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Outline of a new approach to the nature of mind

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  • University of Crete; Heraclion-Hellas

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I propose a new approach to the constitutive problem of psychology 'what is mind?' The first section introduces modifications of the received scope, methodology, and evaluation criteria of unified theories of cognition in accordance with the requirements of evolutionary compatibility and of a mature science. The second section outlines the proposed theory. Its first part provides empirically verifiable conditions delineating the class of meaningful neural formations and modifies accordingly the traditional conceptions of meaning, concept and thinking. This analysis is part of a theory of communication in terms of inter-level systems of primitives that proposes the communication-understanding principle as a psychological invariance. It unifies a substantial amount of research by systematizing the notions of meaning, thinking, concept, belief, communication, and understanding and leads to a minimum vocabulary for this core system of mental phenomena. Its second part argues that written human language is the key characteristic of the artificially natural human mind. Overall, the theory both supports Darwin's continuity hypothesis and proposes that the mental gap is within our own species.
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Outline of a new approach to the nature of mind
Petros A. M. Gelepithis*
Oxford University Research Archive
http://ora.ouls.ox.ac.uk/objects/uuid:0c28b7df-d3dc-4786-95fd-e6c8886f4341
* Presently, Graduate programme in the Brain & Mind Sciences, Faculty of Medicine, University of Crete.
Written while at the Faculty of Philosophy, University of Oxford.
Current contact: Petros 2004@phs.uoa.gr and Petros2101@gmail.com.
Abstract
I propose a new approach to the constitutive problem of psychology ‘what is
mind?’ The first section introduces modifications of the received scope,
methodology, and evaluation criteria of unified theories of cognition in accordance
with the requirements of evolutionary compatibility and of a mature science. The
second section outlines the proposed theory. Its first part provides empirically
verifiable conditions delineating the class of meaningful neural formations and
modifies accordingly the traditional conceptions of meaning, concept and thinking.
This analysis is part of a theory of communication in terms of inter-level systems of
primitives that proposes the communication-understanding principle as a
psychological invariance. It unifies a substantial amount of research by systematizing
the notions of meaning, thinking, concept, belief, communication, and understanding
and leads to a minimum vocabulary for this core system of mental phenomena. Its
second part argues that written human language is the key characteristic of the
artificially natural human mind. Overall, the theory both supports Darwin’s continuity
hypothesis and proposes that the mental gap is within our own species.
Keywords: Cognitive science, communication, meaning, nature of mind,
psychology, representation, thinking, understanding, written human language.
© 2009 by Petros A. M. Gelepithis
2
1. Foundational issues
Mind is the constitutive problem of Psychology. Psychology’s disunity is
contrastively interpreted. For some it is inherent (e.g., Koch 1981) for others it is sign
of a “would-be-science” in need of unification to achieve the status of a mature
science (e.g., Staats 1999). I assume that full unification is not necessarily impossible.
At this point the following caveat should be made. If practically possible, the working
hypothesis objective is both far away in the future and not achievable along the lines
of most current research programs. Therefore, my main objective in this article is to
briefly argue for the need of the cognitive science community to take a radically new
approach to the study of mind and subsequently illustrate it by systematizing the
following three core research areas of the nature and workings of mind: 'thinking',
'representation' and 'communication'. That is to squarely tackle the foundations of
cognitive science.
The first explicit statement of the need to discuss the foundations of psychology
was Staats (1981, p. 253): “it is important to consider the nature of unified theory and
the methods involved in unified theory construction. These are topics our science has
thus far not addressed.” To date the most comprehensive and theoretically coherent
description of the current foundations of cognitive science is contained in Newell’s
(1990) Unified Theories of Cognition.1 It constitutes the undisputed basis of the still
dominant computational paradigm and is squarely based on Turing’s (1936, 1950)
work and the physical symbol systems hypothesis (Newell & Simon 1976). Recent,
more or less, promising alternatives are still much less developed in terms of their
foundational descriptions of the nature of mind.2
The rest of this section, except the last paragraph, proposes modifications with
respect to the received scope, methodology, and evaluation criteria of a unified theory
of mind (UTM) in accordance with the requirements of evolutionary compatibility
and of a mature science.
Newell (1990 p. 16) was fully aware of the enormity of the task. “Clearly, I can’t
mean a theory of all that! A unified theory of cognition is just a fantasy.”
Consequently, he proposed the unification of a subset of behaviour along the lines of
the following priority list: Problem solving, decision-making, routine action.
Memory, learning, skill. Perception, motor behavior. Language. Motivation, emotion.
Imagining, dreaming, daydreaming, …. He was crystal clear. A unified theory “is a
cognitive theory that gets significantly further down the list cumulatively than we
have ever done before. If someone keeps asking how the unified theory explains
dreaming or how it describes personality, I will simply point back to this list. It is
right to ask, but wrong to insist.” (ibid. p. 15). Although, Newell was right on the
cumulative aspect of a unified theory he was mistaken about his priority list. A theory
of mind that does not address a minimum core of mental phenomena like meaning,
thinking, emotion, and communication should not count as a UTM. As a result,
Newell’s foundational vocabulary cannot account for phenomena like language and
consciousness.
Newell’s methodology is probably the most important characteristic of his work
and it is widely followed. He argued for unified theories of cognition to be
formulated as architectures.3 The choice of architecture as the theoretical tool for
developing a unified theory is conceived to be particularly important because it
provides the interface between structure and content (Newell 1990, p. 82) or the
abstraction that gets at the essence of mind (Anderson 2007a, p. 7). This position can
be based on the familiar philosophical distinction of the personal sub-personal level
3
(Dennett 1969) and the associated discussions of levels of descriptions and of the
relation between psychology and physiology (e.g., Anderson 1987; Broadbent 1985;
Changeux & Dehaene 1989; Rumelhart and McClelland 1985).
Nevertheless, such an interface may usefully be employed for AI systems only.
As Newell (1990, p. 86), from a slightly different perspective, put it: “[in] any
analysis of the architectures of natural systems, the concepts available from computer
architectures are useful, although they hardly do the whole job.” Currently, cognitive
architectures are inadequate as tools for a UTM because they are hardly comparable
to either the human nervous system or the individual human architecture at large.
Recent attempts to utilise data from imaging research (e.g., Anderson 2007b;
Anderson et. al. 2004) are highly commendable. Nevertheless, they do not change the
fact of the inadequacy of cognitive architectures as the key tool for unified theories
construction for as long as their specifications fall short of accommodating design
constraints like evolutionary compatibility and the full temporal scale of human
action (in contrast to focusing on the cognitive and rational bands).
With respect to abstraction, neither cognitive architectures nor, more generally,
mathematical modelling is adequate for the current level of development of cognitive
science. It is true that precision, completeness, and self-consistency are the key
advantages of computational modelling and indeed, as Abbott (2008) remarks, of
equations. Nonetheless, a language-based system of time-dependent definitions can
have the same characteristics, while at the same time being enhanced by the
vagueness of human language. As Werner Heisenberg (1959, p. 188) wrote:
"one of the most important features of the development and the analysis of
modern physics is the experience that the concepts of natural language,
vaguely defined as they are, seem to be more stable in the expansion of
knowledge than the precise terms of scientific language, derived as an
idealization from only limited groups of phenomena."
This position should not be seen as being against the use of mathematics or
computational modelling. It is only against their premature use. We first need to sort
out, and most likely expand and extend, our concepts before formalising them. The
human conceptual system is far richer than human language and that in turn is far
richer than our formal systems. We cannot put the cart before the horse.
Seeking a UTM across the full temporal scale of human action demands
interdisciplinarity, and the latter demands in turn field-wide theoretical constructs.
They provide a common reference frame for discussion, facilitate criticism and the
finding of gaps or inconsistencies and minimize potential misunderstandings. We do
not currently have even a partially complete system of such theoretical constructs for
a UTM. The ones proposed in section 2.1 are illustrative of the posits required for
bridging biology and sociology.
Evolutionary compatibility demands the variability of both the space of mental
phenomena and of particular mental phenomena themselves. For instance, written
language was not in the space of mental phenomena of Homo habilis and key
phenomena like thinking have been modified in the course of Homo evolution. In
addition, the rate of human evolutionary change is, in some important respects,
different from that of other animal species. Still, other phenomena like
‘representation’ go back for hundreds of millions of years and therefore have to be
seen in the light of their successive transformations through evolution (cf. Table 3).
Furthermore, transformations of different phenomena influence each other by means
of multiple feedback loops throughout their evolutionary existence. For a UTM such
phenomena include: ‘representation’, ‘thinking’, ‘communication’, and ‘language’
4
(cf. Figure 2). Identification of the multiple, distinct but related senses of such
phenomena is a requisite first step. The explicit use of the time variable in defining
them is a useful reminder of their evolutionary characteristics and a necessary tool in
the gradual transition from our vague conceptual apparatus to a less imprecise theory.
Evaluation criteria –by revealing weaknesses- constitute a significant tool in the
development of a scientific field. Newell’s final list of thirteen evaluation criteria
(constraints in his words) fall into two categories: performance requirements and
construction constraints (Newell 1990, pp. 18-21).
A revised version of those criteria was used by Anderson & Lebiere (2003) as
the Newell test for the evaluation of cognitive theories.4 Although there was
agreement of both the target article authors and commentators that the N-test is not
complete (e.g., Agassi 2003, Anderson & Lebiere 2003, Gelepithis 2003, Sirois 2003,
Taatgen 2003), and some argued it is not fully appropriate (e.g., Young’s (2003)
proposal to substitute compliancy for universality, Wang et al.’s (2003) questioning
of its theoretical attainability), no-one made the point that the N-test is actually more
inadequate than the original list as a basis for evaluating a unified ToM.
The argument is simple. Newell’s original list includes two criteria that are
absent from the proposed Newell test and which Newell himself considered
necessary, namely, “operate autonomously, but within a social community” and “be
constructible by an embryological growth process.” (e.g., Newell 1990, p. 20). In
addition, the first criterion on the original list does address a major human capability
while reflecting a performance requirement (ibid. p. 20). In contrast the first criterion
on the proposed N-test (computational universality) provides straightforward grading
but leads to contradictions (Young 2003).5 The inadequacy of the original list itself is
due to the omission of field requirements like invariant laws and minimum
vocabulary. Simon (1990) has elevated the discovery of invariant laws to the status of
the fundamental goal of science and has suggested two laws of qualitative structure
and four quantitative findings as invariants. Surprisingly, although Newell (1990)
strongly believed that the computer hierarchy is an invariant law, he did not included
invariant laws as a criterion of a unified theory of mind. I fully agree with Simon. In
section 2.1.2.3 I propose the communication understanding principle (CUP) as a
psychological invariance.
A minimum vocabulary is a clear sign of the maturity of a science (Russell
1948). Even if not completely attainable, their quest is useful in accordance with the
principle of parsimony. Cognitive science needs a minimum vocabulary to serve as
its descriptive base and substantially decrease the bewildering multiplicity of terms
used. In section 2.3, I propose a set of words that seem to constitute a minimum
vocabulary for a small but significant part of cognitive science. It is a consequence of
the theory outlined in section 2. Concluding on the evaluation criteria of a UTM, I
propose that invariant laws and minimum vocabularies should be an integral part of
such a system.
The next section proposes an account of mind that is both in accordance with the
constraints identified and breaks away with the long tradition of the intrinsic
individuality of mental phenomena traced back to James’s conception of Psychology
as the study of “finite individual minds”. In addition, although there are many
specific, contemporary research programs dealing with ‘thinking’, ‘representation’,
and ‘communication’, there was none that had attempted to synthesize all these areas
as well as a considerable part of the disparate underlying research and propose a,
much needed, minimum vocabulary for this cluster of core mental phenomena. This is
the objective that next section approximates. Specifically, in the introduction to
5
section 2 I set out the central working hypothesis of the proposed approach and
introduce the key relations among the foundational notions of my theory. Section 2.1
presents the key features of the exclusively natural mind, and section 2.2 argues for
the key characteristics of the artificially natural mind. In evolutionary terms the latter
stage is only a fraction of the former. Accordingly, the bulk of the proposed theory is
in 2.1 where thinking, meaning, communication and understanding are addressed.
This cluster of ever evolving abilities and structures accounts for the continuity
between humans and non-human animals. Section 2.2 tackles the issue of
representation and argues that the ability to create external representations was the
necessary breakthrough for the eventual appearance of written human language and
the consequent dawn of the era of the artificially natural mind. The uniqueness of
modern Homo sapiens is due to this artificiality. Our uniqueness is of our own
species construction. Section 2.3 summarizes the key points.
2. The Evolving Nature of Mind
Within the scientific community, it is generally agreed that ‘mind’ is not
immaterial and that it is embodied and situated. In essence when one talks of ‘mind’
it is taken to mean ‘the mind of an individual’. Still, it is not in accordance with the
widely accepted perspective, in the biological community, of both species and of their
constitutive organisms as individuals. The following working hypothesis incorporates
this view:
‘The mind of individual E ‘individual E of noémon species E’. 6
I make use of the adjective noémon (plural: noémona) in order to avoid misleading
connotations by the use of ‘mental’ or ‘cognitive’. It is derived from noûs, a Hellenic
language noun and it is used in this article in the technical sense introduced by the
following definition.
Definition-1: Noémon species E is a species whose individuals:
a) Possess one or more sensory systems.
b) Possess one or more motor systems.
c) Possess the ability of thinking.
d) Are able to communicate with other individuals of their own species.
e) Possess the ability of creating representations.
My reason for this radical departure from the received wisdom is simple. Within
a naturalistic Weltanschauung, ‘species’ is the essential prerequisite notion for both
biological and social sciences and a theory of mind requires the integration of both
perspectives. This requisite integration, coupled with the inadequacies of the
computational paradigm pointed out in section one, necessitates a re-description of
mind. Figure 1 depicts the key relations among the foundational notions of such a
theory. This nexus is fleshed out in the subsequent sections.
6
Figure 1. Relations among key capabilities, structures, individuals and their
environment. Bold face arrows stand for ‘part of’; regular arrows for ‘defined in
terms of’.
A first look at Figure 1 gives the impression that the sought theory of noémona
species (TonE) is purely cognitive and hence inappropriate for the task. This is not the
case. Although the terms ‘thinking’, ‘understanding’, ‘meaning’ and
‘communication’ are associated with a cognitive (i.e., information processing)
approach, the theory redefines them (sections 2.1 & 2.2) in a way that makes the
perceptual, affective, cognitive, motivational, and action aspects of mind inseparable.
To be noted in particular that the sensory and motor systems posited in definition-1
are literally foundational in the sense that all animals possessed bodies before they
possessed nervous systems.
Equally important is the time parameter characterising all key elements of the
theory that necessitates consideration of the complex developmental aspects of the
individual. All aspects of an individual (including its unconscious) are inseparable.
The usual methodological strategy of divide and conquer is fundamentally wrong. We
need to consider all aspects of the individual however crudely at first and refine
subsequently. Refinement is necessary in order to understand nearly any phenomenon
deeply. But such division of labour should be constrained by both the inseparability
constraint and general overall principles. Naturally, the latter may change when
adequate new evidence accumulates. But such a change will reflect deeper
understanding rather than patchy additions to the results of a biased strategy. Apart
from specific arguments and proposals, an important objective of the proposed theory
is to illustrate the potential of this approach.
Finally, I want to make explicit the following two working hypotheses. First, I
adopt the mind-brain identity (MBI) hypothesis.7 Second, I will use extensively a
special case of the evolutionary compatibility constraint introduced in section one,
namely, the range of problems a ‘mental’ phenomenon may refer to depends on the
particular evolutionary period and the taxon that one is considering. This rather
obvious point has important consequences that are usually overlooked.
2.1. The era of the exclusively natural mind
7
Unobjectionably, thinking and communication constitute significant aspects of
the human mind. Moreover, each phenomenon and associated notion encompasses a
cluster of related mental phenomena and notions. The common key structural element
of the two clusters is meaning. This section brings together into a theoretical system
the constituent elements of these two clusters by proposing:
(i) A naturalistic theory of meaning that for the first time delineates the class
of meaningful neural formations (section 2.1.1).
