The response-signal method reveals age-related changes in object working memory.

Kumar, Arjun; Rakitin, Brian C.; Nambisan, Rohit; Habeck, Christian; Stern, Yaakov

doi:10.1037/0882-7974.23.2.315

Cited by 13 publications

(15 citation statements)

References 85 publications

(185 reference statements)

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“…These findings complement those of a previously reported behavioral study. In that study of a different set of young and older participants, we also found asymptote lower in the older than the younger group, indicating lower capacity, while the x-intercept parameter did not differ across groups (Kumar et al, 2008). In that study we also found a higher rate in the young subjects, suggesting greater efficiency.…”

Section: 0 Discussionmentioning

confidence: 67%

Task difficulty modulates young–old differences in network expression

et al. 2012

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The extent of task-related fMRI activation can vary as a function of task difficulty. Also the efficiency or capacity of the brain networks underlying task performance can change with aging. We asked whether the expression of a network underlying task performance would differ as a function of task demand in old and young individuals. 26 younger and 23 older healthy adults performed a delayed item recognition task that used the response signal method to parametrically manipulate the extrinsic difficulty of the task by imposing five different deadlines for recognition response. Both age groups showed a speed accuracy trade-off, but the younger group achieved greater discriminability at the longer deadlines. We identified a spatial pattern of fMRI activation during the probe phase whose expression increased as the response deadline shortened and the task became more difficult. This pattern was expressed to a greater degree by the old group at the long deadlines, when the task was easiest. By contrast, this pattern was expressed to greater degree by the younger group at the short deadlines, when the task was hardest. This suggests reduced efficiency and capacity of this network in older subjects. These findings suggest that neuroimaging studies comparing task-related activation across groups with different cognitive abilities must be interpreted in light of the relative difficulty of the task for each group.

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Section: 0 Discussionmentioning

confidence: 67%

Task difficulty modulates young–old differences in network expression

et al. 2012

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“…To analyze the effects of CR covariates on MPUBS and RT, we constructed two separate general linear models (GLM) that were analyzed in stages (heterogeneous slopes) (Kumar, Rakitin, Nambisan, Habeck, & Stern, 2008; Siegel, 1956). In each, we introduced various proxies for CR into our model, including score on the NART IQ and years of education (EDU).…”

Section: Methodsmentioning

confidence: 99%

The Influence of Cognitive Reserve on Strategy Selection in Normal Aging

Barulli

Rakitin

Lemaire

et al. 2013

J Int Neuropsychol Soc

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Cognitive reserve (CR) has been proposed as a latent variable that can account for the frequent discrepancy between an individual’s underlying level of brain pathology and their observed clinical outcome. A possible behavioral manifestation of CR is best strategy choice. Older adults have been shown to choose sub-optimal strategies for performing various tasks. The present study attempted to investigate whether greater levels of CR could predict greater strategy selection, particularly in older adults. A computational estimation task was administered to 20 healthy young adults (mean age = 24.7 ± 3.6; 20–31 years) and 18 healthy older adults (68.2 ± 4.5; 62–77 years) wherein participants needed to estimate the product of two two-digit numbers by using one of two strategies. The results revealed an effect of age group on strategy choice and supported the hypothesis that CR is associated with increased strategy selection abilities.

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“…Within such paradigms, the participants' stimulus processing is interrupted at different times after stimulus presentation (e.g., Boldini, Russo, & Avons, 2004;Boldini, Russo, Punia, & Avons, 2007;Corbett & Wickelgren, 1978;Dosher, 1981Dosher, , 1982Göthe & Oberauer, 2008;Kumar, Rakitin, Nambisan, Habeck, & Stern, 2008;Lohman, 1986;McElree & Dosher, 1989, 1993McElree, Plykkänen, Pickering, & Traxler, 2006;Miller, Sproesser, & Ulrich, 2008;Öztekin & McElree, 2006;Ratcliff, 2006;Reed, 1973;Schouten & Bekker, 1967). In this way, different intervals between stimulus presentation and the response signal can be used, allowing for an examination of the variation in the amount of processing that can occur before the response signal and, ultimately, the amount of accuracy associated with that amount of processing time.…”

Section: Studying Satsmentioning

confidence: 99%

The time course of task switching: A speed—accuracy trade-off analysis

Samavatyan

Leth‐Steensen

2009

Memory & Cognition

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Response time (RT) and accuracy are highly dependent (Pachella, 1974). Typically, more efficient information processing results in both decreases in RT and increases in accuracy. However, in any response process, an optimal balance of speed and accuracy can also be considered by the responder on the basis of the priorities of the current situation. The mutual dependence of RT and accuracy is evident when more emphasis on accuracy results in increases in RTs and when, conversely, more emphasis on speed (i.e., shorter RTs) causes accuracy to decrease. As was noted by Wickelgren (1977), the study of RTs in conjunction with accuracy (i.e., the whole speed-accuracy trade-off [SAT] function) has the potential to provide much greater knowledge about information processing dynamics than can the study of either the RT or accuracy aspects of performance separately.Switching between tasks results in costs in terms of both RT and accuracy (Monsell, 2003). A review of the influential studies in the task-switching area reveals that the issue of SATs and how corresponding speed-accuracy manipulations can affect task-switching performance has rarely been directly examined. One exception is Gopher, Armony, and Greenshpan (2000), whose major interest in SATs, however, involved a comparison of the costs associated with switching between tasks and the costs associated with switching between speed and accuracy strategy emphases. Another exception is Lien, Ruthruff, Remington, and Johnston (2005), involving time deadlines, which were utilized by Lien et al. in order to provide their participants with the strongest possible motivation for optimal performance. Studying SATsTrading off accuracy for speed or vice versa can be expected in presumably any task. Systematic experimental work on the phenomenon began in the 1950s and '60s (for a discussion of this work, see Wickelgren, 1977). The SAT paradigm in cognitive psychology addresses the inverse relationship between speed and accuracy (or, correspondingly, the positive relation between RTs and accuracy) by examining the process of information accumulation through time. In this way, an experimenter can observe how different methods of manipulation of speed emphasis result in changes in both the RTs and the accuracy of the responses. Under speed pressure, more incorrect responses are expected, and SAT curves can be derived to specify how much time is needed to achieve a particular accuracy level. This procedure was initially used by a few researchers in the 1970s (e.g., Reed, 1973Reed, , 1976) to study cognitive processing.One important method through which speed-accuracy performance can be explicitly manipulated is by using response signals. Within such paradigms, the participants' stimulus processing is interrupted at different times after stimulus presentation (e.g., Boldini, Russo, & Avons, 2004;Boldini, Russo, Punia, & Avons, 2007;Corbett & Wickelgren, 1978;Dosher, 1981Dosher, , 1982Göthe & Oberauer, 2008;Kumar, Rakitin, Nambisan, Habeck, & Stern, 2008;Lohman, 1986;McElree & Dosher,...

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The response-signal method reveals age-related changes in object working memory.

Cited by 13 publications

References 85 publications

Task difficulty modulates young–old differences in network expression

Task difficulty modulates young–old differences in network expression

The Influence of Cognitive Reserve on Strategy Selection in Normal Aging

The time course of task switching: A speed—accuracy trade-off analysis

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