Age-related differences in memory-encoding fMRI responses after accounting for decline in vascular reactivity

Liu, Peiying; Hebrank, Andrew; Rodrigue, Karen M.; Kennedy, James L.; Section, Jarren; Park, Denise C.; Lu, Hanzhang

doi:10.1016/j.neuroimage.2013.04.053

Cited by 96 publications

(89 citation statements)

References 47 publications

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“…First, our conclusion that age has little impact on retrieval-related neural activity rests on the assumption that the transfer function mediating between neural activity and the fMRI BOLD signal is age-invariant. There is evidence however that cerebro-vascular reactivity (CVR) – an important non-neural determinant of BOLD signal magnitude – declines with age (e.g., Lu et al, 2011; Liu et al, 2013). Therefore it will be important to see whether the present findings require qualification in light of further research in which retrieval-related BOLD activity is corrected for individual differences in CVR (cf.…”

Section: Discussionmentioning

confidence: 99%

The neural correlates of recollection and retrieval monitoring: Relationships with age and recollection performance

et al. 2016

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The relationships between age, retrieval-related neural activity, and episodic memory performance were investigated in samples of young (18–29 yrs), middle-aged (43–55 yrs) and older (63–76 yrs) healthy adults. Participants underwent fMRI scanning during an associative recognition test that followed a study task performed on visually presented word pairs. Test items comprised pairs of intact (studied pairs), rearranged (items studied on different trials) and new words. fMRI recollection effects were operationalized as greater activity for studied pairs correctly endorsed as intact than for pairs incorrectly endorsed as rearranged. The reverse contrast was employed to identify retrieval monitoring effects. Robust recollection effects were identified in the core recollection network, comprising the hippocampus, along with parahippocampal and posterior cingulate cortex, left angular gyrus and medial prefrontal cortex. Retrieval monitoring effects were identified in the anterior cingulate and right dorsolateral prefrontal cortex. Neither recollection effects within the core network, nor the monitoring effects differed significantly across the age groups after controlling for individual differences in associative recognition performance. Whole brain analyses did however identify three clusters outside of these regions where recollection effects were greater in the young than in the other age groups. Across-participant regression analyses indicated that the magnitude of hippocampal and medial prefrontal cortex recollection effects, and both of the prefrontal monitoring effects, correlated significantly with memory performance. None of these correlations were moderated by age. The findings suggest that the relationships between memory performance and functional activity in regions consistently implicated in successful recollection and retrieval monitoring are stable across much of the healthy adult lifespan.

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Section: Discussionmentioning

confidence: 99%

The neural correlates of recollection and retrieval monitoring: Relationships with age and recollection performance

et al. 2016

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“…CVR mapping has been shown to provide valuable information in the evaluation of various cerebrovascular conditions, including arterial stenosis (Donahue et al, 2013; Gupta et al, 2012; Mandell et al, 2008; Mikulis et al, 2005), stroke (Geranmayeh et al, 2015), small vessel disease (Greenberg, 2006), brain tumors (Zaca et al, 2014), traumatic brain injury (Chan et al, 2015; Kenney et al, 2016), substance abuse (Han et al, 2008), and normal aging (Gauthier et al, 2013; Lu et al, 2011). CVR also has important utility in normalizing blood-oxygenation level dependent (BOLD) fMRI signal to differentiate neuronal from vascular alternations in brain function (Liu et al, 2013a; Liu et al, 2013b). …”

Section: Introductionmentioning

confidence: 99%

“…using arterial-spin-labeling MRI) due to its higher signal-to-noise ratio (SNR). This CVR mapping method has been successfully applied in a number of research studies in healthy and chronic disease patients (Donahue et al, 2013; Donahue et al, 2014; Han et al, 2008; Liu et al, 2013b; Lu et al, 2011; Mandell et al, 2008; Marshall et al, 2014; Mikulis et al, 2005; Thomas et al, 2013). However, the inherent need of gas inhalation and the associated apparatus setup requires additional time and expertise for handling and monitoring, which may limit the applications of this technique.…”