(ii) A hybrid theory of communication that bridges biology and sociology
(section 2.1.2).
The inseparability constraint is satisfied by systems of primitives (section 2.1.2.2)
that bind together all aspects of the individual as member of a society (with or
without a culture).
2.1.1. Thinking
There are three major approaches to the study of ‘thinking’: philosophical (the
oldest), computational (the currently dominant), and biological. Each has contributed
its own requirements for a theory of ‘thinking’. Philosophy rightly assumes,
implicitly or explicitly, that cracking the problem of meaning is the real issue that
needs to be accounted for. Consequently, all theories of thinking (and of concepts)
end up as one or another of a large number of theories of meaning (e.g., Davidson,
2001; Lurtz 2007; Millikan 1998; Newen & Bartels 2007; Peacocke 2001.
Computational approaches are split between those adopting the strong AI view
(thinking is computation) shared by a large number of investigators from Turing
(1950) through Newell and Simon (1976) to Dietrich (2007), and a more or less
computationally oriented view shaped by the need to incorporate the substantial
expansion of research into areas like implicit thinking (e.g., Litman & Reber 2005),
motivated thinking (e.g., Molden & Higgins 2005), emotional effects (e.g., Ashby et
al 1991; Thagard 2002*2006). The latter perspective is probably best exemplified by
Holyoak and Morrison’s (2005a) reader. In remarking on the difficulty of providing
scientific definitions of mental terms, they illustrate that difficulty with their own
preliminary definition of thinking:
“Thinking is the systematic transformation of mental representations of
knowledge to characterize actual or possible states of the world, often in
service of goals.” (Holyoak and Morrison 2005b, p. 2, their emphasis).
As they self-critically remark, their definition introduces “a plethora of terms with
meanings that beg to be unpacked, but which we can only hint.” (ibid). The implicit
requirement is for a theory of thinking within a wider context. Probably, the most
general proposal is mental models (Johnson-Laird 1993; 2005).
Biologically, the most elaborate treatment of the nature and basic mechanisms of
thought and mind as the activity of the brain is still by Hebb (1949, 1968, 1976,
1980a, 1980b). Subsequent work in this tradition either tried to expand on some of
his ideas (e.g., Changeux 1983*1985; Edelman 1987; Edelman & Mountcastle 1978;
Freeman 1975; 1999) or moved into the fascinating area of animal thinking (e.g.,
Bates et al. 2007; Köhler 1925; Norman et al. 2001; Shetlleworth 1998; Sulkowski &
Hauser 2001; Premack 1985; Taylor et al. 2007). In both cases no contribution to the
nature or basic mechanisms of thought was made. It should be noted that despite
Hebb’s legacy, his argued view (Hebb 1949, 1980) that the study of mind can be
advanced if only we develop biologically constrained theories was not really taken
up.
8
The objective of this section is to build on and extend Hebb’s theory of thought
consistently with the key requirements of the philosophical and computational
approaches. Specifically, such a theory should ideally be:
a) Described in terms of a naturalistic theory of meaning.
b) Broad enough to encompass animal, and ideally machine, thinking.
c) Rich enough to be able to account for human thinking.
d) In accordance with observable behavior and biological evidence.
e) An integral part of a (much larger) theory of mind.
The proposed theory makes only two additions to Hebb’s classic work. First, it
addresses the mind-body problem in terms of neural formations. Second, it extends
the notion of ‘thinking’ to fully cover condition (b).
2.1.1.1 The structure of the animal mind: A biological theory of meaning
The pursuit of a theory of meaning is one of the fundamental issues of cognitive
science. Some would argue that it is the discipline’s holy grail (e.g., Jackendoff 2002,
2003). Among philosophers, a few claim that it is an eliminable notion (e.g., Searle
1992, meaning as derived intentionality of linguistic elements), others that is the
foundation for all philosophy (Dummett 1973). Having accepted its necessity, some
have argued for (e.g., Katz 1972) and some against (e.g., Putnam 1988) the
possibility of developing a theory of meaning. Table 1 provides a summary of the key
advantages and disadvantages of the main theories of meaning along with a succinct
presentation of their views on its nature.8 Despite the immense amount of work
though, no widely accepted theory of the nature of meaning exists.
Table 1. Summary of key advantages and disadvantages of the main theories of
meaning.
Name and Key
proponents
Nature of Meaning
Main Advantage
Main Disadvantage
RTM. Russell 1905,
1919.9
The language-world link
Pinpointed the relation of
language to the world
Too narrow. It cannot account for e.g.,
indexicals.
ITM. Grice, 1957, 1968,
1969.
Intended effect on
audience.
Distinguishes between linguistic
and non-linguistic meaning.
Inability to combine personal with
public meanings.
UTM. Wittgenstein,
†1953.
Use.
Recognizes the effect of context
on meaning.
Ignores underlying mechanisms.
LTM10. Katz & Fodor
1963; Chomsky 1965.
Purely linguistic.
Inclusion of syntax to account
for meaning.
Excludes context and the world.
TTM. Tarski 1944;
Davidson, 1967, 1973,
1974.11
Knowledge of truth
conditions.
(a) Pinpoints the relation of
thought to the world. (b)
Succinct representations.
Cannot account for non-truth
conditions.
AITM. Jonhson-Laird
1977.
Procedure.
As with UTM.
As with TTM (b)
Cannot account for non-executable
expressions.
Id.TM. Locke 1690;
Saussure 2006; Ogden
and Richards 1923.
Encoding.
Considers the close relation of
language to thought.
Cannot account for the abstraction
problem.
BTM. a) Osgood, 1971,
Osgood & McGuigan
1973.
b) Dretske 1981.
c) Millikan 1984,
Macdonald & Papineau
2006.
a) Function of response.
b) The condition that
typically causes an
intentional state.
c) Truth conditions of
intentional states in terms
of the biological functions
of these states.
Brings in our relation to things.
Does not recognize perceptual effects
on meaning.
STM, Mead †1934*1962.
Reside in social
collectivities.
Take into account the
sociocultural dimension of
meaning.
Ignore the biological dimension.
9
In what follows I propose a theory of meaning that put the MBI hypothesis on an
empirical basis.12 The assumption requires human meanings to be identified with
neural formations.13 Consequently, and most significantly, one has, first, to crack the
fundamental problem of delineating a class of meaningful neural formations. The
following two definitions provide conditions that do just this.
Definition-2: For an animal A, I call neural formation, N, a structure of interacting
sub-cellular components across nerve cells able to influence the survival or
reproduction of A.
A clear example of N is a synapse; any type of neuronal synapse. A second
example is the type of structure developed by the interaction among astrocytes, pre-
synaptic and post-synaptic terminals. I italicized ‘interacting’ to emphasize the fact
that processes are part and parcel of neural formations. As is well known such
interactions involve extremely complex reentrants. The reader will also have noticed
that I used the word ‘structure’ rather than system in the above definition. The reason
is that I wanted to avoid drawing any connotations of necessary completeness and, on
the contrary, I wanted to indicate the sense of potential fleeting existence. In other
words, neural formations may be either sort-term or long-term. Naturally in
accordance with standard biology, the cardinality, size, shape, composition and
interconnections of neural formations change over time. These characteristics are
aspects of what I mean by the term ‘complexity’ of a neural formation. The time
dependence of such neural complexity (i.e., its evolutionary development) gives rise,
through phylogenetic changes, to multiple types of, potentially qualitative,
complexity. Table 3 tentatively introduces some indicative levels of such neural
complexity.
Two more points should be noted. First, the proposed notion is heavily based on
Hebb’s (1949, 1980) notion of cell assemblies. Their key difference boils down to the
former being more inclusive allowing for instance the possibility of non-synaptic
plasticity (Kandel & Pittinger 1999; Bollmann & Engert 2009) and non-neuronal
correlates of mental abilities (e.g., Bennett 2007). Second, neural formations are not,
necessarily, mental representations (see definition-16). The next definition delineates
the class of meaningful neural formations and therefore extends the traditional sense
of meaning. As we shall see it is used to redefine the traditional senses of meaning
(definitions 5, 6 and relation (2)). It is thus a truly foundational notion (cf. the
memory-meaning postulate in 2.1.1.2).
Definition-3: For an animal with nerve tissue, A, a neural formation is meaningful
(symbol Nm), if and only if it is an N that influences the attention of that A.
Two remarks should be made here: (i) on the nature of attention; and (ii) on the
verifiability of Nm. My main justification for making attention the distinguishing
feature of the class Nm (the time-dependent totality of all Nm structures) is threefold:
its relation to working memory (e.g., Baddeley 2003; Postle 2006); James’ attribution
of the features of “degree of reactive spontaneity”, focalization, and interest, and
Freud’s attribution of special significance to the link of ‘attention’ to the unconscious.
The very considerable amount of subsequent psychological research has not
improved our understanding of ‘attention’ (Johnston & Dark 1986) but it has
confirmed initial conclusions (e.g., Awh et al. 2006). More recently, neuroscientific
10
work both added a significant link to the anatomy of attention (Posner & Peterson
1990) and provided added details (e.g., Knudsen 2007; Nummenmaa & Calder 2008;
Reynolds & Heeyer 2009). It should be noted that despite its neuroscientific interest
and potential applications neuroscientific research has not, to date, contributed to the
elucidation of the nature of attention.
In conclusion and for the purpose of this article, I will assume that ‘attention’ is
proto-characterised by James’ features of “degree of reactive spontaneity” and
focalization, and subsequently shaped by the special evolutionary compatibility
(SEC) constraint. This implies the time dependence of Nm and therefore of attention.
In other words, the proposed definition is a definition of proto-Nm. In accordance
with the SEC constraint, the A taxon includes a very large variety of Nm and
corresponding attentions. Obviously, this variety cannot reflect the posterior
reflection of any single species (not even of the Homo sapiens!). Therefore, human
aspects of attention do not enter the definition of attention at the A level. As the
theory develops though and higher complexity levels of Nm are introduced, the space
of A narrows down (i.e., there is a smaller number of species possessing such
increasingly higher levels of neural complexity). In accordance to the TonE proposed
here, exclusively human meanings only appear when we reach external
representations (section 2.2). Still humans are an extant biological species and as such
their meanings have to share at least some of the earliest developments of nervous
systems. In the rest of this section after the next paragraph, we redefine the traditional
senses of human meaning and meaning-related notions in accordance with definition-
3. In summary, A-meanings are subject to the SEC constraint and a variety of factors
may apply to one or more species but not to others. This is particular true of certain
human factors like affect, motivation, and scientific curiosity.
On verifiability, as Mike Elstob noted (personal communication), given the
inadequate current resolution of fMRI scanning there seems to be a problem in
actually linking Nms to conditions like (a) and (b) above. Although, this is true there
appear to be at least two routes to a possible solution. One route may be via
exploitation of the bridge between neural formations and homeostasis that glia cells
provide.14 The second route is linking the reproduction or survival of extremely
simple animals like sponges to genes in their proto-post-synaptic scaffold. Such a link
would seem to provide further justification for the proposed definition through
advances in our understanding of the evolutionary transition from sponges who lack
neurons with clearly recognizable synapses to earliest nerve systems (Sakarya et al.
2007). To account for the traditional senses of meaning, I first need the following:
Definition-4: I will use the symbol Sc to stand for a stimulus within its context.15
Sc may be either perceptual or linguistic or a combination of the two. With respect to
a human H, an Sc may be novel (i.e., not previously encountered) or not. If novel, two
sub-cases can be distinguished: (i) for whatever reason, no meaning is assigned to Sc
(an N may be created though); and (ii) a meaning is assigned to Sc. The following
two definitions address the case of a novel Sc and previously encountered Sc in turn.
Definition-5: The meaning of a novel Sc, for the human H at time t, is whatever Nm is
created by the interaction of Sc and H at time t.
11
Definition-6 The meaning of a previously encountered Sc, for the human H, at time t
is the prevailed Np of Np.
Some terminology and a couple of remarks are in order here. Np is that
subsystem of Nm that has been relatively permanently developed by the time t. Of
course, Np is a proper subsystem of Nm. It is only natural to identify Np with H’s long-
term memory. ‘Prevailed’ means the particular neural formation, Np that is eventually
selected among its family members Np. Now, the strength of Np to Sc does not
necessarily determine whether a neural formation will eventually prevail or not. The
term is used to indicate the potential complexity involved in the struggle for selection
(e.g., unconscious vs. conscious processes). Needless to stress that both external (e.g.,
Pavlovian or operant conditioning) and internal (e.g., emotions, understanding)
processes are usually involved. Second, the proposed definition does not require of H
to be aware of the previous occurrence of Sc. In other words, it allows the possibility
of subliminal stimuli recording.
So far we have introduced the notion of meaningful neural formations and the
meaning of external (either perceptual or linguistic) stimuli. When the external
stimulus is linguistic, its associated meaning usually comes under the heading of
linguistic meaning. When the external stimulus is perceptual, its associated meaning
has usually been considered under Grice’s notion of natural (or non-linguistic)
meaning (see Table 1). To complete the range of senses that ‘meaning’ does cover we
need to move into the partly uncharted waters of thought expression. Warning:
thought expression is not the same as language production.
To date, structured utterances or written expressions, l, are taken to convey a
person’s idea(s) beliefs, desire, emotions, motivations, etc. To refer to any –or any
combination of- such mental states, I will use the words ‘skepsis’ or ‘skepseis’ for the
singular or plural cases respectively in the following technical sense:
Definition-7. Skepseis are structures of neural formations that may or may not
involve Nm, although normally they do.
Now the traditional scientific view holds that:
(1) M (skepsis) = M (l).
I hold that (1) can be mistaken and that it usually is especially when a skepsis is
unusual, unconventional, half-baked, vague, novel etc. In all such cases:
(2) M (skepsis) M (l).
The symbol stands for ‘not necessarily equal’.16
Barring abnormal circumstances, their divergence is due to the creative aspect of
thinking and the constraining character of language. Neural formations have a history
of at least half a billion years. Genetically, a good number of Homo sapiens sapiens
Ns may well be identical with neural formations that existed hundreds of millions
years ago. Evolution is a near infinite well that modern humans are capable of
drawing upon. And this is a key contributor to the expression of new skepseis (i.e.,
novelty). Language will never become able to exhaust nervous systems evolution.
Our current models, framed by assumption (1), essentially address the structure
and constraining character of human language. I think it is time to adopt a more
comprehensive approach: Relation (2) should replace assumption (1) as framework
hypothesis for realistic models of skepseis. Any serious neuroscientific account of
meanings and thinking should not push under the carpet the huge complexity
involved in the creation of utterances or expressions out of skepseis. It has to be
realised that language is a substructure of thought.17
12
So, when relation (1) is not the case, what is the M(skepsis)? It is an l whose
meaning, even for the speaker or scriber, only approximates her skepsis. My
argument is appeal to private evidence. Nevertheless, empirical verification is, in
principle, possible by linking a computational system to a human’s brain.
Furthermore, in accordance with Boden’s (1992) distinction between historical and
psychological creativity, a historically novel l is more likely to be caused by (N, Nm,
H, t,), and a psychologically novel l by (Nm, H, t,). In summary, although we are
bound by language we can also extend it thanks to our evolutionary past and our
ability to create external representational systems (section 2.2).
The following four definitions and concluding remarks complete the outline of
our theory of thinking:
Definition-8: Let 1Nm be the first neural formation created by the specific triad (Sc1,
H, t1). Then the system of all jNm (j a natural number) of human H that have been
created by time t later than t1 I call it a concept of H up to t and I symbolize it by εNm.
For simplicity we may use the letter ε to refer to a concept but it has to be understood
that ε is identical with εNm. Naturally, a εNm is a very tiny subsystem of Nm.
Definition-9: σ is a thought of human H if and only if σ is a flexible and not
necessarily permanent structure of concepts and/or Nm (i.e., meaningful neural
formations, as per definition-3).
