Balasubramaniam, Ramesh ; Dam, Loes C. J. van ; Ernst, Marc O. (2024)
Knowing Each Random Error of Our Ways, but Hardly Correcting for It: An Instance of Optimal Performance.
In: PLoS ONE, 2013, 8 (10)
doi: 10.26083/tuprints-00027548
Artikel, Zweitveröffentlichung, Verlagsversion
 | Es ist eine neuere Version dieses Eintrags verfügbar. |
Kurzbeschreibung (Abstract)
Random errors are omnipresent in sensorimotor tasks due to perceptual and motor noise. The question is, are humans aware of their random errors on an instance-by-instance basis? The appealing answer would be ‘no’ because it seems intuitive that humans would otherwise immediately correct for the errors online, thereby increasing sensorimotor precision. However, here we show the opposite. Participants pointed to visual targets with varying degree of feedback. After movement completion participants indicated whether they believed they landed left or right of target. Surprisingly, participants' left/right-discriminability was well above chance, even without visual feedback. Only when forced to correct for the error after movement completion did participants loose knowledge about the remaining error, indicating that random errors can only be accessed offline. When correcting, participants applied the optimal correction gain, a weighting factor between perceptual and motor noise, minimizing end-point variance. Together these results show that humans optimally combine direct information about sensorimotor noise in the system (the current random error), with indirect knowledge about the variance of the perceptual and motor noise distributions. Yet, they only appear to do so offline after movement completion, not while the movement is still in progress, suggesting that during movement proprioceptive information is less precise.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Balasubramaniam, Ramesh ; Dam, Loes C. J. van ; Ernst, Marc O. |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Knowing Each Random Error of Our Ways, but Hardly Correcting for It: An Instance of Optimal Performance |
| Sprache: | Englisch |
| Publikationsjahr: | 23 Juli 2024 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 2013 |
| Ort der Erstveröffentlichung: | San Francisco |
| Verlag: | PLOS |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | PLoS ONE |
| Jahrgang/Volume einer Zeitschrift: | 8 |
| (Heft-)Nummer: | 10 |
| Kollation: | 9 Seiten |
| DOI: | 10.26083/tuprints-00027548 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/27548 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichungsservice |
| Kurzbeschreibung (Abstract): | Random errors are omnipresent in sensorimotor tasks due to perceptual and motor noise. The question is, are humans aware of their random errors on an instance-by-instance basis? The appealing answer would be ‘no’ because it seems intuitive that humans would otherwise immediately correct for the errors online, thereby increasing sensorimotor precision. However, here we show the opposite. Participants pointed to visual targets with varying degree of feedback. After movement completion participants indicated whether they believed they landed left or right of target. Surprisingly, participants' left/right-discriminability was well above chance, even without visual feedback. Only when forced to correct for the error after movement completion did participants loose knowledge about the remaining error, indicating that random errors can only be accessed offline. When correcting, participants applied the optimal correction gain, a weighting factor between perceptual and motor noise, minimizing end-point variance. Together these results show that humans optimally combine direct information about sensorimotor noise in the system (the current random error), with indirect knowledge about the variance of the perceptual and motor noise distributions. Yet, they only appear to do so offline after movement completion, not while the movement is still in progress, suggesting that during movement proprioceptive information is less precise. |
| ID-Nummer: | Artikel-ID: e78757 |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-275484 |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 100 Philosophie und Psychologie > 150 Psychologie 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin, Gesundheit |
| Hinterlegungsdatum: | 23 Jul 2024 14:06 |
| Letzte Änderung: | 31 Jul 2024 08:15 |
| PPN: | |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
Verfügbare Versionen dieses Eintrags
- Knowing Each Random Error of Our Ways, but Hardly Correcting for It: An Instance of Optimal Performance. (deposited 23 Jul 2024 14:06) [Gegenwärtig angezeigt]
 |
Frage zum Eintrag |
Optionen (nur für Redakteure)
 |
Redaktionelle Details anzeigen |
Drucken
Impressum