Aging effects on functional auditory and visual processing using fMRI with variable sensory loading

Cliff, Michael; Joyce, Dan W.; Lamar, Melissa; Dannhauser, Thomas; Tracy, Derek K.; Shergill, Sukhwinder S.

doi:10.1016/j.cortex.2012.04.003

Cited by 45 publications

(43 citation statements)

References 52 publications

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“…Perception considerably interacts with cognition and deficits in the auditory and visual acuity; the sensory and motor ability were common in the elderly . Decreased functional connectivity in these three basic function networks was noted in both our study and previous task‐dependent fMRI studies . Therefore, these deficits are probably because of not only structural or physical degeneration but also functional processing in the brain or perhaps, decreased functional connectivity is just the result of less external information input.…”

Section: Discussionsupporting

confidence: 76%

Age‐Related Changes in Resting‐State Networks of A Large Sample Size of Healthy Elderly

et al. 2015

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Section: Discussionsupporting

confidence: 76%

Age‐Related Changes in Resting‐State Networks of A Large Sample Size of Healthy Elderly

et al. 2015

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“…These changes include a reduction in visual acuity and auditory sensitivity due to changes in transduction processes in the retina and cochlea (Baltes and Lindenberger, 1997,Lindenberger and Baltes, 1997,Lindenberger and Ghisletta, 2009), as well as age-related changes along the sensory processing hierarchies (Cliff, et al, 2013,Hugenschmidt, et al, 2009,Nagamatsu, et al, 2011). In the current study we saw such effects very clearly, with a significant main effect of age group for both the auditory-only and visual-only conditions in which younger adults performed better than younger adults.…”

Section: Discussionmentioning

confidence: 99%

Deficits in audiovisual speech perception in normal aging emerge at the level of whole-word recognition

Stevenson

Nelms

Baum

et al. 2015

Neurobiology of Aging

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Over the next two decades, a dramatic shift in the demographics of society will take place, with a rapid growth in the population of older adults. One of the most common complaints with healthy aging is a decreased ability to successfully perceive speech, particularly in noisy environments. In such noisy environments, the presence of visual speech cues (i.e., lip movements) provide striking benefits for speech perception and comprehension, but previous research suggests that older adults gain less from such audiovisual integration than their younger peers. To determine at what processing level these behavioral differences arise in healthy-aging populations, we administered a speech-in-noise task to younger and older adults. We compared the perceptual benefits of having speech information available in both the auditory and visual modalities and examined both phoneme and whole-word recognition across varying levels of signal-to-noise ratio (SNR). For whole-word recognition, older relative to younger adults showed greater multisensory gains at intermediate SNRs, but reduced benefit at low SNRs. By contrast, at the phoneme level both younger and older adults showed approximately equivalent increases in multisensory gain as SNR decreased. Collectively, the results provide important insights into both the similarities and differences in how older and younger adults integrate auditory and visual speech cues in noisy environments, and help explain some of the conflicting findings in previous studies of multisensory speech perception in healthy aging. These novel findings suggest that audiovisual processing is intact at more elementary levels of speech perception in healthy aging populations, and that deficits begin to emerge only at the more complex, word-recognition level of speech signals.

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“…Potential sources of longitudinal within-subject variance in fMRI recordings include, but are not limited to: habituation effects (Hamid et al, 2015), strategy shifts/practice effects (Kelly and Garavan, 2005), fatigue, lapses of attention, caffeine (Koppelstaetter and Poeppel, 2010; Liu et al, 2004), nicotine (Warbrick et al, 2012, 2011), time-of-day (Gaggioni et al, 2014; Schmidt et al, 2015), aging (Cliff et al, 2013; Koch et al, 2010), residual levels of physiological noise(Birn, 2012), distinct geometric distortions across sessions (Raemaekers et al, 2012), or progression of clinical conditions. As our understanding of natural within-subject variability in both neuronal and fMRI responses improves, additional factors may need to be added to this list.…”

Section: Discussionmentioning

confidence: 99%

Variance decomposition for single-subject task-based fMRI activity estimates across many sessions

et al. 2017

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Here we report an exploratory within-subject variance decomposition analysis conducted on a task-based fMRI dataset with an unusually large number of repeated measures (i.e., 500 trials in each of three different subjects) distributed across 100 functional scans and 9 to 10 different sessions. Within-subject variance was segregated into four primary components: variance across-sessions, variance across-runs within a session, variance across-blocks within a run, and residual measurement/modeling error. Our results reveal inhomogeneous and distinct spatial distributions of these variance components across significantly active voxels in grey matter. Measurement error is dominant across the whole brain. Detailed evaluation of the remaining three components shows that across-session variance is the second largest contributor to total variance in occipital cortex, while across-runs variance is the second dominant source for the rest of the brain. Network-specific analysis revealed that across-block variance contributes more to total variance in higher-order cognitive networks than in somatosensory cortex. Moreover, in some higher-order cognitive networks across-block variance can exceed across-session variance. These results help us better understand the temporal (i.e., across blocks, runs and sessions) and spatial distributions (i.e., across different networks) of within-subject natural variability in estimates of task responses in fMRI. They also suggest that different brain regions will show different natural levels of test-retest reliability even in the absence of residual artifacts and sufficiently high contrast-to-noise measurements. Further confirmation with a larger sample of subjects and other tasks is necessary to ensure generality of these results.

show abstract

Aging effects on functional auditory and visual processing using fMRI with variable sensory loading

Cited by 45 publications

References 52 publications

Age‐Related Changes in Resting‐State Networks of A Large Sample Size of Healthy Elderly

Age‐Related Changes in Resting‐State Networks of A Large Sample Size of Healthy Elderly

Deficits in audiovisual speech perception in normal aging emerge at the level of whole-word recognition

Variance decomposition for single-subject task-based fMRI activity estimates across many sessions

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