Definition-10: Belief =def A structure of neural formations and meaningful neural
formations on the basis of which one is prepared to act, argue, or live by.18
Definition-11: Thinking, T, is the interaction of meanings, or concepts, or thoughts,
or beliefs, or of any combinations of them.19
The meanings and meaning related structures identified by definitions 3, 5-10
correspond to different levels of neural complexity. Collectively, they constitute the
semantic structures, M, of an individual’s nervous systems. Hebb’s theory had a
similar structure up to third-level cell assemblies and had also allowed subassemblies
of 2-3 neurons. The theory proposed here hardly adds anything to that conception.
With respect to actual and potential structural neural complexity the two theories are
essentially indistinguishable. Nevertheless, Hebb’s theory does not include a theory
of meaning and that is a difference of fundamental significance with far reaching
consequences.20 Assuming my theory of meaning holds, the mind-body problem
collapses.
Concerning thinking the two theories take the same stance with respect to
thinking as a single series of neural formations. Their difference stems from
definition-11 that allows for both random and directional thinking. As such thinking
operates at any and across any of the complexity levels of an individual’s semantic
structures (M). When the complexity levels of M are coupled with the potential
number of neural states (of hyper-astronomical cardinality), we get the space of
neural thinking. Modern human concepts and beliefs constitute huge subspaces (in
terms of the number of N & Nm involved) of this neural space. Still, at the same time,
they are the constituents of our conscious attention.
The immensity of the neural space of thinking creates a problem for directed
thinking. To account for that, Hebb (1976) proposed that the exceptionally high
13
frequency of inhibitory neurons may have the essential function of streamlining
thought. That may indeed be the case. Given the complexity of the neural processes
involved we are somehow agnostic on that line of thought. As a theoretical
alternative, we suggest the process of understanding (section 2.1.2.1).
The theory developed so far is only a small part of the TonE proposed. As we
proceed with the latter’s development, aspects of the theory of thinking outlined in
this section will be modified. Nevertheless, even this far the challenges are immense
and so may be the rewards. The next section focuses on some of these ramifications
and challenges.
2.1.1.2 Ramifications and challenges
The proposed biological theory of meaning extends the sense of meaning to
include the fundamental class of meaningful neural formations. This has far reaching
consequences as it is applicable to all A species according to the SEC constraint.
Some of the ramifications follow.
First, the theory satisfies all of the key points made by the earlier theories of
meaning as codified in Table 1 albeit on the naturalistic basis of Nm. On this basis it
redefines the traditional senses of meaning and meaning-related notions (definitions
5-11, relation (2)) in terms of empirically verifiable conditions. It also provides
grounding to all four bands of the time scale of human action that Newell (1990)
identified through the processes of communication and understanding (see section
2.1.2 and in particular subsection 2.1.2.2 on primitives). Being part and parcel of
TonE, the theory plays an ineliminable role in addressing also Loar’s (1999, p. 546)
requirement: “A fundamental element of a theory of meaning is where it locates the
basis of meaning, in thought, in individual speech, or in social practices.” In the
precise senses given in sections 2.1.1.1, and 2.1.2, the proposed TonE explains why
meaning is “locatedin all three: thought (i.e., M & T), individual speech and social
practices. It follows that since human meanings are constitutively determined by both
a human and her or his environment (physical as well as social and cultural), pure
internalism and externalism are bankrupt in either their semantic or epistemological
variety. This may be glimpsed by the sort of sophisticatedly gerrymandering
arguments developed in the recent literature (e.g., Goldberg 2007; Williamson 2006).
Similarly, the coupling between H and her environment (postulated by the
dynamicists) can be precisely identified by the links specified in 2.1.1.1.
Second, in contrast to Putnam’s (1988) argument against the view that
‘meanings’ (or ‘contents’) can be seen as ‘theoretical entities’, our theory has
identified the class of meaningful neural formations as the class of “‘psychologically
real’ entities which have enough of the properties we pre-analytically assign to
‘meanings’ to warrant an identification.” (ibid, p. 4).
Third, definitions 5 & 6 explain word meaning as an inseparable feedback loop
combination of contextual learning (of situation, events, and objects) and cellular
(primarily neural) mechanisms. Furthermore, the postulated mechanisms get
empirical support from Markson and Bloom’s (1997) evidence that the system
underlying word learning is not specific to language. These two points reinforce each
other and taken together weigh considerably against the possibility of word learning
being an FLN (faculty of language in the narrow sense) mechanism (Fitch et al.
2005).
14
Fourth, our analysis provides a naturalistic account of the distinction between
token and type meanings that is essentially identical with that of Hebb (1980b for a
brief argument). It is therefore unlikely to be convincing to those considering the
type-token question a philosophical minefield (Aylwin 1985, p. 44) and even an
important topic for serious scholarship (Wetzel 2008). We are though obliged to say
that within our theory tokens of a type are identified with jNm, and the type itself with
εNm. It should be noticed that in the case of Homo sapiens prevailed Np of higher
order Nms (definitions 8-10) may well capture multiple characteristics of a complex
stimulus like that of a beautiful woman.21 Here we would enter the overlapping
phenomena of generalization, categorization and abstraction but consideration of
these issues is beyond the scope of this paper.
Fifth, the proposed so far theory of thinking can be used as a preliminary system
of criteria for deciding whether a particular animal species qualifies the appellation
‘thinking species’ and, more importantly, to what degree. On this preliminary basis, I
would say that parrots as exemplified by Alex (Pepperberg 1999), bonobos as
exemplified by Kanzi (Savage-Rumbaugh et al 1998), cephalopoda as exemplified by
the mimic octopus (Norman et al 2001), and dolphins (e.g., Herman 1984 et al.) seem
to fully pass them to at least some degree. These criteria can be enhanced by the
introduction of animal primitive systems (see 2.1.2.1 justification) and should be seen
to be compatible with test in comparative biology (e.g., Lefebvre et al. 2004).
Finally, I propose the following memory-meaning postulate (MMP): The
memory systems of an individual constitute a proper subsystem of that individual’s
semantic system which in turn constitutes a proper subsystem of that individual’s
neural formations. The first step of my argument starts with the observation that the
semantic memory tradition (Collins & Loftus 1975; Collins & Quilian 1969) and its
later incarnations as the study of categories and concepts (e.g., Medin and Rips 2005)
along with suggestions of meaning theories criteria involving memory (Edelman &
Mountcastle 1978), indicate a respectable link between memory and meaning. That
link becomes stronger when one further observes that both memory and meaning
depend on context, time and the individual concerned. Psychiatry provides numerous
cases (e.g., Krystal et al. 1995). Nevertheless, understanding the meaning of an Sc
does not imply memorisation of Sc (suggestion that the memory system is a
subsystem of the meaning system). In addition, there are instances of meaningless
utterances or inscriptions producible by an individual (suggestion that the meaning
system is a subsystem of the nervous system). Finally, memory traces (materialised at
sub-cellular level: Kandel 2006; Koch 1999) can be identified with meaningful neural
formations.
Taking seriously the MMP implies that the key issues of memory research
become key problems for any theory of meaning (cf. and contrast with Sutton
2004).22 In return, most, but not necessarily all, of the questions on meaning become
obsolete or can be translated in the more rigorous framework of memory research to
provide a much-needed breath of fresh air. In the millennium issue of the
Philosophical Transactions of the Royal Society B, Kandel and Pittenger (1999, p.
2027) reviewed a century of accomplishments in the study of memory along “the two
major questions that have dominated thinking in this area: the systems question of
memory, which concerns where in the brain storage occurs; and the molecular
question of memory, which concerns the mechanisms whereby memories are stored
and maintained.” Although work at the molecular level has monopolized the research
on memory mechanisms, the possibility of non-synaptic plasticity is explicitly stated
as one possible direction of future memory research. A second important remark is
15
that “[w]hile human memory, both explicit and implicit, is likely to employ similar
basic mechanism as that of simpler animal systems, it is also doubtlessly unique in
other respects.” (ibid, pp. 2042-3). Nevertheless, no specific suggestions are made for
either. Meaning results properly incorporated in the memory field (that may well
necessitate the development of new memory terms and ideas) can help with both
endeavours. A potential basis for a sketchy modeling answer to the systems question
(not a proposal for specific neurophysiological mechanisms though) has been
suggested in Gelepithis (1989).
In summary and conclusion, meanings, concepts, skepseis, thoughts and beliefs
jointly constitute the semantic structures of an individual’s nervous systems. The
frequency, architectural modifications and even existence of these structures depend
on the individual, the species and their environment (physical, cultural or otherwise).
Applied to humans, this simple characteristic gives human ‘mind’ both its fleeting
appearance and protean structure. Nevertheless, recognition of the existence of
meaningful neural formations and even of the possibility of a full naturalist theory of
thinking does not imply a reductionist conception of the human mind. For, as in
evolutionary biology the gene is not the object of selection (e.g., Mayr 2004), so
meaningful neural formations, and therefore meanings, do not constitute in
themselves the criterion of the mental. They provide a necessary substratum. They are
not adequate. Several levels of additional organisational complexity are required as
the following sections demonstrate.
Challenges. The reader will have noticed that the key difference between
definitions 5 & 6 on the one hand and M(l) on the other lies with the source of
meaning. In the former cases the source is external (Sc), in the latter it is internal (N
and/or Nm). What is common in both cases though, is the complexity of the
mechanisms involved in the creation of the semantic structures of an individual. This
complexity is staggering. Its source is threefold: (i) neural; (ii) environmental; and
(iii) evolutionary. The rest of this section points out some of its elements. The focus
is on some of the distinct and related systems involved.
With respect to the notion of meaningful neural formations, the system of
mechanisms, Mm, responsible for the creation and modification of Nm is very
complex. This is due to the interaction between the host of basic memory
mechanisms involved and the additional mechanisms of novelty as they may be
glimpsed from the brief discussion concerning relation (2). Concerning meaning in its
traditional sense (definitions 5&6), at least two systems of creation mechanisms are
required. First, a system, Mp, that is responsible for creating Np. The literature on
LTM (long-term memory) should be able to provide some useful models. Second, a
system, Map, that is responsible for the appearance of the prevailed Np of Np. The
literature on recall should be useful in this case. Finally, the system of mechanisms,
Ms, responsible for the creation of expressions out of an individual’s skepseis should
be the most complex of all due to the fact that it is, normally, closely knit to both Mm
and the neural aspects of language. This is definitely not helped by the fact that we
are largely ignorant of the derivation mechanisms of l that vary from the routine to
the creative.23 It is worth noticing that current (e.g., Abbott 2006) neuroscientific
research on cognitive processing is both at its very beginning and possibly barking on
the wrong tree with respect to the level questions posed (e.g., switching of neural
circuits).
Focusing on humans, is there a system of core mechanisms for semantic
structures creation that is at work for all humans (barring pathological cases)? Such a
16
system would be an important human universal. The majority of linguistic approaches
postulate syntax or, more recently, the FLN (e.g., Hauser et al 2002) as playing a
significant role in human meaning construction. Syntactic considerations do play a
role in creating l, and therefore, M (l). Nevertheless, that is a far cry from explaining
meaning construction (cf. relation (2)). I think that this is a much more complicated
and wide-open issue that FLN may be willing to accept.
The theory of thinking developed so far is wide enough to be applicable to a
variety of animal species across the evolutionary bush but it is inadequate to capture
important aspects of the mind of a large number of animal species and to account for
the richness of human thought as manifested in the range of human activities we are
aware in everyday life and scientific pursuits. Its key inadequacies are lack of
sociality and of the ability to create external representational systems. The next
section proposes a theory of communication (the defining characteristic of the social
stage of at least animal evolution). Section 2.2 addresses the latter inadequacy.
2.1.2. Communication
Communication is basic to all members of a society. But, what is it really?
Despite its vast literature, the problem of the nature of communication is either
ignored or ‘communication’ is used, even within a single discipline, as an orienting
term rather than as an explanatory theoretical construct.24 With respect to the former
point, it is both interesting and revealing to note that two comprehensive reference
works, the MIT Encyclopedia of the Cognitive Sciences Wilson and Keil (1999) and A
Companion to Cognitive Science (Bechtel and Graham, 1998) do not include an entry
on communication itself. Instead, the former refers the reader to three related entries:
on animal communication (Hauser and Marler, 1999), on Grice (Bach, 1999) and on
language and communication (Duncan, 1999).25 The latter refers one to cognitive
linguistics (Tomasello, 1998). None of these entries considers the nature of
‘communication’. The same is essentially the case for any of the contributions in six
readers, spanning more than eight decades of research in communication (Cobley
1996; D’Ettorre & Hughes 2008; Haliday & Slater 1983; Pool et al. 1973; Smith
1966; Vaina and Hintikka 1984*1985). It is also true for at least indirectly related
work on the social nature of human and animal mind (e.g., Connor 2007; Mead
†1934*1962; Moll and Tomasello 2007; Vygotsky †1934*1986).
With respect to the ad hoc, discipline-based treatment of communication one
may distinguish several perspectives. Act of sharing signs (e.g., Cherry 1978*1980,
Dimbleby & Burton 1998, Schramm, 1973).26 The mathematical theory of signal
transmission (Shannon and Weaver 1949). Communication as signalling beneficial to
sender (e.g., Slater 1983). “[T]he social mediation of information” (e.g., Hauser 1996;
Matessi et al 2008; Roberts 1973). Communication as a means to manage audiences
ranging from instructional communication (e.g., Mottet et al 2006) to political
communication (e.g., Stanyer 2007). Identification with interaction (e.g., Katz and
Danet 1973). Identification with its two commonsense meanings, (e.g., Arlington and
Baird’s 2005; Benowitz et al. 1984*1985; Murray (1998); Sass (1984*1985); Scott
(1996); Tomasello et al 2005).27[A]ny exchange of messages between human
beings” (e.g., Runcan 1985). Identification with context (e.g., Sperber & Wilson
(1995). Intention-based (e.g., Messer 1994). Intention to produce understanding (e.g.,
Searle 1999a*2000). The practice of producing meanings and their negotiations by
participants in a culture (e.g., Schirato and Yell 2000). Among humans, the process of
responding to each other’s symbolic behaviour (e.g., Adler and Rodman 2000).
17
Finally, communication as jointly beneficial signalling (e.g., Maynard Smith &
Harper 2003).
Probably, the strongest objection against the use of ‘Communication’ as a
theoretical construct is that it, as opposed to gravity, is claimed to be a socially
constructed notion rather than an objective reality and, therefore, any attempt to
provide an objective account of it is doomed to failure. Interestingly, this is the view
of both those postulating the existence of characteristically social ‘facts’ la
Durkheim) and those postulating ‘meanings’ as the key methodological approach of
sociology (à la Weber). This debate in sociology is reflected in the systems and
interpretive perspectives in communication studies (Monge 1977; Putnam 1983). The
objection sounds powerful but misses an important point. Both ‘gravity’ and
‘communication’ are humanly constructed concepts and both refer to some external
phenomena. Their only difference is that ‘gravity’ has a generally accepted meaning
within the Earth-based physicists, whereas ‘communication’ does not have one within
the community of scientists using this notion. It is high time for a conception of
communication that could be used as an explanatory tool across the disciplines
studying it.
2.1.2.1 A hybrid theory of communication: Sociology and Biology bridged
So far, each disciplinary theory of communication has been built on the basis of
a single significant feature of it. Some have chosen the notion of sharing; some the
notion of understanding; some the notion of meaning. In addition, no theory has
explicitly and consistently taken into account the fact that communication involves
persons or other respectable animals and takes time to be completed. The following
system of three definitions combines all five fundamental features of
communication.28
Definition-12: A human H 1 has communicated with H 2 on a topic T if, and only if:
a) H 1 has understood T -symbol: U (H 1, T);
b) H 2 has understood T -symbol: U (H 2, T);
c) U (H 1, T) is presentable to and understood by H 2; and
d) U (H 2, T) is presentable to and understood by H 1.
