A Neuroeconomics Approach to Inferring Utility Functions in Sensorimotor Control
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{"title"=>"A neuroeconomics approach to inferring utility functions in sensorimotor control", "type"=>"journal", "authors"=>[{"first_name"=>"Konrad P.", "last_name"=>"Körding", "scopus_author_id"=>"6603812799"}, {"first_name"=>"Izumi", "last_name"=>"Fukunaga", "scopus_author_id"=>"57197488615"}, {"first_name"=>"Ian S.", "last_name"=>"Howard", "scopus_author_id"=>"7102515552"}, {"first_name"=>"James N.", "last_name"=>"Ingram", "scopus_author_id"=>"10341258600"}, {"first_name"=>"Daniel M.", "last_name"=>"Wolpert", "scopus_author_id"=>"35495089500"}], "year"=>2004, "source"=>"PLoS Biology", "identifiers"=>{"sgr"=>"8844245702", "issn"=>"15449173", "scopus"=>"2-s2.0-8844245702", "pmid"=>"15383835", "pui"=>"39532926", "isbn"=>"1545-7885 (Electronic)\\r1544-9173 (Linking)", "doi"=>"10.1371/journal.pbio.0020330"}, "id"=>"cbfa6ec6-0d1a-3c47-bdb9-b77cc34a8cec", "abstract"=>"Making choices is a fundamental aspect of human life. For over a century experimental economists have characterized the decisions people make based on the concept of a utility function. This function increases with increasing desirability of the outcome, and people are assumed to make decisions so as to maximize utility. When utility depends on several variables, indifference curves arise that represent outcomes with identical utility that are therefore equally desirable. Whereas in economics utility is studied in terms of goods and services, the sensorimotor system may also have utility functions defining the desirability of various outcomes. Here, we investigate the indifference curves when subjects experience forces of varying magnitude and duration. Using a two-alternative forced-choice paradigm, in which subjects chose between different magnitude-duration profiles, we inferred the indifference curves and the utility function. Such a utility function defines, for example, whether subjects prefer to lift a 4-kg weight for 30 s or a 1-kg weight for a minute. The measured utility function depends nonlinearly on the force magnitude and duration and was remarkably conserved across subjects. This suggests that the utility function, a central concept in economics, may be applicable to the study of sensorimotor control.", "link"=>"http://www.mendeley.com/research/neuroeconomics-approach-inferring-utility-functions-sensorimotor-control", "reader_count"=>200, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>29, "Researcher"=>57, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>57, "Student > Postgraduate"=>4, "Student > Master"=>17, "Other"=>7, "Student > Bachelor"=>6, "Lecturer"=>4, "Professor"=>16}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>29, "Researcher"=>57, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>57, "Student > Postgraduate"=>4, "Student > Master"=>17, "Other"=>7, "Student > Bachelor"=>6, "Lecturer"=>4, "Professor"=>16}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Agricultural and Biological Sciences"=>53, "Philosophy"=>4, "Business, Management and Accounting"=>4, "Computer Science"=>12, "Decision Sciences"=>1, "Economics, Econometrics and Finance"=>2, "Engineering"=>28, "Nursing and Health Professions"=>1, "Mathematics"=>1, "Medicine and Dentistry"=>13, "Neuroscience"=>18, "Sports and Recreations"=>2, "Physics and Astronomy"=>3, "Psychology"=>49, "Social Sciences"=>3, "Linguistics"=>4}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>13}, "Social Sciences"=>{"Social Sciences"=>3}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>3}, "Psychology"=>{"Psychology"=>49}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>2}, "Engineering"=>{"Engineering"=>28}, "Neuroscience"=>{"Neuroscience"=>18}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>53}, "Computer Science"=>{"Computer Science"=>12}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>4}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Linguistics"=>{"Linguistics"=>4}, "Philosophy"=>{"Philosophy"=>4}}, "reader_count_by_country"=>{"Republic of Singapore"=>1, "United States"=>13, "Japan"=>1, "United Kingdom"=>2, "Portugal"=>1, "Switzerland"=>1, "Spain"=>1, "Sweden"=>1, "Belgium"=>2, "Ireland"=>1, "Brazil"=>2, "Italy"=>2, "France"=>4, "Chile"=>1, "Australia"=>1, "Germany"=>3}, "group_count"=>7}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/963370"], "description"=>"<div><p>(A–C) The predicted indifference lines are shown that minimize (A) the integrated force <i>(F × T),</i> (B) the integrated squared force <i>(F<sup>2</sup> × T),</i> and (C) the maximal force <i>(F)</i>.</p>\n <p>(D) Experimental data from a single subject. The open circles are the reference forces. The blue full circles connected by the black lines represent indifference points. Error bars denote the 95% confidence intervals. Force profiles are illustrated (blue curves for single forces, pink curve for doubling points).</p>\n <p>(E) Inferred color plot of the loss function (warmer colors represent greater cost).</p></div>", "links"=>[], "tags"=>["indifference", "curves"], "article_id"=>633315, "categories"=>["Mental Health", "Neuroscience"], "users"=>["Konrad P Körding", "Izumi Fukunaga", "Ian S Howard", "James N Ingram", "Daniel M Wolpert"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.0020330.g002", "stats"=>{"downloads"=>1, "page_views"=>17, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Hypothesized_and_Measured_Indifference_Curves_and_Loss_Function_from_a_Single_Subject_/633315", "title"=>"Hypothesized and Measured Indifference Curves and Loss Function from a Single Subject", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-22 09:10:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/963276"], "description"=>"<p>The subject's hand position (pink circle) was visible on the screen. The hand movement was restricted to stay within a small area (blue box). The direction of the force is represented by the blue arrow, and the temporal profile of the force is shown by the blue curve.</p>", "links"=>[], "tags"=>["neuroscience", "mental health/psychology"], "article_id"=>633221, "categories"=>["Mental Health", "Neuroscience"], "users"=>["Konrad P Körding", "Izumi Fukunaga", "Ian S Howard", "James N Ingram", "Daniel M Wolpert"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.0020330.g001", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_Experimental_Setup_/633221", "title"=>"The Experimental Setup", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-22 09:10:05"}
  • {"files"=>["https://ndownloader.figshare.com/files/963440"], "description"=>"<p>The black curves are the iso-loss curves. Error bars denote the standard error of the mean over the population. The color plot represents the inferred loss function (warmer colors represent greater loss) obtained by interpolating the data from the double-hump forces.</p>", "links"=>[], "tags"=>["contours"], "article_id"=>633382, "categories"=>["Mental Health", "Neuroscience"], "users"=>["Konrad P Körding", "Izumi Fukunaga", "Ian S Howard", "James N Ingram", "Daniel M Wolpert"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.0020330.g003", "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Iso_Loss_Contours_and_Loss_Function_for_the_Set_of_All_Subjects_/633382", "title"=>"Iso-Loss Contours and Loss Function for the Set of All Subjects", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-22 09:11:15"}

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