not all philosophers are at one with me on this point. [2]
Additionally, I am convinced that the right strategy for understanding psychological capacities is essentially reductionist, by which I mean, broadly, that understanding the neurobiological mechanisms is not a frill but a necessity. Whether science will finally succeed in reducing psychological phenomena to neurobiological phenomena is, needless to say, yet another empirical question. Adopting the reductionist strategy means trying to explain the macro levels (psychological properties) in terms of micro levels (neural network properties).
The fundamental rationale behind this research strategy is straightforward: if you want to understand how a thing works, you need to understand not only its behavioral profile, but also its basic components and how they are organized to constitute a system. If you do not have the engineering designs available for reference, you resort to reverse engineering -- the tactic of taking a part a device to see how it works.[3] Insofar as I am trying to discover macro-to-micro explanations, I am a reductionist. Because many philosophers who agree with me on the brain-based nature of the soul nonetheless rail against reductionism as ridiculous if not downright pitiful, it may behoove me to begin by explaining briefly what I do and, most emphatically, do not mean by a reductionist research strategy.[4]
Clearing away the negatives first, may I say that I do not mean that a reductionist research strategy implies that a purely bottom-up strategy should be adopted. So far as I can tell, no one in neuroscience thinks that the way to understand the nervous system is first to understanding everything about the basic molecules, then everything about every neuron and every synapse, and to continue ponderously thus to ascend the various levels of organization until, at long last, one arrives at the uppermost level -- psychological processes. (Figure 1) Nor is there anything in the history of science that says a research strategy is reductionist only if it is purely bottom-up. That characterization is straw through and through. The research behind the classical reductionist successes -- explanation of thermodynamics in terms of statistical mechanics; of optics in terms of electromagnetic radiation; of hereditary transmission in terms of DNA -- certainly did not conform to any purely bottom-up research directive.
Figure 1 about here
So far as neuroscience and psychology are concerned, my view is simply that it would be wisest to conduct research on many levels simultaneously, from the molecular, through to networks, systems, brain areas, and of course behavior. Here, as elsewhere in science, hypotheses at various levels can co-evolve as they correct and inform one another. [5] Neuroscientists would be silly to make a point of ignoring psychological data, for example, just as psychologists would be silly to make a point of ignoring all neurobiological data.
Second, by reductionist research strategy I do not mean that there is something disreputable, unscientific or otherwise unsavory about high level descriptions or capacities per se. It seems fairly obvious, to take a simple example, that certain rhythmic properties in nervous systems are network properties resulting from the individual membrane traits of various neuron types in the network, together with the way the set of neurons interact. Recognition that something is the face of Arafat, for another example, almost certainly emerges from the responsivity profiles of the neurons in the network plus the ways in which those neurons interact. "Emergence" in this context is entirely non-spooky and respectable, meaning, to a first approximation, "property of the network". Determining precisely what the network property is, for some particular feat, will naturally take quite a lot of experimental effort. Moreover, given that neuronal behavior is highly nonlinear, the network properties are never a simple "sum of the parts". They are some function -- some complicated function -- of the properties of the parts. High level capacities clearly exist, and high level descriptions are therefore needed to specify them.
"Eliminative materialism", refers to the hypothesis that (1) materialism is most probably true, and also (2) many traditional aspects of explanation of human behavior are probably not adequate to the reality of the etiology of behavior. [6] The standard analogy here is that just as "caloric fluid" was useful but fundamentally mistaken in understanding thermal phenomena (conduction, convection, radiation) so some psychological categories currently invoked may be somewhat useful but fundamentally mistaken in fathoming behavioral etiology. Other existing characterizations of capacities may have a core of adequacy but undergo major redrawings, in something like the way Mendel's notion of "factor" came to be modified by genetics into the notion of "gene" which itself was modified and deepened with the development of molecular biology. Some categories such as "attitude" are extremely vague and might be replaced altogether; others, such as "is sleeping" have already undergone a fractionation as EEG and neurophysiological research has revealed important brain differences in various stages of sleep. Categories such as "memory", "attention" and "reasoning" are likewise undergoing revision, as experimental psychology and neuroscience proceed.[7] It remains to be seen whether there is a neurobiological reality to sustain notions such as "belief" and "desire" as articulated by modern philosophers such as Fodor[8] and Searle[9], though Paul Churchland and I have argued that revision here too is most probable. [10] The revisionary prediction too is an empirical hypothesis, and one for which empirical support already exists. [11]
The possibility of nontrivial revision and even replacement of existing high level descriptions by 'neurobiologically harmonious' high level categories is the crux of what makes eliminative materialism eliminative. [12] By 'neurobiologically harmonious' categories, I mean those that permit coherent, integrated explanations from the whole brain on down through neural systems, big networks, micronets, and neurons. Only the strawman is so foolish as to claim that there are no high level capacities, that there are no high level phenomena. [13] In its general aspect, my point here merely reflects this fact: in a profoundly important sense we do not understand exactly what, at its higher levels, the brain really does. Accordingly, it is practical to earmark even our fondest intuitions about mind/brain function as revisable hypotheses rather than as transcendental absolutes or introspectively given certainties. Acknowledgment of such revisability makes an enormous difference in how we conduct psychological and neurobiological experiments, and in how we interpret the results.
A. The Goal is Absurd (Incoherent)
One set of reasons for dooming the reductionist research strategy is
summed up thus: "I simply cannot imagine that seeing blue or the
feeling of pain, for example, could consist in some pattern of activity
of neurons in the brain," or, more bluntly, "I cannot imagine how
you can get awareness out of meat." There is sometimes considerable
filler between the "it's unimaginable" premise and the "it's
impossible" conclusion, but so far as I can tell, the filler is
typically dust which cloaks the fallacious core of the argument. [14]
Given how little in detail we currently understand about how the human
brain "en-neurons" any of its diverse capacities, it is altogether
predictable that we should have difficulty imagining the neural
mechanisms. When the human scientific community was comparably ignorant
of such matters as valence, electron shells, and so forth, natural
philosophers could not imagine how you could explain the malleability
of metals, the magnetizability of iron, and the rust resistance of gold
, in terms of underlying components and their organization. Until the
advent of molecular biology, many people thought it was unimaginable,
and hence impossible, that to be a living thing could consist in a
particular organization of "dead" molecules. "I cannot imagine", said
the vitalists, "how you could get life out of dead
stuff".