Definition-13: A human H has understood something, S, if and only if, H can think
of S in terms of a system of human primitives (symbol ΠH).
Definition-14. π is a primitive of/for H if and only if the meaning of π is immediate
for H.
The rest of this section justifies the proposed system of definitions by providing
a full account of the nature of its key notion of understanding in accordance with both
the literature and common sense usage.
The philosophical underpinnings of human 'understanding' can be traced back at
least as far as the times of Plato and Aristotle and their attempts to provide an account
for the human mind. More recently, Locke (1690) and Hume (1758) have written
treatises on "human understanding". For both of them, 'human understanding' was
essentially taken to be coextensive with the functioning of the human mind. A
conception that is more in tune with that of Plato’s and Aristotle’s rather than any of
18
today’s workers in the field of human cognition.29 Rejecting the coextensive
assumption helped in focusing on the process nature of understanding.
As a process, human understanding is applicable to the full time scale of human
action. It is observed from approximately 10ms (cf. definition-14) to days, years and
more. Most of cognitive science is primarily concerned with phenomena whose
duration varies from approximately 100ms to about 10min.30 The large majority of
work on understanding falls within this time scale; it usually comes under the name
of comprehension. Orthogonal to the time scale dimension is the analyticity
dimension of human understanding. Along the latter dimension schools of thought are
distinguished according to whether they consider human understanding as a process
to be further analysed into some simpler notions (the analytic school) or consider it as
a primitive notion (the hermeneutic school). Most work falls in the analytic-
cognitive/rational quadrant (e.g., Greeno 1977; Johnson-Laird 2003; Just & Carpenter
1987; Schank 1972; St. John & McClelland 1990; Winograd 1972).31 In the analytic-
social band quadrant the most important work is that of Pask (1976) and Ziff (1972).
Finally, in the hermeneutic-social quadrant the work of Dilthey (1900), Moravcsik
(1979), Ricouer (1981) and Habermas (1981*1984; 1987) stand out. Some recent
work in the area of mirror neuron systems has attempted to link results in this area to
action and in particular the understanding of action (e.g., Jeannerod 2006; Rizzolatti
& Sinigaglia 2006). They did not address the issue of understanding per se.
The key conclusion in reviewing the literature on the nature of understanding is
that although agreement on its nature has not been reached two attributes of it are
virtually universally accepted. First, human understanding always involves the grasp
of meaning. Second, human understanding is a process that takes place in human
brains/minds.32 I submit that the reason for the existing disagreements on the nature
of understanding stem primarily from having focused on different bands of the time
scale of human action. In contrast, the combination of definitions 13&14 and of the
analysis that follows cover both the full scale of human action and incorporate all
major features of human understanding. In particular it is consistent with both the
process nature of understanding and its end result that may be seen as a state. The
latter point raises significant philosophical questions that fall beyond the scope of this
article.
Now, the important question is ‘what are the conditions under which
understanding has achieved? Work in the cognitive-analytic quadrant take successful
behavior in question-answering tasks, for instance, to constitute an adequate
terminating condition. That may be true but it is inapplicable when human
understanding is concerned with tasks requiring time scales that fall outside the
cognitive and rational bands. Such tasks constitute the bread and butter of the larger
part of science (I use the term to include both physical and social sciences and the
humanities). Without loss of generality the subsequent development of my analysis
will assume tasks of the latter type being the object of human understanding.
Naturally, thinking processes may, and do, terminate somewhere; but not all
thinking is called, or can be, understanding. One may, for instance, be interrupted
while trying to understand something and subsequently fail to catch again the thread
of that particular thinking process. To be sure, there may be future recall of the
interrupted process but the point is that at the time of interruption no understanding
may be said to have occurred. So, we conclude that not all terminated thinking
processes are processes of understanding.
Let us assume then that we witness a case of an undisturbed thinking process.
What additional conditions should be fulfilled in order to say that one has understood
19
something? There is a thinking process that will help us to specify these conditions. It
may be called alleged understanding, (or misunderstanding), and it occurs whenever
people think they have understood something only later to discover that what they
had concluded was not the case. The key point in a case of misunderstanding is the
fact that one's own predictions or explanations, according to her model or belief
system, turn out not to be the case. Assuming there was not any fault in the inference
process one concludes that there must have been mistaken premises. We see,
therefore, that whenever misunderstanding is reached some mistaken premises must
have been involved. We take this fact to be a strong suggestion that to reach
understanding one's premises –with regard to the task or phenomenon to be
understood- must hold true. Factually, an individual’s premises may be a system of
primitives or not. Consequently, I distinguish between thinking processes that end up
in a system of primitives (ΠH) or in a foundational belief system (that may include
some primitives). The former type of thinking processes I call understanding, the
latter reasoning.33 What both types of thinking have in common is the notion of
mathematical validity.34
There are six reasons supporting the proposed theory of communication and
understanding. First, it provides necessary and sufficient conditions for human
understanding which: (a) capture the fact that understanding always involve the grasp
of meaning; (b) capture the process nature of understanding; (c) capture the two most
significant aspects of the analytic tradition, namely, (c1) systematicity (since
definition-13 implies the existence of a sequence of steps although neither necessarily
formal nor necessarily conscious); and (c2) the requirements of context and
motivation as contributing factors in human understanding; (d) are not in conflict
with the hermeneutic approach. Second, it does not violate the common sense of
understanding as described by most dictionaries and encyclopedias (e.g., Oxford,
Longman, Britannica) and used in both scientific and vernacular language. Third, it
can accommodate both conscious and unconscious understanding. The former can be
quite effortful and take considerable amount of time. Fourth, it naturalises at least
part of the process of human understanding by making the end result of it empirically
investigable. This may well happen through primitives- or premises- based
descriptions and, conceivably, through neural level imaging. Fifth, the integrated
character of understanding seems to be in accordance with the integrated character of
the brain. Specifically, the context dependence of the end result of understanding in
the form of ΠH is in accordance with the context-related functions of the right
hemisphere while the process nature of it seems to be in accordance with the left one
(Bookheimer 2002). Last, and at least equally importantly, the proposed theory can
be straightforwardly generalized to any A taxon. Appropriate taxon primitives can
contribute to the design of methodologies that are less biased towards humans, thus
addressing Emery & Clayton’s (2008) important design requirement of cognitive
tests.
Both as a process and at its end result, understanding can be extremely complex
depending on the depth that the process is required to go to achieve its end result.35
The complexity of the process itself is far beyond the scope of this article. The next
section looks at the complexity of its end result, namely, systems of primitives.
2.1.2.2 On primitives
Definition-13 is cast in terms of “a system of human primitives”. It follows that
an H may have understood a particular topic in terms of several different systems of
primitives. Such systems may be of their own, of someone else’s or of a school of
20
thought (established or not). In relation to reasoning, it is widely recognized how easy
it is for someone to reason to different conclusions from those of her fellow if their
two foundational belief systems are different.
But what meanings count as immediate? Could the set of human primitives be
specified? Suppose we are asked to classify the words set, electron, water and pain in
either one of the following two mutually exclusive sets: (i) the set of primitives P; (ii)
its complementary P'. It seems that set falls in P electron in P'. What about water and
pain? It might seen obvious that H2O being analyzable to its constituents parts and
these in their turn to electrons (among other similar types of entities) should be placed
in P'. Still, I can think of no one who would not place water in P. Moreover, set and
water are two quite different types of primitives. Set can be a primitive for a
mathematician whereas water is a primitive to anyone. What about pain? It might
seems obvious to everybody that pain should be put in P, but Dennett (1978) has
given a nice, although sketchy, model of pain; it follows that one should put pain in
P'. So, we observe that three out of the four concepts can be placed either in P or in P'
depending on whom we asked to classify them.36 So, primitives are of two types
linguistic and pre-linguistic or sense ones. The latter are inseparable from the
corresponding organism concerned. The former depend on the particular individual H
possessing them. To be noted that as soon as linguistic primitives are expressed they
become data and they may only acquire meaning if processed by another human. In
summary, ΠH is both subjectively and community dependent. More generally, one
can convincingly argue that ΠE is both individual and species-specific. It becomes
obvious now that a ΠH or a ΠE constitutes an extremely complex system. To get a
better idea of this complexity consider the following further characteristics and
examples.
First, the fact that the meaning of the elements of a ΠH is immediate does not
imply that they are necessarily atomic (i.e., not able to be split into simpler ones).
Qualia constitute an important class of atomic ΠH. The second, related, feature is that
ΠH can change with time. A human may split some of the elements of a ΠH into
simpler ones or she may actually abandon some. An important special case of ΠH
modification is usually involved in conceptual change (e.g., Vosniadou & Verschaffel
2004). Third, TonE allows acquired primitives in contrast to Fodor’s (1994) strongly
innatist account according to which primitives are inherited as part of the structure of
the brain. Fourth, the systems of ΠH are not in accordance with either Fodor’s (1983)
modularity thesis or Tooby and Cosmides (1992) massive modularity one. Contra
Fodor systems of ΠH are interrelated via thinking or understanding and therefore not
encapsulated. Contra massive modularity, a large number of ΠH systems are
ontogenetically specific and therefore not adaptations. Fifth, a ΠH system is
fundamentally different from formal systems of primitives like those identified with
pixels or curves (see Schyns et al. 1998 for a discussion). Sixth, since primitives are
meanings, a ΠH is a subsystem of an Nm. Moreover their characteristics imply that
they are quite diverse and diffuse systems of Nm. This claim is in accordance with
fMRI results of brain’s semantic organisation (Bookheimer 2002). Seventh,
primitives are age- individual- cultural- and species-specific. An example of age-
related primitives is ‘electricity’; it can be a primitive for a toddler but not a primitive
for an electrician or quantum physicist. With respect to individuals, 'water' was a
primitive for my grandmother throughout her life but it is not a primitive for those
knowing that 'water' can be thought of in terms of H
2O. Actually, what may be a
21
primitive for someone may be part of a very complicated theory for another. As an
example of cultural primitives consider the host-guest relationship. In India and
Hellas for instance, when a potential host invites a potential guest with an expression
like ‘come at any time’, she expects such an invitation to be taken literally.
Interestingly, if the recipient is an outsider from, say, the Anglo-Saxon culture such
an invitation will definitely not be taken literally but simply interpreted as a kind of
friendly invitation. Finally, smile seems to be a primitive of humans and of some
other primate species only.
To conclude, there is no single definite set of human primitives. Primitives vary
both ontogenetically and phylogenetically. Primitives’ variability applies to both
sense and linguistic ones. Only linguistic primitives can be acquired. Humans and
other animals are born with a range of sense primitives. Sense primitives (i.e., qualia)
are atomic. Linguistic primitives (barring those that are names of sense primitives)
may be atomic but humans have no way to know that. Finally, a human’s
understanding of a particular topic is in terms of a minimum vocabulary for that topic
and human.
2.1.2.3 Summary and the Communication-Understanding Principle
First, understanding is a prerequisite for human communication that, in turn, is at
the very basis of the existence of the human society. Second, there are multiple levels
of understanding corresponding to multiple levels of primitives-based descriptions.
Third, the systematic and structured characteristics of understanding makes it a prime
tool in the acquisition and (re)-structuring of knowledge and consequently of the
shaping of human mental structures. Fourth, the very close relation between
understanding and explanation, the fact that they constitute necessary elements of
human reasoning, and their role in shaping the cognitive structures of both learners
and tutors (Gelepithis and Goodfellow 1992). Fifth, since primitives may, equally
well, be either formal or informal, understanding bridges the formal-informal
interface. Sixth, understanding and therefore communication can operate across both
the conscious/unconscious divide and the linguistic/pre-linguistic stages of human
development providing the integrated characteristic of human behaviour. Finally, the
process of understanding (not its end result) is independent of both any animal
capable of understanding and of time.
Of course, this is not to say that the actual process does not take time; only that
however long it may take its defining characteristics remain invariant. These two
features of understanding: time independence and applicability throughout the
evolving space of understanding entities makes understanding an invariant of that
space. In particular, of course, the process of human understanding is a human
cognitive invariant.37 It is worth noting that the invariance of the understanding
process does not imply that understanding is a characteristic of human nature in the
sense employed by evolutionary psychologists (e.g., Tooby and Cosmides 1992). For
the understanding process is not a developmental program. It is a complex brain
process affected by both ontogenetic and environmental factors.
Along similar lines of reasoning, the process of communication should also be
an invariant.38 It is important to be noticed that the proposed invariance of
communication does not entail the claim of the invariance of human nature (e.g.,
evolutionary psychology; Wilson 1998). Whether it is a universal in Brown’s (1991)
sense fall outside the scope of this article.
22
On the basis of the above, I propose that the processes of communication and
understanding are the fundamental processes shaping the structure of mind both in the
exclusively natural era and the era of the artificially natural mind. This I call the
communication-understanding principle (CUP). The next section accounts for the
additional characteristics of the latter era.
2.2. The era of the artificially natural human mind
This section identifies the key characteristic of the artificially natural human
mind and the subsequently derived uniqueness of very modern humans (i.e., modern
humans not later than seven thousand years ago –symbol H7kya). Specifically, I
propose that written human language (WHuLa) is the key characteristic of H7kya. It is
the novel result of the combination of two considerably earlier human traits: speech
and external representations. WHuLA is the necessary breakthrough for the
consequent dawn of the era of the cumulatively artificial (i.e., the ever increasing
totality of the human-made systems and structures).
2.2.1 The nature of human representations
The literature on ‘representation’ is daunting and controversial.39 Dietriech
(2007, p. 1) remarks that “no scientist knows how mental representations represent”.
What is worse though is, that it is still the case that what counts as representation is
unclear (Boden 1994). Actually, the literature on representation conflates human
thinking and mental representations with knowledge representation (KR) schemes.
The result is stalled progress on both. This section identifies both important
similarities and the key difference between mental and external representations. The
identified key difference is partly responsible for the uniqueness of human mind
within the continuity of animal evolution.
All approaches to ‘representation’ draw upon or combine, in varying degrees,
two fundamental ideas: (i) aspects of Peircian semiotics; and (ii) the mathematical
notion of isomorphism.40 Von Eckardt (1992) made explicit the common view of the
nature of representation adopted by the majority of cognitive scientists. That view is a
simplification of Peirce’s theory essentially identifying his notion of “interpretant” to
a “thought or series of thoughts in the mind of the interpreter” (ibid). Computational
formalisms, whether logic- or graph-based, try to explicitly describe the
“interpretant”. Within the theory outlined in 2.1.1.1, the latter is usually a concept and
sometimes a skepsis. To refer to either of these, I use the symbol C (cf. Figure 1). The
connectionists’ representational tools (vector spaces) and the dynamicists’ differential
equations share exactly the same objective. Newell (1990) added to this Peircian view
the notion of mathematical isomorphism that he calls “the representation law”. This is
a pretty simple and useful picture but not the whole one. It is a conception avoiding
Peircian complexities but biased towards KR schemes and tool-based reasoning. This
has contributed to relatively powerful computational models but impoverished
conceptual interaction with other fields. The next few paragraphs clarify the above
points.
Consider the following ubiquitous examples of external human ‘representations’
A and try to think of the underlying processes that created them:
a) Designs of all sorts and small scale models like those used to re-present a major
urban development, a spacecraft or a teddy bear.
23
b) Logic expressions, camera images, geometrical diagrams, computer programs,
equations.
c) Ubiquitous artistic forms in theatre, painting, sculpture, or cinema to name the most
obvious ones.
d) Certain patterns or behavioural acts like those involved in speech, sign or written
language.
In all these cases, A are characterised by the following properties: (i) they are
simplifications of some situation K; (ii) they aim to preserve the essential
characteristics of K; (iii) they can be processed by humans; and (iv) they are part of a
physical material. Therefore:
Definition-15: For a human H, an external representation of a situation K is an
artificial construction A characterised by the properties:
a) A is a simplification of K; and
b) A has been designed or constructed by H in order to preserve the essential
characteristics of K.41
We now face two questions. One, what are the essential characteristics of K?
