## 1. The Foils and Inspirations for Embodied Cognition




The ontological and methodological commitments of traditional
computational cognitive science, which have been in play since at
least the mid-Twentieth Century, are by now well understood. Early or
influential applications of computationalism to cognition include
theories of language acquisition (Chomsky 1959), attention (Broadbent
1958), problem solving (Newell, Shaw, and Simon 1958), attention, memory (Sternberg 1969), and perception (Marr 1982).
Common to all computationally-oriented research is the idea that
cognition involves a step-wise series of events, beginning with the
transduction of stimulus energy into a symbolic expression, followed
by transformations of this expression according to various rules, the
result of which is a particular output--a grammatical linguistic
utterance, isolation of one stream of words from another, a solution
to a logic problem, the identification of a stimulus as being among a
set of memorized stimuli, or a 3-D perception of the world




The symbolic expressions over which cognitive processes operate, as
well as the rules according to which these operations proceed, appear
as representational states internal to the cognizing agent. They are
individuated in terms of what they are about (phonemes, light
intensity, edges, shapes, etc.). All of this cognitive activity takes
place in the agent's nervous system. It is in virtue of the
activation of the nervous system that stimuli become encoded into a
"mentalese" language of thought, akin to the programming
languages found in ordinary computers; similarly, the rules dictating
the manipulation of symbols in the language of thought are like the
instructions that a C.P.U. executes in the course of carrying out a
task. Rather than running spread sheets or displaying Tetris pieces,
the computational brain produces language, or perceives the world, or
retrieves items from memory. The methods of computational cognitive
science reflect these ontological commitments. Experiments are designed
to reveal the content of representational states or to uncover the
steps by which mental algorithms transform input into output.




So pervasive has this computational conception of cognition been over
the past decades that many cognitive scientists would be happy to
identify cognition with computation, giving little thought to the
possibility of alternatives. Certainly the great strides toward
understanding cognition that the advent of computationalism has made
possible invites the idea that computational cognitive science, if not
the only game in town, is likely the best. However, ecological
psychology, which J.J. Gibson (1966; 1979) began to develop around the
time that computationalism came to dominate psychological practice,
rejected nearly every plank of the information processing model of
cognition that computational cognitive science epitomizes. More
recently, connectionist cognitive science has challenged the symbolist
commitments of computationalism even while conceding a role for
computational processes. Both ecological psychology and connectionist
psychology have played significant roles in the rise of embodied
cognition and so a brief discussion of their points of influence is
necessary to understand the "embodied turn." Likewise,
some embodied cognition researchers draw on a very different source
for inspiration--the phenomenological tradition with special
attention to Merleau-Ponty's contributions. The next three
subsections examine these various strands of influence.


### 1.1 Ecological Psychology




A primary disagreement between computational and ecological
psychologists concerns the nature of the stimuli to which organisms
are exposed. Computationalists largely regard these stimuli as, in
Chomsky's terminology, *impoverished* (Chomsky 1980). The
linguistic utterances to which an infant comes in contact do not, on
their own, contain sufficient information to indicate the grammar of a
language. Similarly, the visual information present in the light that
stimulates an organism's retina does not, on its own, specify
the layout of surfaces in the organism's environment. Visual
perception faces an "inverse optics" problem. For any
pattern of light on a retina, there exists an infinite number of
possible distal surfaces capable of producing that pattern. The visual
system thus seems to confront an impossible task--while it is
possible to calculate the pattern of light a reflecting surface will
produce on the retina, the inverse of this problem appears to be
unsolvable, and yet visual systems solve it all the time and,
phenomenologically speaking, immediately.




Computationalists regard the inescapable poverty of stimuli as
placing on cognitive systems a need to draw inferences. Just as
background knowledge allows you to infer from the footprints in the
snow that a deer has passed by, cognitive systems, according to
computationalists, rely on sub-conscious background knowledge to infer
what the world is like given the partial clues the stimuli offer. The
perception of an object's size, for instance, would, according to
the computationalist, be inferred on the basis of the size of the
retinal image of the object together with knowledge of the
object's distance from the viewer. Perception of an
object's shape, similarly, is inferred from the shape of the
retinal image along with knowledge of the object's orientation
relative to the viewer.




Ecological psychologists, on the other hand, deny that organisms
encounter impoverished stimuli (Michaels and Palatinus 2014). Such a
view, they believe, falsely identifies whole sensory systems with
their parts--with eyes, or with retinal images, or with brain
activity. Visual perceptual processes, for instance, are not exclusive
to the eye or even the brain, but involve the whole organism as it
moves about its environment. The motions of an organism create an
ever-changing pattern of stimulation in which invariant features
surface. The detection of these invariants, according to the
ecological psychologist, provides all the information necessary for
perception. Perception of an object's shape, for instance,
becomes apparent as a result of detecting the kinds of transformations
in the stimulus pattern that occur when approaching or moving around
the object. The edges of a square, for instance, will create patterns
of light quite different from those that a diamond would reflect as
one moves toward or around a square, thus eliminating the need for
rule-guided inferences, drawing upon background knowledge, to
distinguish the square from a diamond. Insights like these have
encouraged embodied cognition proponents to seek explanations of
cognition that minimize or disavow entirely the role of inference and,
hence, the need for computation. Just as perception, according to the
ecological psychologist, is an extended process involving whole
organisms in motion through their environments, the same may well be
true for many other cognitive achievements.


### 1.2 Connectionism




Connectionist systems offer a means of computation that, in many
cases, eschews the symbolist commitments of computational cognitive
science. In contrast to the computer that operates on symbols on the
basis of internally stored rules, a connectionist system consists in
networks of nodes that excite or inhibit each other's activity
according to weighted connections between them. Different stimuli will
affect input nodes differently, causing distinct patterns of
activation in deeper layers of nodes depending on the values of
activation that the input nodes send upstream. The result of this
activity will reveal itself in the activation values of a final layer
of nodes--the output nodes.




Connectionist networks thus compute--they transform input
activation values into output activation values--but the
imputation of symbolic structures within this computational process,
as well as explicit rules by which a C.P.U. executes operations upon
these symbols, appears unfounded. As Hatfield (1991) describes
connectionist networks, they are *non-cognitive*, in the sense
that their operation involves none of the trappings of cognition upon
which computationalists insist, and yet still computational, insofar
as stimulation of their input nodes creates patterns of activation
that lead to particular activation values in output nodes. For more on
 connectionism generally, see the entry on 
 connectionism.
 




Many embodied cognition researchers saw in connectionist networks a
new way to conceptualize cognition and, accordingly, to explain
cognitive processes. Non-symbolic explanations of cognition, despite
the "only game in town" mantra of computationalists (Fodor
1987), might be possible after all. Adding momentum to the
connectionist challenge was the realization that the mathematics of
dynamical systems theory could often illuminate the unfolding patterns
of activity in connectionist networks and could as well be extended to
include within its explanatory scope the body-environment interactions
between which connectionist networks reside. Consequently, some
embodied cognition researchers have argued that dynamical systems
theory offers the best framework from which to
understand cognition.


### 1.3. Phenomenology




Another source of inspiration for embodied cognition is the
phenomenological tradition. Phenomenology investigates the nature and
structure of our conscious, lived experiences. Although the subject of
phenomenological analyses can vary widely from perception to
imagination, emotion, willing, and intentional physical movements, all
phenomenological analyses aim to elucidate the intentional structure
of consciousness. They do so by analyzing our conscious experiences in
terms of temporal, spatial, attentional, kinesthetic, social, and self
awareness. In contrast to computational accounts of the mind that
model consciousness in terms of input, processing, and output,
phenomenological accounts ground consciousness in a host of rich and
varied attentional experiences, which with practice can be described
and analyzed. For more on phenomenology, see
 see the entry on 
 phenomenology.
 




