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Child Neuropsychology
A Journal on Normal and Abnormal Development in Childhood and Adolescence
Volume 23, 2017 - Issue 6
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Corrigendum

Correction to: Johnson, Healy, Dooley, Kelly, and McNicholas. Children born with very low birth weight show difficulties with sustained attention but not response inhibition

This article refers to:
Children born with very low birth weight show difficulties with sustained attention but not response inhibition

Katherine Anne Johnson, Elaine Healy, Barbara Dooley, Simon Kelly, and Fiona McNicholas. (2015). Children born with very low birth weight show difficulties with sustained attention but not response inhibition. Child Neuropsychology, 21, 629-647. https://doi.org/10.1080/09297049.2014.964193

When the article was published the calculation steps for one of the dependent measures was inadvertently misreported. The measure is the Slow Frequency Area Under the Spectra (SFAUS). Since our original studies developing these spectral measures of response time variability (e.g. Johnson et al., Neuropsychologia 45 (2007) 630-638), we have revised our calculation of this measure, but this update was not reflected correctly in the Methods section of the current paper. The new calculation of the SFAUS now follows the same steps as for our Fast Frequency Area Under the Spectra (FFAUS) measure, which entails (1) segmenting the time series into seven segments of 75 data points with an overlap of 50, then (2) detrending the individual response time (RT) time series to subtract out any linear components. In contrast, our original method had used all 225 trials for the calculation of SFAUS, with no segmenting or detrending. The impact of this change is that the very slowest components of variability related to potential linear trends over the entire task are excluded from the measure. We reasoned that such “time on task” components of variability would be more appropriately captured separately, leaving SFAUS to reflect only slow fluctuations that are non-monotonic in nature, and allow easier comparison with papers using periodic analyses in the “slow 3,” “slow 4,” and “slow 5” spectral ranges. This approach of segmenting and spectral averaging corresponds to Welch’s method of spectral estimation which is known to provide a smoother, more robust measure against noise, tending to average-out spurious spectral peaks that can potentially arise. This also reduces the complexity of the calculations of the SFAUS and FFAUS measures.

The updated Matlab script is available on this website below, for anyone wishing to use the same method:

http://psychologicalsciences.unimelb.edu.au/research/msps-research-groups/attention-dynamics-lab

We apologise for making this error in the description of the calculation of the SFAUS.

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