Two, how does one decide that X is one of the essential characteristics of K? The
received answer to the first question is straightforward: what counts as ‘essential’
depend on the objective(s) of the representation. Within a given KR scheme this is
realised by the following two parameters:
(i) The aspects of K that H has decided to represent (technically known as the
scope of a representation); and
(ii) The amount of their detail (technically known as the grain size).
This standard analysis clarified by definition-15 is quite powerful and adequately
addresses Van Fraassen’s (2008, p. 15) query: “We confront here the general question
of how an item such as a picture can correctly represent, misrepresent, caricature,
flatter, or revile its subject.” Notice for instance that “correctly represent”,
“misrepresent” etc are all representations (as defined above) differentiated by the
parameters of scope and grain.
The second question though falls outside the standard analysis and leads one to
distinguish between thinking (definition-11) and tool-based reasoning. The latter,
although ultimately depends on human thinking and primitives, is characterized by a
system of rules which after having been specified by H - enable anyone to draw
conclusions mechanically. Naturally, such tool-based reasoning whether it is carried
out by grammars, graph theories, or in general, mathematics- either ignores the
psychological mechanisms of thinking or identifies them with the inference
mechanisms of a particular KR scheme.42
At this point, if not earlier, one may question the significance of our second
question. So, let us be clear about it. Its significance stems from the need to
distinguish between ‘the human ability to create (systems of) external
representations’ (extRH) and the end result of that/those process(es). Finding out the
mechanisms of extRH would be a major breakthrough, studying or using its end results
(e.g., grammars and other formal systems) is useful to the extent of their applicability.
In view of the analysis in this and the previous sections, I am tempted to suggest that
an investigation of the mechanisms of extRH through the process of understanding and
its associated systems of primitives may be worth pursuing.
24
The next step in the study of human representations is even more demanding.
What are the neural mechanisms of RH (i.e., the ability to create neural
representations)? The added difficulty may easily be seen when one realizes that RH
may well involve unconscious processes while at the same time its end results lack
the specificity and concreteness of external representations or KR schemes (end
results of extRH). Still, assuming the continuity of the Homo genus (and therefore of
some relation between neural and external representations) and, furthermore, taking
into account the notion of perceptual image, we find it reasonable to adopt the
following working:
Definition-16: For a human H, a neural representation of a situation K is an Nm
structure such that:
a) It is a simplification of K; and
b) It tends to preserve the essential characteristics of K.
This is both in agreement with neurobiological requirements of internal
representations (e.g., Blakemore et al. 2002, Moser et al. 2008) and avoids Ramsey’s
(2003) criticisms of receptor representation. It is also straightforwardly generalisable
to hold for a good number of animal species in full agreement with Bickerton’s
(1990) argument that a primary representational system, developed in various forms,
exists in all higher animals and Hurford’s (2003) argument of powerful neural
representational systems. Finally, it is compatible with the classical ethological
finding of relative uniqueness of nearly every species through their species-specific
representational capabilities. Similarly to extRH, specification of the mechanisms of RH
(in contrast to mere identification of its end result) is a significant open question in
the study of mind. As with extRH, it appears that RH may well be related to
understanding. In contrast to extRH, such understanding, if indeed related, may, more
often than not, be unconscious and hence hardly accessible with the current state of
technology. Whether they do, and if yes, exactly how they are related is a second
important question.
It is worth noting that neuroimaging experiments, incorporating the notions of
scope and grain size of a representation, may just be possible to indicate potential
neural structures that preserve certain characteristics of K. Kurto & Itskov’s (2008)
work on group cells and their relationship to the Kantian concept of space may be
seen as an example of such work. It should be stressed though that the issue of neural
representations, even in the special case of spatial representation with its nearly forty
years history (e.g., O’Keefe & Dostrovsky 1971), has far too many open questions
(e.g., Moser et al 2008) for definitive conclusions on its nature to be drawn.
In conclusion, additionally to characteristics derived from their common root in
neural thinking (cf. section 2.1), mental and external representations share the crucial
feature of ‘preserving the essential characteristics of K.43 The key difference between
the two kinds of representations is the potential permanence of external
representations. This is partly responsible for the uniqueness of human mind. The
next section identifies its complementary part.
2.2.2 The mental gap is within our species
25
The aim of this section is to briefly argue that WHuLa is the key characteristic of
H7kya and therefore the mental gap is within our species; Darwin’s continuity
hypothesis is sound despite recent challenges (e.g., Penn et al 2008; Premack 2007).
WHuLA is the novel result of the combination of two considerably earlier
human traits: speech and external representations. Its unprecedented power stems
from the combination of speech’s compositionality with the potential permanence of
external representations. Its continuous development, along with communication and
appropriate corresponding species actions, eventually led to the era of the
cumulatively artificial. Figure 2 depicts the both the ultimate causes of WHuLa and
the key relations among the requisite abilities and tools that contribute to the ever-
increasing development of human-made structures and systems.
Figure 2. The becoming of modern humans. Symbols are explained in text.
The processes involved are extremely complex with several multiple, time-
dependent and intra-species interactions. Some of them operate in ontogenetic time,
some in phylogenetic time (the double arrow in Figure 2 stands for reminding us of
the significance of such interactions). The following paragraphs intend only to clarify
and strengthen my claim rather than describe the posited process in any detail.
I start with a terminological point. I take writing to be a human communication
system that uses conventional visible marks. This is essentially Gelb’s (1963)
definition of writing and is substantially different from Diringer’s (1968 p. 8)
definition: [w]riting is the graphic counterpart of spoken language.” For the latter
notion I use the abbreviation WHuLa.44 Furthermore, I assume that writing has a
psychological basis and an artefactual existence.45
It is widely agreed, especially in the linguistic and anthropological communities,
that ‘human language’ is the defining characteristic of Homo sapiens (e.g., Sapir
1929; Deacon 1997; Donald 1991). Because of the established historical, functional,
and biological priority of speech over written language (Lyons 1981), the former is
subsequently considered the original defining characteristic.
I stated my disagreement and claim earlier. Here are the reasons for it. WHuLa is
transforming human mind and human society in ways that speech is, in principle,
unable to do.
Skepseis (definition-7) can be expressed in oral, sign, or written form. In the first
two cases they are either lost in the air or, at most, they may affect the state of a
close-by listener or recipient. The third case has a unique characteristic though:
relative permanence. Written skepseis are a sort of a neural fossil. They may well
outlive the person who expressed them.
In the era of the exclusively natural mind, individuals –even with the help of
complex speech- were extremely weak in terms of short-term memory although,
comparatively, very powerful in terms of long-term. The latter feature could and did
26
support traditions but no substantial philosophy, science, technology or history. The
creation of WHuLa resolves both the ephemeral and extremely limited range of short-
term memory and the restricted and potentially distorted permanence of long-term.
Consider, for instance how oral tradition while extending ontogenetic durability at the
same time eventually distorts the transmitted information (for better or worse).
WHuLA enables deeper understanding of a phenomenon, claim, or description
by enabling one to juxtapose and scrutinize ideas independently of the time and place
of their production. Such a technology allows then the transition from speech (a
capability enabling the transfer of ‘useful’ traditional knowledge among generations)
to the stage of knowledge accumulation. Finally, WHuLa enabled tool-based
reasoning in the form of mathematics and eventually KR schemes.
When skepseis are written, they can act as an Sc to any person who may read
them at any point in time. In particular, of course, they act as a stimulus to their
creator. Therefore, a feedback loop is originated that becomes a system of feedback
loops if related skepseis and the their written expressions are further created, or if the
person has ‘second thoughts’ on the precision of her translation. I call such
interactions hybrid ontogenetic loops (HOLs).
A remark concerning hybrid ontogenetic loop systems should be made here.
Clark (2008 p. xxviii), building on Clark & Chalmers (1998), claims that such
systems “are not all in the head”. He is partly right and partly wrong. He is obviously
right when he claims that human technology is enhancing human thinking. This is
indeed the case and happens through HOLs. This is a rather well known view (e.g.,
Ong 1982; Gardenfors 2003*2006). He is wrong nevertheless, in claiming that
thinking itself is literally realised externally in the form of symbolic or material re-
arrangements.46 For, the external parts of HOLs are fossilized skepseis. Without a
person to interpret and think about them, they will forever remain inert. Clark &
Chalmers (1998*2008 p. 222) write that: “If we remove the external component the
system’s behavioural competence will drop, just as it would if we removed part of its
brain.” This is true but beside the issue in hand. The question is what does happen
when there is no brain at all. And the answer is nothing at all. In HOLS, persons are
necessary for the loop to be operational; the external parts of HOLs, on their own, do
not realise any thinking at all. They exclusively record some aspects of the skepseis
of an individual.
Less general than WHuLa, but at the same time much more powerful in their
predictive and design capabilities, are the various KR schemes that modern Homo
sapiens has developed. Their invention/discovery and their further creative use by
very modern humans brought us straight into the era of the cumulatively artificial.
The era of computational systems, electron microscopes, implants, world-wide web,
and robot scientists. Still, their extreme significance and novel consequences should
not disguise the fact that, on their own, they are useless.
It follows that the structural complexity of the modern Homo sapiens is not
going to be found materialised in human brains. Not because the human mind is
immaterial –which is not. Not because part of human thinking is realised outside an
individual’s brain –which as we saw it is not. But because the development of H7kya is
causally shaped by the development of WHuLa and the associated development of
science and technology. They provide the artificial component of the nature of human
mind. Of course there large dissimilarities between human and animal cognition (e.g.,
Premack 2007), my claim is that they are due to WHuLa.
2.3. Summary
27
To facilitate commentary, the complementary Tables 2 & 3 summarize most of
the major points. The following paragraphs either clarify a particular point in the
Tables or state a major point that I could not include in them.
Table 2. Mapping of sections to primary results of TonE.
Sections
Primary results
Section 2.1.1.
Proposed theory of meaning provides empirically verifiable
conditions for delineating class of meaningful neural formations.
Neurolingusitic structures constitute substructures of M.
Proposal of the MMP.
Section 2.1.2.
Proposed theory of communication bridges the collective and
individual aspects of human action and mind in terms of ΠH that
span their full scale from the biological to the socio-historical
bands.
Continuity of human and non-human animal minds, through
partly shared ΠE (see below).
Proposal of the CUP as a psychological invariance.
Section 2.2.
WHuLa is the key characteristic of H7kya. The discontinuity is
within our species. It is caused by the development of the
artificially natural human mind.
Table 3. Rough mapping of key animal abilities to Eras and posited nervous systems.
Finally, it appears that the following words: {species, individual of species,
Earth’s biota, attention, neural formations, interaction} constitute a minimum
vocabulary (V) for the small but significant part of mental phenomena considered in
this article.
3. Open Issues
28
Of the many remaining open issues the following seem to me among the most
important. First, there is the problem of the appropriate formulation of a ‘mental
phenomenon’. If the theory proposed here is accepted a good number of accepted
distinctions will cease to exist and a significant number of new problems will appear.
Among the latter probably the most important is the task of understanding more
thoroughly and deeply the extremely complex interactions between the social and
biological aspects of humans as well as the much more difficult tasks of the relations
among human communities and the emerging new era of the artificial. Among the
former, it seems that the mind-body problem will be the first that will have to be
abandoned with a domino-effect ramifications.
Second, there is the issue of the suitability of our current tools for developing a
theory of individuals as parts of noémona species. It seems to me that most current
mathematics is inadequate for such an endeavour. The precision of equations and
computational systems is at odds with the precise vagueness of the mammalian
nervous system. To describe the M and ΠH structures, as well as the systems of
fundamental processes and associated loops identified earlier, ‘the mathematics of
thinking and communication’ is required. This is a branch of knowledge humans have
not yet developed. It is always good to be kept in brain that even order is not a
prerequisite for phenomena like emotion. As James (1890, Vol.2, p. 146) factually
remarked: “Different feelings may coexist in us without assuming any particular
spatial order.” I would therefore urge that for the foreseeable future the methodology
outlined in the introduction is to be preferred to the usual mathematical tools
employed. Development of a fully-fledged language-based definitional system
compatible with as many field-wide empirical data and regularities as possible seems
the best way to proceed in the present state of the art. This may be one way towards
‘the mathematics of thinking and communication’. Assuming that such mathematics
is possible.
Third, there is a need to try to identify invariant laws for cognitive science.
Simon (1990) has elevated this objective to the status of the fundamental goal of
science and has suggested two laws of qualitative structure and four quantitative
findings as invariants. Newell (1990) strongly believes that the computer hierarchy is
an invariant law. Nevertheless, the issue is far from straightforward. Relations to
universals and classification are just two of these.47
Fourth, cognitive science needs a minimum vocabulary to serve as its descriptive
base. The one proposed in the previous section may be taken as a first step. An
appropriate V must be able to account for at least the following areas of an
augmented cognitive science: knowledge, consciousness, emotion, culture,
motivation, ethical values, and beauty. It appears that consciousness and knowledge
may be explainable in terms of the theory proposed here. To demonstrate such a
hunch and modify or not V is the major task I intend to address next.
Fifth, mental neuroscience needs to map observed types of NS complexity to
fundamental animal abilities and semantic structures (M). In speculative mode, I posit
several such types in Table 3. Empirical evidence may collapse/expand some of the
posited types. Their rough correspondence to fundamental animal abilities and loops
may help the design of neuroscientific experiments.
Finally, as a community, we should pay careful consideration in the emergence
of, and the consequences brought by, the era of the artificial. Definitely, it is not an
exclusively cognitive science issue; not even of an augmented cognitive science. It is
also a political and most importantly an ethical issue. All the more so, that we need to
pay very careful attention to it.
29
Acknowledgements
I thank Yiannis Kontos for the encouragement and the discussions we had, Mike
Elstob for his detailed and politely incisive comments that made me to nearly fully
rewrite a first draft, Nick Shea for his helpful comments, and Peter Hacker for the
spirited and valuable philosophical discussions and the year-long invitation to St
John’s College, Oxford; a unique experience I will always cherish.
References
Abbott, L. F. (2006) Where are the Switches on this Thing? In: 23 Problems in
Systems Neuroscience, ed. J. L. van Hemmen & T. J. Sejnowski, pp. 423-31.
Oxford University Press.
Abbott, L. F. (2008) Theoretical Neuroscience Rising. Neuron 60: 489-495.
Adler, R. B., and Rodman, G. (2000). Understanding Human Communication.
Harcourt College Publishers, NY.
Agassi, J. (2003) Newell’s list. Behavioral and Brain Sciences, 26:601-2.
Cambridge University Press.
Allen, N. J., & Barres, B. A. (2009) Glia – More than just Brain Glue. Nature,
457:675-7.
Anderson, J. R. (1983) The Architecture of Cognition. Harvard University Press.
Anderson, J. R. (1987) Methodologies for studying human knowledge. Behavioral
and Brain Sciences, 10: 467-505.
Anderson, J. R. (1990) The Adaptive Character of Thought. Hillsdale, NJ: Lawrence
Erlbaum Associates.
Anderson, J. R. (1993) Rules of the Mind. Lawrence Erlbaum Associates, Inc.
Anderson, J. R. (2007a) How Can the Human Mind Occur in the Physical Universe?
Oxford University Press.
Anderson, J. R. (2007b) The image of complexity. In: The 29th Annual Conference of
the Cognitive Science Society. Nashville, Tennessee, USA.
Anderson, J. R., & Lebiere C. (1998) The atomic components of thought. Erlbaum,
N.J, USA.
Anderson, J. R., & Lebiere, C. L. (2003) The Newell test for a theory of cognition.
Behavioral & Brain Sciences, 26:587-637.
Anderson, J. R., Bothell, D., Dyrne, M. D., Douglass, S., Lebiere, C., & Qin, Y.
(2004). An Integrated Theory of the Mind. Psychological Review, 111:1036-60.
Aristotle (4th BCE*1984). The Complete Works of Aristotle. The Revised Oxford
Translation. Edited by Jonathan Barnes. Princeton University Press.
