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      The Flatland Fallacy: Moving Beyond Low–Dimensional Thinking

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          Abstract

          Psychology is a complicated science. It has no general axioms or mathematical proofs, is rarely directly observable, and is the only discipline in which the subject matter (i.e., human psychological phenomena) is also the tool of investigation. Like the Flatlanders in Edwin Abbot's famous short story ( 1884), we may be led to believe that the parsimony offered by our low‐dimensional theories reflects the reality of a much higher‐dimensional problem. Here we contend that this “Flatland fallacy” leads us to seek out simplified explanations of complex phenomena, limiting our capacity as scientists to build and communicate useful models of human psychology. We suggest that this fallacy can be overcome through (a) the use of quantitative models, which force researchers to formalize their theories to overcome this fallacy, and (b) improved quantitative training, which can build new norms for conducting psychological research.

          Abstract

          In rebellion against low‐dimensional (e.g., two‐factor) theories in psychology, the authors make the case for high‐dimensional theories. This change in perspective requires a shift towards a focus on computation and quantitative reasoning.

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          Separate neural systems value immediate and delayed monetary rewards.

          When humans are offered the choice between rewards available at different points in time, the relative values of the options are discounted according to their expected delays until delivery. Using functional magnetic resonance imaging, we examined the neural correlates of time discounting while subjects made a series of choices between monetary reward options that varied by delay to delivery. We demonstrate that two separate systems are involved in such decisions. Parts of the limbic system associated with the midbrain dopamine system, including paralimbic cortex, are preferentially activated by decisions involving immediately available rewards. In contrast, regions of the lateral prefrontal cortex and posterior parietal cortex are engaged uniformly by intertemporal choices irrespective of delay. Furthermore, the relative engagement of the two systems is directly associated with subjects' choices, with greater relative fronto-parietal activity when subjects choose longer term options.
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            Integration of the cognitive and the psychodynamic unconscious.

            M Epstein (1994)
            Cognitive-experiential self-theory integrates the cognitive and the psychodynamic unconscious by assuming the existence of two parallel, interacting modes of information processing: a rational system and an emotionally driven experiential system. Support for the theory is provided by the convergence of a wide variety of theoretical positions on two similar processing modes; by real-life phenomena--such as conflicts between the heart and the head; the appeal of concrete, imagistic, and narrative representations; superstitious thinking; and the ubiquity of religion throughout recorded history--and by laboratory research, including the prediction of new phenomena in heuristic reasoning.
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              Neural Networks and the Bias/Variance Dilemma

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                Author and article information

                Contributors
                eshin.jolly.gr@dartmouth.edu
                Journal
                Top Cogn Sci
                Top Cogn Sci
                10.1111/(ISSN)1756-8765
                TOPS
                Topics in Cognitive Science
                John Wiley and Sons Inc. (Hoboken )
                1756-8757
                1756-8765
                21 December 2018
                April 2019
                : 11
                : 2 , Computational Approaches to Social Cognition: Editors: Fiery A. Cushman and Samuel J. Gershman ( doiID: 10.1111/tops.2019.11.issue-2 )
                : 433-454
                Affiliations
                [ 1 ] Computational Social Affective Neuroscience Laboratory Department of Psychological and Brain Sciences Dartmouth College
                Author notes
                [*] [* ]Correspondence should be sent to Eshin Jolly, Computational Social Affective Neuroscience Laboratory, Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755. E‐mail: eshin.jolly.gr@ 123456dartmouth.edu
                Article
                TOPS12404
                10.1111/tops.12404
                6519046
                30576066
                b2c66876-dec4-4dbe-bc0c-dcfbb7456cd3
                © 2018 The Authors Topics in Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 02 October 2017
                : 29 June 2018
                : 13 July 2018
                Page count
                Figures: 3, Tables: 1, Pages: 22, Words: 10415
                Funding
                Funded by: National Institute of Mental Health
                Award ID: R01MH116026
                Award ID: R56MH080716
                Categories
                Forthcoming Topic: Computational Approaches to Social Cognition
                Computational Approaches to Social Cognition Editors: Fiery A. Cushman and Samuel J. Gershman
                Custom metadata
                2.0
                tops12404
                April 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.2.1 mode:remove_FC converted:15.05.2019

                dual‐processing,computational,social,decision‐making,psychological education

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