Innovation of word order harmony across development

The tendency for languages to use harmonic word order patterns—orders that place heads in a consistent position with respect to modifiers or other dependents—has been noted since the 1960s. As with many other statistical typological tendencies, there has been debate regarding whether harmony reflects properties of human cognition or forces external to it. Recent research using laboratory language learning has shown that children and adults find harmonic patterns easier to learn than nonharmonic patterns (Culbertson & Newport, 2015; Culbertson, Smolensky, & Legendre, 2012). This supports a link between learning and typological frequency: if harmonic patterns are easier to learn, while nonharmonic patterns are more likely to be targets of change, then, all things equal, harmonic patterns will be more frequent in the world’s languages. However, these previous studies relied on variation in the input as a mechanism for change in the lab; learners were exposed to variable word order, allowing them to shift the frequencies of different orders so that harmonic patterns became more frequent. Here we teach adult and child learners languages that are consistently nonharmonic, with no variation. While adults perfectly maintain these consistently nonharmonic patterns, young child learners innovate novel orders, changing nonharmonic patterns into harmonic ones

Privileged Computations for Closed-Class Items in Language Acquisition

In natural languages, closed-class items predict open-classitems but not the other way around. For example, in English, ifthere is a determiner there will be a noun, but nouns can occurwith or without determiners. Here, we asked whether languagelearners’ computations are also asymmetrical. In threeexperiments we exposed adults to a miniature language withthe one-way dependency “if X then Y”: if X was present, Ywas also present, but X could occur without Y. We createddifferent versions of the language in order to ask whetherlearning depended on which of these categories was an open orclosed class. In one condition, X was a closed class and Y wasan open class; in a contrasting condition, X was an open classand Y was a closed class. Learning was significantly betterwith closed-class X, even though learners’ exposure wasotherwise identical. Additional experiments demonstrated thatthe perceptual distinctiveness of closed-class items driveslearners to analyze them differently; and, crucially, that theprimary determinant of learning is the mathematicalrelationship between closed- and open-class items and not theirlinear order. These results suggest that learners privilegecomputations in which closed-class items are predictive of,rather than predicted by, open-class items. We suggest that thedistributional asymmetries of closed-class items in naturallanguages may arise in part from this learning bias

Statistical Cues in Language Acquisition: Word Segmentation by Infants

A critical component of language acquisition is the ability to learn from the information present in the language input. In particular, young language learners would benefit from leaming mechanisms capable of utilizing the myriad statistical cues to linguistic structure available in the input. The present study examines eight-month-old infants' use of statistical cues in discovering word boundaries. Computational models suggest that one of the most useful cues in segmenting words out of continuous speech is distributional information: the detection of consistent orderings of sounds. In this paper, we present results suggesting that eight-month-old infants can in fact make use of the order in which sounds occur to discover word-like sequences. The implications of this early ability to detect statistical information in the language input will be discussed with regard to theoretical issues in the field of language acquisition

Critical Period After Stroke Study (CPASS): A phase II clinical trial testing an optimal time for motor recovery after stroke in humans

Restoration of human brain function after injury is a signal challenge for translational neuroscience. Rodent stroke recovery studies identify an optimal or sensitive period for intensive motor training after stroke: near-full recovery is attained if task-specific motor training occurs during this sensitive window. We extended these findings to adult humans with stroke in a randomized controlled trial applying the essential elements of rodent motor training paradigms to humans. Stroke patients were adaptively randomized to begin 20 extra hours of self-selected, task-specific motor therapy at ≤30 d (acute), 2 to 3 mo (subacute), or ≥6 mo (chronic) after stroke, compared with controls receiving standard motor rehabilitation. Upper extremity (UE) impairment assessed by the Action Research Arm Test (ARAT) was measured at up to five time points. The primary outcome measure was ARAT recovery over 1 y after stroke. By 1 y we found significantly increased UE motor function in the subacute group compared with controls (ARAT difference = +6.87 ± 2.63, P = 0.009). The acute group compared with controls showed smaller but significant improvement (ARAT difference = +5.25 ± 2.59 points, P = 0.043). The chronic group showed no significant improvement compared with controls (ARAT = +2.41 ± 2.25, P = 0.29). Thus task-specific motor intervention was most effective within the first 2 to 3 mo after stroke. The similarity to rodent model treatment outcomes suggests that other rodent findings may be translatable to human brain recovery. These results provide empirical evidence of a sensitive period for motor recovery in humans

Acquiring and processing verb argument structure : distributional learning in a miniature language

Adult knowledge of a language involves correctly balancing lexically-based and more language-general patterns. For example, verb argument structures may sometimes readily generalize to new verbs, yet with particular verbs may resist generalization. From the perspective of acquisition, this creates significant learnability problems, with some researchers claiming a crucial role for verb semantics in the determination of when generalization may and may not occur. Similarly, there has been debate regarding how verb-specific and more generalized constraints interact in sentence processing and on the role of semantics in this process. The current work explores these issues using artificial language learning. In three experiments using languages without semantic cues to verb distribution, we demonstrate that learners can acquire both verb-specific and verb-general patterns, based on distributional information in the linguistic input regarding each of the verbs as well as across the language as a whole. As with natural languages, these factors are shown to affect production, judgments and real-time processing. We demonstrate that learners apply a rational procedure in determining their usage of these different input statistics and conclude by suggesting that a Bayesian perspective on statistical learning may be an appropriate framework for capturing our findings

Harmonic biases in child learners: In support of language universals

A fundamental question for cognitive science concerns the ways in which languages are shaped by the biases of language learners. Recent research using laboratory language learning paradigms, primarily with adults, has shown that structures or rules that are common in the languages of the world are learned or processed more easily than patterns that are rare or unattested. Here we target child learners, investigating a set of biases for word order learning in the noun phrase studied by Culbertson, Smolensky & Legendre (2012) in college-age adults. We provide the first evidence that child learners exhibit a preference for typologically common harmonic word order patterns—those which preserve the order of the head with respect to its complements—validating the psychological reality of a principle formalized in many different linguistic theories. We also discuss important differences between child and adult learners in terms of both the strength and content of the biases at play during language learning. In particular, the bias favoring harmonic patterns is markedly stronger in children than adults, and children (unlike adults) acquire adjective ordering more readily than numeral ordering. The results point to the importance of investigating learning biases across development in order to understand how these biases may shape the history and structure of natural languages