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An architecturally constrained model of random number generation and its application to modeling the effect of generation rate

Sexton, NJ; Cooper, RP; (2014) An architecturally constrained model of random number generation and its application to modeling the effect of generation rate. Frontiers in Psychology , 5 , Article 670. 10.3389/fpsyg.2014.00670. Green open access

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Abstract

Random number generation (RNG) is a complex cognitive task for human subjects, requiring deliberative control to avoid production of habitual, stereotyped sequences. Under various manipulations (e.g., speeded responding, transcranial magnetic stimulation, or neurological damage) the performance of human subjects deteriorates, as reflected in a number of qualitatively distinct, dissociable biases. For example, the intrusion of stereotyped behavior (e.g., counting) increases at faster rates of generation. Theoretical accounts of the task postulate that it requires the integrated operation of multiple, computationally heterogeneous cognitive control (“executive”) processes. We present a computational model of RNG, within the framework of a novel, neuropsychologically-inspired cognitive architecture, ESPro. Manipulating the rate of sequence generation in the model reproduced a number of key effects observed in empirical studies, including increasing sequence stereotypy at faster rates. Within the model, this was due to time limitations on the interaction of supervisory control processes, namely, task setting, proposal of responses, monitoring, and response inhibition. The model thus supports the fractionation of executive function into multiple, computationally heterogeneous processes.

Type: Article
Title: An architecturally constrained model of random number generation and its application to modeling the effect of generation rate
Open access status: An open access version is available from UCL Discovery
DOI: 10.3389/fpsyg.2014.00670
Publisher version: http://dx.doi.org/10.3389/fpsyg.2014.00670
Language: English
Additional information: © 2014 Sexton and Cooper. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/).
Keywords: random number generation, executive function, cognitive control, cognitive architecture, computational model, supervisory system
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology
URI: https://discovery.ucl.ac.uk/id/eprint/10074606
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