Some variations of embodied cognition are inspired by the works of
phenomenologists like Martin Heidegger (1975), Edmund Husserl (1929),
and Maurice Merleau-Ponty (1962) who emphasize the physical embodiment
of our conscious cognitive experiences. These thinkers analyze the
various ways in which our bodies shape our thoughts and how we
experience our conscious activities. Some even argue that
consciousness is *constituted* by embodiment. Merleau-Ponty,
for example, argues that consciousness itself is embodied:



> 
> 
> 
> Insofar as, when I reflect on the essence of subjectivity, I find it
> bound up with that of the body and that of the world, this is because
> my existence as subjectivity [= consciousness] is merely one with my
> existence as a body and with the existence of the world, and because
> the subject that I am, when taken concretely, is inseparable from this
> body and this world (Merleau-Ponty 1962, p. 408).
> 
> 
> 




This phenomenological influence can be seen clearly in embodied
cognition analyses of the relation between mind and body. These
analyses reject the idea that mentality is fundamentally different and
separate from physicality and the corollary idea that others'
mentality is somehow hidden from view. Inspired by Husserl and other
phenomenologists, embodied cognition proponents argue that
Cartesian-style analyses of the mind and the body fundamentally
misconstrue cognition (Gallagher and Zahavi, 2008). Cognition is not
purely or even typically an intellectual, solipsistic introspection in
the way Descartes' Meditations suggest. Rather, cognition is
physically interactive, embedded in physical contexts, and manifested
in physical bodies. Even contemporary philosophers and cognitive
scientists who reject mind-body dualism may fall into the trap of
intuitively regarding mental and physical as distinct and thereby
accept the idea that we must infer the existence and nature of other
minds from indirect cues. From the perspective that phenomenologists
favor, however, all cognition is embodied and interactive and embedded
in dynamically changing environments. Attention to the way in which our
own conscious experiences are structured by our bodies and environments
reveals that there is no substantial distinction between mind and body.
The embodiment of cognition makes our own and others' minds just
as observable as any other feature of the world. In other words,
phenomenological analysis of our conscious experiences reveals the
Mind-Body Problem and Problem of Other Minds to be merely illusory
problems. This phenomenological analysis of the relation between mind
and body and our relation to other minds deeply influenced proponents
of embodied cognition such as Shaun Gallagher (2005), Dan Zahavi
(2005), and Evan Thompson (2010).


## 2. Embodied Cognition: Themes and Close Relations




Unlike computational cognitive science, the commitments of which can
be readily identified, embodied cognition is better characterized as a
research program with no clear defining features other than the tenet
that computational cognitive science has failed to appreciate the
body's significance in cognitive processing and to do so requires
a dramatic re-conceptualization of the nature of cognition and how it
must be investigated. Different researchers view the body's
significance for cognition as entailing different consequences for the
subject matter and practice of cognitive science. Nevertheless, through
this very broad diversity of views it is possible to extract three
major themes around which discussion of embodied cognition can be
organized (see Shapiro 2012; 2019a).


### 2.1 Three Themes of Embodied Cognition




The three themes of embodiment around which most of the following
discussion will be organized are as follows.



**Conceptualization:** The properties of an
organism's body limit or constrain the concepts an organism can
acquire. That is, the concepts by which an organism understands its
environment depend on the nature of its body in such a way that
differently embodied organisms would understand their environments
differently.



**Replacement:** The array of computationally-inspired
concepts, including *symbol*, *representation*, and
*inference*, on which traditional cognitive science has drawn
must be abandoned in favor of others that are better-suited to the
investigation of bodily-informed cognitive systems.



**Constitution:** The body (and, perhaps, parts of the
world) does more than merely contribute causally to cognitive
processes: it plays a constitutive role in cognition, literally as a
part of a cognitive system. Thus, cognitive systems consist in more
than just the nervous system and sensory organs.




The theses above are not intended to be individually
exclusive--embodied cognition research might show tendencies
toward more than one at a time. Similarly, descriptions of embodied
cognition might be organized around a larger number of narrower themes
(M. Wilson 2002); however, efforts to broaden the themes, thereby
reducing their number, risks generalizing the description of embodied
cognition to the extent that its purported novelty is jeopardized.




Before examining how these themes receive expression, it is worth
pausing to compare embodied cognition to some closely related research
areas. Sometimes embodied cognition is distinguished from
*embedded* cognition, as well as *extended* cognition and
*enactive* cognition. However, despite the distinctions between
the four "Es"--embodied, embedded, enactive, and
extended--it is not uncommon to use the label
"embodied" to include any or all of these
"Es". The E-fields share the view, after all, that the
brain-centrism of traditional cognitive science, as well as its
dependence on the computer for inspiration, stands in the way of a
correct understanding of cognition.


### 2.2 Embedded Cognition




Embedded cognition assumes that cognitive tasks--dividing a
number into fractions, navigating a large ship, retrieving the correct
book from a shelf--require some quantity of cognitive effort.
The cognitive "load" that a task requires can be reduced
when the agent embeds herself within an appropriately designed
physical or social environment. For instance, Martin and Schwartz
(2005) found that children are more successful at calculating 1/4
of 8 when allowed to manipulate pie pieces than if only viewing the
pieces. The cognitive load required to navigate a large Navy vessel
exceeds the capacity of any single individual, but can be distributed
across a number of specialists, each with his or her own particular
task (Hutchins 1996). Arranging books on a shelf alphabetically makes
searching for a particular title much easier than it would be if the
books were simply set randomly upon the shelf. In all of these cases,
the cognitive capacities of an individual are enhanced when provided
with the opportunity to interact with features of a suitably organized
physical or social environment.


### 2.3 Extended Cognition




Close kin to embedded cognition, extended cognition moves from the
claim that cognition is embedded to claim additionally that the
environmental and social resources that enhance the cognitive
capacities of an agent are in fact *constituents* of a larger
cognitive system, rather than merely useful tools for a cognitive
system that retains its traditional location wholly within an
agent's nervous system (Clark and Chalmers 1998; Menary 2008).
Some interpret the thesis of extended cognition to mean that cognition
actually takes place outside the nervous system--within the
extra-cranial resources involved in the cognitive task (Adams and
Aizawa 2001; 2008; 2009; 2010). Others interpret the thesis more
modestly, as claiming that parts of an agent's environment or
body should be construed as parts of a cognitive system, even if
cognition does not take place within these parts, thus extending
cognitive systems beyond the agent's nervous system (Clark and
Chalmers 1998; Wilson 1994; Wilson and Clark 2001).


### 2.4 Enactive Cognition




Enactivism is the view that cognition emerges from or is constituted
by sensorimotor activity. Currently, there are three distinct strands
of enactivism (Ward, Silverman, and Villalobos 2017). Autopoietic
Enactivism conceives of cognition in terms of the biodynamics of living
systems (Varela, Thompson, and Rosch 2017; Di Paolo 2005). Just as a
bacterium is created and maintained by processes that span the organism
and environment, so too is cognition generated and specified through
operation of sensorimotor processes that crisscross the brain, body,
and world. On this version of enactivism, there is no bright line
between mental processes and non-mental biological processes. The
former simply are an enriched version of the latter. Sensorimotor
Enactivism is another strand of enactivism that focuses on explaining
the intentionality and phenomenology of perceptual experiences in
particular (O'Regan and Noe 2001; Noe 2004). This view holds
that perception consists in active exploration of the environment,
which establishes patterns of dependence between our movements, sensory
states, and the world. Perceivers need not build and manipulate
internal models of the external world. Instead, they need only
skillfully exploit sensorimotor dependences that their exploratory
activities reveal. Finally, Radical Enactivism aims to replace all
representational explanations of cognition with embodied, interactive
explanations (Hutto and Myin 2013; Chemero 2011). The primary tactic
guiding Radical Enactivism is to deconstruct and eliminate the notion
of mental content in cognitive science. This tactic manifests in
critiques of attempts to naturalize intentionality, redescribing
cognitive processes studied in mainstream cognitive science, and
challenging concepts employed even by closely related views, such as
Autopoietic Enactivism's notion of sensemaking (Chemero 2016).
These three strands of enactivism vary in their target explanations and
methodology, however they share the commitment to the idea that
cognition emerges from sensorimotor activity.


## 3. Conceptualization




Returning now to the three themes around which this discussion of
embodied cognition is organized, the first is Conceptualization.
According to Conceptualization, the concepts by which organisms
recognize and categorize objects in the world, reason and draw
inferences, and communicate with each other, are heavily
body-dependent. The morphological properties of an agent's body
will constrain and inform the meaning of its concepts. The claim that
concepts are embodied in this way has been defended via quite distinct
routes.


