Word knowledge and word usage - Representations and processes in the mental lexicon

The final NetWordS Conference, held on the 30th and 31st of March, and 1st of April 2015 in Pisa, was convened by Prof. Pier Marco Bertinetto, Dr. Vito Pirrelli and Dr. Claudia Marzi, and brought together 91 participants (scholars, Post-Docs, PhD students) from numerous European, and some non-European, countries. A 3-day schedule involved all participants in a focused, cross-disciplinary discussion on representations and processes in the mental lexicon. People are known to understand, memorise and parse words in a context-sensitive, opportunistic way, by caching their most habitual and productive processing patterns into routinized behavioural schemes, similarly to what we observe for sequences of coordinated motor acts. Speakers, however, do not only take advantage of token-based information such as frequency of individual, holistically stored words, or episodic memories of word usage, but they are also able to organise stored word forms through abstract paradigmatic structures (or word families) whose overall size and distribution are important determinants of lexical categorisation, inference and productivity. Lexical organisation is, in fact, not necessarily functional to descriptive economy and minimisation of storage, but appears to be influenced by more dynamic, communicationoriented functions such as memorisation, prediction-based recognition and production. Lending support to this view, usage-based approaches to word processing have recently offered novel explanatory frameworks that capitalise on the stable correlation patterns between lexical representations on the one hand and process-based operations that make representations functional to communicative exchanges on the other hand. By focusing on the battery of cognitive functions supporting verbal communication (ranging from input recoding to rehearsal, access, recall and coactivation) and by exploring their psycholinguistic correlates and neuroanatomical substrates, these approaches promote a new view of language architecture as an emergent property of the interaction between language-specific input conditions and low-level, domain-specific cognitive predispositions

Neuroimaging: mania, revolution, or technological evolution? - A critical review

Imaging has become an increasingly important tool in both research and clinical care. A range of neuroimaging technologies provide unprecedented sensitivity to visualisation of brain structure (i.e. anatomy) and function (i.e. physiology) from the level of individual molecules to the whole brain. Many imaging methods are non-invasive and allow dynamic processes to be monitored over time. Imaging is enabling researchers to identify neural networks involved in cognitive processes; understand disease pathways; recognise and diagnose diseases early, when they are most effectively treated; and determine how therapies work. The cognitive neuroscience of higher order auditory processing has advanced enormously in a brief time, in large part benefiting from neuroimaging approaches. A significant amount of progress has been made, and much of it can be attributed to the possibilities for crossing boundaries afforded by neuroimaging tools. More sophisticated experiments combined with fMRI and EEG are helping to know what the brain is doing as people perform cognitive, emotional, and behavioural actions. MEG technology will allow linguists to explore how social interaction and sensorimotor experience affects the cortical processing of language in children; and the combination of behavioural and brain measures may enhance the certainty with which dyslexia can be predicted for a child and promote the possibility of preventive intervention

Variation and Adaptation in Lexical Processing and Acquisition

Recent emphasis on language knowledge as an emergent dynamic system has drawn considerable attention to the role of time in the way speakers acquire and use their own language. There are at least three levels on which time matters. At the processing level, the interaction between processing and memory constraints, and in particular between short-term and long-term memory issues, is understood to shape the way we recode and organise time-bound sequences of linguistic signals. On an ontogenetic scale, the age of acquisition of language input data, and the duration of exposure (in the case of multilingual contexts) are known to interact with issues of cognitive maturation and brain plasticity, yielding different outcomes as a function of different time intervals. In this connection, also the distribution of input data in a particular linguistic environment (both in terms of word type and token frequency) is bound to have an impact on rate and speed of acquisition and on overall knowledge organisation. Finally, all previously mentioned time-effects conspire to make the language system change through usage and acquisition in passing from one generation to the ensuing one

Words In Action: Interdisciplinary Approaches To Understanding Word Processing And Storage

Almost all levels of language knowledge and processing (from phonology, to syntax and semantics) are known to be affected by knowledge of word structure at varying degrees. A better understanding of the human strategies involved in learning and processing word structure thus lies at the heart of our comprehension of the basic mechanisms serving both language and cognition and is key to addressing some fundamental challenges for the study of the physiology of grammar. On the 12th and 13th of October 2009, in the Research Area of the Italian National Research Council (CNR) in Pisa, 26 scholars from Europe, Canada and the United States were convened to take part in the European Science Foundation Exploratory Workshop "Words in Action: Interdisciplinary Approaches To Understanding Word Processing And Storage". The workshop brought together experts of various scientific domains and different theoretical inclinations to advance the current awareness of theoretical, historical, psycholinguistic, computational and neurophysiological issues in morphological processing and learning, with a view to assessing levels of research convergence and exploring the potential for synergy and strategic co-operation

