Neural Net Processing: A Key Factor in the Evolution of Language
© Stephen Plowright
MacKaos Consulting.
ABSTRACT
This paper is an attempt to examine the implications of recent research
in neurocomputing for the question of the evolution of language. An overview
of the existing research is given. A model for the evolution of language
is constructed which postulates peripatric speciation giving rise to a chance
enhancement of vocal articulation, followed by a rapid development of a
generative language with a corresponding adaptation for speech. Language
may have evolved very rapidly driving the selection for the features of
modern anatomy. Also, the development of language was unique to this species
and the major factor in its success.
INTRODUCTION
The question of the evolution of language is necessarily speculative, and
has indeed been a matter of considerable controversy since it was first
debated. Research has typically concentrated on drawing inferences from
the evidence of artefacts and biology of early humans, and the capabilities
and biology of modern humans. Some interpretations have lacked a robust
logical foundation, as has been pointed out by Davidson and Noble (1989,
1993) and Lieberman et al (1992).
Arguments which present features of language acquisition in modern children
as evidence for similar stages in the evolution of language in the species
as a whole are clearly fallacious. A modern child with a known aptitude
for language acquisition, in a language intensive cultural context, is in
no way comparable to an evolving species with no linguistic context.
Also cited as fallacious, are arguments which present the existence of isolated
anatomical features as evidence of language. It is not unusual for species
to evolve structures for a particular purpose, which are later adapted for
other functions. Falk (1989), in reply to Davidson and Noble (1989), states
with complete conviction that "human language depends on a lateralised
brain". This statement, seen by some as an inviolable assumption, does
not entirely accord with the evidence of neurophysiology. It is known that,
following early left hemisphere damage, the right hemisphere is quite capable
of learning language (Feldman, 1992). Also, examples are not uncommon, up
to 5%, of normal individuals who exhibit language processing in the right
hemisphere, or even distributed bilaterally (Cook, 1986; Corballis, 1991).
Lateralisation, in itself, is neither evidence of, nor a prerequisite for
the production of language.
The sophistication of artefacts or human achievements can, as cited by Davidson
& Noble (1989), offer evidence for the latest date by which language
must have been in use. They cannot offer much to the evidence of the earliest
date of language use.
Studies with Chimpanzees, it could be argued, reveal more about the likely
limitations of early Hominid communication than they do about the linguistic
abilities of our early ancestors.
This paper will attempt to bring together the results of recent research
in various fields, notably properties of adaptive neural net information
processing, to arrive at what is bound to be an initially unpopular view
of human and linguistic evolution.
EVIDENCE AND ISSUES
The Fossil Record
The interpretation of fossil evidence is another area of considerable controversy.
The following is a superficial overview of the facts which find general
agreement at present.
The dominant trend in human evolution has been one of increasing adaptability
and brain size. While the various Australopithecines, and probably early
Homo, occupied different ecological niches, later Homo was
increasingly able to occupy all of these niches. The disadvantage of the
less specialised morphology in competition with more specialised species
was countered with increased brain power allowing more effective adaptive
strategies.
Emerging as sole survivor at some time after 2 myr in Africa and Asia (Swisher
et al, 1994) were variants of Homo erectus . This species
evolved slowly for 1.5 million years, it demonstrated basic improvements
in stone tools and probably used fire.
After 1/2 myr variant Homo forms started to emerge, culminating in
Neanderthal and archaic Homo sapiens types by 100,000 B.P. The number
of different forms and their relationships to each other, or to modern humans,
are subjects of debate at present.
At around 100,000 B.P. anatomically modern humans emerged. The earliest
examples were found at Qafzeh, in Israel, some dated at over 90,000 B.P.
This species, Homo sapiens in its anatomically modern form, had replaced
all other Homo types by 35,000 B.P.
The details of the fossil record are controversial, but the feature which
is pertinent to this paper is the rapidity and nature of the morphological
changes of the final transition to anatomically modern humans.
Neural Nets
Modern computers have made it possible to simulate some of the processes
observed in the brain. In particular, recent work done with adaptive neural
nets has produced results which shed much light on the observed features
of brain development.
Bearing in mind that any simulation will represent a very small number of
neural components compared to real brain systems, this research is not expected
to reproduce the complexities of human or animal behaviour. What these simulations
do reveal is the way in which the brain constructs complex computational
systems in response to information from its environment.