### 3.1 Metaphor and Basic Concepts




Lakoff and Johnson (1980; 1999) offered an early and influential
defense of Conceptualization. Their argument begins with the plausible
premise that human beings rely extensively upon metaphorical reasoning
when learning or developing an understanding of unfamiliar concepts.
Imagine, for instance, trying to explain to a child the meaning of
*election*. Drawing a connection between *election* and a
concept the child already understands, like *foot race*, makes
the job easier. The "elections are races" metaphor provides
a kind of scaffolding for introducing and explaining the content of the
*election* concept. Candidates are like *runners* hoping
to win the *race*. They will adopt various *strategies*.
They must be careful not to *start too fast* or they might
*burn out before reaching the finish line*. It's about
*endurance through the long stretch*--more a
*marathon* than a *sprint*. Some will *play
dirty*, trying to *trip* others up, knocking them off their
*stride*. There will be *sore losers* but also
*graceful winners*. Appeal to the content of a familiar
concept--*foot race*--provides the child with a
framework or stance for learning the unfamiliar
concept--*election.*




The next step toward the embodiment of concepts proceeds with the
observation that, through pain of regress, not all concepts can be
acquired through metaphorical scaffolding. There must be a class of
*basic* concepts that (if not innate) we learn some other way.
Lakoff and Johnson argue that these basic concepts derive from the
kinds of "direct physical experience" (1980: 57) that come
from moving a human body through the environment. The concept
*up*, for instance, is basic, emerging from possession of a body
that stands erect, so that "[a]lmost every movement we make
involves a motor program that either changes our up-down orientation,
maintains it, presupposes it, or takes it into account in some
way" (1980, 56). Lakoff and Johnson offer a similar account for
how human beings come to possess concepts like *front*,
*back*, *pushing*, *pulling*, and so on.




Basic concepts reflect the idiosyncrasies of particular kinds of
bodies. Insofar as less-basic concepts depend upon metaphorical
extensions of these most basic concepts, they will in turn reflect the
idiosyncrasies of particular kinds of bodies. All concepts, Lakoff and
Johnson appear to believe, are "stamped" with the
body's imprint as the characteristics of the body "trickle
up" into more abstract concepts. They thus arrive at
Conceptualization: "the peculiar nature of our bodies shapes our
very possibilities for conceptualization and categorization"
(1999, 19). Insofar as this is true, one should expect that
differently-bodied organisms, equipped with a different class of basic
concepts, would conceptualize and categorize their worlds in nonhuman
ways.




Although Lakoff and Johnson see Conceptualization as incompatible with
computational cognitive science, their grounds for doing so are
tenuous. Metaphorical reasoning consists in applying aspects of one
concept's content to that of another. Because such reasoning is
explicitly about content, and because computationalism is a theory
about how to process mental states in virtue of their content, Lakoff
and Johnson's antagonism toward computationalism seems
unwarranted. Additionally, their case for Conceptualization remains
largely *a priori*. They claim that organisms morphologically
distinct from human beings--spherical in shape, say--would
be unable to develop some human concepts (1980, 57), but with no such
beings available to test, this assertion is entirely speculative.


### 3.2 Embodied Concepts




A far more developed and empirically grounded case for
Conceptualization comes from psychological and neurological studies
that show a connection between a subject's use of a concept and
activity in the subject's sensorimotor systems. Arising from
these studies is a view of concepts as containing within their content
facts about the sensorimotor particularities of their possessors.
Because these particularities reflect the properties of an
organism's body--how, for instance, it moves its limbs when
interacting with the world--the content of its concepts too will
be constrained and informed by the nature of its body.




Central to the idea that concepts are embodied is the description of
such concepts as *modal*. This label is intended to make stark
the anti-computationalism that proponents of embodied concepts
endorse. Symbols in a computer--strings of 1s and 0s--are
*amodal*, in the sense that their relationship to their
contents is arbitrary. Words too are amodal symbols. The symbol
'lake' means *lake*, but not in virtue of any
resemblance or nomological connection it bears towards lakes. There is
no reason that 'lake', rather than some other symbol,
should mean *lake*--as is obvious when thinking about
words that mean *lake* in non-English languages. All mental
symbols, from the perspective of computational cognitive science, are
amodal in this sense.




Modal symbols, on the other hand, retain information about the
sources of their origin. They are not just symbols, but, in
Barsalou's (1999; Barsalou et al. 2003) terminology,
*perceptual symbol*s. Thoughts about a lake, for instance,
consist in activation of the sensorimotor areas of the brain that had
been activated during previous encounters with actual lakes. A
*lake* thought re-activates areas of visual cortex that respond
to visual information corresponding to lakes; areas of auditory cortex
that respond to auditory information corresponding to lakes; areas of
motor cortex that correspond to actions typically associated with lakes
(although this activation is suppressed so that it does not lead to
actual motion), and so on. The result is a *lake* concept that
reflects the kinds of sensory and motor activities that are unique to
human bodies and sensory systems. *Lake* means something like
"thing that looks like *this*, sounds like *this*,
smells like *this*, allows me to swim within it like
*this*". Moreover, because how things look and sound
depend on the properties of sensory systems, and because the
interactions something affords depends on the properties of motor
systems, concepts will be body-specific.




Much of the evidence for the modality of concepts arises from
demonstrations of an *orientation-dependent spatial compatibility
effect* (OSC) (Symes, Ellis, and Tucker 2007). Tucker and Ellis
(1998), for instance, asked subjects to judge whether a given object,
e.g., a pan, was right-side-up or upside down. The object was oriented
either rightwards or leftwards. So, for instance, the pan's
handle extended toward the right or left. Subjects would indicate
whether the object was right-side-up or upside down by pressing a
button to their right with their right index finger or to their left
with their left index finger. Subjects' reaction times were
shorter when using a right finger to indicate a response when the
object was oriented to the right than when oriented toward the left,
and, *mutatis mutandis*, for left-finger responses when the
object was oriented to the left. Despite the fact that subjects were
not asked to consider horizontal orientation of the stimulus object,
this orientation influenced response times (for related work on the
OSC, see Tucker and Ellis 2001; 2004).




Relatedly, Glenberg and Kaschak (2002) showed an *action-sentence
compatibility effect* (ASC) Subjects were asked to judge the
sensibility of sentences like "open the drawer" or
"close the drawer." Sentences of the first kind suggested
actions that would require a motion of the hand toward the body and
sentences of the second kind suggested actions with motions away from
the body. Subjects would indicate the sensibility of the sentence by
pressing a button that required a hand motion either away from the body
or toward the body. Glenberg and Kaschak found that reaction times were
shorter when the response motion was compatible with the motion
suggested by the action sentences.




Both the OSC and ASC effects have been taken to show that concepts
are modal. Thoughts about pans, for instance, activate areas in motor
cortex that would be activated when actually manipulating a pan.
Subjects are slower to respond to a leftward oriented pan with their
right finger, because seeing the pan's orientation activates
motor areas in the brain associated with grasping the pan with the left
hand, priming a left finger response while inhibiting a right finger
response. Similarly, the meaning of words like "open" and
"close" include in their content the kinds of motor
activity that would be involved in opening or closing motions. The
meaning of object concepts thus contain information about how objects
might be manipulated by bodies *like ours*; action concepts
consist, in part, of information about how bodies *like ours*
move.




Further evidence for the claim that concepts are packed with
sensorimotor information comes from Edmiston and Lupyan (2017), who
asked subjects questions that required for their answers either
"encyclopedic" knowledge--"Does a swan lay
eggs?"--or visual knowledge--"Does a swan have a
beak?". Interestingly, they found that visual interference
during the task would diminish performance on questions requiring
visual knowledge but not encyclopedic knowledge. They took this as
evidence for the embodiment of concepts insofar as the effect of
visual interference would be expected if concepts were modal--if,
in this case, they involved the activation of vision centers in the
brain--but not if concepts were amodal symbols, divorced from
their sensorimotor origins.




A final source of evidence for embodied concepts comes from
neurological investigations that reveal activation in the sensorimotor
areas of the brain associated with particular actions. Reading a word
like 'kick' or 'punch' causes activity in
motor areas of the brain associated with kicking and punching
(Pulvermuller 2005). Stimulation of these areas by transcranial
magnetic stimulation can affect comprehension of such words
(Pulvermuller 2005; Buccino et al. 2005). Again, results like
these are precisely what an embodied theory of concepts would predict
but would be unexpected on standard computational amodal theories of
concepts. If the concept *kick* includes in its content motions
distinctive of a human leg, as determined by activity in the motor
cortex, then, as Conceptualization entails, it shows the imprint of a
specific sort of embodiment.




