Age-related differences in the use of automatic and controlled processes in a situation of sustained attention

Staub, Bérengère; Doignon-Camus, Nadège; Marques-Carneiro, José Eduardo; Bacon, Élisabeth; Bonnefond, Anne

doi:10.1016/j.neuropsychologia.2015.07.021

Cited by 27 publications

(57 citation statements)

References 46 publications

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“…Accordingly, the SN was calculated as the mean amplitude of the signal between the peak of the P1 wave (96 msec) and the peak of the N1 wave (150 msec). The fP2 peak amplitude was identified at 158 msec (4.14 μV), which is within the time window previously reported for this component in older adults performing the SART (Staub et al, 2015). Mean amplitude values for the fP2 were calculated over a 50-msec window, centred on this peak (i.e., 133-183 msec).…”

Section: Monitoring Sustained Attention Performancesupporting

confidence: 66%

“…In this experiment, sustained attention was measured using the well-known Sustained Attention to Response Task (SART; Robertson, Manly, et al, 1997). This task correlates with attentional failures occurring in everyday life (Smilek, Carriere, & Cheyne, 2010) and has established electrophysiological markers of successful performance (Staub, Doignon-Camus, Marques-Carneiro, Bacon, & Bonnefond, 2015;Dockree, Kelly, Robertson, & Reilly, 2005).…”

Section: General Methodsmentioning

confidence: 99%

“…These participants were then excluded on the given performance measure from further analyses, and the mean and SD were subsequently recalculated. Given the sensitivity of tDCS to timing parameters, particularly in older adults (Fertonani, Brambilla, Cotelli, & Miniussi, 2014), and given that elderly participants have been shown to improve their performance on the SART over longer durations (Staub et al, 2015), the effects of stimulation were investigated per block. Changes in performance during stimulation were therefore assessed using repeated-measures ANOVAs with Stimulation (active vs. sham tDCS) and Time (Block 1 vs. Block 2) as the within-subject factors.…”

Section: Monitoring Sustained Attention Performancementioning

confidence: 99%

“…A notable strength of using the SART to measure the effects of tDCS is that electrophysiological signatures of successful performance have been established in both younger and older adults (Staub et al, 2015;Dockree et al, 2005). Components of interest were therefore selected based on these prior studies (selection negativity [SN; comprising the visual evoked P1 and visual evoked N1], frontal P2 [fP2], and frontal P3 [fP3]).…”

Section: Monitoring Sustained Attention Performancementioning

confidence: 99%

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Prefrontal Modulation of Visual Processing and Sustained Attention in Aging, a tDCS–EEG Coregistration Approach

Brosnan

Arvaneh

Harty

et al. 2018

Journal of Cognitive Neuroscience

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The ability to sustain attention is integral to healthy cognition in aging. The right PFC (rPFC) is critical for maintaining high levels of attentional focus. Whether plasticity of this region can be harnessed to support sustained attention in older adults is unknown. We used transcranial direct current stimulation to increase cortical excitability of the rPFC, while monitoring behavioral and electrophysiological markers of sustained attention in older adults with suboptimal sustained attention capacity. During rPFC transcranial direct current stimulation, fewer lapses of attention occurred and electroencephalography signals of frontal engagement and early visual attention were enhanced. To further verify these results, we repeated the experiment in an independent cohort of cognitively typical older adults using a different sustained attention paradigm. Again, prefrontal stimulation was associated with fewer attentional lapses. These experiments suggest the rPFC can be manipulated in later years to increase top-down modulation over early sensory processing and improve sustained attention performance. This holds valuable information for the development of neurorehabilitation protocols to ameliorate age-related deficits in this capacity.

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Section: Monitoring Sustained Attention Performancesupporting

confidence: 66%

Section: General Methodsmentioning

confidence: 99%

Section: Monitoring Sustained Attention Performancementioning

confidence: 99%

Section: Monitoring Sustained Attention Performancementioning

confidence: 99%

See 2 more Smart Citations

Prefrontal Modulation of Visual Processing and Sustained Attention in Aging, a tDCS–EEG Coregistration Approach

Brosnan

Arvaneh

Harty

et al. 2018

Journal of Cognitive Neuroscience

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show abstract

“…To our knowledge, there has not been a systematic investigation of how either incentive effects or the positivity effect may be impacted by changing the degree to which engagement is driven by 'bottom-up' versus 'top-down' within the same task. One way to differentiate these ideas while controlling for task difficulty might be, e.g., comparing rare-response versus frequent-response versions of the same attention task (c.f., Staub, Doignon-Camus, Marques-Carneiro, Bacon, & Bonnefond, 2015), or varying retention intervals in a working-memory task.…”

Section: Limitations and Comparisons (Or The Lack Thereof) With Previmentioning

confidence: 99%

Losing Money and Motivation: Effects of Loss Incentives on Motivation and Metacognition in Younger and Older Adults

Jang¹,

Lin²,

Lustig³

2019

Preprint

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Incentives are usually expected to increase motivation and the engagement of cognitive control, and to thereby improve performance on cognitively-demanding tasks. However, a closer read of the literature suggests that incentive effects on performance can be elusive. Further, although loss incentives are common in everyday life, most laboratory studies focus on gain effects. Different theoretical perspectives offer competing predictions for the effects of loss incentives, especially in older adults: The intuitive prediction is that loss incentives should improve performance. In contrast, Socioemotional Selectivity Theory and the age-related positivity effect (Carstensen & Mikels, 2005) would predict that older adults should be largely immune to loss-incentive effects. However, Selective Engagement Theory (Hess, 2014) and the Strength and Vulnerability Integration Theory (Charles, 2010) suggest that losses might increase the ‘perceived costs’ for older adults, and thus lead to disengagement and worse performance. Moreover, most studies use changes in performance or other measures as de facto indices of motivation, rather than measuring motivation directly. To address these gaps in the literature, we examined the effects of loss incentives on measures related to subjective engagement, motivation, and meta-cognition as well as working memory. Even though loss incentive did not impact performance, our findings were most consistent with the idea that loss incentives increase the perceived demands of a task and lead to disengagement. The loss incentive also increased the absolute metacognitive accuracy. Despite the lack of age differences in some measures of the incentive effect, the post-task questionnaires suggest different reasons for arriving at these results (distraction vs de-motivation) in younger versus older adults. The results suggest that the effects (or lack thereof) of incentive on performance may reflect factors other than motivation per se.

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Aging of the frontal lobe

Zanto

Gazzaley

2019

The Frontal Lobes

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Age-related differences in the use of automatic and controlled processes in a situation of sustained attention

Cited by 27 publications

References 46 publications

Prefrontal Modulation of Visual Processing and Sustained Attention in Aging, a tDCS–EEG Coregistration Approach

Prefrontal Modulation of Visual Processing and Sustained Attention in Aging, a tDCS–EEG Coregistration Approach

Losing Money and Motivation: Effects of Loss Incentives on Motivation and Metacognition in Younger and Older Adults

Aging of the frontal lobe

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