Abstract
A commentary on: Musicians' Online Performance during Auditory and Visual Statistical Learning Tasks by Mandikal Vasuki, P. R., Sharma, M., Ibrahim, R. K., and Arciuli, J. (2017). Front. Hum. Neurosci. 11:114. doi: 10.3389/fnhum.2017.00114 Statistical learning (SL) is the extraction of the underlying statistical structure from sensory input (Frost et al., 2015). The extent to which this ability is domain-general (with a single central mechanism underpinning SL in any modality) or domain-specific (where the SL mechanism differs by modality) remains a central question in statistical learning (Frost et al., 2015), and two approaches have been adopted to tackle this. First is to examine the extent to which predominantly domain-specific skills such as language proficiency (Arciuli and von Koss Torkildsen, 2012) and musical expertise (Schon and Francois, 2011), and domain-general skills such as working memory and general IQ (Siegelman and Frost, 2015), correlate with SL ability. Second is to compare SL performance across modalities, or even examine cross-modal transfer (Durrant et al., 2016). Mandikal Vasuki et al. (2017) (and the sister paper: Mandikal Vasuki et al., 2016) make an important contribution by adopting both of these approaches. They compare auditory and visual SL using the Saffran triplet learning paradigm (Saffran et al., 1999) in musicians and non-musicians. The three key findings are that musicians are better than non-musicians at segmentation of auditory stimuli only, there is no correlation between auditory and visual performance, and that auditory performance is better overall. This last result could be due to privileged auditory processing of sequential stimuli (Conway et al., 2009), or it could just reflect differences in perceptual or memory capabilities across modalities. However, the fact that SL performance in one modality does not predict performance in another is hard to explain if a single mechanism underlying both is posited. Combined with the fact that overall better performance was found in musicians only in the auditory modality, a domain-specific SL mechanism seems to offer the most parsimonious explanation of this data.
Highlights
Statistical learning (SL) is the extraction of the underlying statistical structure from sensory input (Frost et al, 2015)
The extent to which this ability is domain-general or domain-specific remains a central question in statistical learning (Frost et al, 2015), and two approaches have been adopted to tackle this
In keeping with the behavioral results, differences in the N1 and N400 triplet onset effects between musicians and non-musicians were seen only for the auditory stimuli, while the N400 was not seen at all for visual stimuli. These could suggests a neural mechanism for auditory statistical learning different to that of visual statistical learning, but without source localization based on more electrodes, this remains speculative
Summary
Statistical learning (SL) is the extraction of the underlying statistical structure from sensory input (Frost et al, 2015). The extent to which this ability is domain-general (with a single central mechanism underpinning SL in any modality) or domain-specific (where the SL mechanism differs by modality) remains a central question in statistical learning (Frost et al, 2015), and two approaches have been adopted to tackle this.
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