Percepcija tipičnosti u leksikonu: tipičnost oblika riječi, leksička gustoća i morfonotaktička ograničenja

The extent to which a symbolic time–series (a sequence of sounds or letters) is a typical word of a language, referred to as WORDLIKENESS, has been shown to have effects in speech perception and production, reading proficiency, lexical development and lexical access, short–term and long–term verbal memory. Two quantitative models have been suggested to account for these effects: serial phonotactic probabilities (the likelihood for a given symbolic sequence to appear in the lexicon) and lexical density (the extent to which other words can be obtained from a target word by changing, deleting or inserting one or more symbols in the target). The two measures are highly correlated and thus easy to be confounded in measuring their effects in lexical tasks. In this paper, we propose a computational model of lexical organisation, based on Self–Organising Maps with Hebbian connections defined over a temporal layer (TSOMs), providing a principled algorithmic account of effects of lexical acquisition, processing and access, to further investigate these issues. In particular, we show that (morpho–)phonotactic probabilities and lexical density, though correlated in lexical organisation, can be taken to focus on different aspects of speakers’ word processing behaviour and thus provide independent cognitive contributions to our understanding of the principles of perception of typicality that govern lexical organisation.Pokazano je da stupanj do kojeg je određeni simbolički vremenski slijed (slijed zvukova ili slova) tipična riječ u jeziku, odnosno TIPIčNOST OBLIKA RIJEčI, ima učinaka u proizvodnji i percepciji govora, uspješnosti čitanja, leksičkom razvoju i pristupu leksemima te kratkotrajnoj i dugotrajnoj verbalnoj memoriji. Predložena su dva kvantitativna modela kako bi se objasnili navedeni učinci: serijalne fonotaktičke vjerojatnosti (vjerojatnost pojavljivanja određenog simboličkog slijeda u leksikonu) i leksička gustoća (mjera do koje se druge riječi mogu proizvesti zamjenom, brisanjem ili umetanjem jednog ili više simbola u ciljnu riječ). Te dvije mjere visoko koreliraju, zbog čega su teško razdvojive pri mjerenju njihovih učinaka u leksičkim zadacima. U ovom radu predlažemo računalni model leksičke organizacije koji pruža sustavan algoritamski prikaz učinaka leksičkog usvajanja, obrade i pristupa kako bi se dodatno istražila ova pitanja. Taj se model temelji na samoorganizirajućim mapama s hebijanskim vezama definiranim preko vremenske razine (engl. TSOMs). Posebice pokazujemo da se (morfo-)fonotaktičke vjerojatnosti i leksička gustoća, iako korelirani u leksičkoj organizaciji, mogu shvatiti kao načini usredotočavanja na različite aspekte govornikova ponašanja pri obradi riječi i tako pružiti nezavisne kognitivne doprinose našem razumijevanju principa percepcije i tipičnosti koji upravljaju leksičkom organizacijom

Percepcija tipičnosti u leksikonu: tipičnost oblika riječi, leksička gustoća i morfonotaktička ograničenja

The extent to which a symbolic time–series (a sequence of sounds or letters) is a typical word of a language, referred to as WORDLIKENESS, has been shown to have effects in speech perception and production, reading proficiency, lexical development and lexical access, short–term and long–term verbal memory. Two quantitative models have been suggested to account for these effects: serial phonotactic probabilities (the likelihood for a given symbolic sequence to appear in the lexicon) and lexical density (the extent to which other words can be obtained from a target word by changing, deleting or inserting one or more symbols in the target). The two measures are highly correlated and thus easy to be confounded in measuring their effects in lexical tasks. In this paper, we propose a computational model of lexical organisation, based on Self–Organising Maps with Hebbian connections defined over a temporal layer (TSOMs), providing a principled algorithmic account of effects of lexical acquisition, processing and access, to further investigate these issues. In particular, we show that (morpho–)phonotactic probabilities and lexical density, though correlated in lexical organisation, can be taken to focus on different aspects of speakers’ word processing behaviour and thus provide independent cognitive contributions to our understanding of the principles of perception of typicality that govern lexical organisation.Pokazano je da stupanj do kojeg je određeni simbolički vremenski slijed (slijed zvukova ili slova) tipična riječ u jeziku, odnosno TIPIčNOST OBLIKA RIJEčI, ima učinaka u proizvodnji i percepciji govora, uspješnosti čitanja, leksičkom razvoju i pristupu leksemima te kratkotrajnoj i dugotrajnoj verbalnoj memoriji. Predložena su dva kvantitativna modela kako bi se objasnili navedeni učinci: serijalne fonotaktičke vjerojatnosti (vjerojatnost pojavljivanja određenog simboličkog slijeda u leksikonu) i leksička gustoća (mjera do koje se druge riječi mogu proizvesti zamjenom, brisanjem ili umetanjem jednog ili više simbola u ciljnu riječ). Te dvije mjere visoko koreliraju, zbog čega su teško razdvojive pri mjerenju njihovih učinaka u leksičkim zadacima. U ovom radu predlažemo računalni model leksičke organizacije koji pruža sustavan algoritamski prikaz učinaka leksičkog usvajanja, obrade i pristupa kako bi se dodatno istražila ova pitanja. Taj se model temelji na samoorganizirajućim mapama s hebijanskim vezama definiranim preko vremenske razine (engl. TSOMs). Posebice pokazujemo da se (morfo-)fonotaktičke vjerojatnosti i leksička gustoća, iako korelirani u leksičkoj organizaciji, mogu shvatiti kao načini usredotočavanja na različite aspekte govornikova ponašanja pri obradi riječi i tako pružiti nezavisne kognitivne doprinose našem razumijevanju principa percepcije i tipičnosti koji upravljaju leksičkom organizacijom

