Healthy aging is associated with a multitude of structural changes in the brain. These physical age-related changes are accompanied by increased variability in neural activity of all kinds, and this increased variability, collectively referred to as “neural noise,” is argued to contribute to age-related cognitive decline. In this study, we examine the relationship between two particular types of neural noise in aging. We recorded scalp EEG from younger (20–30 years old) and older (60–70 years old) adults performing a spatial visual discrimination task. First, we used the 1/ f -like exponent of the EEG power spectrum, a putative marker of neural noise, to assess baseline shifts toward a noisier state in aging. Next, we examined age-related decreases in the trial-by-trial consistency of visual stimulus processing. Finally, we examined to what extent these two age-related noise markers are related, hypothesizing that greater baseline noise would increase the variability of stimulus-evoked responses. We found that visual cortical baseline noise was higher in older adults, and the consistency of older adults' oscillatory alpha (8–12 Hz) phase responses to visual targets was also lower than that of younger adults. Crucially, older adults with the highest levels of baseline noise also had the least consistent alpha phase responses, whereas younger adults with more consistent phase responses achieved better behavioral performance. These results establish a link between tonic neural noise and stimulus-associated neural variability in aging. Moreover, they suggest that tonic age-related increases in baseline noise might diminish sensory processing and, as a result, subsequent cognitive performance.

Some evidence suggests that experiencing a given scenario using virtual reality (VR) may engage greater attentional resources than experiencing the same scenario on a 2D computer monitor. However, the underlying neural processes associated with these VR-related effects, especially those pertaining to current consumer-friendly head-mounted displays of virtual reality (HMD-VR), remain unclear. Here, two experiments were conducted to compare task performance and EEG-based neural metrics captured during a perceptual discrimination task presented on two different viewing platforms. Forty participants (20–25 years old) completed this task using both an HMD-VR and traditional computer monitor in a within-group, randomized design. Although Experiment I ( n = 20) was solely behavioral in design, Experiment II ( n = 20) utilized combined EEG recordings to interrogate the neural correlates underlying potential performance differences across platforms. These experiments revealed that (1) there was no significant difference in the amount of arousal measured between platforms and (2) selective attention abilities in HMD-VR environment were enhanced from both a behavioral and neural perspective. These findings suggest that the allocation of attentional resources in HMD-VR may be superior to approaches more typically used to assess these abilities (e.g., desktop/laptop/tablet computers with 2D screens).

Daily experiences demand both focused and broad allocation of attention for us to interact efficiently with our complex environments. Many types of attention have shown age-related decline, although there is also evidence that such deficits may be remediated with cognitive training. However, spatial attention abilities have shown inconsistent age-related differences, and the extent of potential enhancement of these abilities remains unknown. Here, we assessed spatial attention in both healthy younger and older adults and trained this ability in both age groups for 5 hr over the course of 2 weeks using a custom-made, computerized mobile training application. We compared training-related gains on a spatial attention assessment and spatial working memory task to age-matched controls who engaged in expectancy-matched, active placebo computerized training. Age-related declines in spatial attention abilities were observed regardless of task difficulty. Spatial attention training led to improved focused and distributed attention abilities as well as improved spatial working memory in both younger and older participants. No such improvements were observed in either of the age-matched control groups. Note that these findings were not a function of improvements in simple response time, as basic motoric function did not change after training. Furthermore, when using change in simple response time as a covariate, all findings remained significant. These results suggest that spatial attention training can lead to enhancements in spatial working memory regardless of age.

Our attentional focus is constantly shifting: In one moment, our attention may be intently concentrated on a specific spot, whereas in another moment we might spread our attention more broadly. Although much is known about the mechanisms by which we shift our visual attention from place to place, relatively little is known about how we shift the aperture of attention from more narrowly to more broadly focused. Here we introduce a novel attentional distribution task to examine the neural mechanisms underlying this process. In this task, participants are presented with an informative cue that indicates the location of an upcoming target. This cue can be perfectly predictive of the exact target location, or it can indicate—with varying degrees of certainty—approximately where the target might appear. This cue is followed by a preparatory period in which there is nothing on the screen except a central fixation cross. Using scalp EEG, we examined neural activity during this preparatory period. We find that, with decreasing certainty regarding the precise location of the impending target, participant RTs increased whereas target identification accuracy decreased. Additionally, the multivariate pattern of preparatory period visual cortical alpha (8–12 Hz) activity encoded attentional distribution. This alpha encoding was predictive of behavioral accuracy and RT nearly 1 sec later. These results offer insight into the neural mechanisms underlying how we use information to guide our attentional distribution and how that influences behavior.

Selective attention involves top–down modulation of sensory cortical areas, such that responses to relevant information are enhanced whereas responses to irrelevant information are suppressed. Suppression of irrelevant information, unlike enhancement of relevant information, has been shown to be deficient in aging. Although these attentional mechanisms have been well characterized within the visual modality, little is known about these mechanisms when attention is selectively allocated across sensory modalities. The present EEG study addressed this issue by testing younger and older participants in three different tasks: Participants attended to the visual modality and ignored the auditory modality, attended to the auditory modality and ignored the visual modality, or passively perceived information presented through either modality. We found overall modulation of visual and auditory processing during cross-modal selective attention in both age groups. Top–down modulation of visual processing was observed as a trend toward enhancement of visual information in the setting of auditory distraction, but no significant suppression of visual distraction when auditory information was relevant. Top–down modulation of auditory processing, on the other hand, was observed as suppression of auditory distraction when visual stimuli were relevant, but no significant enhancement of auditory information in the setting of visual distraction. In addition, greater visual enhancement was associated with better recognition of relevant visual information, and greater auditory distractor suppression was associated with a better ability to ignore auditory distraction. There were no age differences in these effects, suggesting that when relevant and irrelevant information are presented through different sensory modalities, selective attention remains intact in older age.

Selective attention confers a behavioral benefit on both perceptual and working memory (WM) performance, often attributed to top–down modulation of sensory neural processing. However, the direct relationship between early activity modulation in sensory cortices during selective encoding and subsequent WM performance has not been established. To explore the influence of selective attention on WM recognition, we used electroencephalography to study the temporal dynamics of top–down modulation in a selective, delayed-recognition paradigm. Participants were presented with overlapped, “double-exposed” images of faces and natural scenes, and were instructed to either remember the face or the scene while simultaneously ignoring the other stimulus. Here, we present evidence that the degree to which participants modulate the early P100 (97–129 msec) event-related potential during selective stimulus encoding significantly correlates with their subsequent WM recognition. These results contribute to our evolving understanding of the mechanistic overlap between attention and memory.

Top-down modulation underlies our ability to selectively attend to relevant stimuli and to ignore irrelevant stimuli. Theories addressing neural mechanisms of top-down modulation are driven by studies that reveal increased magnitude of neural activity in response to directed attention, but are limited by a lack of data reporting modulation of neural processing speed, as well as comparisons with a perceptual (passive view) baseline necessary to evaluate the presence of enhancement and suppression. Utilizing functional MRI (fMRI) and event-related potential recordings (ERPs), we provide converging evidence that both the magnitude of neural activity and the speed of neural processing are modulated by top-down influences. Furthermore, both enhancement and suppression occur relative to a perceptual baseline depending on task instruction. These findings reveal the fine degree of influence that goal-directed attention exerts upon activity within the visual association cortex. We further document capacity limitations in top-down enhancement corresponding with working memory performance deficits.