Section: Introductionmentioning

confidence: 99%

Cerebrovascular reactivity mapping without gas challenges

et al. 2017

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Cerebrovascular reactivity (CVR), the ability of cerebral vessels to dilate or constrict, has been shown to provide valuable information in the diagnosis and treatment evaluation of patients with various cerebrovascular conditions. CVR mapping is typically performed using hypercapnic gas inhalation as a vasoactive challenge while collecting BOLD images, but the inherent need of gas inhalation and the associated apparatus setup present a practical obstacle in applying it in routine clinical use. Therefore, we aimed to develop a new method to map CVR using resting-state BOLD data without the need of gas inhalation. This approach exploits the natural variation in respiration and measures its influence on BOLD MRI signal. In this work, we first identified a surrogate of the arterial CO2 fluctuation during spontaneous breathing from the global BOLD signal. Second, we tested the feasibility and reproducibility of the proposed approach to use the above-mentioned surrogate as a regressor to estimate voxel-wise CVR. Third, we validated the “resting-state CVR map” with a conventional CVR map obtained with hypercapnic gas inhalation in healthy volunteers. Finally, we tested the utility of this new approach in detecting abnormal CVR in a group of patients with Moyamoya disease, and again validated the results using the conventional gas inhalation method. Our results showed that global BOLD signal fluctuation in the frequency range of 0.02–0.04 Hz contains the most prominent contribution from natural variation in arterial CO2. The CVR map calculated using this signal as a regressor is reproducible across runs (ICC=0.91±0.06), and manifests a strong spatial correlation with results measured with a conventional hypercapnia-based method in healthy subjects (r=0.88, p<0.001). We also found that resting-state CVR was able to identify vasodilatory deficit in patients with steno-occlusive disease, the spatial pattern of which matches that obtained using the conventional gas method (r=0.71±0.18). These results suggest that CVR obtained with resting-state BOLD may be a useful alternative in detecting vascular deficits in clinical applications when gas challenge is not feasible.

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“…Examples include the use of hypercapnia (i.e., the establishment of a baseline BOLD signal through breath-holding), CO2 inhalation, or using resting state activity as a baseline (Handwerker et al 2007;Kannurpatti et al 2010aKannurpatti et al , 2010b. However, the evidence to date for the need to control for such group differences has been inconclusive, as minimal or inconsistent age differences have been found in the brain response to breath-holding (Handwerker et al 2007), or in vascular reactivity (Kannurpatti et al 2010a(Kannurpatti et al , 2010bLiu et al 2013). Because of such concerns, we attempted to remove all "unwanted" sources of noise in our data by means of rigorous denoising using ICA , so it is unlikely that the age differences we observed were due solely to such influences.…”

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confidence: 99%

Understanding variability in the BOLD signal and why it matters for aging

Grady

Garrett²

2013

Brain Imaging and Behavior

168

116

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Recent work in neuroscience supports the idea that variability in brain function is necessary for optimal brain responsivity to a changing environment. In this review, we discuss a series of functional magnetic resonance imaging (fMRI) studies in younger and older adults to assess agerelated differences in variability of the fMRI signal. This work shows that moment-to-moment brain variability represents an important "signal" within what is typically considered measurement-related "noise" in fMRI. This accumulation of evidence suggests that moving beyond the mean will provide a complementary window into aging-related neural processes.Functional magnetic resonance imaging (fMRI) research has typically focused on changes in mean activity of brain regions across different experimental conditions or between different groups of individuals. This approach draws from statistical and scientific traditions, in which a primary assumption is that central tendency reflects the most representative value in a distribution, and thus, "signal" within distributional "noise." Researchers in this field often attribute blood oxygen level-dependent (BOLD) signal variance to measurement-related confounds and attempt to remove all sources of "noise" to hone the signal related to cognitive activity. Substantial intra-subject variability in the BOLD signal within and across testing sessions is often discounted as merely reflecting issues with task, image acquisition and preprocessing, statistical power, reliability, or other nuisance effects (Huettel et al. 2004;Miller et al. 2002;Neumann et al. 2003;Aguirre et al. 1998;Smith et al. 2005;Jones et al. 2008;Kannurpatti et al. 2010a;Birn 2012). The focus on mean BOLD signal has clearly been very fruitful, and has led to a rapidly growing literature that shows no signs of slowing down (Bandettini 2012). However, no matter how brain activity is measured, it has been shown repeatedly that the brain's natural state is inherently variable (Faisal et al. 2008;Stein et al. 2005; Garrett et al. in press-b). Several areas of neuroscience research have examined the properties and unique functionality of variance, and suggest that by considering rather than ignoring variance, our ability to understand and predict several important phenomena (Faisal et al. 2008;MacDonald et al. 2006;Stein et al. 2005). We have recently attempted to take advantage of BOLD variance as a within-person measure with intrinsic theoretical and predictive meaning.In this review we will describe three experiments that contrast the more traditional measurement of adult age differences in mean activity with assessment of within-subject variability on a voxel-by-voxel basis. We were particularly interested in examining variability of brain activity in aging, in light of a decades-old assumption that cognitive aging may be conceptualized as due to "noisy" and inefficient neural processing (Cremer and Zeef 1987;Salthouse and Lichty 1985;Welford 1981). Human and computational modeling evidence (Li et al. 2001;MacDonald et al...

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Age-related differences in memory-encoding fMRI responses after accounting for decline in vascular reactivity

Cited by 96 publications

References 47 publications

The neural correlates of recollection and retrieval monitoring: Relationships with age and recollection performance

The neural correlates of recollection and retrieval monitoring: Relationships with age and recollection performance

Cerebrovascular reactivity mapping without gas challenges

Understanding variability in the BOLD signal and why it matters for aging

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