Use It and Improve It or Lose It: Interactions between Arm Function and Use in Humans Post-stroke
Publication Date
February 16, 2012
Journal
PLOS Computational Biology
Authors
Yukikazu Hidaka, Cheol E. Han, Steven L. Wolf, Carolee J. Winstein, et al
Volume
8
Issue
2
Pages
e1002343
DOI
https://dx.plos.org/10.1371/journal.pcbi.1002343
Publisher URL
http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1002343
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/22761551
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3385844
Europe PMC
http://europepmc.org/abstract/MED/22761551
Web of Science
000300729900002
Scopus
84861138925
Mendeley
http://www.mendeley.com/research/it-improve-it-lose-it-interactions-between-arm-function-humans-poststroke
Events
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Mendeley | Further Information

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Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/681009"], "description"=>"<p>The models correspond to the models of <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002343#pcbi-1002343-t002\" target=\"_blank\">Table 2</a>.</p>", "links"=>[], "tags"=>["neuroscience", "computer science"], "article_id"=>351504, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Yukikazu Hidaka", "Cheol E. Han", "Steven L. Wolf", "Carolee J. Winstein", "Nicolas Schweighofer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002343.t004", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Positive_Evidence_Ratio_for_use_model_48_subjects_immediate_group_/351504", "title"=>"Positive Evidence Ratio for use model (48 subjects, immediate group).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-16 00:25:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/680878"], "description"=>"<p>Model comparison candidates for predicting arm function <i>F(t)</i>.</p>", "links"=>[], "tags"=>["candidates", "predicting"], "article_id"=>351369, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Yukikazu Hidaka", "Cheol E. Han", "Steven L. Wolf", "Carolee J. Winstein", "Nicolas Schweighofer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002343.t001", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_comparison_candidates_for_predicting_arm_function_F_t_/351369", "title"=>"Model comparison candidates for predicting arm function <i>F(t)</i>.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-16 00:22:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/347292", "https://ndownloader.figshare.com/files/347391", "https://ndownloader.figshare.com/files/347473", "https://ndownloader.figshare.com/files/347569", "https://ndownloader.figshare.com/files/347629", "https://ndownloader.figshare.com/files/347811", "https://ndownloader.figshare.com/files/347879"], "description"=>"<div><p>“Use it and improve it, or lose it” is one of the axioms of motor therapy after stroke. There is, however, little understanding of the interactions between arm function and use in humans post-stroke. Here, we explored putative non-linear interactions between upper extremity function and use by developing a first-order dynamical model of stroke recovery with longitudinal data from participants receiving constraint induced movement therapy (CIMT) in the EXCITE clinical trial. Using a Bayesian regression framework, we systematically compared this model with competitive models that included, or not, interactions between function and use. Model comparisons showed that the model with the predicted interactions between arm function and use was the best fitting model. Furthermore, by comparing the model parameters before and after CIMT intervention in participants receiving the intervention one year after randomization, we found that therapy increased the parameter that controls the effect of arm function on arm use. Increase in this parameter, which can be thought of as the confidence to use the arm for a given level of function, lead to increase in spontaneous use after therapy compared to before therapy.</p> </div>", "links"=>[], "tags"=>["interactions", "humans", "post-stroke"], "article_id"=>128680, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Yukikazu Hidaka", "Cheol E. Han", "Steven L. Wolf", "Carolee J. Winstein", "Nicolas Schweighofer"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002343.s001", "https://dx.doi.org/10.1371/journal.pcbi.1002343.s002", "https://dx.doi.org/10.1371/journal.pcbi.1002343.s003", "https://dx.doi.org/10.1371/journal.pcbi.1002343.s004", "https://dx.doi.org/10.1371/journal.pcbi.1002343.s005", "https://dx.doi.org/10.1371/journal.pcbi.1002343.s006", "https://dx.doi.org/10.1371/journal.pcbi.1002343.s007"], "stats"=>{"downloads"=>14, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Use_It_and_Improve_It_or_Lose_It_Interactions_between_Arm_Function_and_Use_in_Humans_Post_stroke/128680", "title"=>"Use It and Improve It or Lose It: Interactions between Arm Function and Use in Humans Post-stroke", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-02-16 02:24:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/680621"], "description"=>"<p>A. Effect on . B. Effect on . C. Effect on . Only the mean parameter of equation 2 varies from before (Be) to after (Af) therapy. This parameter controls the effect of function on use for the affected arm. The horizontal line in B indicates p<0.05.