Arkin, R. C. (1990) The Impact of Cybernetics on the Design of a Mobile Robot
System: A case study. IEEE Transactions on Systems, Man and Cybernetics, 20:
1245-57.
Arlington, J. W., & Baird, J. A. ed. (2005) Why Language matters for Theory of
Mind. Oxford University Press.
Ashby, F. G., Isen, A. M., & Turken, A. U. (1999) A neuropsychological theory of
positive effect and influence on cognition. Psychological Review, 106:529-50.
Awh, A., Vogel, E. K., & Oh, S.-H. (2006) Interactions between Attention and
Working Memory. Neuroscience, 139:201-08.
Aylwin, S. (1985) Structure in Thought and Felling. Routledge.
Bach, K. (1994). Conversational Impliciture. Mind & Language, 9(2):124-62.
30
Bach, K. (1999). Meaning. In: The MIT Encyclopedia of the Cognitive Sciences, ed.
R. A. Wilson, & F. C. Keil, pp. 513-4. The MIT Press.
Baddeley, A. (2003) Working Memory: Looking Back and Looking Forward. Nature
Reviews, Neuroscience, 4:829-39.
Barnier, A. J. & Sutton, J. (2008) From individual to collective memory: Theoretical
and empirical perspectives. Memory, 16(3):177-82.
Barres, B. A. (2008) The mystery and magic of glia: A perspective on their roles in
health and disease. Neuron, 60:430-40.
Barton, D. & Hamilton, M. (1996) Social and cognitive factors in the historical
elaboration of writing. In: Handbook of Human Symbolic Evolution, ed. A. Lock,
& C. R. Peters, pp. 793-858. Clarendon Press, Oxford.
Bates, L. A., Sayialel, K. N., Njirani, N. W., Moss, C. J., & Poole, J. H. (2007)
Elephants Classify Human Ethnic Groups by Odor and Garment Color. Current
Biology, 17:1938-42.
Bechtel, W. (1998). Representations and cognitive explanations: Assessing the
dynamicist’s challenge in cognitive science. Cognitive Science, 22:295-318.
Bechtel, W., & Graham, G., eds. (1998) A Companion to Cognitive Science.
Blackwell Publishers Ltd.
Bennett, M. (2007) Neuroscience and Philosophy. In: Neuroscience and Philosophy:
Brain, Mind, and Language, ed. M. Bennett, D. Dennett, P. Hacker, & J. R.
Searle, pp. 49-69. Columbia University Press.
Benowitz, L. I., Bear, D. M., Mesulam M-M., Rosenthal, R., Zaidel, E., and Sperry,
R. W. (1984*1985) Contributions of the right cerebral hemisphere in perceiving
paralinguistic cues of emotion. In: Cognitive Constraints on Communications:
Representation and Processes, ed. J. Hintikka, & L. Vaina. D. Reidel Publishing
Company.
Bickerton, D. (1990). Language and species. University of Chicago Press.
Blakemore, S-J., Wolpert, D. M., & Frith, C. D. (2002) Abnormalities in the
awareness of action. Trends in Cognitive Sciences, 6:237-42.
Boden, M. (1992) The Creative Mind: Myths and Mechanisms. Cardinal, London.
Boden, M. A. (1994) New breakthroughs or dead-ends? Philosophical Transactions
of the Royal Society A, 349:1-13.
Bollmann, J. H. & Engert F. (2009) Subcellular Topography of Visually Driven
Dendritic Activity in the Vertebrate Visual System. Neuron, 61:895-905.
Bookheimer, S. (2002) Functional MRI of Language: New Approaches to
Understanding the Cortical Organization of Semantic Processing. Annual Review
of Neuroscience. 25:151-88.
Borst, C. V. ed. (1970) The Mind/Brain Identity Theory. Macmillan Publishers Ltd.
Bowers, J. S. (2009) On the Biological Plausibility of Grandmother Cells:
Implications for Neural Network Theories in Psychology and Neuroscience.
Psychological Review, 116, 1, 220-51.
Broadbent, D. E. (1985) A question of levels: Comments on McClelland and
Rumelhart. Journal of Experimental Psychology: General, 114:189-92.
Brooks, R. A. (1991) Intelligence without representation. Artificial Intelligence, 47:
139-59.
Brown, D. E. (1991) Human Universals. McGraw Hill.
Bunge, M. (1980) The Mind-Body Problem: A Psychobiological Approach.
Pergamon Press.
Chalmers, D. J. ed. (2002) Philosophy of Mind: Classical and Contemporary
Readings. Westview Press, Oxford.
31
Changeux, J-P. (1983*1985) Neuronal Man: The Biology of Mind. Trans. by L.
Garey. Oxford University Press.
Changeux, J-P. & Dehaene, S. (1989) Neuronal models of cognitive functions.
Cognition, 33:63-109.
Cherry, C. (1978*1980) On Human Communication: A Review, a Survey, and a
Criticism. Third Edition. The MIT Press.
Chomsky, N. (1965) Aspects of the theory of syntax. MIT Press, Cambridge, Mass.
Chomsky, N. (1980a) Rules and Representations. Columbia University Press.
Chomsky, N. (1980b) Author’s Response. The Behavioral and Brain Sciences. 3:42-
58.
Chomsky, N. (1995) Language and Nature. Mind 104:1-61.
Clark, A. (2008) Supersizing the Mind: Embodiment, Action, and Cognitive
Extension. Oxford University Press.
Clark, A. & Toribio, J. (1994) Doing without representing? Synthese, 101:401-31.
Clark, A., and Chalmers, D. (1998) The extended mind. Analysis, 58:7-19.
Cobley, P. ed. (1996) The Communication Theory Reader. Routledge.
Collins, A. M. & Loftus, E. F. (1975) A spreading activation theory of semantic
memory. Psychological Review, 82:407-28.
Collins, A. M. & Quillian, M. R. (1969) Retrieval time from semantic memory.
Journal of Verbal Learning and Verbal Memory, 8:240-7.
Connor, R. C. (2007). Dolphin social intelligence: complex alliance relationships in
bottlenose dolphins and a consideration of selective environments for extreme
brain size evolution in mammals. Philosophical Transactions of the Royal
Society B, 362:587-602.
d’Ettorre, P. & Hughes, D. P., eds. (2008) Sociobiology of Communication: An
interdisciplinary perspective. Oxford University Press.
Darwin, C. (1871*1981) The Descent of Man, and Selection in relation to Sex.
Princeton University Press. Introduction by J. T. Bonner & M. May.
Dautenhahn, K. (2007) Socially intelligent robots: dimensions of human-robot
interaction. Philosophical Transactions of the Royal Society B, 362:679-704.
Davidson, D. (1967) Truth and Meaning. Synthese, 17:304-23.
Davidson, D. (1973) Radical interpretation. Dialectica, 27:313-28.
Davidson, D. (1974) Belief and the basis of meaning. Synthese, 27:309-23.
Davidson, D. (1999) The emergence of thought. Erkenntnis, 51:7-17.
Davidson, D. (2001) What Thought Requires. In: The foundations of cognitive
science, ed. J. Branquinho, pp. 121-32. Oxford University Press.
Dennett, D. C. (1969) Content and Consciousness. Routledge & Kegan Paul,
London.
Dennett, D. C. (1978) Why you Can't Make a Computer That Feels Pain. Synthese,
38:415-56.
Dietrich, E. (2007). Representation. In: Philosophy and Psychology of Cognitive
Science, ed. P. Thagard. Elsevier.
Dilthey, (1900*1976). The development of hermeneutics. In: Selected Writings, ed.
H. P. Pickman, Cambridge University Press.
Dimbleby, R., & Burton, G. (1998) More Than Words: An Introduction to
Communication, 3rd edition. Routledge.
Diringer, D. (1968) The alphabet: A key to the history of mankind, 3rd edition.
Hutchinson, London.
Dretske, F. I. (1981). Knowledge and the Flow of Information. Oxford, Blackwell.
Dummett, M. (1973) Frege: Philosophy of Language. Duckworth, London.
32
Duncan, S. (1999). Language and Communication. In: The MIT Encyclopedia of the
Cognitive Sciences, ed. R. A. Wilson, & F. C. Keil, pp. 438-41. The MIT Press.
Edelman, G. M. (1987) Neural Darwinism: The Theory of Neuronal, Group
Selection. Basic Books, NY.
Edelman, G. M., & Mountcastle, V. B. (1978) The Mindful Brain: Cortical
Organization and the Group-selective Theory of Higher Brain Functions. The
MIT Press.
Emery, N. J., & Clayton, N. S. (2008) Imaginative scrub-jays, causal rooks, and a
liberal application of Occam’s aftershave. Behavioral and Brain Sciences,
31:134-5.
Fitch, W. T., Hauser, M. D., Chomsky, N. (2005). The evolution of the language
faculty: Clarifications and implications. Cognition, 97:179-210.
Fodor, J. A. (1975) The Language of Thought. Harvard University Press.
Fodor, J. A. (1980) Methodological solipsism considered as a research strategy in
cognitive psychology. Behavioral and Brain Sciences, 3:63-109.
Fodor, J. A. (1983) The Modularity of Mind. The MIT Press.
Fodor, J. A. (1994) Concepts- a pot boiler. Cognition 50:95-113.
Freeman, W. J. (1975) Mass Action in the Nervous System. Academic Press.
Freeman, W. J. (1999) How brains make up their minds. Phoenix, London.
Gärdenfors, P. (2003*2006). How Homo Became Sapiens: On the Evolution of
Thinking. Oxford University Press.
Gelb, I. J. (1963) A study of writing, 2nd edition. University of Chicago Press.
Gelepithis, P. A. M. (1984) On the Foundations of Artificial Intelligence and Human
Cognition. Ph.D. Thesis, Brunel University, England.
Gelepithis, P. A. M. (1988) Survey of Theories of Meaning. Cognitive Systems,
2:141-62.
Gelepithis, P. A. M. (1989) Knowledge, Truth, Time, and Topological spaces.
Proceedings of the 12th International Congress on Cybernetics, 247-56.
Gelepithis, P. A. M. (1991) The possibility of Machine Intelligence and the
impossibility of Human-Machine Communication. Cybernetica, XXXIV:255-68.
Gelepithis, P. A. M. (1992) True invariants: A response to Herbert Simon.
Proceedings of the 13th International Congress on Cybernetics, 424-28.
Gelepithis, P. A. M. (1999) Embodiments of theories of mind: A review and
comparison. In: Computational Methods and Neural Networks, ed. M. P.
Bekakos, M. Sambandham, & D. J. Evans, pp. 235-64, Dynamic Publishers, Inc,
Atlanta, Georgia, USA.
Gelepithis, P. A. M. (2003) Criteria and Evaluation of Cognitive Theories.
Behavioral and Brain Sciences, 26:607-09.
Gelepithis, P. A. M. & Goodfellow, R. (1992) An alternative architecture for
intelligent tutoring systems: Theoretical and Implementational Aspects.
Interactive Learning International, 8:171-75.
Gintis, H. 2007. A framework for the unification of Behavioral sciences. Behavioral
and Brain Sciences, 30:1-61.
Gleitman, L. & Papafragou, A (2005) Language and Thought. In: The Cambridge
Handbook of Thinking and Reasoning, ed. K. J. Holyoak & R. G. Morrison, pp.
633-61. Cambridge University Press.
Goldberg, S. D. ed. (2007) Internalism and Externalism in Semantics and
Epistemology. Oxford University Press.
33
Greeno, J. G. (1977). Process of Understanding in Problem Solving. In: Cognitive
Theory Vol. 2, ed. N. J. Castellan Jr, D. B. Pisoni, & G. R. Potts, pp. 43-83.
Laurence Erlbaum Associates.
Grice, H. P. (1957) Meaning. Philosophical Review 66:377-88.
Grice, H. P. (1968) Utterer's Meaning, Sentence-Meaning and Word-Meaning.
Foundations of Language, 4:225-42.
Grice, H. P. (1969) Utterers Meaning and Intentions. Philosophical Review, 78:147-
77.
Grossberg, S. & Kuperstein, M. (1989) Neural dynamics of adaptive sensory-motor
control: Expanded edition. Pergamon Press.
Habermas, J. (1981*1984) The Theory of Communicative Action, Vol. 1. Polity Press.
Habermas, J. (1987) The Theory of Communicative Action, Vol. 2. Polity Press.
Halliday, T. R. & Slater, P. J. B. ed. (1983) Animal Behaviour: Volume 2
Communication. Blackwell.
Hauser, M. and Marler, P. (1999) Animal Communication. In: The MIT
Encyclopedia of the Cognitive Sciences, ed. R. A. Wilson, & F. C. Keil, pp. 22-
24. The MIT Press.
Hauser, M. D. (1996) The Evolution of Communication. MIT Press.
Hauser, M. D., Chomsky, N., Fitch, W.T. (2002). The Faculty of Language: What Is
It, Who Has It, and How Did It Evolve? Science, 298:1569-79.
Hebb, D. O. (1949) The Organisation of Behaviour. John Wiley and Sons.
Hebb, D. O. (1968) Concerning Imagery. Psychological Review, 75:466-77.
Hebb, D. O. (1976) Physiological learning theory. Journal of Abnormal Child
Psychology, 4:309-14.
Hebb, D. O. (1980a) Essay on Mind. Lawrence Erlbaum Associates.
Hebb, D. O. (1980b) The structure of thought. In: The Nature of Thought: Essays in
honor of D. O. Hebb, ed. P. W. Jusczyk & R. M. Klein, pp. 19-35. Laurence
Erlbaum Associates.
Heisenberg, W. (1958*1989) Physics and Philosophy: The Revolution in Modern
Science. Penguin Books.
Herman, L. M., Richards, D. G. & Wolz, J. P. (1984) Comprehension of sentences by
bottlenosed dolphins. Cognition, 16:129-219.
Heyes, C. M. (1998) Theory of mind in nonhuman primates. Behavioral and Brain
Sciences, 21:01-48.
Holyoak, K. J., & Morrison, R. G. (2005b) Thinking and Reasoning: A Reader’s
Guide. In: The Cambridge Handbook of Thinking and Reasoning, ed. K. J.
Holyoak, & R. G. Morrison, pp. 1-9. Cambridge University Press.
Holyoak, K. J., & Morrison, R. G. ed (2005a) The Cambridge Handbook of Thinking
and Reasoning. Cambridge University Press.
Hume, D. (1758*1977) An Inquiry Concerning Human Understanding. Bobbs-Merill
Co., U.S.A.
Hunt, E. (1989) Cognitive Science: Definition, Status, and Questions. Annual Review
of Psychology, 40:603-29.
Hurford, J. R. (2003) The neural basis of predicate-argument structure. Behavioral
and Brain Sciences 26:261-316.
Jackendoff, R. (2002) Foundations of language: Brain, meaning, grammar,
evolution. Oxford University Press.
Jackendoff, R. (2003) Précis of Foundations of Language: Brain, Meaning,
Grammar, Evolution. Behavioral and Brain Sciences, 26:651-65.
34
James, W. (1890) The Principles of Psychology, Vol. 1 & 2. Authorised edition by
Dover Publications.
Jeannerod, M. (2006) Motor Cognition: What Actions Tell the Self. Oxford
University Press.
Johnson-Laird P. N. (1977) Procedural Semantics. Cognition, 5:189-214.
Johnson-Laird, P. N. (1993). Human and Machine Thinking. LEA.
Johnson-Laird, P. N. (2003). Models, Causation, and Explanation. In: The Nature
and Limits of Human Understanding, ed. A. J. Sanford. T&T Clark, London.
Johnson-Laird, P. N. (2005) Mental Models and Thought. In: The Cambridge
Handbook of Thinking and Reasoning, ed. K. J. Holyoak, & R. G. Morrison, pp.
185-208. Cambridge University Press.
Johnston, W. A., & Dark, V. J. (1986) Selective Attention. Annual Reviews of
Psychology, 37:43-75.
Just, M. A. & Carpenter, P. A. 1987. The Psychology of Reading and Language
Comprehension. Blackwell.