Perception of typicality in the lexicon: wordlikeness, lexical density and morphonotactic constraints

The extent to which a symbolic time–series (a sequence of sounds or letters) is a typical word of a language, referred to as WORDLIKENESS, has been shown to have effects in speech perception and production, reading proficiency, lexical development and lexical access, short–term and long–term verbal memory. Two quantitative models have been suggested to account for these effects: serial phonotactic probabilities (the likelihood for a given symbolic sequence to appear in the lexicon) and lexical density (the extent to which other words can be obtained from a target word by changing, deleting or inserting one or more symbols in the target). The two measures are highly correlated and thus easy to be confounded in measuring their effects in lexical tasks. In this paper, we propose a computational model of lexical organisation, based on Self–Organising Maps with Hebbian connections defined over a temporal layer (TSOMs), providing a principled algorithmic account of effects of lexical acquisition, processing and access, to further investigate these issues. In particular, we show that (morpho–)phonotactic probabilities and lexical density, though correlated in lexical organisation, can be taken to focus on different aspects of speakers’ word processing behaviour and thus provide independent cognitive contributions to our understanding of the principles of perception of typicality that govern lexical organisation

Evaluating Hebbian Self-Organizing Memories for Lexical Representation and Access

The lexicon is the store of words in long-term memory. Any attempt at modelling lexical competence must take issues of string storage seriously. In the present contribution, we discuss a few desiderata that any biologically-inspired computational model of the mental lexicon has to meet, and detail a multi-task evaluation protocol for their assessment. The proposed protocol is applied to a novel computational architecture for lexical storage and acquisition, the "Topological Temporal Hebbian SOMs" (T2HSOMs), which are grids of topologically organised memory nodes with dedicated sensitivity to time-bound sequences of letters. These maps can provide a rigorous and testable conceptual framework within which to provide a comprehensive, multi-task protocol for testing the performance of Hebbian self-organising memories, and a comprehensive picture of the complex dynamics between lexical processing and the acquisition of morphological structure

Words: structure, meaning, acquisition, processing

By bringing together experts of various scientific domains and different theoretical inclinations, the second NetWordS Summer school contributed to advance the current awareness of theoretical, typological, psycholinguistic, computational and neurophysiological evidence on the structure and processing of words, with a view to fostering novel methods of research and assessment for grammar architecture and language physiology

T2HSOM: Understanding the Lexicon by Simulating Memory Processes for Serial Order

Over the last several years, both theoretical and empirical approaches to lexical knowledge and encoding have prompted a radical reappraisal of the traditional dichotomy between lexicon and grammar. The lexicon is not simply a large waste basket of exceptions and sub-regularities, but a dynamic, possibly redundant repository of linguistic knowledge whose principles of relational organization are the driving force of productive generalizations. In this paper, we overview a few models of dynamic lexical organization based on neural network architectures that are purported to meet this challenging view. In particular, we illustrate a novel family of Kohonen self-organizing maps (T2HSOMs) that have the potential of simulating competitive storage of symbolic time series while exhibiting interesting properties of morphological organization and generalization. The model, tested on training samples of as morphologically diverse languages as Italian, German and Arabic, shows sensitivity to manifold types of morphological structure and can be used to bootstrap morphological knowledge in an unsupervised way