Journal
JOURNAL OF MOTOR BEHAVIOR
Volume 42, Issue 6, Pages 343-349Publisher
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/00222895.2010.526462
Keywords
Bayesianism; falsifiability; motor control
Funding
- Fundacao Calouste Gulbenkian
- Siemens SA
- Fundacao para a Ciencia e Tecnologia [SFRH/BD/33525/2008]
- NIH [R01NS057814, R01NS063399]
- Chicago Community Trust
- NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [R01NS063399, R01NS057814] Funding Source: NIH RePORTER
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The authors argue that otrueo models that aim at faithfully mimicking or reproducing every property of the sensorimotor system cannot be compact as they need many free parameters. Consequently, most scientists in motor control use what are called ofalseo modelsmodels that derive from well-defined approximations. The authors conceptualize these models as a priori limited in scope and approximate. As such, they argue that a quantitative characterization of the deviations between the system and the model, more than the mere act of falsifying, allows scientists to make progress in understanding the sensorimotor system. Ultimately, this process should result in models that explain as much data variance as possible. The authors conclude by arguing that progress in that direction could strongly benefit from databases of experimental results and collections of models.
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