The neurobiology of syntax: beyond string sets

Abstract

The human capacity to acquire language is an outstanding scientific challenge to understand. Somehow our language capacities arise from the way the human brain processes, develops and learns in interaction with its environment. To set the stage, we begin with a summary of what is known about the neural organization of language and what our artificial grammar learning (AGL) studies have revealed. We then review the Chomsky hierarchy in the context of the theory of computation and formal learning theory. Finally, we outline a neurobiological model of language acquisition and processing based on an adaptive, recurrent, spiking network architecture. This architecture implements an asynchronous, event-driven, parallel system for recursive processing. We conclude that the brain represents grammars (or more precisely, the parser/generator) in its connectivity, and its ability for syntax is based on neurobiological infrastructure for structured sequence processing. The acquisition of this ability is accounted for in an adaptive dynamical systems framework. Artificial language learning (ALL) paradigms might be used to study the acquisition process within such a framework, as well as the processing properties of the underlying neurobiological infrastructure. However, it is necessary to combine and constrain the interpretation of ALL results by theoretical models and empirical studies on natural language processing. Given that the faculty of language is captured by classical computational models to a significant extent, and that these can be embedded in dynamic network architectures, there is hope that significant progress can be made in understanding the neurobiology of the language faculty.Keywords: implicit artificial grammar learning; fMRI; repeated transcranial magnetic stimulation; language-related genes; CNTNAP2; spiking neural networks INTRODUCTIONRecent years have seen a renewed interest in using artificial grammar learning (AGL) as a window onto the organization of the language system. It has been exploited in cross-species comparisons, but also in studies on the neural architecture for language. Our focus is on the role AGL can play in unravelling the neural basis of human language. For this purpose, its role is relatively limited and mainly restricted to modelling aspects of structured sequence learning and structured sequence processing, uncontaminated by the semantic and phonological sources of information that co-determine the production and comprehension of natural language. Before going into more details related to the neurobiology of syntax and the role of AGL research, we outline what we think are the major conclusions from the research on the neurobiology of language:

Disruption of hierarchical predictive coding during sleep

“…Our source reconstructions confirm these localizations and suggest that they are specific to the intermediate time window of the MMR. The left inferior frontal pars opercularis area (Broca's area) location is also coherent with our use of vowel sequences, because this region is involved in the representation of structured language sequences (55).…”

Understanding understanding source code with functional magnetic resonance imaging

“…However, these studies, several of which were discussed in Section 5, use tasks involving only English words and sentences, not programs. The following studies are particularly interesting, because they revealed the same Brodmann areas as our study: In studies related to reading comprehension and language processing, participants had to understand text passages or decide whether sequences of letters can be produced with rules of a formal grammar [3,9,21,24,25,26,28,30,55,56,68,74]. Regarding working memory, participants had to identify and apply rules or memorize verbal/numerical material [1,47,58,69].…”

“…Several studies suggest that real-time combinatorial operations in the IFG incorporate the current state of processing and incoming information into a new state of processing [30,56]. Hence, the IFG was proposed to be involved in the unification of individual semantic features into an overall representation at the multi-word level [74].…”

Phonological and syntactic competition effects in spoken word recognition: evidence from corpus-based statistics

“…This mask consisted of bilateral IFG (BA 44, 45, 47), insula, anterior cingulate, STG, MTG, angular gyri, inferior parietal lobule, and supramarginal gyri. The mask covered the typical left perisylvian language areas that are of theoretical interest and their right hemisphere homologues (Dronkers et al, 2004; Friederici, 2012; Hickok & Poeppel, 2004, 2007; Petersson & Hagoort, 2012; Tyler & Marslen-Wilson, 2008), while excluding regions not typically involved in language processing. For visualisation, the volumetric statistically thresholded activation maps were projected onto the PALS-B12 surface atlas in CARET version 5.6.…”