In the simplest case, a neural net is an array of elements in which each
element has inputs from other elements, see Figure 1. Each element or neuron
sums the inputs (Xi) and produces a signal on its outputs (Zi) if the sum
of the inputs is greater than a threshold value. Each of the neuronÕs
inputs is weighted according to its input history. There are a number of
ways the weight vectors (Wi) can be altered to produce an adaptive net (Hecht-Nielsen,
1990; Hertz et al, 1990).
Figure 1. Neurons with weight vectors Wi = (Wi1, Wi2, .... Win).
Researchers have constructed nets to learn many tasks. The common finding
is that, although these nets are not explicitly programmed with information
or learning strategies, they will categorise signals according to features
of the input. Pattern or feature recognition arises as a result of the self
organising nature of these nets. This kind of processing does indeed seem
to be the dominant type of processing in biological neural systems.
The advantage of neural processing is that information processing occurs
as a wave of activity across a large array of elements allowing sophisticated
operations to happen in a small number of steps, typically under 100. As
the wave of activation propagates through the net, features of the input
trigger a pattern of firing in elements of the next layer, which in turn
respond to the pattern in a unique way. In this way, a large number of features
are grouped into categories, which in turn converge to be placed into a
final category or a unique solution. If a unique solution is not found,
the most appropriate category is found. This is often termed a 'parallel
distributive process', and the large data structures arising from the categorisation
process are known as "schemas". These schemas allow the brain
to recognise a wide variety of new information by interpreting through interpolation
(Rumelhart, 1989).
The remarkable property of these adaptive nets is that, without being programmed
with any knowledge or strategy, and by virtue of their structure alone,
they are able to learn quickly to organise information into categories,
effectively creating topological feature maps of their information environment
(Hertz et al, 1990; Allinson & Johnson, 1989).
The Brain
Much has been made of the importance of lateral asymmetry in the brain.
It should be noted that the brain shows more bilateral symmetry than any
other major internal organ except the kidneys (Cook, 1986). Although the
left hemisphere may be subtly better adapted for language, given the extreme
plasticity of the developing brain, and the ability of the right hemisphere
to acquire language after early damage to the left, the observed difference
between hemispheres is more likely to be one of acquired function, not one
of gross structure. This is also supported by the findings of Feldman et
al (1992) that both left and right unilateral brain damage will cause
initial delays in language development followed by normal rates of progress
with no significant differences between the two groups.
Furthermore, proof of the existence of gross structural features from Hominid
endocasts contributes nothing to the evidence of Hominid linguistic ability.
These features may have been adapted for other functions before the development
of language.
As Gerald Edelman points out in Neural Darwinism (1987:143):
"Inasmuch as the functions of a given component of the brain are not
necessarily locally defined, such evolutionary deductions from comparative
neuroanatomy . . . must be based mainly on morphological and structural
criteria; that is, homology can be inferred only for anatomic structures
and not for function."
The advantage of lateralisation is not that it allows the acquisition of
language, it is that various functions can be organised in the most efficient
way. The left hemisphere would not have been wasted in pre-language Homo,
it would have been used to organise other features of the information environment
such as animal behaviour and prediction of predator/prey movements, hunting
strategies, tool making, and social interaction.
A possible mechanism for lateralisation is a differential growth schedule
for different areas of the brain. The language areas are maturing at the
time of language acquisition, while the contralateral areas mature a little
later when spatial skills are learned (Corballis, 1991). Such a process
would have survival value as it would effectively lengthen the period of
maximum plasticity allowing more cognitive skills to be acquired.
If the brain is to be used as evidence, it must be in terms of its general
information processing properties. Recent research in neurophysiology and
neurocomputing has provided convergent models of neural processing which
point toward categorisation and feature mapping as the key to understanding
the power and versatility of the brain. Studies with pigeons and pre-language
human infants show a remarkable ability to categorise and generalise without
language and without tuition (Edelman, 1987).
The Supralaryngeal Vocal Tract (SVT)
The most reasoned and convincing research on the physiology of speech production
in the evolutionary context is that of Lieberman et al (1992). Their
work throws much doubt on the likelihood of language in pre-modern and Neandertal
humans. Although they find that SVTs of non-modern human type may have been
able to produce many of the sounds of speech, they were not well adapted
for that purpose.
