Information and learning in processing adjective inflection

Dušica Filipović Đurđević, Petar Milin

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)
137 Downloads (Pure)


We investigated the processing of inflected Serbian adjective forms to bring together quantitative linguistic measures from two frameworks – information theory and discrimination learning. From each framework we derived several quantitative descriptions of an inflectional morphological system and fitted two separate regression models to the processing latencies that were elicited by inflected adjectival forms presented in a visual lexical decision task. The model, which was based on lexical distributional and information theory revealed a dynamic interplay of information. The information was sensitive to syntagmatic and paradigmatic dimensions of variation; the paradigmatic information (formalized as respective relative entropies) was also modulated by lemma frequency. The discrimination learning based model revealed an equally complex pattern, involving several learning-based variables. The two models revealed strikingly similar patterns of results, as confirmed by the very high proportion of shared variance in model predictions (85.83%). Our findings add to the body of research demonstrating that complex morphological phenomena can arise as a consequence of the basic principles of discrimination learning. Learning discriminatively about inflectional paradigms and classes, and about their contextual or syntagmatic embedding, sheds light on human language-processing efficiency and on the fascinating complexity of naturally emerged language systems.

Original languageEnglish
Pages (from-to)209-227
Number of pages19
Early online date6 Aug 2018
Publication statusPublished - Jul 2019


  • Adjectives
  • Discrimination learning
  • Inflectional morphology
  • Prepositional phrases
  • Relative entropy

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience


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