Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloA Neuro-Computational Approach to Understanding the Mental Lexicon
Anno di pubblicazione2015
FormatoElettronico
Autore/iMarzi, Claudia; Pirrelli, Vito
Affiliazioni autoriInstitute for Computational Linguistics - National Research Council
Autori CNR e affiliazioni
  • VITO PIRRELLI
  • CLAUDIA MARZI
Lingua/e
  • inglese
AbstractHuman lexical knowledge does not appear to be organised to minimise storage, but rather to maximise processing efficiency. The way lexical information is stored reflects the way it is dynamically processed, accessed and retrieved. A detailed analysis of the way words are memorised, of the dynamic interaction between lexical representations and distribution and degrees of regularity in input data, can shed some light on the emergence of structures and relations within fully-stored words. We believe that a bottom-up investigation of low-level memory and processing functions can help understand the cognitive mechanisms that govern word processing in the mental lexicon. Neuro-computational models can play an important role in this inquiry, as they help understand the dynamic nature of lexical representations by establishing an explanatory connection between lexical structures and processing models dictated by the micro-functions of human brain. Starting from some linguistic, psycholinguistic and neuro-physiological evidence supporting a dynamic view of the mental lexicon as an integrative system, we illustrate Temporal Self Organising-Maps (TSOMs), artificial neural networks that can model such a view by memorising time series of symbolic units (words) as routinized patterns of short-term node activation. On the basis of a simple pool of principles of adaptive Hebbian synchronisation, TSOMs can perceive possible surface relations between word forms and store them by partially overlapping activation patterns, reflecting gradient levels of lexical specificity, from holistic to decompositional lexical representations. We believe that TSOMs offer an algorithmic model of the emergence of high-level, global and language-specific morphological structure through the working of low-level, language-aspecific processing functions, thus promising to bridge the persisting gap between high-level principles of grammar architecture (lexicon vs. rules), computational correlates (storage vs. processing) and low-level principles and localisations of brain functions. Extensions of the current TSOM architecture are envisaged and their theoretical implications are discussed.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da493
Pagine a535
Pagine totali43
RivistaJournal of cognitive science (Seoul. Online)
Attiva dal 2000
Editore: Institute for cognitive science, Seoul national university - Seoul
Paese di pubblicazione: Corea del Sud
Lingua: inglese
ISSN: 1976-6939
Titolo chiave: Journal of cognitive science (Seoul. Online)
Titolo abbreviato: J. cogn. sci. (Seoul. Online)
Titolo alternativo: injigwahakjageop (Online) (Seoul. Online)
Numero volume della rivista16
Fascicolo della rivista4
DOI-
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • PUMA (Codice:cnr.ilc/2015-A0-003)
Parole chiaveMental lexicon; dynamic storage; parallel distributed processing; hebbian learning; temporal self-organising maps.
Link (URL, URI)http://j-cs.org/gnuboard/bbs/board.php?bo_table=__vol016i4&wr_id=5
Titolo parallelo-
Data di accettazione16/08/2015
Note/Altre informazioniISSN 1976-6939 (Electronic) 1598-2327 (Print)
Strutture CNR
  • ILC — Istituto di linguistica computazionale "Antonio Zampolli"
Moduli CNR
    Progetti Europei-
    Allegati
    • JournalPaper5_Marzi_Pirrelli
      Descrizione: JournalPaper5_Marzi_Pirrelli