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The primary image analysis was done with spatiotemporal PLS (McIntosh et al. 2004), a multivariate method that enables the identification of the optimal spatial and temporal patterns that either differentiate tasks in terms of activation, or in terms of functional connectivity.
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The assumption was that state-dependent functional activations would be information-nonspecific and should not differentiate task-specific material.
If a cortical area contains neurons that differentiate task targets from distractors, then our work would predict that learning induced plasticity would be observable in that area.
Based on these findings, it has been argued that auditory deprivation results in deficient visual selective attention, with deaf individuals being unable to differentiate task-relevant from task-irrelevant information [16].
A series of studies [ 9– 12] attempted to differentiate task- or process-related ENMs from background or incidental nanoaerosols in workplaces.
We measured nanopowders at two monitoring positions (main and subpositions) to differentiate task- or process-related nanopowder exposures from the background or incidental nanoaerosols.
Seed PLS could identify 1) functional connections that are common for all experimental tasks, 2) functional connections that differentiate task demands (i.e., temporal sequencing tasks vs. comparison tasks), 3) functional connections that differentiate input modality (i.e., auditory versus visual tasks), and 4) functional connections that show an interaction between task demands and modality.
This analysis also allowed us to identify a seed voxel whose activity differentiated task demands, located in BA 47.
To differentiate
A four-part injury severity index, generated by the claims settling process, has been used to differentiate occupations, tasks and activities in terms of priorities for intervention and prevention.
A recent theory differentiates between tasks that we want to do and tasks that we have to do.
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