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Thus the acquisition of skill in a given task involves the performance of a reasonably consistent response pattern, which varies, within limits, from trial to trial.
Underlying the various models of perceptual learning mechanisms are the particular neural changes that take place, which appear to reflect the specific kind of code used by the brain to represent percepts (mental impressions derived from perception with the senses) in a given task.
The context acts like a set of constraints that influence the behavior of a system embedded in a given task (Bazire and Brézillon 2005).
Strengths capacitate the individual to consistently provide dynamic and excellent performance in a given task (Clifton et al. 2006; Clifton and Harter 2003).
To solve the what to imitate issue, we use a probabilistic method, based on Hidden Markov Models (HMM), to extract the relative importance of reproducing either the gesture or the specific hand path in a given task.
We propose a universal delta model and a set of metrics to characterize and compare effectively deltas produced by different algorithms, in order to highlight what are the most suitable ones for use in a given task and domain.
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Think-alouds are useful in identifying difficulties in understanding a given task, in understanding instructions, and in producing an appropriate solution.29 After the think-alouds, we explicitly asked participants to comment on the documents to obtain feedback on cultural and linguistic differences (content and format).
Multivariate image analysis using PCA permits the characterization of different networks that include brain areas changing brain activity in related to a given task and brain areas contributing to the function without necessarily changing their activity [ 28- 31, 67].
In particular, Mueller, Brass, Waszak, and Prinz (2007) have suggested that RCZ is mainly involved in selecting the "what" component, in the context of a given task (Desmet, Fias, Hartstra, & Brass, 2011); whilst preSMA participates in selecting the "when" component of actions.
She draws on recent research with functional magnetic resonance imaging (fMRI), a technique that maps blood flow in the brain during a given task, to show that meaningful squiggles activate not only the occipital regions responsible for vision but also temporal and parietal regions associated with language and computation.
Ultimately, ML is meant to be used in the context of a given task, a problem with inputs and a way to objectively assess how right or wrong an output is.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com