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Coalescing stochastic processes in retrival from semantic memory

Queau P-Y., Woyczyński W. A., Lerner A. J.

Mathematica Applicanda

2015

Vol. 43, No. 2

189--224

Semantic memory retrieval is one of the most fundamental cognitive functions in humans. It is not fully understood and researchers from various fields of science struggle to find a model that would correlate well with experimental results and help understanding the complex background processes involved. To study such a phenomenon we need a relevant experimental protocol which can isolate the basic cognitive functions of interest from other perturbations. A variety of existing medical tests can provide such information, and the one we analyze is the Category Fluency Test (CFT). It was originally designed to measure frontal brain lobe damages in injured patients, and it tests directly the semantic memory retrieval, which is affected in cases of injury but can be also influenced by dementia, Alzheimer syndrome, or just aging. This paper introduces a new paradigm in analysis of the temporal structure of CFT responses by utilizing coalescent stochastic process model. We believe that this particular model is relevant to how this cognitive function operates and can lead to a better understanding of the background processes. The method turns out to be better at separating the two cognitively different groups studied here than the Weibull model from our previous paper Meyer et al.(2012), and could potentially be used for early diagnostics of dementia or Alzheimer's disease. Two other models, one based on the concept of Levy processes, and one related to the fractional Poisson model, are also explored.

Praca proponuje model procesów koalescencyjnych w celu wyjaśnienia mechanizmów odzysku pojęć i nazw z pamięci semantycznej. Model jest pretestowany używając dobrze znanego eksperymentalnego Testu Biegłości Kategorycznej, który jest standardowym narzędziem neurologów badających pacjentów z objawami demencji. Możliwości modelowania opartego na procesach Lévy’ego i ułamkowych procesach Poissona są również zbadane.

Context search algorithm for lexical knowledge acquisition

Szymański J., Duch W.

Control and Cybernetics

2012

Vol. 41, no. 1

81-96

A Context Search algorithm used for lexical knowledge acquisition is presented. Knowledge representation based on psycholinguistic theories of cognitive processes allows for implementation of a computational model of semantic memory in the form of semantic network. Knowledge acquisition using supervised dialog templates have been performed in a word game designed to guess the concept a human user is thinking about. The game that has been implemented on a web server, demonstrates elementary linguistic competencies based on lexical knowledge stored in semantic memory, enabling at the same time acquisition and validation of knowledge. Possible applications of the algorithm in domains of medical diagnosis and information retrieval are sketched.