From the vantage point of considerable ignorance, failure to imagine
some possibility is only that: a failure of imagination-- one
psychological capacity amongst others. It does not betoken any
metaphysical limitations on what we can come to understand , and it
cannot predict anything significant about the future of scientific
research. After reflecting on the awesome complexity of the problem of
thermoregulation in homeotherms such as ourselves, I find I cannot
imagine how brains control body temperature under diverse conditions.
I suspect, however, that this is a relatively uninteresting
psychological fact about me, reflecting merely my current state of
ignorance. It is not an interesting metaphysical fact about the
universe nor even an epistemological fact about the limits of
scientific knowledge.
A variation of the "cannot imagine" proposal is expressed as "we can
never, never know....", or "it is impossible to ever understand...." or
"it is forever beyond science to show that....". The idea here is that
something's being impossible to conceive says something decisive about
its empirical or logical impossibility. I am not insisting that such
proposals are never relevant. Sometimes they may be. But they are
surprisingly high-handed when science is in the very early stages of
studying a phenomenon.
The sobering point here is that assorted "a priori certainties" have,
in the course of history, turned out to be empirical duds, however
obvious and heartfelt in their heyday. The impossibility that space is
non-Euclidean , the impossibility that in real space parallel lines
should converge, the impossibility of having good evidence that some
events are undetermined, or that someone is now dreaming, or that the
universe had a beginning -- each slipped its logical noose as we came
to a deeper understanding of how things are. If we have learned
anything from the many counterintuitive discoveries in science it is
that our intuitions can be wrong. Our intuitions about ourselves and
how we work may also be quite wrong. There is no basis in evolutionary
theory, mathematics, or anything else, for assuming that prescientific
conceptions are essentially scientifically adequate conceptions.
A third variation on this "nay, nay, never" theme draws conclusions
about how the world must actually be, based on linguistic
properties of certain central categories in current use to
describe the world. Permit me to give a boiled down instance: "the
category 'mental' is remote in meaning -- means something completely
different -- from the category 'physical' . It is absurd therefore to
talk of the brain seeing or feeling, just as it is absurd to talk of
the mind having neurotransmitters or conducting current." Allegedly,
this categorial absurdity undercuts the very possibility that science
could discover that feeling pain is activity in neurons in the brain.
The epithet "category error" is sometimes considered sufficient to
reveal the naked nonsense of reductionism.
Much has already been said on this matter elsewhere,[15] and I shall bypass a lengthy discussion of
philosophy of language with three brief points. (1) It is rather
far-fetched to suppose that intuitions in the philosophy of language
can be a reliable guide to what science can and cannot discover about
the nature of the universe. (2) Meanings change as science
makes discoveries about what some macro phenomenon is in terms
of its composition and the dynamics of the underlying structure. (3)
Scientists are unlikely to halt their research when informed that
their hypotheses and theories "sound funny" relative to current usage.
More likely, they will say this: "the theories might sound funny to
you, but let me teach the background science that makes us think the
theory is true. Then it will sound less funny." It may be noted that
it sounded funny to Copernicus' contemporaries to say the Earth is a
planet and moves; it sounded funny to say that heat is molecular motion
or that physical space is non-Euclidean or that there is no absolute
"downness". And so forth.
That a scientifically plausible theory sounds funny is a criterion only
of its not having become common coin, not of its being wrong.
Scientific discoveries that a certain macro phenomenon is a complex
result of the micro structure and its dynamics are typically surprising
and typically sound funny -- at first. Obviously none of this is
positive evidence that we can achieve a reduction of psychological
phenomena to neurobiological phenomena. It says only that sounding
funny does not signify anything, one way or the other.
B. The Goal is Inconsistent with "Multiple Realizability"
The core of this objection is that if a macro phenomenon can be the
outcome of more than one mechanism (organization and dynamics of
components), then it cannot be identified with any one mechanism, and
hence the reduction of the macrophenonomenon to the
(singular) underlying micro phenomenon is impossible. This objection
seems to me totally uninteresting to science. Again, permit me to
ignore important details and merely to summarize the main thrust of the
replies.
(1) Explanations, and therefore reductions, are domain relative. In
biology, it may be fruitful first to limn the general principles
explaining some phenomenon seen in diverse species, and then figure out
how to account for the interspecies differences, and then, if
desirable, how to account for differences across individuals within a
given species. Thus the general principles of how hearts or stomachs
work are figured out, perhaps based on studies of a single species, and
particularities can be resolved thereafter. Frog hearts, macaque hearts
and human hearts work in essentially the same general way, but there
are also significant differences, apart from size, that call for
comparative analyses. Consider other examples: (a) from the general
solution to the copying problem that emerged from the discovery of the
fundamental structure of DNA, it was possible to undertake explorations
of how differences in DNA could explain certain differences in the
phenotype; (b) from the general solution to the problem of how neurons
send and receive signals, it was possible to launch detailed
exploration into the differences in responsivity profiles of distinct
classes of neuron. [16]
(2) Once the mechanism for some biological process has been
discovered, it may be possible to invent devices to mimic those
processes. Nevertheless, invention of the technology for artificial
hearts or artificial kidneys does not obliterate the explanatory
progress on actual hearts and actual kidneys; it does not gainsay the
reductive accomplishment. Again, the possibility that hereditary
material of a kind different from DNA might be found in things
elsewhere in the universe does not affect the basic scaffolding of a
reduction on this planet. Science would have been much the poorer if
Crick and Watson had abandoned their project because of the abstract
possibility of Martian hereditary material or artificial hereditary
material. In fact, we do know the crux of the copying mechanism on
Earth -- namely, DNA, and we do know quite a lot about how it does
its job. Similarly, the engineering of artificial neurons and
artificial neural nets (ANNs) facilitates and is facilitated by
neurobiological approaches to how real neurons work; the engineering
undertakings do not mean the search for the basic principles of nervous
system function is misguided.