</p>", "links"=>[], "tags"=>["parameters", "delayed", "excite"], "article_id"=>351110, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Yukikazu Hidaka", "Cheol E. Han", "Steven L. Wolf", "Carolee J. Winstein", "Nicolas Schweighofer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002343.g004", "stats"=>{"downloads"=>3, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effects_of_therapy_on_mean_model_parameters_for_participants_of_the_delayed_group_in_the_EXCITE_trial_/351110", "title"=>"Effects of therapy on mean model parameters for participants of the delayed group in the EXCITE trial.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-16 00:18:30"}
  • {"files"=>["https://ndownloader.figshare.com/files/680975"], "description"=>"<p>Prediction errors at different time points (leave-one-out points) after therapy.</p>", "links"=>[], "tags"=>["errors", "points"], "article_id"=>351472, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Yukikazu Hidaka", "Cheol E. Han", "Steven L. Wolf", "Carolee J. Winstein", "Nicolas Schweighofer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002343.t005", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Prediction_errors_at_different_time_points_leave_one_out_points_after_therapy_/351472", "title"=>"Prediction errors at different time points (leave-one-out points) after therapy.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-16 00:24:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/680909"], "description"=>"<p>The models correspond to the models of <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002343#pcbi-1002343-t001\" target=\"_blank\">Table 1</a>.</p>", "links"=>[], "tags"=>["neuroscience", "computer science"], "article_id"=>351400, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Yukikazu Hidaka", "Cheol E. Han", "Steven L. Wolf", "Carolee J. Winstein", "Nicolas Schweighofer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002343.t003", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Positive_Evidence_Ratio_for_function_model_48_subjects_immediate_group_/351400", "title"=>"Positive Evidence Ratio for function model (48 subjects, immediate group).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-16 00:23:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/680948"], "description"=>"<p>Model comparison candidates for predicting arm use <i>U(t)</i>.</p>", "links"=>[], "tags"=>["candidates", "predicting"], "article_id"=>351435, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Yukikazu Hidaka", "Cheol E. Han", "Steven L. Wolf", "Carolee J. Winstein", "Nicolas Schweighofer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002343.t002", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_comparison_candidates_for_predicting_arm_use_U_t_/351435", "title"=>"Model comparison candidates for predicting arm use <i>U(t)</i>.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-16 00:23:55"}
  • {"files"=>["https://ndownloader.figshare.com/files/680397"], "description"=>"<p>Classification in the three categories was based on the significance of the slope parameter of a linear model fit of use as a function of time, with a lenient criterion to test the hypothesis that the slope is not different from zero (p<0.25). Use increase category, N = 14; Use decrease category, N = 12; No change in use category, N = 22.</p>", "links"=>[], "tags"=>["mal", "aou", "48", "excite", "illustrating", "24", "months"], "article_id"=>350873, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Yukikazu Hidaka", "Cheol E. Han", "Steven L. Wolf", "Carolee J. Winstein", "Nicolas Schweighofer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002343.g001", "stats"=>{"downloads"=>4, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Longitudinal_arm_and_hand_use_data_as_measured_by_the_MAL_AOU_test_normalized_for_48_participants_of_the_immediate_group_in_EXCITE_illustrating_how_use_can_increase_A_decrease_B_or_not_change_C_in_the_24_months_following_therapy_/350873", "title"=>"Longitudinal arm and hand use data (as measured by the MAL AOU test, normalized) for 48 participants of the immediate group in EXCITE illustrating how use can increase (A), decrease (B), or not change (C) in the 24 months following therapy.