Interfaces (traveling oscillations) + Recursion (delta-theta code) = Language (original) (raw)
Related papers
Why Brain Oscillations Are Improving Our Understanding of Language
Frontiers in Behavioral Neuroscience, 2019
We explore the potential that brain oscillations have for improving our understanding of how language develops, is processed in the brain, and initially evolved in our species. The different synchronization patterns of brain rhythms can account for different perceptual and cognitive functions, and we argue that this includes language. We aim to address six distinct questions-the What, How, Where, Who, Why, and When questions-pertaining to oscillatory investigations of language. Language deficits found in clinical conditions like autism, schizophrenia and dyslexia can be satisfactorily construed in terms of an abnormal, disorder-specific pattern of brain rhythmicity. Lastly, an eco-evo-devo approach to language is defended with explicit reference to brain oscillations, embracing a framework that considers language evolution to be the result of a changing environment surrounding developmental paths of the primate brain.
Implications of Travelling Weakly Coupled Oscillators for the Cortical Language Circuit
UCL Working Papers in Linguistics, 2017
The search for the neural code across a range of cognitive domains has seen a marked transition from the analysis of individual spike timings to larger patterns of synchronisation. It is argued that the study of language should readily embrace these systems-level developments. In particular, recent findings concerning the scope of possible oscillatory synchronisation in the human brain have revealed the existence of travelling/migrating oscillations, adding further impetus to reject the typical stasis found in cartographic neurolinguistics models. After exploring empirically-motivated revisions to the neural code for hierarchical phrase structure, it is discussed how this code could provide a new perspective on language disorders, fluid intelligence and language acquisition.
The rhythms of language: an overview of linguistic processes and neural oscillations
2021
For the last decades neuroscientists have grown interest in the analysis of the rhythmic activity of the brain synchronized at temporal and spatial level. These neural oscillations, grouped by their frequency, have been proposed to govern all cognitive processes. In the field of the neurobiology of language, considerable research has linked speech processing and language comprehension to neural oscillations. On one hand, neural rhythmic activity is thought to synchronize to relevant spectral information of speech on three-time scales – which physically reflect phoneme, syllable and phrase processing. On the other hand, syntactic and semantic processing is subserved by faster oscillatory patterns not necessarily related to the acoustic properties of speech. For each linguistic process, this article summarizes the neural oscillations involved. Further evidence comes from studies on language-related pathologies.
The Brain Dynamics of Linguistic Computation
Frontiers in Psychology, 2015
Neural oscillations at distinct frequencies are increasingly being related to a number of basic and higher cognitive faculties. Oscillations enable the construction of coherently organised neuronal assemblies through establishing transitory temporal correlations. By exploring the elementary operations of the language faculty – labeling, concatenation, cyclic transfer – alongside neural dynamics, a new model of linguistic computation is proposed. It is argued that the universality of language, and the true biological source of Universal Grammar, is not to be found purely in the genome as has long been suggested, but more specifically within the extraordinarily preserved nature of mammalian brain rhythms employed in the computation of linguistic structures. Computational-representational theories are used as a guide in investigating the neurobiological foundations of the human ‘cognome’ – the set of computations performed by the nervous system – and new directions are suggested for how the dynamics of brain (the ‘dynome’) operates and execute linguistic operations. The extent to which brain rhythms are the suitable neuronal processes which can capture the computational properties of the human language faculty is considered against a backdrop of existing cartographic research into the localisation of linguistic interpretation. Particular focus is placed on labeling, the operation elsewhere argued to be species-specific. A Basic Label model of the human cognome-dynome is proposed, leading to clear, causally-addressable empirical predictions, to be investigated by a suggested research program, Dynamic Cognomics. In addition, a distinction between minimal and maximal degrees of explanation is introduced to differentiate between the depth of analysis provided by cartographic, rhythmic, neurochemical and other approaches to computation.
biorXiv, 2017
The neurobiology investigation of language seems limited by the impossibility to link directly linguistic computations with neural computations. To address this issue, we need to explore the hierarchical interconnections between the investigated fields trying to develop an inter-field theory. Considerable research has realized that event-related fluctuations in rhythmic, oscillatory EEG/MEG activity may provide a new window on the dynamics of functional neuronal networks involved in cognitive processing. Accordingly, this paper aims to outline a formal proposal on neuronal computation and representation of syntactic structures within the oscillatory neuronal dynamics. I briefly present the nature of event-related oscillations and how they work on the base of synchronization and de-synchronization processes. Then, I discuss some theoretical premises assuming that reentrant (hierarchical) properties of synchronized oscillatory rhythms constitute the biological endowment that allow the development of language in humans when exposed to appropriate inputs. The main rhythms involved in language and speech processing are examined: i.e. theta, alpha, beta, and gamma bands. A possible formal representation of the syntactic structures on the base of these oscillatory rhythms is discussed: in this model, the theta-gamma rhythms are cross-frequency coupled into the alpha-gamma-beta and into the gamma-beta-theta rhythms to generate the sentence along reentrant cortico-thalamic pathways through Merge, Label and Move operations. Finally, I present few conclusive remarks within an evolutionary perspective.