(3) There are always questions remaining to be answered in science,
and hence coming to grasp the general go of a mechanism, such as the
discovery of base-pairing in DNA, ought not be mistaken for the utopian
ideal of a complete reduction -- a complete explanation. Discoveries
about the general go of something typically raise hosts of questions
about the detailed go of it, and then about the details of the
details. To signal the incompleteness of explanations,
perhaps we should eschew the expression "reduction" in favor of
"reductive contact". Hence we should say the aim of neuroscience is to
make rich reductive contact with psychology as the two broad
disciplines co-evolve. I have experimented with this recommendation
myself, and although some philosophers warm to it, scientists find it
quaintly pedantic. In any case, "reductive contact" between molecular
biology and macrobiology has become steadily richer since 1953, though
many questions remain. Reductive contact between psychology and
neuroscience has also become richer, especially in the last decade,
though it is fair to say that by and large the basic principles of how
the brain works are poorly understood.
(4) What, precisely, are supposed to be the programmatic sequelae to
the multiple realizability argument? Is it that neuroscience is
irrelevant to understanding the nature of the human mind?
Obviously not. That neuroscience is not necessary to
understand the human mind? One cannot, certainly, deny that it is
remarkably useful. Consider the discoveries concerning sleep,
wakeness, and dreaming; the discoveries concerning split brains, humans
with focal brain lesions, the neurophysiology and neuroanatomy of the
visual system, and so on. Is it perhaps that we should not get our
hopes up too high? What, precisely, is "too high" here? Is it the hope
that we shall discover the general principles of how the brain works?
Why is that too high a hope?
C. The Brain Causes Consciousness
Nay saying the reductionist goal while keeping dualism at arm's length
is a manoeuvre requiring great delicacy. John Searle's strategy is to
say that although the brain causes conscious states, any
identification of conscious states with brain activities is unsound.
Traditionally, it has been opined that the best the reductionist can
hope for are correlations between subjective states and brain
states, and although correlations can be evidence for causality they
are not evidence for identity. Searle has tried to bolster that
objection by saying that whereas a/b identifications elsewhere in
science reveal the reality behind the appearance, in the case of
awareness, the reality and the appearance are inseparable -- there is
no reality to awareness except what is present in awareness. There is,
therefore, no reduction to be had.
Synoptically, here is why Searle's manoeuvre is unconvincing: he fails
to appreciate why scientists opt for identifications when they do.
Depending on the data, cross-level identifications to the effect that
a is b may be less troublesome and more comprehensible scientifically
than supposing thing a causes separate thing b. This is best seen by
example.[17]
Science as we know it says electrical current in a wire is not caused
by moving electrons; it is moving electrons. Genes are not
caused by chunks of base pairs in DNA; they are chunks of base
pairs (albeit sometimes distributed chunks). Temperature is not
caused by mean molecular kinetic energy; it is mean molecular
kinetic energy. Reflect for a moment on the inventiveness required to
generate explanations that maintain the nonidentity and causal
dependency of (a) electric current and moving electrons, (b) genes and
chunks of DNA, and (c) heat and molecular motion. Unacquainted with the
relevant convergent data and explanatory successes, one may suppose
this is not so difficult. Enter Betty Crocker.
In her microwave oven cookbook, Betty Crocker offers to explain how a
microwave oven works. She says that when you turn the oven on, the
microwaves excite the water molecules in the food, causing them to move
faster and faster. Does she, as any high school science teacher knows
she should, end the explanation here, perhaps noting, "increased
temperature just is increased kinetic energy of the
constituent molecules "? She does not. She goes on to explain that
because the molecules move faster, they bump into each other more
often, which increases the friction between molecules, and, as we all
know, friction causes heat. Betty Crocker still thinks heat is
something other than molecular KE; something caused by but actually
independent of molecular motion. [18] Why do
scientists not think so too?
Roughly, because explanations for heat phenomena -- production by
combustion, by the sun, and in chemical reactions; of conductivity,
including conductivity in a vacuum, the variance in conductivity in
distinct materials, etc. -- are vastly simpler and more
coherent on the assumption that heat is molecular energy of
the constituent molecules. By contrast, trying to make the data fit
with assumption that heat is some other thing caused by
speeding up molecular motion is like trying to nail jelly to the wall.
If one is bound and determined to cleave to a caloric thermodynamics,
one might, with heroic effort, pull it off for oneself, though
converts are improbable. The cost, however, in coherence with the rest
of scientific theory, not to mention with other observations, is
extremely high. What would motivate paying that cost? Perhaps an
iron-willed, written-in-blood, resolve to maintain unsullied the
intuition that heat is what it is and not another thing. In
retrospect, and knowing what we now know, the idea that anyone would go
to exorbitant lengths to defend the heat intuition seems rather a
waste of time.
In the case at hand, I am predicting that explanatory power, coherence
and economy will favor the hypothesis that awareness just is
some pattern of activity in neurons. I may turn out to be wrong. If I
am wrong, it will not be because an introspectively-based intuition is
immutable, but because the science leads us in a different direction.
If I am right, and certain patterns of brain activity are the
reality behind the experience, this fact does not in and of itself
change my experience and suddenly allow me (my brain) to view my brain
as an MR scanner or a neurosurgeon might view it. I shall continue to
have experiences in the regular old way, though in order to understand
the neuronal reality of them, my brain needs to have lots of
experiences and undergo lots of learning.
Finally, barring a jump to the dualist' s horse, the idea that there
has to be a bedrock of subjective appearance on which
reality/appearance discoveries must ultimately rest is faintly strange.
