Verbal and Figural Recognition Memory: Task Development and Age Associations

Golski, Stephanie; Zonderman, Alan B.; Malamut, Barbara L.; Resnick, Susan M.

doi:10.1080/036107398244193

Cited by 13 publications

(8 citation statements)

References 59 publications

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“…This suggests that if we had taken the most common approach in cognitive aging studies and compared the youngest (say 20-30 years) to the oldest (say >65years) groups, we would have found little evidence of an effect of age on performance. By extension, the study of Golski et al (1998) who compared old (60-69yrs) and older (70-85yrs) participants would have caught only the tail-end of the changes in figural memory performance across the age distribution. It is likely that this is why they did not find age differences on RT or bias in their study.…”

Section: Discussionmentioning

confidence: 99%

“…The task stimuli (20 targets, 20 distractors, counterbalanced between participants) were black line drawings presented against a white background that were matched across uniqueness and resistant to verbal encoding (Figure 1; Beason-Held et al, 2005; Golski et al, 1998). The task consisted of two phases, an encoding and a recognition phase.…”

Section: Methodsmentioning

confidence: 99%

“…The mechanism of the picture superiority effect remains a matter of debate, but most major hypotheses posit that it relies on the ability to encode the picture both verbally and visually, whereas words are primarily encoded verbally. Recent research from Resnick and colleagues (Golski et al, 1998; Beason-Held et al, 2005; see also Beason-Held et al, 2008a; 2008b; Maki et al, 2011) has focused on the development of the figural memory task, a visual recognition memory task that employs picture stimuli that are resistant to verbal encoding (Figure 1). In a sample of elderly (63-82yrs) participants, Beason-Held et al (2005) demonstrated increases in regional cerebral blood flow (rCBF) using positron emission tomography (PET) 2 in prefrontal cortex, anterior cingulate, lateral and medial temporal and occipital regions during encoding of verbal and figural stimuli relative to baseline.…”

Section: Introductionmentioning

confidence: 99%

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Figural memory performance and functional magnetic resonance imaging activity across the adult lifespan

Jamadar

Assaf

Jagannathan

et al. 2013

Neurobiology of Aging

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We examined performance and fMRI activity in participants (n=235) aged 17-81yrs on a non-verbal recognition memory task, figural memory. Reaction time, error rate and response bias measures indicated that the youngest and oldest participants were faster, made fewer errors and showed a more conservative response bias than participants in the median age ranges. Encoding and Recognition phases activated a distributed bilateral network encompassing prefrontal, subcortical, lateral and medial temporal and occipital regions. Activation during Encoding phase did not correlate with age. During Recognition, task-related activation for correctly identified targets (Hit-Targets) correlated linearly positively with age; non-task related activity correlated negative quadratically with age. During correctly identified distractors (Hit-Distractors) activity in task-related regions correlated positive linearly with age, non-task activity showed positive and negative quadratic relationships with age. Missed-Targets activity did not correlate with age. We concluded that figural memory performance and fMRI activity during Recognition but not Encoding was affected both by continued maturation of the brain in the early 20s and compensatory recruitment of additional brain regions during recognition memory in oldage.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Figural memory performance and functional magnetic resonance imaging activity across the adult lifespan

Jamadar

Assaf

Jagannathan

et al. 2013

Neurobiology of Aging

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“…We selected six cognitive tests that have previously been shown to be sensitive to individual differences in primarily memory (Golski et al, 1998; Balthazar et al, 2008; Goh et al, 2012) or both memory and executive function (Paula et al, 2013; Shao et al, 2014) during healthy cognitive aging. These tests included the Boston Naming Test (BNT), the Benton Visual Retention Test (BVRT), California Verbal Learning Test (CVLT), the Clock Drawing Test (CLOCKs), the Category and Letter Fluency Tests.…”

Section: Methodsmentioning

confidence: 99%

Cross-Sectional and Longitudinal Effects of CREB1 Genotypes on Individual Differences in Memory and Executive Function: Findings from the BLSA

Wolf

Tanaka

et al. 2017

Front. Aging Neurosci.

