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| Thursday May 16, 2013 | University of Exeter > eProfile > Listing by Researcher |
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Fayme YeatesSchool: College of Life and Environmental Sciences PhD Project SummaryMy PhD aims to investigate human sequence learning under incidental conditions. Serial reaction time (SRT) tasks have been useful tools for investigating implicit learning ever since Nissen and Bullemer (1987) and Lewicki, Czyzewska and Hoffman (1987) developed the paradigm. Participants are exposed to a series of simple stimuli that follow a particular sequence, but they receive no explicit information about, or reference to, this sequence in the task instructions. This led Nissen et al to suggest learning in the SRT task had occurred without awareness, as participants were unable to explicitly verbalise any knowledge about the sequences involved. To ascertain the extent of participants’ explicit, declarative learning a variety of methods have been used. On the basis of results obtained in these experiments evidence for a dissociation between functionally distinct unconscious and consciously accessible learning processes has been proposed (Willingham, Greeley, & Bardone, 1993). The aim of my PhD is to extend the current understanding of human sequence learning through investigations using both human experiments and computational modelling based on the simple recurrent network (SRN; Elman, 1990). The literature concerning SRT tasks have attracted critical comment for a number of reasons. Recent developments have, however, attempted to answer these criticisms, and further investigation of both the paradigm and human performance on the task is needed. Indeed, the SRN as a model of sequence learning requires further testing against human performance, and taken together the two methods, the experimental and the computational, will enable a greater understanding of the processes underlying implicit learning. In summary, I aim to investigate whether implicit learning is driven by an associative system that is functionally separate to rule-based hypothesis testing. The numerous methodological issues surrounding attempts to dissociate unconscious and conscious mental processes will also be considered. I aim to apply novel paradigms and analyses to my research into sequence learning, as well as extensively testing and developing models that will account for the data. [Last updated May 2012] Supervisory TeamFirst Supervisor: Prof. Ian McLaren Second Supervisor: Prof. Andy Wills External Supervisor: Dr Fergal Jones (Canterbury Christ Church University) Wider Research InterestsMathematics; music perception; consciousness; statistics; computing; Authored Publications/ReportsYeates, F., Jones, F.W., Wills, A.J., Aitken, M.R.F. & McLaren, I.P.L. (2013) [accepted] Implicit learning: A demonstration and a revision to a novel SRT paradigm, Proceedings of the 35th Annual Conference of the Cognitive Science Society McAndrew, A., Yeates, F., Verbruggen, F., McLaren, I.P.L. (2013) [accepted] Modeling a reaction time variant of the Perruchet effect in humans, Proceedings of the 35th Annual Conference of the Cognitive Science Society McLaren, I.P.L., Dunn, B.D., Lawrence, N.S., Milton, F.N., Verbruggen, F., Stevens, T., McAndrew, A., & Yeates, F. () Why decision making may not require awareness [Peer commentary by I. P. L. McLaren et al. on "Unconscious influences on decision making: A critical review"], Behavioral and Brain Sciences, [Submitted] Yeates, F., Jones, F.W., Wills, A.J., Aitken, M.R.F. & McLaren, I.P.L. (2012) Implicit Learning: A Demonstration and a Novel SRT Paradigm, Proceedings of the 34th Annual Conference of the Cognitive Science Society., 1185-1190 Yeates, F., Wills, A., Jones, F. & McLaren, I.P.L. (2012) State-Trace Analysis of Sequence Learning by Simple Recurrent Networks, Proceedings of the 34th Annual Conference of the Cognitive Science Society., 2581-2586 Yeates, F., Jones, F.W., Wills, A.J., McLaren, R. & McLaren, I.P.L. (2013) Human sequence learning under incidental conditions, Journal of Experimental Psychology: Animal Behavior Processes, 39(2), 166-173 |
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