Critics of embodied concepts have issued a number of challenges.
Most basically, one might question whether empirical studies like those
just mentioned are targeting concepts at all. Why think, for instance,
that the meaning of the concept *pan* includes information about
how pans must be grasped; and that the meaning of *open*
includes information about how an arm should move? Claims like these
seem inattentive to a distinction between a *concept* and a
*conception* (Rey 1983; 1985; Shapiro 2019a). The meaning of the
concept *bachelor*, for instance, is *unmarried male*.
But apart from this concept is a *conception* of a bachelor,
where a conception involves something like typical or representative
features. A bachelor conception might include things like being a
lothario, or being young, or participating in bro-culture. These
concepts are *associated* with the concept *bachelor*,
but not actually part of the meaning of the concept. Similarly, that
pans might be grasped *so*, or *opening* involves moving
an arm like *so*, might not be part of the meaning of the
concepts *pan* and *open*, but instead features of
one's conception of pans and one's conception of how to
open things.




Just as defenders of embodied concepts might not be investigating
concepts after all, but instead only conceptions--only features
*associated* with concepts--it may be that the motor
activity that accompanies thoughts about concepts does not contribute
to the meaning of a concept but is instead only associated with the
concept. The psychologists Mahon and Caramazza (2008) argue for this
way of interpreting the neurological studies taken to support of
embodied concepts. The finding that exposure to the word
'kick' causes activity in the motor areas of the brain
responsible for kicking does not show that *kick* is a modal
concept. Mahon and Caramazza suggest that linguistic processing of a
word might create a cascade of activity that flows to areas of the
brain that are *associated* with the meaning of the word. A
thought about *kick* is associated with thoughts about moving
one's leg, which in turn causes activity in the motor system,
but there is no motivation for regarding this activity as part of the
*kick* concept--no motivation for seeing it as evidence
for the modality of the concept (Mahon 2015). Thinking about a kick
causes one to think about moving one's leg, which causes
activity in motor cortex, but the meaning of *kick* is
independent of such activity.




Finally, even granting the modality of concepts like *pan*
and *kick*, one might question whether *all* concepts
are embodied, as some embodied cognition researchers suggest (Barsalou
1999). Of special concern are abstract concepts like
*democracy*, *justice*, and *morality* (Dove 2009;
2016). Unlike *pan*, the meaning of which might involve
information from sensory and motor systems, what sensory and motor
activity might be included in the meaning of *justice*? Barsalou
(2008) and Barsalou and Wiemer-Hastings (2005) offer an account of how
abstract concepts might be analyzed in modal terms, but debate over the
issue is far from settled.


## 4. Replacement




Many who take an embodied perspective on cognition believe that the
commitments of traditional cognitive science must be jettisoned and
replaced with something else. No more computation, no more
representation, no more manipulation of symbols. Researchers who
promote the complete replacement of traditional cognitive science tend
to show the influence of ecological psychology. Less radical are
arguments for abandoning some elements of traditional cognitive
science, for instance the idea that cognition is a product of
rule-guided inference, while retaining others, e.g., the idea that
cognition still involves representational states. This position has
roots in the connectionist alternative to computationalism discussed
in SS1.2. Support for Replacement arrives from several
directions.


### 4.1 Robotics




Early ventures in robotics took on board the idea that cognition is
computation over symbolic representations. The robot Shakey
(1966-1972) for instance, created at the Artificial Intelligence
Laboratory at what was then the Stanford Research Institute, was
programmed to navigate through a room, avoiding or pushing blocks of
various shapes and colors. Guiding Shakey's behavior was a
program, called STRIPS, which operated on symbolically encoded images
of the blocks, combining them with stored descriptions of
Shakey's world. As the roboticist Brooks characterizes
Shakey's architecture, it cycles through iterations of
sense-model-plan-act sequences (Brooks 1991a). A camera senses the
environment, a computer builds a symbolic model of the environment
from the camera images, the STRIPS program combines the model with
stored symbolic descriptions of the environment, creating plans for a
course of action. Shakey's progress was slow--some tasks
would take days to complete--and heavily dependent on an
environment carefully structured to make images easier to process.




Brooks's approach to robotics disavows the computational
principles on which Shakey was designed, embracing instead a
Gibsonian-inspired architecture. The result has been robots that
exhibit far more versatility than Shakey ever displayed--robots
that can roam cluttered environments, avoiding obstacles, setting goals
for themselves, collecting soda cans for recycling, and more.
Brooks's "Creatures" run on what he calls a
*subsumption* architecture. Rather than cycling through
sense-model-plan-act sequences, Creatures contain arrays of sensors
that are connected directly to behavior-generating mechanisms. For
instance, the sensors on Brooks's robot Allen were connected
directly to three different kinds of behavior-generators: Avoid,
Wander, and Explore. When sensors detected an object in Allen's
path, the Avoid mechanism would cause Allen to stop its forward
motion, turn, and then proceed. The Wander generator would simply send
Allen along a random heading, while the Explore generator would steer
Allen toward a selected target. The three kinds of *activity
layers* as Brooks called them, continually compete with each
other. For instance, if Allen were Wandering and came across an
obstacle, Avoid would step in and prevent Allen from a
collision. Explore could inhibit Wander's activation in order to
keep Allen on course toward a target. From the competitive
interactions of the three layers emerged unexpectedly flexible and
seemingly goal-oriented behavior.




According to Brooks, his Creatures have no need for representations.
Implementing an idea from ecological psychology, Brooks says that the
activity layers in his robots connect "perception to action
directly" (1991b, 144). A robot designed in this way need not
represent the world because it is able to "use the world as its
own model" (1991b, 139). The robot's behavior evolves
through a continuous loop: the body moves, which changes the
stimulation its sensors receive, which directly causes new movement,
and so on. Because nothing stands "in between" the sensory
signals and the robot's behavior, there is no need for something
that plays the standard intermediating role of a representational
state. The robot does not require, for instance, a model of its
environment in order to navigate through hallways. The move-sense loop
does its job without one.




Despite the success of Brooks's robots in comparison to their
computational ancestors, and the impact Brooks's ideas have had
on industry (e.g., Roomba vacuum cleaners), whether Brooks's
insights pave the way for a radical, representation-free, cognitive
science, as some enactivists like Chemero (2009) and Hutto and Myin
(2013) believe, is far from certain. A first question concerns whether
the behavior of Brooks's Creatures really proceeds without the
benefit of representational states. The sensors with which the
Creatures are equipped, after all, send signals to the various
activity layers so that the layers can respond to objects in the
environment. Moreover, the various layers communicate with each other
in order to modulate each other's activities. They are, in
effect, signaling each other with messages that seem to have a
semantics: "go ahead," or "stop!".




Skeptics about representation, such as Chemero (2009) and Hutto and
Myin (2013) focus on the continuous contact that Brooks's
Creatures bear to their environments as a reason to deny a role for
representation. Because a Creature is in constant contact with the
world, it does not need to represent the world. But constant contact
does not always obviate a need for representation. Consider, for
instance, that an organism might be in constant contact with many
features of its environment--sunlight, humidity, oxygen, the
gravitational pull of the moon, and so on. Yet, surely it will be
sensitive to only some of these features--only some of these
features will shape the organism's behavior. A natural way to
describe how some features make a difference to an organism while
others do not might appeal to representation--an organism
*detects* some features, represents them, and not others.
Whether detection of this sort must involve representation will depend
on the theory of representation that one adopts. One might therefore
see the success of Brooks's challenge to representation, and the
enactivists' embrace of the challenge, as hostage to a theory of
representation, the details of which will no doubt themselves be
controversial.




Another response to Brooks's work doubts whether something like
the subsumption architecture, even granting that it makes no use of
representations, can "scale up"--can produce the more
advanced sorts of behavior that cognitive scientists typically
investigate (Shapiro 2007). Matthen (2014) argues that once we move
just a little beyond the capabilities of Brooks's Creatures,
explanations of behavior will require an appeal to
representations. For instance, imagine an organism that knows how to
move from point *A* to point *B*, and from point *A* to point
*C*, and on the basis of this knowledge, "figures out"
how to move from point *B* to point *C* (Matthen 2014). It would
seem that such an organism must possess a representation of the
relations between points *A*, *B*, and *C* for such a
calculation to be possible.




Clark and Toribio (1994) describe some cognitive tasks as
"representation-hungry." Examples include imagining or
thinking about non-existent entities (e.g., unicorns) or
counterfactual states of affairs (what would happen if I sawed through
the tree in this direction?). Of necessity, an organism cannot be in
constant contact with non-existents. That human beings so readily and
often entertain such thoughts poses a difficulty for enactivists like
Chemero and Hutto and Myin who see in Brooks's "world as
its own model" slogan a foundation for all or most
cognition. Because the world contains no unicorns, using the world as
a model cannot explain thoughts about unicorns.