Kandel, E. R. (2006) In Search of Memory: The Emergence of a New Science of
Mind. W. W. Norton & Company.
Kandel, E. R., & Pittinger, C. (1999) The past, the future and the biology of memory
storage. Philosophical Transactions of the Royal Society B, 354:2027-52.
Katz, E., and Danet, B. (1973) Communication Between Bureaucracy and the Public:
A Review of the Literature. In: Handbook of Communication, ed. I. S. Pool, F.
W., Frey, W., Schramm, N., Maccoby, & E. B., Parker. Rand McNally College
Publishing Company.
Katz, J. J. (1972). Semantic Theory. Harper and Row Publishers, NY.
Katz, J. J. & Fodor, J. A. (1963) The structure of a semantic theory. Language
39:170-210.
Kelso, J. A. S. (1995) Dynamic Patterns: The self-organization of brain and
behavior. The MIT Press.
Knudsen, E. I. (2007) Fundamental Components of Attention. Annual Review of
Neuroscience, 30:57-78.
Koch, C. (1999) Computing in Single Neurons. In: The MIT Encyclopedia of the
Cognitive Sciences, ed. R. A. Wilson and F. C. Keil pp. 174-76. The MIT Press.
Koch, S. (1981) The Nature and Logic of Psychological Knowledge: Lessons of a
Century qua “Science”, American Psychologist, 36:257-69.
Köhler, W. (1925) The Mentality of Apes. Routledge & Kegan Paul, London.
Krystal, J. H., Bennett, A. L., Bremner, F. D. , Southwick, S. M., & Charney, D. S.
(1995) Toward a Cognitive Neuroscience of Dissociation and Altered Memory
Functions in Post-trautmatic Stress Disorder. In: Neurobiological and Clinical
Consequences of Stress: From Normal Adaptation of Post-Traumatic Stress
Disorder, ed. M. J. Friedman, D. S. Charney, & A. Y. Deutch, pp. 239-69.
Lippincott-Raven.
Kurto, K., & Itskov, V. (2008) Cell Groups Reveal Structure of Stimulus Space.
PLOS Computational Biology, 4:1-13.
Lefebvre, L., Reader, S. M., and Sol, D. (2004) Brains, Innovations and Evolution in
Birds and Primates. Brain, Behavior and Evolution, 63:233-46.
Lepore, E., & Smith, B. C., eds (2006) The Oxford Handbook of Philosophy of
Language. Clarendon Press, Oxford.
Litman, L. & Reber, A. S. (2005) Implicit Cognition and Thought. In: The
Cambridge Handbook of Thinking and Reasoning, ed. K. J. Holyoak, & R. G.
Morrison, pp. 431-53. Cambridge University Press.
35
Loar, B. (1999) Meaning. In: The Cambridge Dictionary of Philosophy, 2nd edition,
ed. R. Audi, pp. . Cambridge University Press.
Locke, J. (1690*1975) An Essay concerning human understanding. Oxford
University Press.
Logan, R. K. (2007) The Extended Mind: The Emergence of Language, the Human
Mind, and Culture. The University of Toronto Press.
Longman (1987) Dictionary of Contemporary English, 2nd edition, The Longman
Group.
Lurz, R. W. (2007) In Defense of Wordless Thoughts About Thoughts. Mind &
Language, 22: 270-96.
Lyons, J. (1981) Language and Linguistics. Cambridge University Press.
Macdonald, G., and Papineau, D. eds. (2006). Teleosemantics: New Philosophical
Essays. Oxford University Press.
Margolis, E., & Lawrence, S. (2007) The Ontology of Concepts- Abstract Objects or
Mental Representations? Noûs, 41(4):561-93.
Markson, L., & Bloom, P. (1997). Evidence against a dedicated system of word
learning in children. Nature, 385:813-15.
Markus, H. R. & Kitayama, S. (1991) Culture and the Self: Implications for
Cognition, Emotion, and Motivation. Psychological Review, 98:224-53.
Matessi, G., Matos, R. J., & Dabelsteen, T. (2008) Communication in social
networks of territorial animals: networking at different levels in birds and other
systems. In: Sociobiology of Communication: An interdisciplinary perspective,
ed. P. d’Ettorre, & D. P. Hughes, pp. 33-53. Oxford University Press.
Mattelart, A., and Mattelart, M. (1995*1998). Theories of Communication: A Short
Introduction, trans. Taponier, S. G., and Cohen, J. A. SAGE Publications Ltd.
Maynard Smith, J. & Harper, D. (2003) Animal Signals. Oxford University Press.
Mayr, E. (2004) What Makes Biology Unique? Considerations on the Autonomy of a
Scientific Discipline. Cambridge University Press.
Mead, G. H. (†1934*1962) Mind, Self and Society: From the Standpoint of a Social
Behaviorist. University of Chicago Press.
Medin, D. L., and Rips, L. J. (2005). Concepts and Categories: Memory, Meaning,
and Metaphysics. In: The Cambridge Handbook of Thinking and Reasoning, ed.
K. J. Holyoak, & R. G. Morrison, pp. 37-72. Cambridge University Press.
Messer, D. I. (1994). The Development of Communication: From Social Interaction
to Language. John Wiley & Sons.
Millikan, R. (1984) Language, Thought, and Other Biological Concepts. MIT Press.
Millikan, R. (1998) A common structure for concepts of individuals, stuffs and real
kinds: More Mama, more milk and more mouse. Behavioral and Brain Sciences,
21:55-100.
Molden, D. C., & Higgins, E. T. (2005) Motivated Thinking. In: The Cambridge
Handbook of Thinking and Reasoning, ed. K. J. Holyoak, & R. G. Morrison, pp.
295-317. Cambridge University Press.
Moll, H. & Tomasello, M. (2007). Cooperation and human cognition: the Vygotskian
intelligence hypothesis. Philosophical Transactions of the Royal Society B,
362:639-48.
Monge, P. R. (1977) The systems perspective as a theoretical basis for the study of
human communication. Communication Quarterly, Vol. 25.
Moravcsik, J. M. (1979). Understanding. Dialectica, 33: 201-16.
36
Moser, E. I., Kropff, E., & Moser, M-B. (2008) Place Cells, Grid Cells and the
Brain’s Spatial Representation System. Annual Review of Neuroscience, 31:69-
89.
Mottet, T., Richmond, V. & McCroskey, J. eds (2006) Handbook of instructional
communication. Pearson, Boston.
Murray, J. (1998). Information, Communication and Technology- What can second
order cybernetics contribute to the literate debate. In: Cybernetics & Human
Knowing, 5:43-57.
Newell, A. (1980) Physical symbol systems. Cognitive Science, 4:135-83.
Newell, A. (1990) Unified theories of cognition. Harvard University Press.
Newell, A. (1992) Précis of Unified theories of cognition. Behavioral and Brain
Sciences,15:425-492.
Newell, A., & Simon, H. A. (1972) Human Problem Solving. Prentice Hall.
Newell, A., & Simon, H. A. (1976) Computer Science as Empirical Enquiry:
Symbols and Search. Communications of the ACM, 19:113-26.
Newen, A. & Bartels, A. (2007) Animal Minds and the Possession of Concepts.
Philosophical Psychology, 20:283-308.
Nilsson, N. J. (1991) Logic and Artificial Intelligence. Artificial Intelligence, 47:31-
56.
Norman, M. D., Finn, J., and Tregenza, T. (2001) Dynamic mimicry of an Indo-
Malayan octopus. Proceedings of the Royal Society London B, 268:1755-8.
Nummenmaa, L., & Calder A. J. (2009) Neuronal mechanisms of social attention.
Trends in Cognitive Science, 13:135-43.
O’Brien, G., & Opie, J. (2004) Notes Toward a Structuralist Theory of Mental
Representation. In: Representation in Mind: New Approaches to Mental
Representation, ed. H. Clapin, P. Staines, & P. Slezak, pp 1-20. Elsevier.
O’Keefe, J. & Dostrovsky, J. (1971) The hippocampus as a spatial map: Preliminary
evidence from unit activity in the freely moving rat. Brain Research, 34:171-5.
Ogden, C. K., & Richards, I. A. (1923*1956) The Meaning of Meaning. In: The
Meaning of Meaning: A Study of The Influence of Language upon Thought and
of The Science of Symbolism. Harcourt Brace and Co.
Ong, W. J. (1982) Orality and Literacy. Routledge.
Osgood, C. E. (1971) Where do sentences come from? In: Semantics. D. D.,
Steinberg & L. A. Jakobovits eds. Cambridge University Press.
Osgood, C. E. & McGuigan, F. J. (?*1973) Psychological correlates of meaning:
Essences or tracers? In: The Psychophysiology of thinking, ed. F. J. McGuigan &
Schooner. Academic Press.
Pask, A. G. S. (1976) Conversation, Cognition and Learning: a cybernetic theory
and methodology. Elsevier.
Peacocke, C. (1992) A Study of Concepts. The MIT Press.
Peacocke, C. (2001). Theories of Concepts: A Wider Task. In: The foundations of
cognitive science, ed. J. Branquinho, pp. 157-81. Oxford University Press.
Penn, D. C., Holyoak, K. J., & Povinelli, D. J. (2008) Darwin’s mistake: Explaining
the discontinuity between human and nonhuman minds. Behavioral and Brain
Sciences, 31:109-178.
Pepperberg, I. (1999) The Alex Studies. Harvard University Press.
Pool, I. S., Frey, F. W., Schramm, W., Maccoby, N., and Parker, E. B., eds. (1973)
Handbook of Communication. Rand McNally College Publishing Company.
Posner, M. I., & Peterson, S. E. (1990) The Attention System of The Human Brain.
Annual Review of Neuroscience, 13:25-42.
37
Postle, B. R. (2006) Working Memory as an Emergent Property of the Mind and
Brain. Neuroscience, 139:23-38.
Premack, D. (1985) “Gavagai!” or the future history of the animal language
controversy. Cognition, 19:207-96.
Premack, D. (2007) Human and animal cognition: Continuity and discontinuity.
Proceedings of the National Academy of Sciences of the USA, 104:13861-7.
Putnam, H. (1988). Representation and Reality. The MIT Press.
Putnam, L. L. (1983). The interpretive perspective: An alternative to functionalism.
In: Communication and Organizations: An Interpretive Approach, ed. L. L.
Putnam and M. E. Pacanowsky.
Ramsey, W. (2003) Are receptors representations? Journal of Experimental and
Theoretical Artificial Intelligence, 15:125-41.
Ramsey, W. M. (2007). Representation Reconsidered. Cambridge University Press.
Reynolds, J. H. & Heeyer, D. J. (2009) The Normalization Model of Attention.
Neuron, 61: 168-85.
Ricoeur, P. (1981) The task of hermeneutics. In: Hermeneutics and the human
sciences. J. B. Thompson ed. Cambridge University Press, and Maison des
Sciences de l' Homme.
Rizzolatti, G. & Sinigaglia, C. (2006) Mirrors in the Brain-How Our Minds Shape
Actions and Emotions. Oxford University Press.
Roberts, D. F. (1973). Communication and Children: A Developmental Approach.
In: Handbook of Communication, ed. I. S. Pool, F. W., Frey, W., Schramm, N.,
Maccoby, and E. B., Parker. Rand McNally College Publishing Company,
Chicago.
Roediger, H. L. (2008) Relativity of Remembering: Why the Laws of Memory
Vanished. Annual Review of Psychology, 59:225-54.
Rogers, T. T., & McClelland, J. L. (2008) Précis of Semantic Cognition: A Parallel
Distributed Approach. Behavioral and Brain Sciences, 31, pp. 689-749.
Rumelhart, D. E., & McClelland, J. L. (1985b) Levels Indeed! A Response to
Broadbent. Journal of Experimental Psychology: General, 114:193-97.
Runcan, A. (1985). Towards a Logical Model of Dialogue. In: Cognitive Constraints
on Communications: Representation and Processes, ed. J. Hintikka, and L.
Vaina. D. Reidel Publishing Company.
Russell, B. (1905*1969) On denoting. In: Problems in the Philosophy of Language,
T. M. Olshewsky, ed. Holt, Rinehart and Wilson, NY.
Russell, B. (1919*1971) Descriptions. In: Readings in the Philosophy of Language.
Rosenberg and C. Travis eds. Prentice Hall.
Russell, B. (1921). The Analysis of Mind. Allen & Unwin.
Russell, B. (1948). Human knowledge: its scope and limits. George Allen and
Unwin.
Sakarya, O., Armstrong, K. A., Adamska, M. Adamski, M., Wang, I-F., Tidor, B.,
Degnan, B. M., Oakley, T. H., & Kosik, K. S. (2007) A Post-Synaptic Scaffold
at the Origin of the Animal Kingdom. PLoS ONE, 6, e506:1-9.
Sanford, A. J. ed. (2003) The Nature and Limits of Human Understanding. T&T
Clark.
Sapir, E. (1929) The Status of Linguistics as a Science. Language, 5:207-14.
Sass, L. A. (1984*1985) Parental Communication Deviance and Schizophrenia: A
Cognitive-Developmental Analysis. In: Cognitive Constraints on
Communications: Representation and Processes, ed. J. Hintikka, and L. Vaina.
Reidel Publishing Company.
38
Saul, J. M. (2002) Speaker meaning, what is said, and what is implicated. Noûs, 36,
228-48.
Saussure, F. de (2006) Writings in General Linguistics. Oxford University Press.
Savage-Rambaugh, S., Shanker, S. G. & Taylor, T. J. (1998) Apes, Language, and
the Human Mind. Oxford University Press.
Schank, R. C. (1972) Conceptual dependency: A theory of natural language
understanding. Cognitive Psychology 3:552-631.
Schirato, T., & Yell, S. (2000). Communication and Culture: An Introduction. Sage
Publications.
Schmandt-Besserat, D. (1980) The Envelopes that Bear the First Writing. Technology
and Culture, 21(3):357-85.
Schramm, W. (1973) Channels and Audiences. In: Handbook of Communication, ed.
I. S. Pool, F. W., Frey, W., Schramm, N., Maccoby, and E. B., Parker. Rand
McNally College Publishing Company.
Schyns, P. G., Goldstone, R. L., Thibaut, J-P. (1998) The development of features in
object concepts. Behavioral and Brain Sciences, 21:1-54.
Scott, B. (1996) Inadvertent Pathologies of Communication in Human Systems.
Kybernetes, 26:824-36.
Searle, J. R. (1992) The Rediscovery of the Mind. The MIT Press.
Searle, J. R. (1999a*2000) Mind, Language and Society: Philosophy in the Real
World. Phoenix.
Searle, J. R. (2007) Putting Consciousness Back in the Brain: Reply to Bennett and
Hacker, Philosophical Foundations of Neuroscience. In: Neuroscience and
Philosophy: Brain, Mind, and Language, ed. M. Bennett, D. Dennett, P.
Hacker, & J. R. Searle, pp. 97-124. Columbia University Press.
Shannon C., & Weaver, W. (1949) The Mathematical Theory of Communication.
University of Illinois Press.
Shettleworth, S. J. (1998) Cognition, Evolution, and Behavior. Oxford University
Press.
Silverberg, A (2003) Psychological Laws. Erkenntnis, 58:275-302.
Simon, H. A., (1990) Invariants of human behavior. Annual Review of Psychology,
41:1-19.
Sirois, S. (2003) Rethinking learning and development in the Newell Test.
Behavioral and Brain Sciences, 26: 619-20.
Slater, P. J. B. (1983) The Study of Communication. In: Animal Behaviour: Volume
2 Communication, ed. T. R. Halliday, & P. J. B. Slater, pp. 9-42. Blackwell.
Smith, A. G., ed. (1966) Communication and Culture: Readings in the codes of
human interaction. Holt, Rinehart and Winston, Inc.
Smolensky, P. & Legendre, G. (2006) The Harmonic Mind: From neural
computation to optimality-theoretic grammar. Volume 1: cognitive architecture.
The MIT Press.
Speaks, J. (2008) Conversational Implicature, Thought, and Communication. Mind &
Language, 23:107-22.
