We agree with Heintz & Scott-Phillips that pragmatics does not supplement, but is prior to and underpins, language. Indeed, human non-linguistic communication is astonishingly rich, flexible, and subtle, as we illustrate through the game of charades, where people improvise communicative signals when linguistic channels are blocked. The route from non-linguistic charade-like communication to combinatorial language involves (1) local processes of conventionalization and grammaticalization and (2) spontaneous order arising from mutual constraints between different communicative signals.

If human language must be squeezed through a narrow cognitive bottleneck, what are the implications for language processing, acquisition, change, and structure? In our target article, we suggested that the implications are far-reaching and form the basis of an integrated account of many apparently unconnected aspects of language and language processing, as well as suggesting revision of many existing theoretical accounts. With some exceptions, commentators were generally supportive both of the existence of the bottleneck and its potential implications. Many commentators suggested additional theoretical and linguistic nuances and extensions, links with prior work, and relevant computational and neuroscientific considerations; some argued for related but distinct viewpoints; a few, though, felt traditional perspectives were being abandoned too readily. Our response attempts to build on the many suggestions raised by the commentators and to engage constructively with challenges to our approach.

This study examined whether musical training, ethnicity, and experience with a natural tone language influenced sensitivity to tone while listening to an artificial tone language. The language was designed with three tones, modeled after level-tone African languages. Participants listened to a 15-min random concatenation of six 3-syllable words. Sensitivity to tone was assessed using minimal pairs differing only in one syllable (nonword task: e.g., to-kà-su compared to ca-fí-to) or only in tone (tone task: e.g., to-kà-su compared to to-ká-su). Proficiency in an East Asian heritage language was the strongest predictor of success on the tone task. Asians without tone language experience were no better than other ethnic groups. We conclude by considering implications for research on second language learning, especially as approached through artificial language learning.

Memory is fleeting. New material rapidly obliterates previous material. How, then, can the brain deal successfully with the continual deluge of linguistic input? We argue that, to deal with this “Now-or-Never” bottleneck, the brain must compress and recode linguistic input as rapidly as possible. This observation has strong implications for the nature of language processing: (1) the language system must “eagerly” recode and compress linguistic input; (2) as the bottleneck recurs at each new representational level, the language system must build a multilevel linguistic representation; and (3) the language system must deploy all available information predictively to ensure that local linguistic ambiguities are dealt with “Right-First-Time”; once the original input is lost, there is no way for the language system to recover. This is “Chunk-and-Pass” processing. Similarly, language learning must also occur in the here and now, which implies that language acquisition is learning to process, rather than inducing, a grammar. Moreover, this perspective provides a cognitive foundation for grammaticalization and other aspects of language change. Chunk-and-Pass processing also helps explain a variety of core properties of language, including its multilevel representational structure and duality of patterning. This approach promises to create a direct relationship between psycholinguistics and linguistic theory. More generally, we outline a framework within which to integrate often disconnected inquiries into language processing, language acquisition, and language change and evolution.

Although Pickering & Garrod (P&G) argue convincingly for a unified system for language comprehension and production, they fail to explain how such a system might develop. Using a recent computational model of language acquisition as an example, we sketch a developmental perspective on the integration of comprehension and production. We conclude that only through development can we fully understand the intertwined nature of comprehension and production in adult processing.

There are numerous models of how speech segmentation may proceed in infants acquiring their first language. We present a framework for considering the relative merits and limitations of these various approaches. We then present a model of speech segmentation that aims to reveal important sources of information for speech segmentation, and to capture psycholinguistic constraints on children's language perception. The model constructs a lexicon based on information about utterance boundaries and deduces phonotactic constraints from the discovered lexicon. Compared to other models of speech segmentation, our model performs well in terms of accuracy, computational tractability and the number of components of the model. Finally, our model also reflects the psycholinguistic effects of language learning, in terms of the early advantage for segmentation provided by the child's name, and by revealing the overlap in usefulness of information for segmentation and for grammatical categorization of the language.

Evans & Levinson (E&L) argue that language universals are a myth. Christiansen and Chater (2008) have recently suggested that innate universal grammar is also a myth. This commentary explores the connection between these two theses, and draws wider implications for the cognitive science of language.

Two studies examined the role of phonological cues in the lexical categorization of new words when children could also rely on learning by exclusion and whether the role of phonology depends on extensive experience with a language. Phonological cues were assessed via phonological typicality – an aggregate measure of the relationship between the phonology of a word and the phonology of words in the same lexical class. Experiment 1 showed that when monolingual English-speaking seven-year-olds could rely on learning by exclusion, phonological typicality only affected their initial inferences about the words. Consistent with recent computational analyses, phonological cues had stronger impact on the processing of verb-like than noun-like items. Experiment 2 revealed an impact of French on the performance of seven-year-olds in French immersion when tested in a French language environment. Thus, phonological knowledge may affect lexical categorization even in the absence of extensive experience.

It is widely assumed that human learning and the structure of human languages are intimately related. This relationship is frequently suggested to derive from a language-specific biological endowment, which encodes universal, but communicatively arbitrary, principles of language structure (a Universal Grammar or UG). How might such a UG have evolved? We argue that UG could not have arisen either by biological adaptation or non-adaptationist genetic processes, resulting in a logical problem of language evolution. Specifically, as the processes of language change are much more rapid than processes of genetic change, language constitutes a “moving target” both over time and across different human populations, and, hence, cannot provide a stable environment to which language genes could have adapted. We conclude that a biologically determined UG is not evolutionarily viable. Instead, the original motivation for UG – the mesh between learners and languages – arises because language has been shaped to fit the human brain, rather than vice versa. Following Darwin, we view language itself as a complex and interdependent “organism,” which evolves under selectional pressures from human learning and processing mechanisms. That is, languages themselves are shaped by severe selectional pressure from each generation of language users and learners. This suggests that apparently arbitrary aspects of linguistic structure may result from general learning and processing biases deriving from the structure of thought processes, perceptuo-motor factors, cognitive limitations, and pragmatics.

Our target article argued that a genetically specified Universal Grammar (UG), capturing arbitrary properties of languages, is not tenable on evolutionary grounds, and that the close fit between language and language learners arises because language is shaped by the brain, rather than the reverse. Few commentaries defend a genetically specified UG. Some commentators argue that we underestimate the importance of processes of cultural transmission; some propose additional cognitive and brain mechanisms that may constrain language and perhaps differentiate humans from nonhuman primates; and others argue that we overstate or understate the case against co-evolution of language genes. In engaging with these issues, we suggest that a new synthesis concerning the relationship between brains, genes, and language may be emerging.

Cognitive developmental disorders cannot be properly understood without due attention to the developmental process, and we commend the authors’simulations in this regard. We note the contribution of these simulations to the nascent field of connectionist modeling of developmental disorders and outline a set of criteria for assessing individual models in the hope of furthering future modeling efforts.

We agree with Caplan & Waters that there are problems with the single-resource theory of sentence comprehension. However, we challenge their dual-resource alternative on theoretical and empirical grounds and point to a more coherent solution that abandons the notion of working memory resources.