### 4.2 Dynamical Systems Approaches to Cognition




Around the turn of the century, some cognitive scientists (Beer 2000;
2003; Kelso 1995; Thelen and Smith 1993; Thelen et al. 2001) and
philosophers (Van Gelder 1995; 1998) began to advocate for dynamical
systems approaches cognition. Van Gelder (1995; 1998) argued that the
computer, as the defining metaphor for cognitive systems, should be
replaced with something more like the Watt's centrifugal
governor. A centrifugal governor regulates the speed of a steam engine
by modulating the opening of a steam valve. As the valve opens, a
spindle to which flyballs are connected spins faster, causing the
flyballs to rise, which then cause the steam valve to close,
decreasing the speed at which the spindle spins, causing the flyballs
to drop, thus opening the steam valve, and so on. Whereas a
computational solution to maintaining engine speed might represent the
engine's current speed, compare it to a representation of the
engine's desired speed, and then calculate and correct for the
difference, the centrifugal governor does its job without having to
represent or calculate anything (although some have argued that
representations are indeed present in the governor: Bechtel 1998;
Prinz and Barsalou 2000).




The centrifugal governor is an example of a dynamical system. Typical
of dynamical systems is behavior that changes continuously through
time--the height of the flyballs, the speed of the spindle, and
the size of the steam valve opening all change continuously through
time, and the rate of change in each effects the rate of change of the
others. Dynamical systems *theory* provides the mathematical
apparatus--differential and difference equations--to model
dynamical systems. It is to these equations that *dynamical
cognitive science* looks for explanations of cognition.




Among the most-cited examples of a dynamical explanation of cognition
is the Haken-Kelso-Bunz (HKB) model of coordination dynamics (Haken,
Kelso, and Bunz 1985; Kelso 1995). This model, consisting of a single
differential equation, captures the dynamics of coordinated finger
wagging. Subjects are asked to wag their right and left index fingers
either in-phase, where each finger moves toward and away from each
other, or out-of-phase, like windshield wipers. As the rate of finger
wagging increases, out-of-phase motion will "flip" to
in-phase motion, but motion that starts in-phase will remain
in-phase. In dynamical terms, the coordination of finger wagging has
two *attractors*, or regions of stability, at slower speeds
(in-phase and out-of-phase) but only one attractor at a higher speed
(in-phase). The HKB model makes a number of predictions borne out by
observation, for instance that there are only two stable wagging
patterns at lower speeds, that erratic fluctuations in coordination
will occur near the critical threshold at which out-of-phase wagging
transforms to in-phase, and that deviations from out-of-phase wagging
will take longer to correct near the speed of transformation to
in-phase (see Chemero 2001 discussion).




Other influential examples of dynamical explanations of cognition have
focused on the coordination of infants' legs for stepping
behavior (Thelen and Smith 1993), perseverative reaching behavior in
infants (Thelen et al. 2001), and categorization in a simulated agent
(Beer 2003). Authors of these studies have been explicit in their
belief that traditional cognitive science should be replaced with the
commitments of dynamical cognitive science. Among these commitments is
a rejection of representation as a necessary component of cognition as
well as a view of cognition as "unfolding" from the
continuous interactions between an organism's brain, body, and
environment rather than as emerging from discrete, rule-guided,
algorithmic steps. This latter commitment returns us to the theme of
embodiment. As Thelen et al. explain:



> 
> 
> 
> To say that cognition is embodied means that it arises from bodily
> interactions with the world. From this point of view, cognition
> depends on the kinds of experiences that come from having a body with
> particular perceptual and motor capabilities that are inseparably
> linked and that together form the matrix within which reasoning,
> memory, emotion, language, and all other aspects of mental life are
> meshed" (2001, 1).
> 
> 
> 




Of course, computational cognitive scientists can accept as well that
cognition "arises from bodily interactions with the
world," in the sense that the inputs to cognitive processes
often arise from bodily interactions with the world. Thelen et
al. (2001) must then mean something more than that. Presumably, the
idea is that the body is like a component in a centrifugal governor,
and cognition arises from the continuous interactions between the
body, the brain, and the world. Spivey, another prominent dynamical
cognitive scientist, puts matters like this: "For the new
psychology on the horizon, perhaps we are ready to discard the
metaphor of the mind as computer...and replace it with a
treatment of the mind as a natural continuous event" (2007, 29),
much as, presumably, how the regulation of a steam engine's
speed is the result of the continuous interactions of the components
of a centrifugal governor.




One challenge facing dynamical approaches to cognition echoes that
confronting roboticists like Brooks. Just as the principles underlying
the subsumption architecture may not scale-up in ways that can explain
more advanced cognitive capacities, so too one might wonder whether
dynamical approaches to such capacities will succeed. Perhaps finger
wagging and infant stepping behavior are not instances of cognition in
the first place, or are so only in an attenuated sense (Shapiro 2007;
2013), in which case any lessons learned from their investigation have
little relevance to cognitive science.




Or perhaps as dynamical cognitive scientists examine more explicitly
cognitive phenomena, they will find themselves in need of tools
associated with standard cognitive science. Spivey, a pioneer of
dynamical systems approaches, is on friendly terms with the idea of
representations. Dietrich and Markman (2001) have argued that even
behavior like coordinated finger wagging depends on representation,
although perhaps not a conception of representation as
"thick" as one usually attributed to
computationalism. Once again, it is evident that resolving some of the
controversy surrounding the Replacement thesis hinges on the theory of
representation that one adopts.




Another criticism of dynamical cognitive science questions whether the
differential equations that are offered as explanations of cognitive
phenomena are genuinely explanatory. Chemero (2001) and Beer (2003)
insist that they are. The equations can be used to
*predict* the behavior of organisms as well as to address
*counterfactuals* about behavior (how would the organism have
behaved if such and such had occurred?)--both hallmarks of
explanation. Dietrich and Markman (2001), on the other hand, argue that
the equations offer only descriptions of phenomena rather than
explaining them (see also Eliasmith 1996; van Leeuwen 2005). Spivey,
despite his devotion to dynamical cognitive science, shares this view.
Dynamical systems theory, he thinks, does not explain cognition. Its
utility consists in "*modeling* how the mind works"
(2007, 33, his emphasis). He continues:



> 
> 
> 
> The emergence of mind takes place in the medium of patterns of
> activation across neuronal cell assemblies in conjunction with the
> interaction of their attached sensors (eyes, ears, etc.) and effectors
> (hands, speech apparatus, etc.) with the environment in which they are
> embedded. Make no mistake about it, *that* is the stuff of
> which human minds are made: brains, bodies, and
> environments. Trajectories through high-dimensional state spaces are
> merely convenient ways for scientists to describe, visualize, and
> model what is going on in those brains, bodies, and
> environments" (2007, 33, his emphasis).
> 
> 
> 




However, as Zednik (2011) has noted (see also Clark 1997 and Bechtel
1998), the differential equations on which dynamical explanations
depend contain terms that permit interpretation. This is what turns a
piece of pure mathematics into applied mathematics, which routinely is
understood as describing causal processes (Sauer 2010). As an instance
of applied (rather than pure) mathematics, The Lotka Volterra
equations, for instance, do indeed explain the dynamics of
predator-prey populations when their terms are taken to refer to
predation rate and reproductive rate. The equations
reveal *how* predation affects the size of the prey population,
and *how* depletion in the prey population affects the size of
the predator population, and *how* reproduction restores the
prey population. So, Spivey may be right that the "stuff"
of minds consists in brains, bodies, and environments, but this does
not preclude the differential equations that describe these
interactions from being explanatory. They are
explanatory *because* they describe how brains, bodies, and
environments interact and the consequences ensuing from these
interactions.


## 5. Constitution




Baking powder is a constituent of a scone, and its presence causes the
scone to rise when baked. A hot oven is also a cause of the
scone's rising, but it is not a constituent of the scone. You
eat baking powder when you eat a scone, but you do not eat a hot oven.
According to computational cognitive science, the constituents of a
cognitive system are brain processes, where these processes are
performing computations. The causes of cognition will be whatever
causes these brain processes--stimulation to the body from the
environment, for instance. Many embodied cognition theorists believe
that this account of the constituents of cognition is incorrect. The
constituents of a cognitive system extend beyond the brain, to include
the body and the environment. A difficulty for this view is justifying
the claim that the body and world are better construed as constituents
of cognition rather than causes. Why are they more like baking powder
than a hot oven?