It seems a bit like insisting that "down" cannot be relative to where
one is in space; down is down. Or like insisting that time cannot be
relative, that either two events happen at the same time or they don't,
and that's that. Humans are products of evolution; nervous systems have
evolved in the context of competition for survival -- in the struggle
to succeed in the four F's: feeding fleeing, fighting, and
reproduction. The brain's model of the external world enjoys
improvement through appreciating various of reality/appearance
distinctions -- in short, through common critical reason and through
science. In the nature of things, it is quite likely that the brain's
model of its internal world also allows for appearance/reality
discoveries. The brain did not evolve to know the nature of the sun as
it is known by a physicist, nor to know itself as it is known by a
neurophysiologist. But, in the right circumstances, it can come to know
them anyhow. [19]
D. Because Consciousness is a Virtual Machine
This is the view of D. C. Dennett. [20] Like Searle,
Dennett is no dualist. Unlike Searle, who thinks that quite a lot,
if not all, about consciousness can be discovered by neuroscience,
Dennett has long been convinced that study of the brain itself -- its
physiology and anatomy -- is largely a waste of time so far as
understanding the nature of consciousness and cognition are
concerned. Simplified, the crux of his idea is this: humans become
conscious as they acquire language and learn to talk to themselves.
What happens in this transformation is that a parallel machine (the
neural networks of the brain) simulates a serial machine (operations
are performed one at a time, in a sequence, according to rules, which
may be recursive.)
By acquiring a language and then learning to speak silently to oneself,
one allegedly creates a consciousness virtual machine in the brain.
Dennett explains what this by means of a pivotal analogy: it is like
creating a virtual machine for simulating piloting a plane on your
desktop computer by installing software, such as Flight
Simulator. Consciousness bears the same relation to the brain as
the flight simulation bears to the events inside the computer.
Dennett's methodological moral is unambiguous: just as we cannot hope
to learn anything much about the flight simulator (it scope and limits,
how it works) by studying the computer's innards while it is running
Flight Simulator so we cannot hope to learn much about
consciousness by studying the brain's innards while it is conscious.
If one wants to know about Flight Simulator and its many
properties, the best you can do is study its performance -- in a sense,
there really is not anything else to Flight Simulator than its
performance. We find it fruitful in talking about Flight
Simulator to say things like "its altimeter registers altitude",
but this does not mean that there is something in my computer that
really is high in the sky or something that measures how high it really
is. Such talk is simply an economical, convenient way of making sense
of the computer's screen performance when it is running Flight
Simulator software.
Ditto (more or less) for consciousness. The brain is the hardware on
which the consciousness software runs, hence looking at the brain
itself is not going to teach us much about the software itself. Even as
it is mistaken to suppose the computer has a little runway hidden
tucked inside that gets rolled out when I press a button, so it is
mistaken to think the brain really does anything like fill in the
blindspot or fill in during seeing subjective motion (as in a movie).
[21] Dennett believes he has shown us that there
really is not so much in the way of inner experience to be explained
after all. As with Flight Simulator, if you want to know about
consciousness and its properties, it is performance under a variety of
conditions that needs to be studied. Based on the performance you can
of course infer the various computational properties of the software.
And that is all there will be to explaining consciousness.
Consequently, the tools of experimental psychology will suffice. The
details of neuroscience might tell us something about how the software
runs on the brain; that won't tell us anything about the nature of
consciousness, but only about how the brain runs software. This, in
capsule, is my understanding of the conviction that inspires Dennett to
his book's title, Consciousness Explained.
How plausible is the Dennett story? My criticism here draws on work of
Paul Churchland[22] and will focus mainly on this
question: is it remotely reasonable that when we are consciousness the
parallel machine (the brain) is simulating a serial machine? As an
archival preliminary, however, note that Dennett's package has been
subjected to intense and careful analysis. First, his claim that
acquisition of human language is a necessary condition of human
consciousness has been repeatedly challenged and thoroughly criticized.
[23] Endlessly it has been noted that this seems to
imply that preverbal infants are not conscious; that other animals,
such as chimpanzees and orangs are not conscious; that subjects with
global aphasia or left hemispherectomies are not conscious. Briefly,
Dennett's response is this: yes indeed, nonverbal subjects are not
aware in the way a fully verbal human is aware; e.g., they cannot
think about whether interest rates will go down next month.
Unfortunately, Dennett's response is tangential to the criticism. The
issue is whether preverbal children and animals can be conscious of
colors, sounds, smells, spatial extent, motion, being dizzy, feeling
pain, etc. in rather like the way I am conscious of them.
Second, Dennett's according pre-eminent status to linguistic activity
and his correlative "debunking" of sensory experiences (e.g. filling
in), feelings, and nonlinguistic cognition generally, have been
subject to a constant barrage of complaints. [24]
Regrettably, I can give here only a highly truncated version of the
long and sometimes convoluted debates between Dennett and various
critics. The heart of the complaints is that Dennett wrongly assumes
that performance is all that needs explaining -- that explaining
reports of conscious experience is tantamount to explaining
conscious experience itself. Dennett's core response here has been to
wave off the complainers as having failed properly to understand him,
scolding them for being still in the grip of bad old conceptual habits
implying homunculi, ghosts in the machine, furtive Cartesianism, and
kindred mistakes. Suffice it to say that Dennett's
"if-you-disagree-you-have-misunderstood" stance, while conceivably
true of some critics, does not appear true of all.
Is a "virtual serial machine" necessary to get a
one-after-another temporal ordering? Not at all. For example, it has
been well known for at least eight years that neural nets with
recurrent loops can yield temporal sequencing, and do so very
economically and elegantly.[25] For a recent
example, beautiful work in using "real-valued genetic algorithms to
evolve continuous-time recurrent neural networks capable of sequential
behavior and learning" has been done by Randall Beer and other
sequencing work has been done by Michael Mozer.[26]
Clearly, sequencing tasks per se do not imply the existence
of a simulated serial machine. [27]
Is a virtual serial machine necessary to get rule-following behavior as
seen in linguistic performance? Not at all. Again, as Elman and his
colleagues have shown, recurrent neural nets can manage this very
well.[28] Is a virtual serial machine needed to
restrict a certain class of operations to one at a time? Not at all.
