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  1.  22
    State‐Trace Analysis: Dissociable Processes in a Connectionist Network?Fayme Yeates, Andy J. Wills, Fergal W. Jones & Ian P. L. McLaren - 2015 - Cognitive Science 39 (5):1047-1061.
    Some argue the common practice of inferring multiple processes or systems from a dissociation is flawed. One proposed solution is state-trace analysis, which involves plotting, across two or more conditions of interest, performance measured by either two dependent variables, or two conditions of the same dependent measure. The resulting analysis is considered to provide evidence that either a single process underlies performance or there is evidence for more than one process. This article reports simulations using the simple recurrent network in (...)
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    Allah has told us everything: An interpretative phenomenological analysis exploring the lived experiences of British Muslims.James Murphy, Fergal W. Jones & Dennis Nigbur - 2023 - Archive for the Psychology of Religion 45 (2):133-151.
    There is a need to better understand how individuals in different religious groups construct and maintain their worldviews. This study explores how religious practices, beliefs, and relationships create and sustain the worldviews of five British Muslims. Semi-structured interviews were inductively analyzed using interpretative phenomenological analysis (IPA) to idiographically explore the participants’ lived experiences. This analysis developed multiple subordinate themes that formed two superordinate themes: “Submitting to Allah” and “Being a British Muslim.” The participants’ experiences of being raised in Muslim families (...)
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    Out of control: An associative account of congruency effects in sequence learning.Tom Beesley, Fergal W. Jones & David R. Shanks - 2012 - Consciousness and Cognition 21 (1):413-421.
    The demonstration of a sequential congruency effect in sequence learning has been offered as evidence for control processes that act to inhibit automatic response tendencies via unconscious conflict monitoring. Here we propose an alternative interpretation of this effect based on the associative learning of chains of sequenced contingencies. This account is supported by simulations with a Simple Recurrent Network, an associative model of sequence learning. We argue that the control- and associative-based accounts differ in their predictions concerning the magnitude of (...)
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