### 5.1 Constitution Through Coupling




The previous discussion of dynamic cognitive science serves also to
illustrate the Constitution theme. As the quotation above from Spivey
indicated, dynamically-oriented cognitive scientists regard cognition
to be the product of interactions between brain, body, and world. The
continuous interactions between these things, Chemero writes, explains
why "dynamically-minded cognitive scientists do not assume that
an animal must represent the world to interact with it. Instead, they
think of the animal and the relevant parts of the environment as
together comprising a single, coupled system" (2001, 142).
Chemero continues this idea: "It is only for convenience (and
from habit) that we think of the organism and environment as separate;
in fact, they are best thought of as comprising just one
system...the animal and environment are not separate to begin
with" (2001, 142).




Chemero's description of the animal and environment as coupled
is ubiquitous in dynamical cognitive science. Coupling is a technical
notion. The behaviors of objects are coupled when the differential
equations that describe the behavior of one contains a term that
refers to the behavior of the other. The equations that apply to the
centrifugal governor, for instance, contain terms referring to the
height of the flyballs and the size of the steam valve opening. The
Lotka Volterra equations contain terms that refer to the number of
predators and the number of prey. The co-occurrence of terms in the
equations that describe a dynamical system shows that the behavior of
the objects to which they refer are co-dependent. They are thus
usefully construed as constituents of a single system--a system
held together by the interactions of parts whose relationships are
captured in coupled differential equations.




In addition to the technical sense of coupling, philosophers often
appeal to a looser sense when defending Constitution. Clark, for
instance, discusses the process of writing. When writing, "[i]t
is not always that fully formed thoughts get committed to paper.
Rather, the paper provides a medium in which, this time via some kind
of coupled neural-scribbling-reading unfolding, we are enabled to
explore ways of thinking that might otherwise be unavailable to
us" (2008, 126). Clark's idea is that the cognitive system
that produces writing extends beyond a subject's brain, to
include among its constituents the paper on which words are written.
The paper and the acts of reading and writing are literally parts of
the cognitive process, no less than neural processes, because of the
continuous interactions between all of these things. If it were
possible to provide differential equations that describe the
production of writing, they would include terms referring to the
behaviors of each of these things. Thus, the reasoning that brings us
to the conclusion that the components of a centrifugal governor are
constituents of a single system, and that predator and prey are
constituents of single system, leads also to the conclusion that the
constituents of many cognitive systems will include parts of the body
and world.




The coupling concept underlies some arguments for *extended
cognition*. When brain processes are coupled to processes in the
body or world, either in the technical sense deriving from dyamical
systems theory or in the less strict sense involving loops of
dependency, the resulting "brain+" is itself a single
cognitive system. It is a cognitive system that extends beyond the
head because the constituents of the system are not brain-bound.




Adams and Aizawa (2008; 2009; 2010) have objected to coupling-inspired
defenses of Constitution, and hence the idea of extended cognition, on
the grounds that they commit a
*coupling-constitution* fallacy: "The pattern of
reasoning here involves moving from the observation that process *X*
is in some way causally connected (coupled) to a process *Y* of type
*j* to the conclusion that *X* is part of the process of type
*j*" (2009, 81). They argue that this reasoning leads to
absurd results. For instance, "[i]t is the interaction of the
spinning bowling ball with the surface of the alley that leads to all
the pins falling. Still, the process of the ball's spinning does
not extend into the surface of the alley or the pins (2009,
83). Similarly, Adams and Aizawa would claim, the process of cognition
does not extend into the paper and scribblings involved in
writing.




This response is unlikely to impress supporters of coupling arguments
for Constitution. Firstly, coupling arguments require that process
*X* be more than simply causally connected to process *Y* of type
*j* for *X* to be part of the *j* process. Suppose that process
*Y* of type *j* is the production of a written paragraph on a
piece of paper. Let *X* be the sound of the pencil as it leaves
graphite on the surface of the paper. The sound is causally connected
to the production of writing, but defenders of Constitution need not
regard it as a constituent in the system of that results in the
written paragraph. The sound does not contribute to the
"loop"--neural events, scribbling, reading--from
which the paragraph emerges. So, not just any causal connections
suffice for constituency in a process.




Second, Clark and other defenders of Constitution would not claim that
the writing process *itself* occurs in the constituents of the
cognitive system that produces writing. Certainly the bowling
ball's spinning does not extend into the floor of the alley, and
of course the writing process does not extend into a piece of paper.
But the Constitution thesis is not committed to such claims (Shapiro
2019a). Just as one can say that a neuron is a constituent of a brain
even if cognition does not take place in a neuron, it might make sense
to say that the floor of the alley is a constituent in a system that
results in the ball's spinning even if spinning does not take
place in the floor, and the paper is a constituent in a system that
produces writing even if the writing process does not take place
*in* the paper. Such conclusions, even if ultimately
unwarranted, do not fail for the reasons Adams and Aizawa muster.


### 5.2 Constitution Through Parity and Wide Computationalism




Apart from coupling arguments, some philosophers, e.g., Clark and
Chalmers (1998) and Clark (2008), have defended the idea that
cognitive systems include constituents outside the brain by appeal to
a
*parity principle,* whereas Wilson (2004) invokes the idea of
*wide computationalism*. The arguments are similar, both seeking
to reveal how a functionalist commitment to mental states or processes
licenses the possibility of cognitive processes that extend beyond the
brain.




The parity principle says "[i]f, as we confront some task, a
part of the world functions as a process which, were it done in the
head, we would have no hesitation in recognizing as part of the
cognitive process, then that part of the world is...part of the
cognitive process" (Clark 2008, 222). As illustration, Clark and
Chalmers (1998) compare the occurrent beliefs of Otto, who is
afflicted with Alzheimer's disease, to those of Inga, who has a
normal biological brain. Otto keeps a notebook containing information
of the sort that would be stored in the hippocampus of a normally
functioning brain. When Inga wants to visit MoMA, she pulls from her
biological memory the information that MoMA is on 53rd
St. which prompts her to take a subway to the destination. When Otto
has the same desire, he consults his notebook in which is written
"MoMA is on 53rd St.", which in turn induces
his trip to that location. By stipulation, the representation of
MoMA's location in Otto's notebook plays an identical
functional role to the representation in Inga's brain. Hence, by
the parity principle, the notebook entry is a memory--an
occurrent belief about the location of MoMA. The notebook is thus home
to constituents of many of Otto's cognitive processes.




In a similar vein, Wilson (2004) discusses a person who wishes to
solve a multiplication problem involving two large
numbers. Calculating the product "in the head" is a
possibility, but solving the problem with the aid of pencil and paper
would be much easier. In the latter case, Wilson claims that the brain
"offloads" onto the paper some of the work that it would
otherwise have to do on its own. Crucial to Wilson's argument is
the idea that solving the multiplication problem is a computational
process and that computational processes are not confined to
particular spatial regions. When the multiplication problem is solved
"in the head" the computational processes occur within the
brain alone. But some of the steps in the computation could as well
take place outside the head, on a piece of paper, in which case a
computational process might partly occur outside the head. There is,
then, a parity in the two processes, whether the particular
computations are internal or external to the agent. To the extent that
this is plausible, one can find additional support for
Constitution.




Most criticism of extended cognition has been aimed at Clark and
Chalmers's original proposal, although because Wilson's
position is similar, it is as much victim to these criticisms insofar
as they succeed. Among the most vocal critics are Adams and Aizawa
(2001; 2008; 2009; 2010), who argue that extended cognitive systems
like those involving Otto and his notebook or a person doing
multiplication with a paper and pencil, cannot actually be cognitive
because they fail to satisfy two "marks" of the cognitive.
The first mark is that "cognitive states must involve intrinsic,
non-derived content" (Adams and Aizawa 2001, 48). The second is
that cognitive systems must display processes of sufficient uniformity
to fall within the domain of a single science (Adams and Aizawa
2010).




The intrinsic content criterion assumes a distinction between content
that is derived from human thought, as the content of the word
'martini' is derived from thoughts about martinis, and
content that arises "on its own" without having to depend
on some other contentful state for its origin. The thought
*martini*, for instance, presumably does not (or need not)
derive from other contentful states but arises from some naturalistic
process involving relationships between brain states and martinis
(relationships that it is the business of a naturalistic theory of
content to specify). Words, maps, signs, and so on possess derived,
non-intrinsic content whereas thoughts have intrinsic, non-derived,
*original* content. Granting this distinction and its importance
for identifying genuinely cognitive states and processes, Adams and
Aizawa dismiss the plausibility of extended cognition on the grounds
that things like notebook entries and numerals written on paper do not
have intrinsic content.




