Improvement in performance in a task following practice can be a result of various cognitive and neural processes. While improvement can occur through fast mechanisms as a result of selecting a more successful response instead of the previous one, skill learning refers to a much slower process that results in improved execution achieved through reaching an ability level that was not available before. Thus, skill can be defined across sensory and motor domains as a change in the psychometric curve of a given task following training.
This feature propose interesting mechanistic and computational parallels between perceptual learning and motor skill learning, as in both cases task’s psychometric curve changes following days of training. Indeed, both processes are associated with expansion of cortical representations (Kleim et al. 2004; Recanzone et al. 1992) and increased synaptic density (Xu et al. 2009; Yang et al. 2009). Nevertheless, despite this broad perspective across modalities, the neural mechanisms of skill acquisition are still largely unknown, and computational modeling of skill learning is still in its infancy.
The goal of this Research Topic is to collect theoretical and experimental investigations of skill learning using behavioral, imaging, pharmacological and electrophysiological approaches. We aim to combine experimental results and perspectives from the perceptual learning and the motor learning communities in order to delineate the key components of skill learning. Researches are welcome to contribute experimental reports, perspectives and reviews.
This topic is cross-listed, therefore please see further articles in Frontiers in Human Neuroscience:
"The computational and neural substrates of skill learning" Improvement in performance in a task following practice can be a result of various cognitive and neural processes. While improvement can occur through fast mechanisms as a result of selecting a more successful response instead of the previous one, skill learning refers to a much slower process that results in improved execution achieved through reaching an ability level that was not available before. Thus, skill can be defined across sensory and motor domains as a change in the psychometric curve of a given task following training.
This feature propose interesting mechanistic and computational parallels between perceptual learning and motor skill learning, as in both cases task’s psychometric curve changes following days of training. Indeed, both processes are associated with expansion of cortical representations (Kleim et al. 2004; Recanzone et al. 1992) and increased synaptic density (Xu et al. 2009; Yang et al. 2009). Nevertheless, despite this broad perspective across modalities, the neural mechanisms of skill acquisition are still largely unknown, and computational modeling of skill learning is still in its infancy.
The goal of this Research Topic is to collect theoretical and experimental investigations of skill learning using behavioral, imaging, pharmacological and electrophysiological approaches. We aim to combine experimental results and perspectives from the perceptual learning and the motor learning communities in order to delineate the key components of skill learning. Researches are welcome to contribute experimental reports, perspectives and reviews.
This topic is cross-listed, therefore please see further articles in Frontiers in Human Neuroscience:
"The computational and neural substrates of skill learning" 