Neural oscillations at distinct frequencies are increasingly being related to a number of basic and higher cognitive faculties. Oscillations enable the construction of coherently organized 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 the brain (the “dynome”) operate 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 localization 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.

Autism spectrum disorders (ASD) are pervasive neurodevelopmental disorders involving a number of deficits to linguistic cognition. The gap between genetics and the pathophysiology of ASD remains open, in particular regarding its distinctive linguistic profile. The goal of this article is to attempt to bridge this gap, focusing on how the autistic brain processes language, particularly through the perspective of brain rhythms. Due to the phenomenon of pleiotropy, which may take some decades to overcome, we believe that studies of brain rhythms, which are not faced with problems of this scale, may constitute a more tractable route to interpreting language deficits in ASD and eventually other neurocognitive disorders. Building on recent attempts to link neural oscillations to certain computational primitives of language, we show that interpreting language deficits in ASD as oscillopathic traits is a potentially fruitful way to construct successful endophenotypes of this condition. Additionally, we will show that candidate genes for ASD are overrepresented among the genes that played a role in the evolution of language. These genes include (and are related to) genes involved in brain rhythmicity. We hope that the type of steps taken here will additionally lead to a better understanding of the comorbidity, heterogeneity, and variability of ASD, and may help achieve a better treatment of the affected populations.

Autism spectrum disorders (ASD) are pervasive neurodevelopmental disorders entailing social and cognitive deficits, including marked problems with language. Numerous genes have been associated with ASD, but it is unclear how language deficits arise from gene mutation or dysregulation. It is also unclear why ASD shows such high prevalence within human populations. Interestingly, the emergence of a modern faculty of language has been hypothesized to be linked to changes in the human brain/skull, but also to the process of self-domestication of the human species. It is our intention to show that people with ASD exhibit less marked domesticated traits at the morphological, physiological, and behavioral levels. We also discuss many ASD candidates represented among the genes known to be involved in the “domestication syndrome” (the constellation of traits exhibited by domesticated mammals, which seemingly results from the hypofunction of the neural crest) and among the set of genes involved in language function closely connected to them. Moreover, many of these genes show altered expression profiles in the brain of autists. In addition, some candidates for domestication and language-readiness show the same expression profile in people with ASD and chimps in different brain areas involved in language processing. Similarities regarding the brain oscillatory behavior of these areas can be expected too. We conclude that ASD may represent an abnormal ontogenetic itinerary for the human faculty of language resulting in part from changes in genes important for the “domestication syndrome” and, ultimately, from the normal functioning of the neural crest.

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.

For the past two decades, it has widely been assumed by linguists that there is a single computational operation, Merge, which is unique to language, distinguishing it from other cognitive domains. The intention of this paper is to progress the discussion of language evolution in two ways: (i) survey what the ethological record reveals about the uniqueness of the human computational system, and (ii) explore how syntactic theories account for what ethology may determine to be human-specific. It is shown that the operation Label, not Merge, constitutes the evolutionary novelty which distinguishes human language from non-human computational systems; a proposal lending weight to a Weak Continuity Hypothesis and leading to the formation of what is termed Computational Ethology. Some directions for future ethological research are suggested.

This thesis addresses the lexical and psycholinguistic properties of copredication. In particular, it explores its acceptability, frequency, cross-linguistic and electrophysiological features. It proposes a general parsing bias to account for novel acceptability data, through which Complex-Simple predicate orderings are degraded across distinct nominal types relative to the reverse order. This bias, Incremental Semantic Complexity, states that the parser seeks to process linguistic representations in incremental stages of semantic complexity. English and Italian acceptability data are presented which demonstrate that predicate order preferences are based not on sense dominance but rather sense complexity. Initial evidence is presented indicating that pragmatic factors centred on coherence relations can impact copredication acceptability when such copredications host complex (but not simple) predicates. The real-time processing and electrophysiological properties of copredication are also presented, which serve to replicate and ground the acceptability dynamics presented in the thesis.

Drawing on cutting-edge ideas from the biological and cognitive sciences, this book presents both an innovative neuro-computational model of language comprehension and a state-of-the-art review of current topics in neurolinguistics. It explores a range of newly-emerging topics in the biological study of language, building them into a framework which views language as grounded in endogenous neural oscillatory behaviour. This allows the author to formulate a number of hypotheses concerning the relationship between neurobiology and linguistic computation. Murphy also provides an extensive overview of recent theoretical and experimental work on the neurobiological basis of language, from which the reader will emerge up-to-date on major themes and debates. This lively overview of contemporary issues in theoretical linguistics, combined with a clear theory of how language is processed, is essential reading for scholars and students across a range of disciplines.

Schizophrenia is characterized by marked language deficits, but it is not clear how these deficits arise from the alteration of genes related to the disease. The goal of this paper is to aid the bridging of the gap between genes and schizophrenia and, ultimately, give support to the view that the abnormal presentation of language in this condition is heavily rooted in the evolutionary processes that brought about modern language. To that end we will focus on how the schizophrenic brain processes language and, particularly, on its distinctive oscillatory profile during language processing. Additionally, we will show that candidate genes for schizophrenia are overrepresented among the set of genes that are believed to be important for the evolution of the human faculty of language. These genes crucially include (and are related to) genes involved in brain rhythmicity. We will claim that this translational effort and the links we uncover may help develop an understanding of language evolution, along with the etiology of schizophrenia, its clinical/linguistic profile, and its high prevalence among modern populations.