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1 Ergebnisse
1
Comparison of different target selection models:
Tianyao Zhu
;
Jason P. Gallivan
;
Daniel M. Wolpert
.
doi:10.1371/journal.pcbi.1011596.g008. , 2023
Link:
https://doi.org/10.1371/journal.pcbi.1011596.g008
RT Journal T1
Comparison of different target selection models
UL https://suche.suub.uni-bremen.de/peid=base-ftdeakinunifig:oai:figshare.com:article_24491773&Exemplar=1&LAN=DE A1 Tianyao Zhu A1 Jason P. Gallivan A1 Daniel M. Wolpert A1 J. Randall Flanagan YR 2023 K1 Molecular Biology K1 Evolutionary Biology K1 Sociology K1 Cancer K1 Science Policy K1 Biological Sciences not elsewhere classified K1 two processes interact K1 select targets close K1 always selecting targets K1 less noisy regions K1 reaching toward targets K1 bias often failed K1 noise varies across K1 selecting reach targets K1 noise </ p K1 40 degrees bias K1 participants experienced noise K1 40 degrees K1 three targets K1 reaching task K1 noisy direction K1 without noise K1 noise components K1 constant bias K1 bias learning K1 visuomotor rotation K1 thereby allowing K1 standard deviation K1 simulations indicate K1 quickly learned K1 participants reach K1 participants experienced K1 partially adapt K1 motor learning K1 increased linearly K1 improving performance K1 improved ability K1 improve performance K1 even though K1 direction dependent K1 chosen direction K1 also experienced K1 across groups JF doi:10.1371/journal.pcbi.1011596.g008 LK http://dx.doi.org/https://doi.org/10.1371/journal.pcbi.1011596.g008 DO https://doi.org/10.1371/journal.pcbi.1011596.g008 SF ELIB - SuUB Bremen
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