It is important to consider that rapid articulate speech requires fine motor
control not available to other primates. It seems unlikely that such control
would have evolved without noticeable adaptation of the SVT for speech.
Figure 2. The anatomy of speech production (after Lieberman et al,
1992).
Duchin (1990) compares metrics of the oral cavities of Pan troglodytes,
H. erectus, H. sapiens neanderthalensis, and modern humans concluding
that H. erectus, and H. sapiens neanderthalensis, were capable
of articulate speech. Leiberman et al (1992), however, point out
the importance of the lowered larynx, unique to modern anatomy, in the production
of rapidly changing formant frequencies which characterise human speech
and which make rapid and accurate encoding and decoding possible. Note the
length of the pharynx is similar to the length of the oral cavity, see Figure
2. Such a configuration was not possible in other species.
Language
While many species are known to communicate, only humans are known to be
capable of language. The difference is in the generative nature of language.
Communication can relate facts about the immediate environment, or the state
of an individual, but only with language can we relate things which are
completely new.
Only a language speaker could ask "Tell me something that never happens"
and only a language speaker could reply to such a request with an original
and meaningful response, eg "A dog flying". A four year old human
would have no trouble responding appropriately, we are yet to see any other
species master such a task. This is not the same as simple lying, in which
an incorrect response is given for some chance of gain. Simple lying is
not generative as the context is set by the situation or by the querant.
All languages have the same basic hierarchical order: a perceived number
of discrete units of sound, or phonemes, which are a subset of the possible
human sounds. Clusters of phonemes with corresponding meanings, these are
words and morphemes. Concatenation of words to form sentences, no language
is restricted to single word discourse. Rules of sentence structure, no
language concatenates in a random way (Kess, 1990).
This hierarchical structure is not surprising in the light of neural processing,
it is exactly what would be expected. One need not postulate a special type
of circuitry, the order seen in language is a natural product of the way
neural nets process information. Lakoff (1987) proposes that language and
thought are fundamentally structured by spatial metaphor. Lakoff sees spatial
metaphorical mapping and transformations as the general way humans understand
abstract concepts (Jubak, 1992). Perhaps the difference between the two
hemispheres is not as great as first thought. While the nature of verbal
and spatial information differ in form and modality, they are both processed
in much the same manner.
The prerequisites for language are, firstly, an efficient channel. This
requires an organ which is capable of a sufficient range and speed of articulation,
and is easily and accurately sensed by the receiver.
Secondly, sufficient processing power to recognise and categorise a large
number of linguistic units and clusters of units, along with the rules of
grammar.
Thirdly, sufficient short term memory to use as a buffer to hold a meaningful
amount, a sentence, of the received message for processing. If the buffer
is too small, or the articulation too slow, grammatical structure can not
evolve.
A Model for Human Evolution
Middle Pleistocene Homo had a fairly large brain and was able to
adapt to a variety of environments. Although they made tools and spread
across large areas of the globe, there is no evidence of any sea crossings,
nor other co-operative ventures of this type. Also, biological adaptation
to verbal language cannot be demonstrated.
There probably was some form of gestural and vocal communication but it
is unlikely to have gone beyond pointing, motioning and imitation, like
the hunting signs used by some hunter-gatherers today. Most of the gesturing
behaviour would have been directed toward food gathering and survival. It
is unlikely that most infants would have been exposed to a sufficient number
of discrete gestures often enough, or rapidly enough, to learn it as a generative
language. Also, if gesture had become generative, it would have conferred
such a survival advantage that there would have been rapid selection for
adaptations to gestural language. Verbal communication would have conferred
more disadvantages than advantages over gesture and would never have become
dominant. Although deaf people can acquire signing as a first language,
it must be remembered that these sign languages are derived from verbal
languages, there is no known example of a fully generative native sign language.
At some time probably around 100,000 B.P., probably in Africa (Cavalli-Sforza,
1989; Stringer, 1984), a group from one of the varieties of Homo
became isolated. Inbreeding in a species already undergoing change produced
some features which would have reduced its probability of survival, except
that one feature conferred an advantage which more than compensated. Such
peripatric speciation can result from a rapid reorganisation of the gene
pool when a population passes through a bottleneck in population size, and
is usually accompanied by rapid and drastic morphological changes (Mayr,
1981).