Clark (2010) responds to this objection, in part pressing Adams and
Aizawa to clarify how much intrinsic content must be present in a
system for the system to qualify as cognitive. After all, brains, if
anything, are cognitive systems but not all activity occurring in a
brain involves states or processes with intrinsic
content. Accordingly, Clark wonders, why should the fact that some
elements of the Otto+ notebook system, because they lack
intrinsic content, preclude the system from counting as cognitive?




Adams and Adams propose in response that "if you have a process
that involves no intrinsic content, then the condition rules that the
process is non-cognitive (2010, 70). However, this response leaves
open whether Otto+ notebook constitutes a cognitive system. Because
Otto's brain does indeed contain states and processes that
"involve" intrinsic content--states and processes by
which the notebook entries are read and understood and used to guide
behavior--Clark can readily accept Adams and Aizawa's
stipulation. Some of the Otto+ notebook system involves intrinsic
content, some does not, and the cognitive system as a whole
incorporates both these elements.




The second mark of the mental that Adams and Aizawa take to preclude
systems like Otto+ notebook from counting as cognitive raises issues
concerning the identification of scientific domains. If one supposes,
reasonably enough, that the objects, processes, properties, etc. that
fall into the domain of a particular science do so in virtue of sharing
particular features, then one should expect the same for the domain of
cognitive science. The parts, properties, and activities taking place
in brains do seem to share important features, features that explain
how it is possible to identify brains in newly discovered species, how
they differ from igneous rocks, and so on. But now suppose that
cognitive systems can be extended in ways that Clark, Chalmers and
Wilson have argued. Such systems would now contain constituents that
could not possibly fit into the domain of a single science. Extended
systems might include notebooks, or pencil and paper, or tools of just
about any sort. "[F]or this reason," Adams and Aizawa
argue, "a would-be brain-tool science would have to cover more
than just a multiplicity of causal processes. It would have to cover a
genuine motley" (2010, 76).




Rupert (2004) shares a similar concern, noting that the processes by
which Otto and Inga locate MoMA differ so considerably that it makes
no sense to treat them as of a kind--as within the domain of a
single science. Additionally, Rupert argues, there is no good reason
to regard the various implements that combine with brain activity to
be constituents of a cognitive system rather than simply tools that
cognitive systems use to ease the processing they require to complete
some task. Instead of insisting that cognitive systems extend, Rupert
asks, why not regard them as seeking ways to embed themselves among
tools that make their jobs easier? An axe does not become part of a
person when she uses it to chop down a tree, why does a notebook
become part of cognitive system when a brain uses it to locate MoMA? A
sensible conservatism, Rupert thinks, speaks in favor of seeing
cognitive systems as embedded in environments that allow ready use of
tools to reduce their workloads, rather than as constituted, in part,
by such tools. The hypothesis that cognitive systems use tools
"is significantly less radical" (2004, 7) than the
hypothesis that tools are constituents of cognitive systems and would
seem to provide adequate explanations for all the phenomena that
initially motivated the idea of extended cognition.




From Clark's perspective, however, there is nothing motley, as
Adams and Aizawa claim, about the brain+ tool systems that he
believes constitute a legitimate kind for scientific
investigation. Moreover, the processes by which Otto and Inga locate
MoMA are not, as Rupert insists, vastly different. Once one steps back
form the physical particularities of the constituents of extended
cognitive systems and focuses just on the functional, computational,
roles they play, such systems are identical, or very similar, to
wholly brain-bound cognitive systems.




Similarly, Clark would deny Rupert's claim that the hypothesis
of embedded cognition can equally well save the phenomena that the
hypothesis of extended cognition was intended to capture and do so
while requiring less revision of existing ideas about how cognitive
systems operate. A brain, Clark claims, is "'cognitively
impartial': It does not care how and where key operations are
performed" (2008, 136). Rupert's conservatism in fact
reflects a misunderstanding--it conceives of brains as having the
function of cognizing, which is true in a sense, but more accurate
would be a description of the brain's function as directing the
construction of cognizing systems--some (many?) of which include
constituents outside the brain proper (see also Wilson and Clark
2009).




Finally, Shapiro (2019b; 2019c) has suggested that the parity and
wide-computationalist defenses of Constitution do not sit well with
other commitments of embodied cognition. As mentioned, such defenses
rest on a functionalist theory of cognition (for more on
 functionalism, see the entry on
 functionalism).
 Functionalism may well justify the claim that states and processes
outside the brain can be identical to states and processes internal to
a brain (can stand in a relation of parity towards them), which in
turn grounds the possibility that cognitive systems can contain
non-neural constituents. But, Shapiro argues, this strategy for
defending extended cognition seems contrary to the central theme of
embodied cognition. Motivating the embodied turn in cognitive science
is the idea that bodies are somehow essential to cognition. But the
parity and wide-computational arguments for extended cognition entail
just the opposite--important for cognition are computational
processes, and because computational processes are "hardware
neutral", one need not consider the specifics of bodies in order
to describe them. Thus, it appears, arguments in favor of extended
cognition succeed to the extent that bodies, *qua* bodies, do
not matter to cognition.


## 6. The Reach of Embodied Cognition




In addition to the usual cognitive terrain--language, perception,
memory, categorization--that embodied cognition encompasses,
researchers have recruited the concepts and methods of embodied
cognition for the purpose of investigating other psychological
domains. In particular, embodied cognition finds application in the
fields of social cognition and moral cognition.


### 6.1 Social Cognition




Social cognition is the ability to understand and interact with other
agents. A wide variety of cognitive capacities are involved in social
cognition, such as attention, memory, affective cognition, and
metacognition (Fiske and Taylor 2013). Traditionally, however, the
philosophical discussion of social cognition has narrowly conceived of
it in terms of mentalizing (also called *theory of mind* or
*mindreading*). Mentalizing refers to the attribution of mental
states, often restricted to propositional attitudes, and typically for
the purpose of explaining and predicting others' behavior. Thus,
although social cognition is enabled by and involves numerous and
diverse cognitive processes, many philosophers have tended to think of
it simply as involving the attribution of propositional attitudes in
order to predict and explain behavior. For canonical expressions of
this view of social cognition, see Davies and Stone (1995a) and
(1995b). More recently, philosophers have begun to conceive of social
cognition more broadly. See Andrews, Spaulding, and Westra (2020) for
a survey of Pluralistic Folk Psychology.




Embodied cognition theorists have rejected this narrow construal of
social cognition. Though they do not deny that neurotypical adult
humans have the capacity to attribute beliefs and desires and to
explain and predict behavior, they argue that this is a specialized
and rarely used skill in our ordinary social interactions (Gallagher
2020; Gallagher 2008; Hutto and Ratcliffe 2007). Most social
interactions require only basic underlying social cognitive capacities
that are known as primary and secondary intersubjectivity (Trevarthen
1979).




Primary intersubjectivity is the pre-theoretical, non-conceptual,
embodied understanding of others that underlies and supports the
higher-level cognitive skills involved in mentalizing. It is
"the innate or early developing capacity to interact with others
manifested at the level of perceptual experience--we see or more
generally perceive in the other person's bodily movements,
facial gestures, eye direction, and so on, what they intend and what
they feel" (Gallagher 2005, 204). Primary intersubjectivity is
present from birth, but it continues to serve as the basis for our
social cognition in adulthood. It manifests as the capacity for facial
imitation, the capacity to detect and track eye movement, detect
intentional behavior, and "read" emotions from actions and
expressive movements of others. Primary intersubjectivity consists in
informational sensitivity and appropriate responsiveness to specific
features of one's environment. It does not, embodied cognition
theorists argue, involve representing and theorizing about those
features. It simply requires certain practical abilities that have
been shaped by selective pressures, e.g., sensitivity to certain
bodily cues and facial expressions.




Around one year of age, neurotypical children develop the capacity for
secondary intersubjectivity. This development enables a subject to
move from one-on-one, immediate intersubjectivity to shared attention.
At this stage, children learn to follow gazes, point, and communicate
with others about objects of shared attention. According to embodied
cognition, the cognitive skills acquired through secondary
intersubjectivity are not rich, meta-cognitive representations about
other minds. Rather, children learn practical skills when getting
others to attend to an object and when learning to attend to objects
others are attending to. This allows for a richer understanding of
other agents, but it is still meant to be a behavioral, embodied
understanding rather than a representation of others'
propositional attitudes (Gallagher 2005, 207).