Biolinguistics
This brief piece argues that it is desirable to reconceptualize the syntactic combinatorial mechanism Merge as a higher-order function that takes two functions (= a selector function and its ‘argument’ function) and yields a composite function in the context of I-language. On this functional characterization of Merge, all of the elements involved in Merge are conceived as functions as well: lexical items (LIs) as input of Merge and syntactic objects (SOs) as both input and output of Merge. It is claimed that this perspective of Merge is a bridging step toward further facilitating the mesoscopic-level (= dynome-level) investigation of the brain oscillatory nature of human language in the field of biolinguistics. In this framework, I make the case that it would be possible to analyze the brain oscillatory nature of Merge by appealing to the mathematical operation of the Fourier transform (FT) to the extent that Merge-related brain oscillations as physical waves can be captured by comp...
Still a bridge too far? Biolinguistic questions for grounding language on brains
Physics of Life Reviews, 2008
In this paper we discuss how Fibonacci growth patterns are apparent in the structure of human language. We moreover show how familiar dynamics yielding these sorts of patterns in nature may be taken to apply, at some level of abstraction, for the human faculty of language. The overall picture casts doubts on any simplistic treatment of language behavior, of the sort stemming from classical behaviorism in psychology (which is again popular in contemporary computational models). Instead, it appears to be more profitable to study language as a complex dynamic system, emerging in human brains for physical reasons which are yet to be fully comprehended, but which in the end disfavor any dualistic approach to the study of mind in general, and the human mind in particular.
Subcortical syntax: Reconsidering the neural dynamics of language
Journal of Neurolinguistics, 2022
Subcortical contributions to core linguistic computations pertaining to syntax-semantics remain drastically under-studied. We critique the cortico-centric focus which has largely accompanied research into these higher-order linguistic functions and suggest that, while much remains unknown, there is nevertheless a rich body of research concerning the possible roles of subcortex in natural language. Although much current evidence emerges from distinct domains of cognitive neuroscience, in this review article we attempt to show that there is a clear place for subcortex in models of natural language syntax-semantics, including a role in binary set-formation, categorized object maintenance, lexico-semantic processing, conceptual-to-lexical transformations, morphosyntactic linearization, semantic feature-binding, and cross-cortical representational integration. In particular, we consult models of language processing relying on oscillatory brain dynamics in order to investigate both the apparent and possible functional roles of subcortex in language.
Toward a neural theory of language: Old issues and new perspectives
Journal of Neurolinguistics, 2012
The cognitive neuroscience of language is an exciting interdisciplinary perspective that suffers from unresolved epistemological and methodological issues. Despite the impressive amount of neural evidence accumulated until now, the field of research results fragmented and it is quite difficult to reach a unit of analysis and consensus on the object of study. This frustrating state of the art results in a detrimental reductionism consisting in the practice of associating linguistic computation hypothesized at theoretical level with neurobiological computation. However, these two entities are at the moment ontologically incommensurable. The problem lies in the fact that a theory of language consistent with a range of neurophysiological and neuroimaging techniques of investigation and verifiable through neural data is still lacking. In this article, I focus on the main issues, questions, and concerns that prevent the integrated study of language and brain and I explore a feasible way for linguistics to pursue a theory susceptible of neuroscientific testability in the light of recent neurocognitive models and of data on the functional-anatomic organization of language in the brain. Finally, I discuss a possible interdisciplinary program in order to achieve a theory capable of predictions on the real-time neural constrains characterizing the biological bases of language.
The dynamics of language-related brain images
Neurocase, 2005
The advent of functional brain imaging has renewed our knowledge of the brain correlates of cognitive processes. Based on different physical principles, Positron Emission Tomography (PET), functional Magnetic Resonance Imaging (fMRI), and multi-channel Electro-or Magneto-Encephalography (EEG, MEG) make it possible to measure changes in various indices of ongoing neural activities arising from the brain 'in action.' These techniques soon became popular because they produce suggestive colorful 'maps', intuitively perceived as the neural anatomy of cognitive functions such as language processing. Despite the revolutionary input of neuroimaging, conceptualizations of the language/brain relationships are still too static. 'Neuroimages' do not just consist of maps of the crucial nodes activated within largescale neural systems throughout the brain. They should rather be viewed as representations of transient states and time series of activities in these systems. However, the time scale which defines such transient states varies largely from the ms order for EEG and MEG to a few seconds for fMRI and a few minutes for PET. Language, as a high-speed process of incoming information and real-time programming of responses, is a typical example in which it is critical to consider the dynamics of the ever-changing functional status of its neural counterparts (for a review, Démonet et al., in press).