Having gained by chance an enhanced ability and propensity for vocalisation,
their infants were exposed to a large range of sounds which they would eventually
imitate. The natural ability of the developing brain to categorise and recognise
features would result in the perception of these sounds as discrete units.
This is what one would expect from an adaptive neural net.
Having developed a group phonology, sounds and clusters of sounds would
become arbitrarily associated with meanings as individuals engaged in basic
gestural communication. This enhanced communication would have conferred
survival benefits and encouraged social interaction. It is also likely that
the more expressive individuals were more successful reproducers, the "smooth
talker" effect.
At this stage the proto-language could be seen as an information virus inhabiting,
in an opportunistic way, those parts of the brain close to the sites involved
in hearing and articulation. The synergistic relationship between language,
biology, and society would have ensured a rapid evolution of each to the
benefit of the others. Language optimised human biology for speech, while
the existing organisation of the brain optimised language itself. Social
encouragement and survival pressures reinforced both language and the anatomy
of articulation. This model implies that language and human biology evolved
in step and very rapidly.
To appreciate the possible rapidity of the structuring and evolution of
the proto-language into a simple but fully grammatical language, consider
that an unstructured pidgin, used by diverse linguistic groups to communicate,
can evolve into a creole with a fully developed and original grammar within
two generations (Kess, 1990). This structure arises from the way in which
the brain organises linguistic information. It is not inconceivable that
the evolution of a simple but generative language, along with the basic
features of modern anatomy, occurred within, say, one hundred generations
of isolation. Such an event would appear punctuational on the Pleistocene
time scale.
Language would have evolved in a rapid sequence of revolutions. A chance
modification of anatomy gave rise to a phonology. As soon as concatenations
of sounds became long enough and rapid enough they became percieved as units
and started to be associated with meanings to become words. The number of
words increased gradually, perhaps quite rapidly once the advantages were
understood, until the number of words and the speed of concatenation were
sufficient to produce grammar. The transitions from phonemes to words, and
from words to sentences, would each have occurred within two generations,
while the periods in between may have been several generations. The transitions
would have occured as a result of the general ability of the brain to recognise
patterns and categorise information. The periods between transitions would
have been characterised by steady, perhaps conscious, improvement in speed,
accuracy, and number of spoken units, along with first acoustic then semantic
feature mapping and categorisation laying the foundation for transitions
to higher levels of organisation.
On the face of it, anatomically modern humans were less robust than their
ancestors or competitors, with fragile crania, a much greater risk of choking
due to the low position of the larynx, difficulties giving birth to the
large cranium, and problems with compacted wisdom teeth due to shortening
of the jaw. There must have been a powerful advantage to allow these relatively
weak creatures to survive while their more robust competitors failed. The
sudden appearance of anatomical adaptations most of which could only be
useful for speech, and which were a disadvantage in many other ways, argues
powerfully for the development of generative spoken language at this time.
SUMMARY
Language is a very complex phenomenon and it is understandable to assume
that it evolved over a very long period. Such an assumption is most often
made, but is not necessarily true. This paper views language as a product
of the emergent properties of very large adaptive neural nets. It was bound
to evolve suddenly and rapidly as soon as the chance deviation of the vocal
tract allowed for sufficient speed and clarity of articulation.
Language evolved as a social phenomenon, increasing the fitness of the individual
only within the social context, and increasing the fitness of the society
as a whole. Language conferred such a social advantage that it could evolve
at the expense of the fitness of the isolated individual.
The structure of language reflects the ordering principles of the brain.
It is not necessary to postulate a radical new mode or process of thought,
the ATO (Klein, 1989), or GAD (Corballis, 1991). Although language represents
a great enhancement of thought, it is processed by pre-existing neural circuitry
in a manner which is not fundamentally different to the type of spatial
and temporal processing which would have been used in pre-language thought.
This paper proposes that anatomically modern humans emerged suddenly with
a fully generative language after a relatively short period of isolation
and rapid evolution. Also that it is unlikely that any other species of
Homo had evolved any form of generative communication system.
Supporting evidence is likely to come from the analysis of genetic and linguistic
trees.
ACKNOWLEDGMENTS
Dr Colin Groves, for kind advice and encouragement.
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