First, a special class of operations could be the output of one
network, albeit a widely distributed network. Second, they could be the
output of a winner-take-all interaction between nets.[29] And there are lots of other architectures for
accomplishing this. The motor system probably functions thus, but
there is no reason to think it simulates a serial machine. [30]
Third, should we assume that consciousness involves only one operation
at a time? Almost certainly not. Granting that the attentional
capacity is much smaller than the extra-attentive capacity to
represent[31], why conclude that we can attend to
only one thing at a time? When I look at a bowl of colored M&M's, can
I see more than one M&M at once? Probably. Fourth, is the serial
machine simulation necessary in order to enable recursive properties,
such that one can be self aware (think about what one just said to
oneself)? Not at all. Recurrent neural nets are powerful enough and
complex enough to manage this very nicely. Indeed, recurrence probably
is a key feature of various self-monitoring subsystems in the nervous
system, including thermoregulation. Is there any rationale for
saying, "when we are conscious the brain must simulating a serial
machine?" I see none.[32] This does not entail that
Dennett must be wrong, but only that there is no reason to think he is
on the right track.
E. The Problem is Beyond our Feeble Intelligence
Initially, this claim appears to be a modest acknowledgment of our
limitations (Colin McGinn 1990). In fact, it is a powerful prediction
based not on solid evidence, but on profound ignorance. For all we can
be sure now, the prediction might be correct, but equally, it might
very well be false. How feeble is our intelligence? How difficult is
the problem? How could you possibly know that solving the problem
beyond our reach, no matter how science and technology develop?
Inasmuch as it is not known that the brain is more complicated than it
is smart, giving up on the attempt to find out how it works would be
disappointing. On the contrary, as long as experiments continue to
produce results that contribute to our understanding, why not keep
going? [33]
In neuroscience there are many data at higher levels relevant to
consciousness. Blindsight, hemineglect, split brains, anosognosia
(unawareness of deficit), for starters, are powerful constraints to
guide theoretical reflection. Careful studies using scanning devices
such as magnetic resonance imagining (MRI) and positron emission
tomography (PET) have allowed us to link specific kinds of functional
losses with particular brain regions.[34] This helps
narrow the range of structures we consider selecting for preliminary
micro exploration. [35]
For example, the hippocampus might have seemed a likely candidate for a
central role in consciousness because it is a region of tremendous
convergence of fibres from diverse areas in the brain. We now know,
however, that bilateral loss of the hippocampus, though it impairs the
capacity to learn new things, does not entail loss of consciousness. At
this stage, ruling something out is itself a valuable advance. We also
know that certain brain stem structures such as the locus coereleus
(LC) are indirectly necessary, but are not part of the mechanism for
consciousness. LC does play a nonspecific role in arousal, but not a
specific role in awareness of particular contents, such as awareness at
a moment of the color of the morning sky rather than the sound of the
lawn sprinklers. The data may be fascinating in its own right, but the
question remains: how can we get from an array of intriguing data to
genuine explanations of the basic mechanism? How can we get
started?
In thinking about this problem, I have been greatly influenced by
Francis Crick. His basic approach is straightforward: if we are going
to solve the problem, we should treat it as a scientific problem to be
tackled in much the way we tackle other difficult scientific problems.
As with any scientific mystery, what we want is a revealing
experimental entry. We want to find a thread which, when pulled, will
unloose a whole lot else. To achieve that, we need to devise testable
hypotheses that can connect macro effects with micro dynamics.
Boiled down, what we face is a constraint satisfaction problem: find
psychological phenomena that (a) have been reasonably well studied by
experimental psychology, (b) are circumscribed by lesion data from
human patients as well as data from precise animal microlesions, (c)
are known to be related to brain regions where good neuroanatomy and
neurophysiology has been done and (d) where we know quite a lot about
connectivity to other brain regions. The working assumption is that
if a person is aware of a stimulus, his brain will be different in some
discoverable respect from the condition where he is awake and attentive
but unaware of the stimulus. A auspicious strategy is to hunt down
those differences, guided by data from lesion studies, PET scans,
magnetoencephalograph (MEG) studies, and so forth. Discovery of those
differences, in the context of neurobiological data generally, should
aid discovering a theory of the mechanism.
The central idea is to generate a theory constrained by data at many
levels of brain organization -- sufficiently constrained so that it
can be put to meaningful tests. Ultimately a theory of consciousness
will need to encompass a range of processes involved in awareness,
including attention and short term memory. Initially, however, it may
target a subset, such as integration across space and across time.
Whether the theory falls to falsifying evidence or whether it
survives tough tests, we shall learn something. That is, either we
shall have ruled out specific possibilities -- a fine prize in the
early stages of understanding -- or we can go on deepen and develop
the theory further -- an even finer prize. In any case, the trick is to
generate testable, meaty hypotheses rather than loose, frothy
hypotheses susceptible only to experiments of fancy. The trick is to
make some real progress.
B. Visual Awareness
What plausible candidates surface from applying the constraint
satisfaction procedure? Interestingly, the choices are quite
limited. Although metacognition, introspection, and awareness of
emotions, for example, are indeed aspects of consciousness, either we
do not have good lesion data to narrow the search space of relevant
brain regions, or the supporting psychophysics is limited or both.
Consequently, these processes are best put on the back burner for
later study.
Visual awareness, by contrast, is a more promising candidate. In the
case of vision, as Crick points out, there is a huge literature in
visual psychophysics to draw upon, there is a rich literature of human
and animal lesion studies, and relative to the rest of the brain, a lot
is known about the neuroanatomy and neurophysiology of the visual
system, at least in the monkey and the cat. Visual phenomena such as
filling in, binocular rivalry, seeing motion, seeing stereoptic depth,
and so forth might reward the search for the neurobiological
differences between being aware and not being aware in the awake,
attentive animal. This may get us started, and I do emphasize
started.
