Too much neural reuse, even for a metaphorical brain
Conceptual mappings are correspondances between conceptual domains (space, time, force,
emotion, etc.) or between entities within the same conceptual domain. Through mapping,
we project inferences, elements, and relations from one mental configuration to another.
Sets of mappings can become entrenched, creating powerful cognitive habits. For example,
across many cultures around the world, temporal relations are conceived by means of
spatial relations, in language (“Saturday is almost here”), artifacts (timelines,
calendars, sundials), or gesture (Núñez and Sweetser, 2006). Some of the mappings
for this template are: duration is spatial extent, events are landmarks, or time is
motion along a path.
From over 30 years of conceptual mappings research emerges a picture of the conceptual
system as a set of mapping habits. Instead of a static repository of concepts, we
have a dynamic network connecting mental structures. Mapping is not exceptional: it
is the norm. It is through mapping that concepts are formed, learned, and developed
creatively. These ideas have boosted the interest in the most remarkable manifestations
of mapping in language and thought: metaphor, metonymy, analogy, counterfactuals,
etc.
Metaphor has received far more attention than all the other phenomena combined. Researchers
in Conceptual Metaphor Theory (CMT) (Lakoff and Johnson, 1980; Lakoff, 1993), have
identified many sets of cross-domain mappings underlying conventional metaphorical
expressions: time is space, life is a journey, anger is heat, events are actions,
etc. According to CMT, conceptual metaphors are static, ontological, fixed sets of
partial correspondances between two conceptual domains. Metaphor transfers inferences
from the source domain, more concrete or better structured, to the target domain,
which is more abstract or less delineated. A system of thousands of metaphorical mappings
constitutes the main mechanism for abstract thought in the human mind.
From the nineties, the semantic postulates of CMT have been used to develop the Neural
Theory of Language (NTL) (Gallese and Lakoff, 2005; Feldman, 2008; Lakoff, 2008).
In NTL, conceptual metaphors are replaced by neural mappings, combinations of simple
neural circuits that carry out conceptual mappings. The major function of all this
neural binding is the reuse of sensorimotor brain mechanisms for new roles in language
and reasoning. This is congenial with the grounding of abstract concepts in perceptual
experience (Barsalou, 1999, 2008), called embodiment in conceptual mappings research
(Johnson, 1987, 2008; Lakoff, 1987; Lakoff and Johnson, 1999). The overarching idea
of CMT-NTL is a “metaphorical mind-brain,” based on direct, binary transfer across
domains. The transfer is carried out through static cognitive habits, which are implemented
by neural circuitry connecting pairs of brain areas. For the brain, metaphor is once
more privileged over all other manifestations of mapping, just like it was for the
mind. A good example of the rapidly growing interest in the neuroscience of metaphor
is the Frontiers issue about the topic, currently being edited by Vicky T. Lai and
Seana Coulson.
But the metaphorical brain seems quite insufficient to account for the pervasiveness
and complexity of neural reuse. In a recent BBS target article, Michael Anderson (2010)
shows that what is going on in the brain dwarfs the predictions of embodiment or CMT-NTL.
Statistics run on thousands of fMRI studies indicate that even fairly small brain
regions are typically reused in multiple tasks, with even higher reuse probabilities
if a region is involved in perception or action (Anderson et al., 2010).
Neural reuse is ubiquitous and dynamic, and many of its results cannot be explained
as domain-structuring inheritance. Anderson examines, among others, the following
examples: the SNARC effect (a mental number line with magnitudes increasing from left
to right), the correlation between finger representation and numerical cognition,
the interaction of word and gesture, or the phonological loop in working memory. These
cases present no metaphorical projection, and some of them involve more than two components.
Rather than direct transfer of information, a given system seems to be reused for
a non-primary purpose because it happens to have a function or structure that are
appropriate for the particular cognitive task at hand. As Anderson claims, we need
a broader theoretical framework, able to account for those individual phenomena as
well as for the general prevalence of neural reuse.
From transfer to emergence: the network model of conceptual integration
Can conceptual mappings research provide such a framework? For one thing, the CMT-NTL
model is certainly not the only one in the field. CMT and the pervasiveness of mapping
were the point of departure of Gilles Fauconnier's Mental Space Theory (Fauconnier,
1985, 1997), later developed by Fauconnier and Mark Turner into Conceptual Integration
Theory, or Blending Theory (BT) (Turner, 1996, 2014; Fauconnier and Turner, 2002).
Beyond the common ground with CMT (Fauconnier and Lakoff, 2013), BT introduces significant
innovations. Mental spaces are not vast domains such as time or space, but small conceptual
packets that flexibly combine entrenched structures and contextual information, for
local purposes of thought and action. Mappings are established through structural
or functional correspondances between input spaces in a generic mental space. The
participation of more than two inputs is quite typical. Selectively projected to a
blended space or conceptual blend, elements from the inputs interact, typically producing
emergent structure, which cannot be accounted for by direct transfer between domains.
Inferences can take place in the blend, but also be projected back to the inputs,
which can be modified as the process unfolds. The mappings, the emergence of novel
structure, the adjustment of the inputs, and everything else going on is guided by
universal governing principles and competing optimality principles, by the functional
requirements of the particular network of mental spaces, dictated by context and goals,
and by the creativity of the individual or group who are striving to make the most
of it all.
