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Creating Language across Multiple Time-Scales

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, 2010; processing: Christiansen & Chater, 2016). A comprehensive account of the CNL research can be found in the book Creating language: Integrating evolution, acquisition, and processing by Christiansen & Chater (2016).

An overview of our evolutionary account of language can be found in the streaming video of Dr. Christiansen's keynote, Language Evolution: Complexity across Multiple Timescales, at the 2013 European Conference on Complex Systems (ECCS’13), Barcelona, Spain.

To get an idea of our perspective on language processing and its importance for acquisition, see the streaming video of Dr. Christiansen's plenary, Language Acquisition as Learning to Process, at the 2014 International Congress for the Study of Child Language, Amsterdam, the Netherlands.

Language as Shaped by the Brain

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; Baronchelli, Chater, Pastor-Satorras & Christiansen, 2012). 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; Chater & Christiansen, 2010). 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 (Reali & Christiansen, 2009). This work includes studies investigating some of the basic limitations on sequential learning (Conway & Christiansen, 2005, 2006, 2009) as well as potential overlaps in neural substrates for sequential learning and language (Christiansen, Kelly, Shillcock & Greenfield, 2010; Christiansen, Conway & Onnis, 2012). 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.

Language Acquisition as Multiple-Cue Integration

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 (Christiansen, 2013). 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; Monaghan & Christiansen, 2010) 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 (Fitneva, Christiansen & Monaghan, 2009) but also affect syntactic processing in adulthood (Farmer, Christiansen & Monaghan, 2006; Monaghan, Christiansen, Farmer & Fitneva, 2010). 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).

Language Processing as a Usage-Based Skill

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 (Misyak, Christiansen & Tomblin, 2010; de Vries, Geukes, Zwitserlood, Petersson & Christiansen, 2012). Additional computational modeling results indicate that such sequential learning may also support the processing of recursive sentence constructions (Christiansen & Chater, 1999, 2015; Christiansen & MacDonald, 2009). Seen together, this research indicates that language processing is best construed as a usage-based skill, relying on the integration of multiple constraints.

Research funded by

Cornell University