1. The Crick Hypothesis
Immersed in the rich context of multi-level detail, Crick has sketched
an hypothesis concerning the neuronal structures he conjectures make
the salient differences, depending on whether the animal is or is not
visually aware of the stimulus. [36] Integration of
representations across spatially distributed neural networks -- the
unity in apperception, so to speak -- is thought be accomplished by
temporal 'binding', namely synchrony in the output responses of the
relevant neurons. Very crudely, Crick's suggestion is that (1) for
sensory awareness, such as visual awareness, the early corteces are
pivotal (e.g. visual areas V2, V3, V5). This makes sense of lesion
data, as well as recent PET data (Damasio, Grabowski et al. 1993;
Kosslyn et al. 1993) and single cell data (Logothetis and Schall
1989). (2) Within the early sensory cortical areas, pyramidal cells
in layer 5 and possibly layer 6, play the key role.
What good is this idea ? Part of its appeal is its foothold in basic
structure. In biology, the solution to difficult problems about
mechanism can be greatly facilitated by identification of critical
structures. Crudely, if you know "what", it helps enormously in
figuring out "how". On its own, the Crick hypothesis can be only a
small piece of the puzzle. If we are lucky, however, it, or something
like it, may be a key piece of the puzzle. This is not the
time for a fuller discussion of this hypothesis. Suffice it to say
that true or false, the Crick hypothesis provides a bold illustration
of how to approach a problem so tricky it is often scrapped as
unapproachable.
2. The Llinas Hypothesis
Another promising entry route is suggested by the differences --
phenomenological and neurobiological -- between
sleep/dreaming/wakeness[37] (SDW) states. [38] This entry point is attractive first because there
is the familiar and dramatic loss of awareness in deep sleep, which is
recovered as we awake, and is probably present also during dreaming.
The phenomenon is highly available in lots of different subjects and
across many species. Second, MEG and EEG techniques reveal global
brain features characteristic of different states. Human and animal
lesion data are important, especially as they concern deficits in
awareness during wakeness. Here again I note the significance of
research on blindsight, hemineglect (tendency to be unaware of stimuli
in various modalities on the left side of the body), simultanagnosia
(inability to see several things simultaneously), anosognosia
(unawareness of deficits such as paralysis) blindness denial,
unawareness of jargon aphasia (of not making sense) and so forth.
Third, we have learned a great deal from abnormalities in and
manipulation of the SDW cycle and the link to specific brain
properties. Fourth, some of the global changes in state in the SDW
cycle seen by macro techniques have been linked by micro techniques to
interactions between specific circuits in the cortex and subcortical
circuits, especially circuits in several key structures in the
thalamus. Fifth, and more specifically, MEG data reveal an robust 40
Herz wave form during wakeness and dreaming.[39] The
definition and amplitude is much attenuated during sleep, and the
amplitude is modulated during wakeness and dreaming. Analysis of the
wave from by MEG reveals it to be a traveling wave, moving in the
anterior to posterior direction in the brain, covering the distance in
about 12 to 13 milliseconds. Cellular data suggest that these
dynamical properties emerge from particular neural circuits and their
dynamical properties.
What does all this add up to? Based on these data, and mindful of the
various high-level data, Rodolfo Llinas and colleagues (1991; 1993)
have hypothesized that the fundamental organization subserving
consciousness and the shifts seen in the SDW pattern are pairs of
coupled oscillators, each of which connect thalamus and cortex, but
each connects distinct cell populations via its own distinctive
connectivity style. (Figure 2) One oscillator 'family' connects
neurons in a thalamic structure known as the intralaminar nuclei, a
bagel-shaped constellation of structures whose neurons reach to the
upper layers of cortex to provide a highly regular fan-like coverage of
the entire cortical mantle. The other oscillator 'family' connects
neurons in thalamic nuclei for modality-specific information (MS
nuclei) originating for example, in the retina or the cochlea, with
modality specialized cortical areas (e.g. V2, S2). During deep sleep,
the intralaminar neurons projecting to cortex cease their 40 Hz
behavior. During deep sleep and dreaming, external signals to the
cortex are gated by the reticular nucleus of the thalamus. Joseph Bogen
(1993) also hypothesis a crucial role for intralaminar structures,
noting especially the wide fan out from those nuclei to cortex, and the
heavy connection to striatum.
Ever so crudely, the idea is that the second oscillator 'family'
provides the content (visual, somatosensory etc. ) while the first
provides the integrating context. In deep sleep the oscillators are
decoupled; in dreaming they are coupled but the MS oscillating circuit
is largely nonresponsive to external signals from the periphery; in
wakeness, the oscillators are coupled, and the MS circuit is
responsive to external signals.
What are the effects in humans of lesions to the intralaminar thalamic
structures (bagel)? First, it is highly unlikely that a lesion should
occur exclusively to the intralaminar nuclei, with sparing of other
thalamic structures. Bearing that caution in mind, I note that the main
result of small unilateral lesions believed to reside mainly in the
intralaminar nuclei, is neglect (unawareness) of all stimuli
originating the opposite body side. (Watson and Heilman 1979; Watson,
Valenstein and Heilman 1981). Bilateral lesions apparently result in
general unarousability, meaning roughly that the patient initiates no
behavior and responds very poorly to sensory stimuli or questions
(Castaigne et al. 1981; Guberman and Stuss 1983). The few animal
studies that exist are consistent with the human data (Henderson,
Alexander and Nalser 1982; Watson, Miller and Heilman 1978). Bogen
(1993) also points out that the human lesion data, together with the
connectivity patterns, makes the intralaminar nuclei a candidate for
"the where of awareness" . These data are important and provide a
useful starting point, but further studies, especially using functional
MRI to locate areas of relative low and high activity, are desirable.
Lesions to modality-specific regions of the thalamus, by contrast, lead
to modality specific losses in awareness -- visual awareness, for
example will be lost, but awareness of sounds, touches etc. can be
normal. Intriguingly, the MEGs of Alzheimer's patients who have
degenerated to a state of inanition show a dilapidated 40 Hz wave form
when it exists at all. Obviously these data are not decisive, but at
least they are consistent with the hypothesis.
Do the Llinas hypothesis and the Crick hypothesis fit together ?
