Making decisions with a continuous mind

Scherbaum, Stefan; Dshemuchadse, Maja; Kalis, Annemarie

doi:10.3758/cabn.8.4.454

Cited by 26 publications

(33 citation statements)

References 229 publications

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“…First, the discussion questioning a strict modularity of mind (Fodor, 1983(Fodor, , 2001(Fodor, , 2005Pinker, 1997Pinker, , 2005aPinker, , 2005b and the dynamic approach to cognition (e.g. Bressler and Kelso, 2001;Kelso, 1995;Scherbaum et al, 2008;Thelen et al, 2001) both promote a view focusing on the emergence of cognitive function from the interaction dynamics within the system. Hence, instead of a specific mapping of fine grained function (e.g.…”

Section: Discussionmentioning

confidence: 99%

Dynamic goal states: Adjusting cognitive control without conflict monitoring

et al. 2012

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Section: Discussionmentioning

confidence: 99%

Dynamic goal states: Adjusting cognitive control without conflict monitoring

et al. 2012

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“…By this application, forward inference could help to convey JDM research into a more proces-orientated paradigm (Oppenheimer & Kelso, 2015;Scherbaum, Dshemuchadse, & Kalis, 2008;Schulte-Mecklenbeck, Johnson, et al, 2017). In Marr's (1982) terminology, forward inference could help to switch decision theory from the computational level, where problems are specified in the generic manner to the algorithmic level describing how exactly the computational problems are solved.…”

Section: Future Directionsmentioning

confidence: 99%

Forward inference in risky choice: Mapping gaze and decision processes

Schoemann

Schulte‐Mecklenbeck

Renkewitz

et al. 2019

Behavioral Decision Making

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The study of cognitive processes is built on a close mapping between three components: overt gaze behavior, overt choice, and covert processes. To validate this overt–covert mapping in the domain of decision‐making, we collected eye‐movement data during decisions between risky gamble problems. Applying a forward inference paradigm, participants were instructed to use specific decision strategies to solve those gamble problems (maximizing expected values or applying different choice heuristics) during which gaze behavior was recorded. We revealed differences between overt behavior, as indicated by eye movements, and covert decision processes, instructed by the experimenter. However, our results show that the overt–covert mapping is for some eye‐movement measures not as close as expected by current decision theory, and hence question reverse inference as being prone to fallacies due to a violation of its prerequisite, that is, a close overt–covert mapping. We propose a framework to rehabilitate reverse inference.

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“…The continuous nature of CTRNN controllers is very important for the study of cognitive process related to rule switching, because real brain operates also in a continuous mode [20]. Therefore the present study can reveal new unexplored aspects of brain processes involved in switching from one behavioral strategy to another in conditions of varying trial duration.…”

Section: Rule Ss Durationmentioning

confidence: 96%

Time perception in shaping cognitive neurodynamics of artificial agents

Maniadakis

Tani

Trahanias

2009

2009 International Joint Conference on Neural Networks

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Recent research in cognitive systems aims to uncover important aspects of biological cognitive processes and additionally formulate design principles for implementing artificially intelligent systems. Despite the increasing amount of research efforts addressing cognitive phenomena, the issue of time perception and how it is linked to other cognitive processes remains largely unexplored.In the current paper, we make a first attempt for studying artificial time perception by means of simulated robotic experiments. Specifically, we investigate a behavioral rule switching task consisting of repeating trials with dynamic temporal duration. An evolutionary process is used to search for neuronal mechanisms accomplishing the rule switching task taking also into account its particular temporal characteristics. Our repeated simulation experiments showed that (i) time perception and ordinary cognitive processes may co-exist in the system sharing the same neural resources, and (ii) time perception dynamics bias the functionality of neural mechanisms with other cognitive responsibilities. Finally, in the current paper we make contact of the obtained results with previous brain imaging studies on time perception, and we make predictions for possible time-related dynamics in the real brain.

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Making decisions with a continuous mind

Cited by 26 publications

References 229 publications

Dynamic goal states: Adjusting cognitive control without conflict monitoring

Dynamic goal states: Adjusting cognitive control without conflict monitoring

Forward inference in risky choice: Mapping gaze and decision processes

Time perception in shaping cognitive neurodynamics of artificial agents

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