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On the contrary, smaller age-related declines in studies with vs. without ongoing task age confounds favoring older adults (e.g., easier ongoing tasks for older adults) suggest that retrieval of the plan requires cognitive resources and is anything but automatic, obligatory, or reflexive.
In the Go/No-Go task, age was not a significant predictor of the ERN or ΔERN whereas older age predicted a larger Pe.
For the Gaze task, age effects were also found in the left supramarginal gyrus, a region that has been shown in recent modeling studies to be part of an extended cortical eye gaze network (Nummenmaa et al. 2010).
In contrast to the healthy children, the children with CP clearly used their affected arm and hand less during the muffin task compared to the beads task (age group 1, mean difference: 29.6 ± 12.2%, t = -8.1, p < 0.001; age group 2, mean difference: 13.5 ± 13.7%, t = -4.6, p < 0.001).
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For the Expression task, age-dependent activation in FG and ITG brain regions was accompanied by structural brain changes, in particular an increase in WM (Fig. 3).
With all the insights gained from the diagnosing process, we finally build a deep multi-task age estimation model which obtains a MAE of 2.96 on the Morph II dataset and 5.75 on the WebFace dataset, both of which improve previous best results by a large margin.
However, because age-related changes in ΔCBF and ΔCMRO2 are heterogeneous across cortex and tasks, age differences in the BOLD response could be differentially affected by fluctuations in one or both of these factors (Buxton et al. 2004).
We evaluate our method on three tasks: age-invariant face identification on the MORPH database, age-invariant face retrieval on the CACD database and age-invariant face verification on CACD-VS database.
Money, children, household tasks, aging parents and blackberries at the dinner table have been topics of a few shouting matches and sleepless nights.
Perhaps not surprisingly, claims of no age-related declines in ProM with focal cues are similarly based on data compromised by ceiling effects, intelligence age-confounds, ongoing task-age confounds, low statistical power, and studies of vigilance.
However, it has been reported that in motor tasks, aged persons seem to employ adaptive strategies that counterbalance (at least partially) their reduced capacities [30].
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com