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      Cultural effects on computational metrics of spatial and temporal context

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          Abstract

          The concept of “prediction error” - the difference between what occurred and was expected - is key to understanding the cognitive processes of human decision making. Expectations have to be learned so the concept of prediction error critically depends on context, specifically the temporal context of probabilistically related events and their changes across time (i.e. volatility). While past research suggests context differently affects some cognitive processes in East Asian and Western individuals, it is currently unknown whether this extends to computationally-grounded measures of learning and prediction error. Here we compared Chinese and British nationals in an associative learning task that quantifies behavioural effects of prediction error, and—through a hierarchical Bayesian learning model—also captures how individuals learn about probabilistic relationships and their volatility. For comparison, we also administered a psychophysical task, the tilt illusion, to assess cultural differences in susceptibility to spatial context. We found no cultural differences in the effect of spatial context on perception. In the domain of temporal context there was no effect of culture on sensitivity to prediction error, or learning about volatility, but some suggestion that Chinese individuals may learn more readily about probabilistic relationships.

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          Most cited references32

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          Scientific method: statistical errors.

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            Revised standards for statistical evidence.

            Recent advances in Bayesian hypothesis testing have led to the development of uniformly most powerful Bayesian tests, which represent an objective, default class of Bayesian hypothesis tests that have the same rejection regions as classical significance tests. Based on the correspondence between these two classes of tests, it is possible to equate the size of classical hypothesis tests with evidence thresholds in Bayesian tests, and to equate P values with Bayes factors. An examination of these connections suggest that recent concerns over the lack of reproducibility of scientific studies can be attributed largely to the conduct of significance tests at unjustifiably high levels of significance. To correct this problem, evidence thresholds required for the declaration of a significant finding should be increased to 25-50:1, and to 100-200:1 for the declaration of a highly significant finding. In terms of classical hypothesis tests, these evidence standards mandate the conduct of tests at the 0.005 or 0.001 level of significance.
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              The computation of social behavior.

              Neuroscientists are beginning to advance explanations of social behavior in terms of underlying brain mechanisms. Two distinct networks of brain regions have come to the fore. The first involves brain regions that are concerned with learning about reward and reinforcement. These same reward-related brain areas also mediate preferences that are social in nature even when no direct reward is expected. The second network focuses on regions active when a person must make estimates of another person's intentions. However, it has been difficult to determine the precise roles of individual brain regions within these networks or how activities in the two networks relate to one another. Some recent studies of reward-guided behavior have described brain activity in terms of formal mathematical models; these models can be extended to describe mechanisms that underlie complex social exchange. Such a mathematical formalism defines explicit mechanistic hypotheses about internal computations underlying regional brain activity, provides a framework in which to relate different types of activity and understand their contributions to behavior, and prescribes strategies for performing experiments under strong control.
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                Author and article information

                Contributors
                rebecca.lawson@ucl.ac.uk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                1 February 2018
                1 February 2018
                2018
                : 8
                : 2027
                Affiliations
                [1 ]ISNI 0000 0004 1936 7486, GRID grid.6572.6, Institute for Conflict, Cooperation and Security, , University of Birmingham, ; Birmingham, UK
                [2 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Department of Experimental Psychology, , University of Oxford, ; Oxford, UK
                [3 ]ISNI 0000 0001 2167 3675, GRID grid.14003.36, Department of Psychiatry, , University of Wisconsin-Madison, ; Madison, USA
                [4 ]ISNI 0000 0001 0807 5670, GRID grid.5600.3, Cardiff University Brain Research Imaging Centre, , School of Psychology, Cardiff University, ; Cardiff, UK
                [5 ]ISNI 0000000121901201, GRID grid.83440.3b, Institute of Cognitive Neuroscience, , University College London, ; London, UK
                [6 ]ISNI 0000000121901201, GRID grid.83440.3b, Wellcome Trust Centre for Neuroimaging, , University College London, ; London, UK
                [7 ]ISNI 0000000121885934, GRID grid.5335.0, Department of Psychology, , University of Cambridge, ; Cambridge, UK
                Author information
                http://orcid.org/0000-0001-9233-1066
                http://orcid.org/0000-0002-5418-5747
                http://orcid.org/0000-0002-9623-7007
                http://orcid.org/0000-0003-1228-1244
                Article
                20200
                10.1038/s41598-018-20200-y
                5794846
                29391522
                dfa62234-df2b-45ff-a273-db2b43403efe
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 27 September 2017
                : 8 January 2018
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