Neurolinguistics

In standard models of language production or comprehension, the elements which are retrieved from memory and combined into a syntactic structure are “lemmas” or “lexical items.” Such models implicitly take a “lexicalist” approach, which assumes that lexical items store meaning, syntax, and form together, that syntactic and lexical processes are distinct, and that syntactic structure does not extend below the word level. Across the last several decades, linguistic research examining a typologically diverse set of languages has provided strong evidence against this approach. These findings suggest that syntactic processes apply both above and below the “word” level, and that both meaning and form are partially determined by the syntactic context. This has significant implications for psychological and neurological models of language processing as well as for the way that we understand different types of aphasia and other language disorders. As a consequence of the lexicalist assumptions of these models, many kinds of sentences that speakers produce and comprehend—in a variety of languages, including English—are challenging for them to account for. Here we focus on language production as a case study. In order to move away from lexicalism in psycho- and neuro-linguistics, it is not enough to simply update the syntactic representations of words or phrases; the processing algorithms involved in language production are constrained by the lexicalist representations that they operate on, and thus also need to be reimagined. We provide an overview of the arguments against lexicalism, discuss how lexicalist assumptions are represented in models of language production, and examine the types of phenomena that they struggle to account for as a consequence. We also outline what a non-lexicalist alternative might look like, as a model that does not rely on a lemma representation, but instead represents that knowledge as separate mappings between (a) meaning and syntax and (b) syntax and form, with a single integrated stage for the retrieval and assembly of syntactic structure. By moving away from lexicalist assumptions, this kind of model provides better cross-linguistic coverage and aligns better with contemporary syntactic theory.

A fascinating descriptive property of human language processing whose explanation is still debated is that subject-gap relative clauses are easier to process than object-gap relative clauses, across a broad range of languages with different properties. However, recent work suggests that this generalization does not hold in Basque, an ergative language, and has motivated an alternative generalization in which the preference is for gaps in morphologically unmarked positions—subjects in nominative-accusative languages, and objects and intransitive subjects in ergative-absolutive languages. Here we examined whether this generalization extends to another ergative-absolutive language, Georgian. ERP and self-paced reading results show a large anterior negativity and slower reading times when a relative clause is disambiguated to an object relative vs a subject relative. These data thus suggest that in at least some ergative-absolutive languages, the classic descriptive generalization—that object relative clauses are more costly than subject relative clauses—still holds.

Speech processing is highly incremental. It is widely accepted that human listeners continuously use the linguistic context to anticipate upcoming concepts, words, and phonemes. However, previous evidence supports two seemingly contradictory models of how a predictive context is integrated with the bottom-up sensory input: Classic psycholinguistic paradigms suggest a two-stage process, in which acoustic input initially leads to local, context-independent representations, which are then quickly integrated with contextual constraints. This contrasts with the view that the brain constructs a single coherent, unified interpretation of the input, which fully integrates available information across representational hierarchies, and thus uses contextual constraints to modulate even the earliest sensory representations. To distinguish these hypotheses, we tested magnetoencephalography responses to continuous narrative speech for signatures of local and unified predictive models. Results provide evidence that listeners employ both types of models in parallel. Two local context models uniquely predict some part of early neural responses, one based on sublexical phoneme sequences, and one based on the phonemes in the current word alone; at the same time, even early responses to phonemes also reflect a unified model that incorporates sentence level constraints to predict upcoming phonemes. Neural source localization places the anatomical origins of the different predictive models in non-identical parts of the superior temporal lobes bilaterally, with the right hemisphere showing a relative preference for more local models. These results suggest that speech processing recruits both local and unified predictive models in parallel, reconciling previous disparate findings. Parallel models might make the perceptual system more robust, facilitate processing of unexpected inputs, and serve a function in language acquisition.