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-16 00:14:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/680486"], "description"=>"<p>The blue lines show the actual data. The red lines are generated by the model with the mean model parameters, trained with 7 data points. (A) Both arm function and use improve (mean model parameters  = 0.76,  = 2.98 and  = 0.42) (B) Arm function is more or less constant, while arm use shows “non-use” (mean model parameters  = 0.14,  = 3.36 and  = 3.03). (C) Arm function slightly decreases, while arm use rises after 4 month and keeps the level (mean model parameters  = 0.19,  = 3.48 and  = 1.88). See how the model fit is in general good for use over the 24 months and for function in the first year but then is getting worse for function in the second year (see <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002343#pcbi-1002343-t003\" target=\"_blank\">Table 3</a> and <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002343#pcbi-1002343-t004\" target=\"_blank\">4</a> for a systematic evaluation of model fit).</p>", "links"=>[], "tags"=>["extremity", "24", "months", "subjects", "corresponding", "equations", "fonts"], "article_id"=>350968, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Yukikazu Hidaka", "Cheol E. Han", "Steven L. Wolf", "Carolee J. Winstein", "Nicolas Schweighofer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002343.g002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Examples_of_model_fit_for_upper_extremity_function_and_use_over_24_months_post_therapy_for_three_subjects_in_the_immediate_group_using_the_model_of_Equation_1_and_2_in_the_main_text_and_corresponding_equations_in_bold_fonts_in_Table_1_and_2_/350968", "title"=>"Examples of model fit for upper extremity function and use over 24 months post therapy for three subjects in the immediate group using the model of <b>Equation (1</b>) and (2) in the main text (and corresponding equations in bold fonts in <b>Table 1</b> and <b>2</b>).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-16 00:16:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/680745"], "description"=>"<p>A. Simulations of the effect on use after hypothetical changes in the confidence parameter as a result of therapy. Initial parameters values:  = 0.6,  = 3,  = 3. For simplicity, we assumed here that therapy has only an effect on the parameter and not on use and performance (which it did in actual participants of the EXCITE trial <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002343#pcbi.1002343-Wolf1\" target=\"_blank\">[3]</a>). The increase in parameter from before to after therapy parallels the increase in this parameter in the delayed group of the EXCITE trial (see <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002343#pcbi-1002343-g004\" target=\"_blank\">Figure 4</a>). B. Parameter sensitivity analysis showing the asymptotic value of arm function <i>F</i> as a function of parameter for a number of values of . LP: limit point. The line labeled  = 3 is generated by the same model as in A. For values of >3 the system behavior exhibits a non-stable range between the two limit points. For  = 3.5 and  = 5 for instance, arm function F converges to either a low or a high value.</p>", "links"=>[], "tags"=>["simulations", "dependence"], "article_id"=>351236, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Yukikazu Hidaka", "Cheol E. Han", "Steven L. Wolf", "Carolee J. Winstein", "Nicolas Schweighofer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002343.g005", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Computer_simulations_of_arm_function_showing_dependence_on_model_parameters_/351236", "title"=>"Computer simulations of arm function showing dependence on model parameters.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-16 00:20:36"}
  • {"files"=>["https://ndownloader.figshare.com/files/680556"], "description"=>"<p><b>, </b><b>, and </b><b> of the model estimated with data of the immediate group in the EXCITE trial.</b> Blue and Red: subjects with all estimated mean parameters. Blue: subjects with mean parameters after application of convergence criteria (see Results). The numbers N's indicate the numbers of subjects with good convergence for each parameter. Note that for , the means of all parameters with good convergence are in the range [0; 1] supporting the “Use it and improve it, or lose it” model. Similarly, for , the means of most parameters with good convergence are positive, supporting an actual influence of function on use (Refer to Equation (1) and (2) in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002343#s2\" target=\"_blank\">Methods</a> for the role of these parameters in the model).</p>", "links"=>[], "tags"=>["means", "parameters"], "article_id"=>351049, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Yukikazu Hidaka", "Cheol E. Han", "Steven L. Wolf", "Carolee J. Winstein", "Nicolas Schweighofer"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002343.g003", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Histograms_of_the_means_of_parameters_/351049", "title"=>"Histograms of the means of parameters", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-16 00:17:29"}

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Relative Metric

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