The overarching picture that results from BT bears important differences with that
of CMT-NTL. Advanced blending underlies all manifestations of mapping, including metaphor,
which is just one more surface product of this species-defining capacity for integrating
disparate mental components into new, meaningful wholes. The human brain is a bubble
chamber of mental spaces, constantly building new integration networks, and a culture
is an even larger bubble chamber (Fauconnier and Turner, 2002, p. 321–322). Just like
evolution—and neural reuse—, blending is opportunistic: it reuses whatever is functionally
suitable, right there and then. As it happens with the natural selection of living
organisms, the process of trial and error in conceptual and neural reuse never stops.
Through it, minds and cultures select the few integrations that are really useful,
anchor them by means of symbolic procedures, and pass them on to the next generation.
To become productive habits, both generic templates of conceptual integration and
patterns of neural reuse need to find an adequate niche within the general system
(about the notion of neural niche, see: Anderson, 2010, and the commentary by Atsushi
Iriki therein; Iriki and Sakura, 2008; Iriki and Taoka, 2012).
One example: opportunistic reuse in the number line and the timeline
In blending as in neural reuse, a given item, once identified as potentially useful,
is integrated into the network under construction. If necessary and possible, the
item is adjusted for optimization in its new function. If it works, the item is kept
in the network, although it still remains available for its older functions. Networks
and their components are discarded and entrenched in a dynamic, extremely agile process.
What is going on here is not direct transfer of structure, but rather the construction
of a new whole with old pieces. The novel properties are not borrowed from the structures
being reused, but result from their performance in a new network.
Among other examples, Anderson (2010) illustrates this with the spatial-numerical
association of response codes (SNARC) effect, that is, a mental number line in which
numerals are arrayed from left to right, in order of increasing magnitude (Dehaene
et al., 1993). As Anderson explains, there is no metaphoric mapping or perceptual
grounding here: in sensorimotor experience, magnitude may increase with height (the
more is up metaphor), but not laterally, and certainly not in the direction of writing.
Numerals do not inherit the structure of the spatial shifting mechanism: the left-to-right
line has been picked opportunistically, and integrated with numeral magnitude, simply
because the resulting blend meets the requirements of the task. We could add to Anderson's
argument by pointing out that the mental number line, as a symbolic device, needed
considerable cultural time to emerge: it was only invented in seventeenth-century
Europe, although awareness of potential correspondances between numbers and spatial
relations dates back to Babylon (Núñez, 2009). It took thousands of years for the
pattern to find an appropriate niche, alongside a representational format that would
ensure its transmission.
The number line is what gets called a material anchor for a conceptual blend (Hutchins,
2005). A perceptual structure is used as an input in the integration process. In the
blend, perceptual relations are fused with conceptual relations. Now consider a very
similar case. Varied psycholinguistic evidence shows that processing temporal expressions
causes the automatic activation of a mental timeline, also running from left to right
in cultures with that writing system (Torralbo et al., 2006; Weger and Pratt, 2008;
Santiago et al., 2010). Blending theorists have revised the time is space metaphor,
and shown that it is a complex network that produces a motion scene with special rules
and constraints, designed to facilitate the representation of time: all observers
are on the same spot, all objects move along the same path, and spatial relations
can even be modified by the emotional attitude of the observer: “Monday is almost
here, but Friday is so far away” (Fauconnier and Turner, 2008). The straight line
is particularly useful for anchoring this blended scene. The result is a graphic representation
with novel properties, which allow us to see diachrony at a glance, to divide it easily
into periods, to represent events as dots, etc.
The timeline is a generic integration template that blends at least four inputs: time
and time measures, spatial extent, objects, and events (Coulson and Cánovas, 2013).
Spatial shifting from left to right is absent from all these components, but it happens
to facilitate the task immensely, and thus it is imported to the blend, for local
purposes. The pattern is not functional as a metaphor in language, where past and
future are not on the left or right, but it is extremely productive in gesture (Casasanto
and Jasmin, 2012), where the lateral axis is more easily available. Again, the timeline
has a long history of failed cultural representations behind it (Rosenberg and Grafton,
2010), but, once the blending template found its niche, it is reused time and again,
and can even be adapted for representing complex emotions and creating sophisticated
poetic effects (Cánovas and Jensen, 2013). Metaphor is useful, but not enough to understand
the timeline: a broader framework of reuse and integration is needed.
What kind of model we need
BT researchers have indeed identified many recurrent patterns and theorized about
them, but we still lack a general framework for generic integration templates (some
work along those lines: Fauconnier and Turner, 2002; Fauconnier, 2009; Cánovas, 2010,
2011; Turner, 2014). A fruitful interaction with research on neural reuse can impose
further constraints and requisites than those observed in the semantic or semiotic
analyses. A model of conceptual mapping habits fully compatible with neural reuse
may include the following:
Network thinking (Mitchell, 2006) rather than direct binary transfer.
Flexibility in the activation, selection, and integration of conceptual and neural
patterns.
Focus on emergence.
Emphasis on competing optimality principles, e.g., a left-to-right straight line leaves
aside many relevant aspects of time or magnitude, but its functionality is privileged.
Detailed examination of how context and goals, including cultural diachrony, shape
the process of integration.
A model of entrenchment not based on ontological projection, but on the idea of “attaining
a niche” through instance-based learning and context-sensitive usage.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial
or financial relationships that could be construed as a potential conflict of interest.