The neurobiology of syntax: beyond string sets

Area of Science:

• Neuroscience
• Computational Linguistics
• Cognitive Science

Background:

• Human language acquisition is a complex challenge, involving brain processing, development, and environmental interaction.
• Existing knowledge includes the neural organization of language and insights from artificial grammar learning (AGL) studies.
• The Chomsky hierarchy and formal learning theory provide computational context.

Purpose of the Study:

• To propose a neurobiological model for language acquisition and processing.
• To explore the role of adaptive, recurrent, spiking network architectures.
• To integrate computational models with neurobiological insights.

Main Methods:

• Reviewing neural organization of language and AGL findings.
• Examining the Chomsky hierarchy within computation and learning theory.
• Outlining a neurobiological model using adaptive, recurrent, spiking networks.

Main Results:

• The brain's connectivity represents grammars, enabling syntax through structured sequence processing.
• An adaptive dynamical systems framework accounts for the acquisition of language abilities.
• Recursive processing is implemented via an asynchronous, event-driven, parallel system.

Conclusions:

• The neurobiological infrastructure supports structured sequence processing, forming the basis of syntactic ability.
• Artificial language learning (ALL) paradigms can investigate acquisition and processing within neurobiological models.
• Combining ALL results with theoretical and empirical studies is crucial for advancing understanding of the language faculty.