Minimally, they are consistent. Additionally, they are mutually
supporting at the neuron and network levels. One encouraging point is
this: the two families of oscillators (MS and intralaminar) richly
connect to each other mainly in cortical layer 5 (Figure 2).
From what we can tell now, those connections seem to be the chief means
whereby the oscillators are coupled. The possibility entertained here
is that the temporal synchrony Crick hypothesizes in neurons carrying
signals about external stimuli may be orchestrated by the
intralaminar-cortical circuit. Connections between brain stem
structures and the intralaminar nucleus could have a role in
modulating arousal and alertness.
Figure 2 about here
Many questions now suggest themselves. For example, how do the pivotal
structures for awareness interface with behavior? More specifically,
what are the connections between the intralaminar nuclei and motor
structures, and between layer 5 of sensory corteces and motor
structures; do the projections from the intralaminar nuclei to the
cingulate cortex have a role in attention? These are questions
motivated by independent data. Convergence of hypotheses is of course
encouraging, but it is well to remember that it can also encourage us
down the proverbial garden path. Wisdom counsels guarded optimism.
But is something missing here ? Probably. As Kant might have said to
Hume, the brain will not produce awareness unless the nervous system
also generates a representation of self -- a representation which
carries what we would call "a point of view". And this is indeed
precisely the hypothesis tendered by Antonio Damasio (1994). According
to the Damasio perspective, the neurobiological mechanisms for visual
awareness, for example, are essentially interconnected with the
mechanisms for representing oneself as a thing that has experiences,
that feels, remembers and plans; as a thing occupying space and
enduring through time. To suppose that visual awareness can be
understood independently of the self-representation is like supposing
evolution can be understood independently of environment.
Damasio's ideas on this score have emerged from many years of observing
brain damaged patients, and reflecting on the ways in which awareness
is related to self-representation and how that in turn is related to
body-representation (For the details of his hypothesis, see his book,
Descartes' Error 1994). Against a backdrop of basic
neuroanatomy and neurophysiology, Damasio sees representational
complexity and interdependence as key elements in explaining
consciousness. Crudely, synchrony of firing in certain visual circuits
may be a necessary condition for visual awareness, but a
sufficient condition it surely is not. Constructing a
plausible hypothesis to capture a necessary condition is hard enough;
identifying the additional neural conditions that jointly are necessary
and sufficient will be harder still. Even so, Damasio's central idea is
both powerful and reasonable: body-representation, which
systematically integrates bodily-stimulation and body-state
information, provides a scaffolding for self-representation,
and self-representation is the anchor point for awareness -- modality
specific and otherwise. Moreover the adaptive advantages of an
integrated body-representation in life are pretty obvious (see again
Damasio 1994). One needs only to think of subdominant vervet monkey
males sneaking around at night to mate with females while the alpha
male dozes, to realize the importance of "knowing which way is up", to
put knowledge of one's body-self in its most general form.
Whereas Kant, a dyed-in-the-wool anti-reductionist, was convinced that
the nature of the self was forever unresearchable empirically, Damasio
finds places where scientific progress is possible; whereas Kant
thought of the self in terms of a highly mysterious "transcendental
unity of apperception", Damasio gives it a reassuringly concrete base
in terms of neural representation of the body: the skin, muscles,
joints, viscera, and so forth. Like other brain representations, the
nature of body-representation is researchable with the combined
techniques of neuropsychology, neurobiology, and neural network
modeling. And if Damasio is right, then the neural mechanisms of
self-representation are researchable too.
The three broadly neuroscientific approaches -- that of Crick, Llinas,
and Damasio -- I see as complementary strategies for addressing
different but overlapping segments of a large and puzzling problem.
Each has particular strengths viz-a-viz some aspect of the problem, and
each presents questions and challenges for the other -- the very
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Figure Captions
Figure 1
Schematic illustration of levels of organization in the nervous system.
The spatial scales at which anatomical organization can be identified
varies over many orders of magnitude. Icon to the left depicts the
"neuron man", showing the brain, spinal cord, and peripheral nerves.
Icons to the right represent structures at distinct levels: (top) a
subset of visual areas in visual cortex; (middle) a network model
proposing how ganglion cells could be connected to "simple" cells in
visual cortex; and (bottom) a chemical synapse. (From Churchland and
Sejnowski 1992)
Figure 2
Schematic diagram of the circuits between the thalamus and the cerebral
cortex proposed to serve temporal binding. (A) Diagram of two different
types of circuit connecting thalamus and cortex. On the left, specific
sensory nuclei or motor nuclei of the thalamus project to Layer IV of
cortex, producing cortical oscillation by direct activation and
feed-forward inhibition via 40Hz inhibitory interneurons. Collaterals
of these projections produce thalamic feedback via the reticular
nucleus (a kind of rind covering the thalamus). The return pathway
projects back to specific and reticular nuclei via Layer VI cells. On
the right, the second loop shows nonspecific intralaminar nuclei
projecting to Layer I of cortex, and giving collaterals to the
reticular nucleus. Layer V cells return oscillation to the reticular
and the intralaminar nuclei, establishing a second resonant loop. The
conjunction of the specific and nonspecific loops is proposed to
generate temporal binding. Connectivity between the loops is seen
chiefly in Layer V. (B) Schematic diagram showing the intralaminar
nucleus as a circular neuronal mass (stipple shading). Other parts of
the thalamus are shown in hatched shading. The intralaminar nucleus
projects widely across the cortex, to Layer I. (From Llinas and Ribary
1993)
*. This paper is based
on my Presidential Address to the American Philosophical Association,
Pacific Division, March, 1993, published in Proceedings and
Adresses of the APA (1994). I am indebted to many people for
discussion and criticism: Francis Crick, Rodolfo Llinas, Antonio
Damasio, Hanna Damasio, Joe Bogen, Ramachandran, Robert Van Gulick,
Owen Flanagan, Dan Lloyd, and especially Paul Churchland.
1. See our discussion in
The Computational Brain, Churchland and Sejnowski
(1992).
2.