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Purpose: Previously, we have shown that the SNP rs10932201 genotype of the cyclic AMP responsive element binding protein 1 gene (CREB1) contributes to individual differences in executive and memory function at the neural system and behavioral levels in healthy, young adults. However, longitudinal effects of CREB1 genotypes on cognition have not yet been addressed. Furthermore we were interested in replicating associations between CREB1 genotypes and human cognition in previous cross-sectional studies and explore whether APOE𝜀4 status might modify these relations.Materials and Methods: We investigated whether common, independent tag SNPs within CREB1 (rs2253206, rs10932201, rs6785) influence individual differences in age-related longitudinal change and level of executive function and memory performance independent of baseline age, sex, APOE𝜀4 status, and education. Our analysis included data from cognitively unimpaired older adults participating in the Baltimore Longitudinal Study of Aging. Eleven measures from six cognitive tests (sample sizes range 617–786) were analyzed using linear mixed effects and generalized estimating equations models. Mean baseline age ranged from 50 to 69 years and mean time of follow-up (interval) ranged from 8 to 22 years.Results: We found significant effects of all three CREB1 SNPs on performance level and/or longitudinal change in performance based on eight measures assessing semantic memory, episodic memory, or both executive function and semantic memory. SNP rs10932201 showed the most significant and largest effect (Cohen’s d = -0.70, p < 0.01) on age-related longitudinal decline of semantic memory. Additionally, we show interactions between all three CREB1 SNPs and APOE𝜀4 status on age-related longitudinal declines and levels of memory and executive function.Conclusion: Our results suggest that CREB1 genotypes independently and by interactions with APOE𝜀4 status contribute to individual differences in cognitive aging.

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“…After the isotope reached threshold level in the brain, scanning occurred for 60 seconds while task performance continued until the subject completed 40 trials. During the task, participants were asked to indicate whether or not they had seen each item before by pressing buttons in their right or left hands (a detailed description of the task can be found in (Beason-Held, Golski, Kraut, Esposito, & Resnick, 2005; Golski, Zonderman, Malamut, & Resnick, 1998). Accuracy and reaction times were recorded throughout the task.…”

Section: Methodsmentioning

confidence: 99%

Brain network changes and memory decline in aging

Beason‐Held

Hohman

Venkatraman

et al. 2016

Brain Imaging and Behavior

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One theory of age-related cognitive decline proposes that changes within the default mode network (DMN) of the brain impact the ability to successfully perform cognitive operations. To investigate this theory, we examined functional covariance within brain networks using regional cerebral blood flow data, measured by 15O-water PET, from 99 participants (mean baseline age 68.6 ±7.5) in the Baltimore Longitudinal Study of Aging collected over a 7.4 year period. The sample was divided in tertiles based on longitudinal performance on a verbal recognition memory task administered during scanning, and functional covariance was compared between the upper (improvers) and lower (decliners) tertile groups. The DMN and verbal memory networks (VMN) were then examined during the verbal memory scan condition. For each network, group differences in node-to-network coherence and individual node-to-node covariance relationships were assessed at baseline and in change over time. Compared with improvers, decliners showed differences in node-to-network coherence and in node-to-node relationships in the DMN but not the VMN during verbal memory. These DMN differences reflected greater covariance with better task performance at baseline and both increasing and declining covariance with declining task performance over time for decliners. When examined during the resting state alone, the direction of change in DMN covariance was similar to that seen during task performance, but node-to-node relationships differed from those observed during the task condition. These results suggest that disengagement of DMN components during task performance is not essential for successful cognitive performance as previously proposed. Instead, a proper balance in network processes may be needed to support optimal task performance.

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Verbal and Figural Recognition Memory: Task Development and Age Associations

Cited by 13 publications

References 59 publications

Figural memory performance and functional magnetic resonance imaging activity across the adult lifespan

Figural memory performance and functional magnetic resonance imaging activity across the adult lifespan

Cross-Sectional and Longitudinal Effects of CREB1 Genotypes on Individual Differences in Memory and Executive Function: Findings from the BLSA

Brain network changes and memory decline in aging

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