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Language is a hallmark of the human species; the flexibility and
unbounded expressivity of our linguistic abilities is
unparalleled in the biological world. As such, language poses
fundamental questions for the cognitive sciences: How did
language evolve in response to environmental and biological
forces? How is language acquired by each new generation? And how
is language processed 'on-line' in everyday social interactions?
These questions have typically been treated as separate topics,
to be addressed more or less independently. The work done in the
Cognitive Neuroscience Lab suggests this tendency is misguided
— there are strong constraints across domains, allowing each to
shed light on one another.
CNL research is therefore conducted within a unified framework
for understanding language across multiple time-scales:
evolution, acquisition and processing. The theoretical
foundations for this framework are laid out in three key
publications, each relating one of the time-scales to the others
(evolution: Christiansen & Chater, 2008;
acquisition: Chater & Christiansen, in press;
processing: Christiansen & Chater, in preparation).
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Our research on language evolution has shown that traditional
notions of universal grammar as a biological endowment of
abstract linguistic constraints can be ruled out on evolutionary
grounds (Chater, Reali & Christiansen, 2009). Instead, the
fit between the mechanisms employed for language and the way in
which language is acquired and used can be explained by
processes of cultural evolution shaped by the human brain
(Christiansen & Chater, 2008). On this account, language
evolved by 'piggy-backing' on pre-existing neural mechanisms,
constrained by socio-pragmatic considerations, the nature of our
thought processes, perceptuo-motor factors, and cognitive
limitations on learning, memory and processing. Using a variety
of different methods, the CNL Lab has been exploring how one of
these constraints -- the ability to learn and process
sequentially presented information -- might have played an
important role in shaping language through cultural evolution.
This work includes studies investigating some of the basic
limitations on statistical learning of sequential structure
(Conway & Christiansen, 2005, 2006). Most recently, we have
embarked on molecular genetics research that, so far, has
indicated that the FOXP2 gene may provide a genetic link
between sequential learning and language. Together, the results
from this and other cross-disciplinary research indicate that
most of the constraints that have shaped language evolution
still affect our current use of language, suggesting that
language universals are best viewed as probabilistic tendencies
resulting from multiple-constraint satisfaction.
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The idea of language as shaped by the brain suggests that
much of the neural hardware involved in language may not be
specific to it. This means that language has to be acquired
largely by mechanisms that are not uniquely dedicated for
this purpose. A substantial amount of CNL Lab research is
therefore dedicated to testing the hypothesis that language
has evolved to rely on a constellation of probabilistic
information sources, or 'cues', for its acquisition.
Although each cue may be only partially reliable in
isolation, when integrated they allow language to be as
expressive as it is while still being learnable by
domain-general learning mechanisms. Some of this research
focuses on computational modeling (Christiansen, Allen &
Seidenberg, 1998) and infant studies (Curtin, Mintz &
Christiansen, 2005) of speech segmentation, including how
the same phonological cues may get the child from
unsegmented speech to lexical categories (Christiansen,
Onnis & Hockema, 2009). Other work has underscored the
probabilistic contributions of phonological and
distributional information to the learning of basic aspects
of syntax. Results from cross-linguistic corpus analyses
have shown that a probabilistic relationship exists between
the sound of a word and how it is used: nouns tend to sound
like other nouns and verbs like other verbs (e.g., Monaghan,
Christiansen & Chater, 2007). Importantly, these
phonological cues not only play a fundamental role in
language acquisition but also affect syntactic processing in
adulthood (Farmer, Christiansen & Monaghan, 2006). These
results suggest that the integration of phonological cues
with other types of information is integral to the
computational architecture of our language system. This
integration, in turn, is what makes language learnable
without universal grammar given the rich sources of
information available in the input (Reali & Christiansen,
2005).
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The multiple-cue integration perspective on language
acquisition highlights the rich nature of the input. In
combination with the emphasis on cultural evolution of
language, this points to a usage-based account of language
processing in which linguistic experience plays a crucial
role in determining language ability. A third line of CNL
Lab research thus investigates the impact of experience on
language processing. Much of this work has focused on the
processing of relative clauses as an example. Evidence from
corpus analyses and on-line sentence processing experiments
has shown that variations in the distribution of different
relative clause types are directly reflected in the ease
with which adults process such constructions (Reali &
Christiansen, 2007). Further differences in relative clause
processing are hypothesized to emerge from variation across
individuals in their experience with language. Predictions
from this account are supported by studies manipulating
language exposure in both connectionist networks (MacDonald
& Christiansen, 2002) and human subjects (Wells,
Christiansen, Race, Acheson & MacDonald, 2009).
Experimental data from ongoing work moreover suggest that
individual differences in basic abilities for sequential
learning and processing, in turn, may affect individuals'
ability to learn from experience. Additional computational
modeling results indicate that such sequential learning may
also support the processing of recursive sentence
constructions (Christiansen & Chater, 1999). Seen
together, this research indicates that language processing
is best construed as a usage-based skill, relying on the
integration of multiple constraints.
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