Sperber, D., & Wilson, D. (1995) Relevance: Communication and Cognition, 2
nd
edition. Blackwell Publishing.
St. John, M., and McClelland, J. (1990) Learning and applying contextual constraints
in sentence comprehension. Artificial Intelligence 46:217-57.
Staats, A. W. (1981) Paradigmatic Behaviourism, Unified Theory, Unified Theory
Construction Methods, and the Zeitgeist of Separatism. American Psychologist,
36:239-56.
39
Staats, A. W. (1999) Unifying Psychology Requires New Infrastructure, Theory,
Method, and a Research Agenda. Review of General Psychology, 3:1-13.
Stanyer, J. (2007) Modern Political Communication. Polity Press, Cambridge, Mass.
Stevenson, C. L. (1944) Ethics and Language. New Haven.
Stich, S. (1978). Autonomous psychology and the belief-desire thesis. Monist
61:573-91.
Stufflebeam, R. S. (1998) Representation and Computation. In: A Companion to
Cogntive Science, ed. W. Bechtel, & G. Graham, pp. 636-48. Blackwell.
Sulkowski, G. M. & Hauser, M. D. (2001) Can rhesus monkeys spontaneously
subtract? Cognition, 79:239-62.
Sun, R. (2002) Duality of the mind: A bottom-up approach toward cognition.
Erlbaum.
Sutton, J. (2004) Representation, Reduction, and Interdisciplinarity in the Sciences of
Memory. In: Representation in Mind: New Approaches to Mental Representation,
ed. H. Clapin, P. Staines, & P. Slezak, pp 187-216. Elsevier Ltd.
Taatgen, N. A. (2003). Poppering the Newell Test. Behavioral and Brain Sciences,
26:621-2. Cambridge University Press.
Tarski, A. (1944*1969) The semantic conception of truth. In: Problems in the
Philosophy of Language, ed. T. M. Olsewsky. Holt, Rinehart and Wilson, New
York.
Taylor, A. H., Hunt, G. R., Holzhaider, J. C., & Gray R. D. (2007) Spontaneous
metatool use by New Caledonian Crows. Current Biology, 17: 1504-1507.
Thagard, P. (2002*2006) How Molecules Matter to Mental Computation. In: Hot
Thought: Mechanisms and Applications of Emotional Cognition, ed. P.
Thagard, pp. 115-31. The MIT Press.
Tomasello, M. (1998) Cognitive Linguistics. In: A Companion to Cognitive Science,
ed. W. Bechtel & G. Graham, pp. 477-87. Blackwell Publishers.
Tomasello, M., Carpenter, M., Call, J., Behne, T, & Moll, H. (2005). Understanding
and Sharing Intentions: The Origins of Cultural Cognition. Behavioral and Brain
Sciences, 28:675-735.
Tooby, J., & Cosmides, L. (1992) The Psychological Foundations of Culture. In: The
Adapted Mind: Evolutionary Psychology and the Generation of Culture, ed. J. H.
Barkow, L. Cosmides, & J. Tooby, pp. 19-136. Oxford University Press.
Turing, A. M. (1936) On Computable Numbers with an application to the
Entscheidungsproblem. Proceedings of the London Mathematical Society, Ser. 2,
42:230-65.
Turing, A. M. (1950) Computing machinery and intelligence. Mind, 59:433-60.
Vaina, L., & Hintikka, J. ed. (1984*1985) Cognitive Constraints on
Communications: Representation and Processes. D. Reidel Publishing
Company.
Van Fraassen, B. C. (2008). Scientific Representation: Paradoxes of Perspective.
Oxford University Press.
Van Gelder, T. (1998) The dynamical hypothesis in cognitive science. Behavioral
and Brain Sciences, 21:615-65.
Vernon, D., Metta, G., & Sandini, G. (2007) A Survey of Artificial Cognitive
Systems: Implications for the Autonomous Development of Mental Capabilities
in Computational Agents. IEEE Transactions on Evolutionary Computation,
11:151-80.
Von Eckardt, B. (1992) What is cognitive science? The MIT Press.
40
Vosniadou, S., & Verschaffel, L. (2004) Extending the conceptual change approach
to mathematics learning and teaching. Learning and Instruction, 14:445-51.
Vygotski, L. (1934*1986) Thought and Language. Second edition. The MIT Press.
Wang, H., Todd, R. J., and Zhang, J. (2003) A multilevel approach to modeling
human cognition. Behavioral and Brain Sciences, 26:626-7.
Wang, P. (2005) Experience-grounded semantics: A theory for intelligent systems.
Cognitive Systems Research, 6:282-302.
Wetzel, L. (2008) Types and Tokens: An Essay on Universals. Cambridge University
Press.
Williams, P., Winzer, K., Chan, W. C. and Cámara, M. (2007) Look who’s talking:
communication and quorum sensing in the bacterial world. Philosophical
Transactions of the Royal Society B, 362:1119-34.
Williamson, T. (2006) Can Cognition be Factorized into Internal and External
Components? In: Contemporary Debates in Cognitive Science, ed. R. J. Stainton,
Blackwell Publishing.
Wilson, E. O. (1998) Consilience: The Unity of Knowledge. Abacus, London.
Wilson, R. A. & Keil, F. C. eds. (1999). The MIT Encyclopedia of the Cognitive
Sciences. The MIT Press.
Winograd, T. (1972) Understanding natural language. Cognitive Psychology, 3:1-
191.
Wittgenstein, L. (1953*1976) Philosophical Investigations. Basil Blackwell, London.
Young, R. M. (2003) Cognitive architectures need compliancy, not universality.
Behavioral and Brain Sciences, 26:628.
Ziff, P. (1972) Understanding Understanding. Cornell University Press, NY, USA.
1 Whether cognitive science is a perspective rather than a science (Hunt 1989) or whether it constitutes
a renaming of the field of psychology (Newell 1990) raise potentially important issues beyond the
scope of this article. In what follows I use the two terms interchangeably.
2 Within the cognitive architectures approach examples include: Anderson 1983; Anderson & Lebiere
(1998); Anderson et. al. 2004; Grossberg & Kuperstein (1989); Smolenski & Legendre (2006); Sun
(2002). Alternative approaches include: vector spaces (e.g., Bunge 1980); modularity (e.g., Chomsky
1980a, 1980b; Fodor 1983); extended mind hypothesis (e.g., Clark & Chalmers 1998; Logan 2007);
the dynamical hypothesis (e.g., Van Gelder 1998); mind as a decision-making organ (e.g., Gintis
2007); the Pleistocene mind hypothesis (e.g., Tooby & Cosmides 1992); the theory of neuronal group
selection (e.g., Edelman 1987); brain-inspired non-linear dynamics (e.g., Freeman 1999).
3 As a result of this a lot of AI systems have been proposed as cognitive architectures (for a recent
survey see Vernon et. al 2007).
4 For an earlier, different, list of criteria and comparison of Act-R (e.g., Anderson 1990, 1993), AuRA
(e.g., Arkin 1990), Soar (e.g., Newell 1990,1992) and TNGS (e.g. Edelman 1987), see Gelepithis
(1999).
5 Anderson and Lebiere’s argument for computational universality is essentially based on earlier views
of Newell (1980). But Newell made references to his earlier work including Newell (1980) whenever
he thought it appropriate and he most definitely did not do that in the case of the first criterion. For
more on the overlap among the various proposed criteria see Gelepithis (2003).
6 Interestingly and importantly, the posited hypothesis is consistent with the indterdependent construal
of self characterising non-western cultures as well as parts of western psychology and social sciences
(e.g., Markus & Kitayama 1991). A good example of the latter is the increasing interest in social
cognition and, in particular, collective memory (see editorial (Barnier & Sutton 2008) and associated
theoretical and empirical papers in a special issue of Memory).
7 It should be noted that acceptance of the MBI is a minority viewpoint. The majority view, outside the
computational paradigm, is that mental processes are caused/produced by the firing of neurons (Searle
2007 for a brief argument). See Borst (1970) for a still excellent provision of the main variants of MBI
(or identity theory as it is alternatively known). For some important recent work see Chalmers’s (2002)
collection of readings.
41
8 Table 1 is a lightly revised version of a similar one in Gelepithis (1988). It does not include new
names for earlier theories (e.g., experience-grounded semantics, conceptual role semantics or model-
theoretic semantics for the TTM, functional role semantics for essentially the use theory of meaning,
or informational semantics for essentially Grice’s theory of natural meaning), since newer theories
have not modified the nature of earlier ones. For a recent technical survey the reader may consult
Wang (2005) and, in particular, the third part (nature of meaning pp.151-389) of Lepore & Smith
(2006).
9 He changed his mind in 1921.
10 Chomsky's Aspects of the theory of Syntax was the last major work in generative linguistics before
the appearance of a fundamental split in transformational-generative grammar. The split concerns the
relationship between syntax and semantics. The result was the appearance of two diametrically
opposed conceptions concerning the nature of semantics: interpretative semantics and generative
semantics. Proponents of the former approach believe that basic syntactic structures can be specified
independently of semantic considerations. Adherents to the second conception claim the inverse to be
true.
11 Davidson’s (1999, 2001) more recent theories have not substantially enhanced his previous work.
12 A couple of important early seeds of this theory were presented in Gelepithis (1984, 1989).
13 It should be noticed that the stated identification does not imply membership to the individualist
tradition (e.g., Chomsky 1995, Fodor 1980, Stich 1978).
14 For a recent survey of their roles see Allen and Barres (2009), Barres (2008).
15 Subsequent definitions are in terms of human animals. Generalisations to non-human animals and
machines are straightforward.
16 It should be noted that the phenomenon indicated by relation (2) is significantly more complex than
the phenomenon of semantic underdetermination (e.g., Bach 1994; and Saul 2002; Speaks 20008 for
more recent discussions). Actually, the latter (explicitly introduced by Grice 1968) is a special case of
the former. Naturally, skepseis (and more fundamentally Nm) constitute a third class of meaning in
addition to the natural/nonnatural (Grice 1957), or the natural/conventional (e.g., Stevenson 1944)
distinctions.
17 A slightly weaker claim has been argued by Hebb (1980b, p24), namely, verbal language is «an
adjunct to a primarily nonverbal mechanism.» For a similar conclusion to Hebb’s argued from the
philosophical viewpoint see Lurz (2007); for a recent debate Heyes (1998).
18 This is a minimalist definition of belief. It could have been stated in a way that it explicitly included
any combination of concepts, thoughts and skepseis. Since all three of the latter are defined in terms of
N and/or Nm, the minimalist definition was thought to be more appropriate.
19 Clearly, the proposed theory of thinking is in sharp contrast to both major approaches, namely the
standard psychological view of concepts (e.g., initially Fodor 1975; recently Margolis & Lawrence
2007) and the propositional (equivalently, Fregean or semantic) view (e.g., Peacocke 1992).
20 The same is true for major recent work both in the Hebbian tradition (e.g., Edelman 1987) and in
biologically inspired non-linear dynamics (e.g., Freeman 1999).
21 Thanks to Yiannis Kontos for raising this point (personal communication).
22 Acceptance of the MMP is not in conflict with Roediger’s (2008) conclusion of lack of memory
laws. It is actually compatible with the huge complexity and interactivity of memory phenomena that
is fully recognized by the science of memory community.
23 Wittgensteins (1953*1976) investigations may be illuminating in this respect if they are read as
such rather than as an argument for the nature of meaning.
24 Mattelart and Mattelart (1995*1998) state eleven disciplines involved with its study: Philosophy,
history, cybernetics, geography, psychology, biology, sociology, ethnology, economics, political
science, and the cognitive sciences!
25 Essentially, Grices’s important work is primarily on meaning (Table 1).
26 It should be noted that perceived in this way, ‘communication’ gives rise to numerous further splits
of interest. As Schramm remarks: such a relationship is very complex and due to the lack of “general
theoretical insights, researchers have typically worked on parts of the relationship”.
27 a) To make (opinions, feelings, information, etc.) known or understood by others; and b) to share or
exchange opinions, feelings, information, etc. (Longman, 1987).
28 The earliest conception of definition-12 can be found in Gelepithis (1984).
29 An exception in tackling understanding as a specific cognitive phenomenon can be seen in Sanford’s
(2003) reader.
42
30 That is, in Newell’s terms, phenomena covering all of the cognitive band and most of the rational
one.
31 Johnson Laird’s (2003) thesis is that human understanding depends on the construction of mental
models from perception, imagination and the comprehension of language.
32 Moravcsik (1979) has argued that understanding should be seen as the state of mind that yields the
insight that unites one’s knowledge required to arrive at the solution to a problem.
33 The literature on reasoning has not defined its very object of investigation. We therefore feel
justified to use the term in this rather iconoclastic way.
34 Is mathematical validity materialised in the nervous system? My hunch is that it is. It appears that it
only needs the following two basic capabilities to have been neurally materialised: (i) recognition of
identities and differences; and (ii) sense of direction. Concerning the former, it appears that the
existence of neural inhibitions and the hierarchical semantic structures identified in 2.1.1.1 offer a
reasonable ground for the recognition of identities and differences by the individual. Hebb does not
seem to have addressed this issue and I am not aware of relevant literature. My strongest reason for
this suggestion is its reasonableness and the lack of any logical objections to it. With respect to
directionality, I have no better reasons than Hebb’s (1976) and Russell’s (1921) mnemic causation.
35 Part of this complexity, and probably its power, is due to its unconscious nature. We are in full
agreement with Kandel’s (2006, p. 375) remark: “most students of the brain believe, as Freud did, that
we are not conscious of most cognitive processes, only of the end result of those processes.” Gelepithis
(2005) stated a number of factors contributing to the complexity of the process of understanding.
36 Electron is the only one of the four that cannot be placed in P. Moreover, the class of concepts like
electrons which can be placed in P' but not in P is not a singleton. The distinction cannot be swept
away as a single oddity. Nevertheless, one should notice that if we were able to distinguish electrons
we could place ‘electron’ in P (future technology may enable us to do that).
37 For Herbert Simon’s view on cognitive invariants and a critical review of it see Simon (1990) and
Gelepithis (1992) respectively.
38 Within the theory proposed here, chorum sensing (e.g., Williams, et. al. 2007) does not constitute
communication.
39 Even the existence of ‘representation’ has been debated (e.g., Brooks 1991, Kelso 1995 against;
Bechtel 1998, Clark & Toribio 1994 for). Stufflebeam (1998) sits on the fence with a leaning towards
the against side.
40 There is a large number of scientists whose view of ‘representation’ is based on the assumption that
if a structure is regularly and reliably activated by a distal condition then that is adequate reason to
believe that structure as representing the distal condition. This assumption of «receptor representation»
has been effectively criticized by Ramsey (2003).
41 This definition is in accordance with both Aristotle’s (4th BCE*1984) views on poetry and drama as
human endeavours to mimic (i.e., re-present) the essence of human actions and the standard cognitive
science view stated earlier.
42 Some early work on semantic networks attempted to address some of the psychological mechanisms
of thinking but it was soon forgotten and abandoned.
43 Some further interesting similarities and consequences follow that are beyond the scope of this
article.
44 Evidence of writing marks of an expressive and presumed ritualistic nature goes back to about
32kya. Closer to our times geometrical and property markings have been found that have been
interpreted to have been used as devices for reckoning time and for counting. Nevertheless, these
markings are substantially different from even the elements of a writing system since they lack any
sequencing or hint of narrative. They are static and self-contained (Barton & Hamilton 1996). The first
link of visible marks to the original Sumerian cuneiform writing system has come with the work of
Schmandt-Besserat 1978, 1980). Such marks (in the form of tokens) are dated back to ~10kya.
45 Barton & Hamilton (1996) provide an excellent clarification of this relationship and of associated
issues like the language-thought debate and potential evolutionary mechanisms.
46 And so is Chalmers to the extent he accepts their active externalism thesis (Clark & Chalmers
1998*2008).
47 For a recent philosophical discussion see Silverberg (2003).
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