A MISSING LINK IN THE CULTURAL EVOLUTION OF LANGUAGE: CONNECTING SEQUENTIAL LEARNING AND LANGUAGE EMPIRICALLY

Within the growing perspective of cultural transmission as a pivotal component to language evolution (e.g., Kirby, Christiansen & Chater, 2009; Tomasello, 2008), it has been proposed that language has been substantially shaped by the human brain—constrained in its evolution by socio-pragmatic, perceptuo-motor, cognitive and other nonlinguistically-specific factors defining the nature of human learning and processing biases (Christiansen & Chater, 2008). As one such factor, pre-existing learning mechanisms for the processing of sequential structure may have played a substantial role in the evolution of human language. This hypothesis is supported from artificial grammar/language learning studies and computational simulations examining the relationship between sequential learning biases and the structure of evolved languages (see, e.g., Kirby et al., 2009), but few studies exist that directly test within individuals for an empirical link between such learning and language.

A clear prediction of the above theoretical view would be that observed variation in language processing performance should be associated with variation in sequential learning abilities. We investigated this hypothesis, using a within-subjects design in which 50 monolingual native English speakers were assessed on both sequence learning and on-line language processing. In our sequence-learning task, an artificial language (Gómez, 2002) was instantiated within an adapted serial reaction time (SRT) task, thereby providing continuous reaction-time (RT) measures of learning as it unfolded. The group learning trajectory revealed a gradually emerging sensitivity to nonadjacent dependencies in the artificial language. Learning was further confirmed by an offline standard grammaticality judgment post-test in which scores were significantly above chance. Crucial to our study aim, we calculated a learning score for each participant by subtracting their RT performance in the initial training block of string-trials from that in the final training block, with resulting scores reflecting substantial individual differences in pattern-specific sequential learning.

To determine whether good sequential learners are also good at tracking the long-distance dependencies characteristic of natural language, the same participants completed a word-by-word self-paced reading task involving sentences with center-embedded subject- (SR) and object-relative (OR) clauses. Individual differences in processing these sentences are well documented, with ORs eliciting longer reading times, especially at the main verb (King & Just, 1991). We found a positive relationship between continuous individual differences in sequential learning and better processing performance for the relative clauses at the main verb. Additionally, when classifying learners as "good"/"poor" based on scores from the sequence learning task, good learners displayed reading patterns characteristic of more proficient language processors, with less difficulty at the OR main verb and less of a divergence in processing patterns for the two clause-types.

These findings thus provide an empirical association between individuals' on-line sequential learning of nonadjacencies and their on-line processing of complex, long-distance dependencies in natural language. These results further dovetail with recent molecular genetics findings implicating the involvement of FOXP2 in sequential learning on a SRT task. Common allelic variation in FOXP2 was associated with differences in sequential learning patterns, which in turn were linked to variation in grammatical abilities (Tomblin et al., 2007). This suggests that FOXP2 may have served as a pre-adaptation for human sequential learning mechanisms, while providing further evidence for a key role of such abilities in the cultural transmission of language. By empirically connecting sequential learning and language, these studies thus offer a heretofore missing link in the cultural evolution of language.

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