A new measure of clustering and switching based on bigrams

Maria K. Wolters, Sarah E. MacPherson, Jinseon You, Rize Jin, Seung-Cheol Baek, Jong C. Park

Research output: Contribution to conferencePosterpeer-review


The category fluency task (CFT) provides important information about executive abilities such as initiation, set-shifting and inhibition. CFT sequences are generated by retrieving groups of related words (“clusters“) from semantic
memory. Manual annotation schemes have been developed for inferring these clusters from transcribed CFT sequences (Troyer 2008), but these are time-consuming and require training. We propose an automatic analysis technique that is based on a simple statistical model of CFT sequences.
This model can be easily adapted to different languages and domains, given sufficient training data. CFT sequences (domain “animals“) were generated by 104 younger adults aged 18-34 years and 100 older adults aged 50-84 years
who were native speakers of UK English. The sequences were categorised both manually and using our automated method with key measures such as the number of switches significantly correlating (rho=0.4, 95% CI [0.28-0.51]). Both
methods also resulted in the significant age differences that are consistently reported in the cognitive aging literature.
Original languageEnglish
Publication statusPublished - 2015
Event56th Annual Meeting of the Psychonomic Society - Chicago, United States
Duration: 19 Nov 201522 Nov 2015


Conference56th Annual Meeting of the Psychonomic Society
Country/TerritoryUnited States


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