Although primary and secondary intersubjectivity are described in
developmental terms, according to embodied cognition these
intersubjective practices constitute our primary mode of social
cognition even as adults (Fuchs 2012; Gallagher 2008). For example,
Hutto claims, "Our primary worldly engagements are
nonrepresentational and do not take the form of intellectual
activity" (2008, 51). One can see in Hutto's description
of social cognition a tendency toward the Replacement theme insofar as
he seeks to minimize or reject completely a role for representation in
the human capacity for understanding others'
behavior. Mentalizing, it is argued, is a late developing, rarely
used, specialized skill. Primary and secondary intersubjectivity are
fundamental insofar as they are sufficient for navigating most typical
social interactions and insofar as they enable the development of
higher-level social cognition, like mentalizing. Although, see
Spaulding (2010) for a critique of these arguments.




Mirror neurons may be an important mechanism of social cognition on
this kind of view. Mirror neurons are neurons that activate both
endogenously in producing a behavior and exogenously in observing that
very same behavior. For instance, neurons in the premotor cortex and
inferior parietal lobule activate when a subject uses, say, a
whole-handed grasp to pick up a bottle. These very same neurons
selectively activate when a subject observes a target using a
whole-handed grasp to pick up an object. Neuroscientists have
discovered similar patterns of activation in neurons in various parts
of the brain, leading to the proposal that there are mirror neuron
systems for action, fear, anger, pain, disgust, etc. Though the
interpretation of these findings is subject to a great deal of
controversy (Hickok 2009), many theorists propose that mirror neurons
are a basic mechanism of social cognition (Gallese 2009; Goldman 2009;
Goldman and de Vignemont 2009; Iacoboni 2009). The rationale is that
mirror neurons explain how a subject understands a target's
mental states without needing complicated, high-level inferences about
behavior and mental states. In observation mode, the subject's
brain activates as if the subject is doing, feeling, or experiencing
what the target is doing, feeling, or experiencing. Thus, the
observation of the target's behavior is automatically meaningful
to the subject. Mirror neurons are a possible mechanism for embodied
social cognition. If the findings and interpretations are upheld, they
substantiate the claim that we can understand and interact with others
without engaging in mentalizing. For a survey of the reasons to be
cautious about these interpretations of mirror neurons, see Spaulding
(2011; 2013).


### 6.2 Moral Cognition




Embodied moral cognition takes moral sentimentalism as a starting
 point. 
 Moral sentimentalism
 is the view
that our emotions and desires are, in some way, fundamental to
morality, moral knowledge, and moral judgments. A particular version
of moral sentimentalism holds that emotions, moral attitudes, and
moral judgments are generated by our "gut reactions," and
any moral reasoning that occurs is typically post-hoc rationalization
of those gut reactions (Haidt 2001; Nichols 2004; Prinz
2004). Embodied moral cognition takes inspiration from this kind of
moral sentimentalism. It holds that many of our moral judgments stem
from our embodied, affective states rather than abstract
reasoning.




Various sources of empirical evidence support this kind of view.
Consider, for example, pathological cases, such as psychopaths or
individuals with damage to the ventromedial prefrontal cortex (vmPFC).
Such individuals are impaired in making moral judgments. Psychopaths
feel little compunction about behaving immorally and sometimes have a
hard time differentiating moral from conventional norms (Hare 1999).
Individuals with damage to the vmPFC retain knowledge of abstract
moral principles but struggle in making specific, everyday moral
decisions (Damasio 1994). In both cases, individuals lack the
physiological responses that accompany neurotypical moral
decision-making. Lacking these "somatic markers" that
guide moral judgments, these individuals behave in impulsive, selfish,
and immoral ways (Damasio 1994). Embodied cognition would predict this
connection between physiological responses (like increased heartrate
and palm sweating) and moral decision-making.




Psychologists and neuroscientists have observed the influence of
embodied cues on moral judgments in neurotypical individuals, as well.
For instance, experimentally manipulated perception of one's
heartrate seems to influence one's moral judgments, with
perceptions of faster heartrates leading to feelings of higher moral
distress and more just moral judgments (Gu, Zhong, and Page-Gould
2013). Relatedly, there is some evidence that eliciting a feeling of
disgust leads to harsher moral judgments (Schnall et al. 2008).
Perceptions of cleanliness seem to lead to less severe moral judgments
(Schnall, Benton, and Harvey 2008). In each of these cases, perception
of embodied cues seems to mediate moral judgments. Moral
sentimentalists have observed that many people have strong aversive
reactions to harmless actions that violate taboos, such as consensual
protected sex between adult siblings, cleaning a toilet with the
national flag, eating one's pet that had been run over, etc. In
these cases, the strong negative affective response precedes the moral
judgment, and often people have a difficult time articulating
*why* they think these victimless, harmless actions are morally
wrong (Strejcek and Zhong 2014; Haidt 2001; Haidt, Koller, and Dias
1993; Cushman, Young, and Hauser 2006). From the perspective of
embodied cognition, this ordering confirms the notion that we make
moral judgments on the basis of embodied cues.




Dual process theories of moral psychology reject the moral
sentimentalism claim that all moral judgments are made in the same
way. Dual process theories maintain that we have two systems of moral
decision-making: a system for Utilitarian reasoning that is driven by
affect-less, abstract deliberation, and system for Deontological
reasoning that is driven by automatic, intuitive, emotional heuristics
like gut feelings (Greene, 2014). Dual process theories are meant to
explain the seemingly inconsistent moral intuitions ordinary folks
have about moral dilemmas. For example, in a standard trolley case
where an out-of-control trolley is heading toward five innocent,
unaware individuals on the track ahead, most people have the intuition
that we ought to throw the switch so that the trolley goes onto a spur
of the track, thereby killing one person on the spur but saving five
lives. However, in the footbridge variation of the trolley problem
where saving the five lives requires pushing an individual off a
footbridge to derail the trolley, most people have the intuition that
we should not do this even though the consequences are the same as in
the standard trolley dilemma. The dual process theory holds that in
the former case, our reasoning is guided by a System-2 type of
abstract reasoning. However, in the latter case, our moral reasoning
is guided by an aversive physiological response triggered by imagining
pushing an individual off a footbridge. The dual process view
partially vindicates the moral sentimentalist position insofar as it
posits a distinctive System 1 type of moral reasoning that is based on
embodied gut instincts. However, it maintains that there is a separate
system operating on different inputs and processes for more abstract
moral reasoning.




Recently, theorists have challenged dual process theories'
strict dichotomy between reason and emotion (Huebner 2015; Maibom
2010; Woodward 2016). On the one hand, brain areas that are associated
with emotions like fear, anger, and disgust are implicated in complex
learning and inferential processing. On the other hand, individuals
who are clearly impaired in moral decision-making--psychopaths
and those with damaged vmPFC--also suffer deficits in other kinds
of learning and inferential processing. Abstract reasoning is not, as
it turns out, cut off from affective processes. Somatic markers,
affective cues, and physiological responses are central to reasoning,
learning, and decision-making. For the proponent of embodied moral
cognition, this serves as further confirmation of the idea that all
cognition, including moral cognition, is deeply shaped by embodied
cues. Though see May (2018), May and Kumar (2018) and Railton (2017)
for a moral rationalist take on these findings.


## 7. Conclusion




This article aims to convey a sense of the breadth of topics that fall
within the field of embodied cognition, as well as the numerous
controversies that have been of special philosophical interest. As
with any nascent research program, there remain questions about how
embodied cognition relates to its forebears, in particular
computational cognitive science and ecological psychology. Some of the
hardest philosophical questions arising within embodied cognition,
such as those concerning representation, explanation, and the very
meaning of 'mind', are of a sort that any theory of mind
must address. Apart from philosophical challenges to the conceptual
integrity of embodied cognition there loom psychological concerns
about the replicability of some of the most-cited findings within
embodied cognition; although, in fairness, worries about replicability
have recently arisen in many areas of psychology (Goldhill 2019;
Lakens 2014; Maxwell, Lau, and Howard 2015; Rabelo et
al. 2015). Whatever the future of embodied cognition, careful study of
its aims, methods, conceptual foundations, and motivations will
doubtless enrich the philosophy of psychology.