For concordant opinions, see also Francis Crick (1994); Paul Churchland
(1989) Daniel Dennett (1991); Owen Flanagan (1992); William G. Lycan
(1987); John Searle (1993).
3. As P. S. Churchland and T. J.
Sejnowski argued in (1989)
4.
For an outstanding discussion of reductionism that includes many of the
complexities I am not worrying too much about here, see Schaffner
(1993).
5.
P. S. Churchland (1986), Neurophilosophy.
6. See Paul Churchland's
characterization and defense of this view in (1981), reprinted in P. M.
Churchland 1989.
7. See P. S. Churchland,
Neurophilosophy (1986)
8. Jerry Fodor (1990).
9. John Searle (1992)
10. Op .cit.
11.
See Churchland and Sejnowski (1992); Paul M. Churchland (1989)
12. Or, as we have preferred
but decided not to say "what makes revisionary materialism
revisionary" (P. S. Churchland 1987). See also P. M.
Churchland (1993). For a related but somewhat different picture, see
Bickle (1992).
13.
Ibid. See also P. M. Churchland and P. S. Churchland (1990).
14.
For example, Colin McGinn (1990).
15.
See for example, Feyerabend (1981).
16. See also Owen Flanagan
(forthcoming).
17.
In the following discussion, the ideas are mostly owed to Paul
Churchland (1994) . For his discussion, see "Betty Crocker's Theory of
the Mind: A Review of John Searle's The Rediscovery of the
Mind. The London Review of Books .
18.
Paul Churchland made this discovery in our kitchen about eight years
ago. It seemed to us a bang-up case of someone's not really
understanding the scientific explanation. Instead of thinking the
thermodynamic theory through, Betty Crocker just clumsily grafts it
onto on old conception as though the old conception needed no
modification. Someone who thought electricity was caused by
moving electrons would tell a comparable Betty Crocker story: "voltage
forces the electrons to move through the wire, and as they do so, they
cause static electricity to build up, and a sparks then jump from
electron to electron, on down the wire."
19.
See P. M. Churchland (1993).
20. D. C. Dennett,
Consciousness Explained (1992).
21. For a criticism of Dennett
on filling in, See P. S. Churchland and Ramachandran (1993).
22. Paul Churchland ,The
Engine of Reason; The Seat of the Soul (1995).
23. See especially Owen Flanagan
(1992) and Ned Block (1993).
24. Ibid. Also John Searle The
Rediscovery of the Mind (1992).
25. See for example, Singh
(1992); Mozer (1992); Sutton, Mamelak and Hobson (1992).
26. Beer and Gallagher (1992);
Beer (1995 a), Beer (1995 b).
27. See our discussion of
various nets in Churchland and Sejnowski (1992).
28. Elman (1991). See also Mozer
and Bachrach (1991; Pollack (1991); Giles et al. (1992), Jain (1992);
Pinkas (1992); Sumida and Dyer (1992).
29. Lange (1992).
30. E.g. Viola, Lisberger and
Sejnowski (1992); Berthier, Singh, Barto and Houk (1992).
31. Verghese and Pelli (1992)
conclude from their studies that the capacity of the attentional
mechanism is limited to about 44 15 bits per glimpse. They calculated
the pre-attentive capacity to be much greater -- about 2106 bits. Their
data on the attentional capacity is consistent with paying attention to
(and being aware of ) more than one thing at a time.
32.
Rick Grush has a brilliant
exploration of the idea that brains emulate aspects of the world,
including the body, in his PhD. dissertation, Emulation and
Cognition. For an approach to the problem using recurrent
nets, see also Dan Lloyd, "Consciousness: A Connectionist Manifesto"
(unpublished).
33.
See Owen Flanagan's convincing and more detailed discussion of
McGinn's naysaying (Flanagan 1992).
34.
See especially H. Damasio and A. R. Damasio (1990); H. Damasio (1991);
A. R. Damasio (forthcoming); Farah (1994).
35.One possibility explored by
Penrose (1994) is that consciousness is a quantum mechanical
phenomenon, produced in organelle structures called microtubules. For a
criticism of that hypothesis, see Grush and Churchland (1995).
36.
This point is made in Crick and Koch (1990) and in Crick (1994).
37. 'Wakeness' is a bit of a
neologism. I prefer not to use 'wakefulness' inasmuch as it connotes
some difficulty in sleeping, or being easily awoken, as in "the baby
was wakeful when he had a rash." I prefer it also to the phrase 'being
awake' which is both rather cumbersome and fails to preserve parallism
with 'dreaming', 'sleeping'. Clealry one cannot use 'waking' as
synonymous with 'being awake' . It is a quirk of English that methought
to remedy by 'wakeness'.
38.
See also my discussion in P. S. Churchland (1988)
39.
See Llinas and Pare (1991)
III Tracking Down The Neural Mechanisms of Consciousness
A. Finding a Route InIV CONCLUDING REMARKS
Viewing matters from the mystery side of a phenomenon,
solutions can seem impossible, and perhaps even unwanted. On the
understanding side, however, solutions seem almost obvious and hard to
miss. Why, one might wonder, did it take so long to figure out what the
elements are? How could someone as brilliant as Aristotle miss the
plausibility in Aristarchus' idea that the Earth was a sphere moving
around the sun? The deeper truths are all too easy to miss of course,
just as it is all too easy for us to miss whatever it is that explains
why animals sleep and dream, and what autism is. The problems for
neuroscience and experimental psychology are hard, but as we inch our
way along and as new techniques increase noninvasive access to global
brain processes in humans, intuitions change. What seems obvious to us
was hot and surprising news only a generation earlier; what seems
confounding to our imagination is routinely embraceable by the new
cohort of graduate students. Who can tell with certainty whether or not
all our questions about consciousness can eventually be answered? In
the meantime, it is rewarding see progress -- to see some questions
shift status from Mysteries We Can Only Contemplate in Awe, to Tough
Problems We Are Beginning to Crack.References
Beer, R. D. (1995a) A dynamical systems perspective on
agent-environment interaction. Artificial
Intelligence. 72:173-215.