Linked Sources of Neural Noise Contribute to Age-related Cognitive Decline

Abstract

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 slope 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.

The development of theta and alpha neural oscillations from ages 3 to 24 years

“…An age-related decrease in aperiodic slope indicates that the 1/f spectrum becomes less steep with age, and an age-related decrease in offset indicates that the overall spectral power decreases with age. Two studies that examined the aperiodic component of human EEG data have also found age related decrease in the aperiodic slope during human lifespan ( He et al, 2019 ; Schaworonkow and Voytek, 2020b ; Tran et al, 2020 ; Voytek et al, 2015 ). Voytek et al (2015) found that the aperiodic slope is significantly flatter in older adults (60–70 years old) than in younger adults (20–30 years old), while He et al (2019) found the aperiodic slope to be flatter in adults (23–58 years old) than children (ages 5.5–10.5 years).…”

Resting-state aperiodic neural dynamics predict individual differences in visuomotor performance and learning

“…Here, we demonstrated that both a high 1/ƒ intercept (reflective of higher overall neural spiking) and a steeper 1/ƒ slope were predictive of enhanced perceptual sensitivity under more difficult conditions of information processing (i.e., Block 4). A steeper 1/ƒ slope is posited to represent an increase in neural inhibition activity (i.e., a shift toward more inhibitory states; Gao et al, 2017), and thus increase the consistency of stimulus processing (Tran et al, 2020). By contrast, a shallower slope (i.e., flattening of the aperiodic spectrum) may reflect a diminished neural excitation/inhibition balance and consequently, reduced information processing capacity.…”

“…By contrast, a shallower slope (i.e., flattening of the aperiodic spectrum) may reflect a diminished neural excitation/inhibition balance and consequently, reduced information processing capacity. For example, children with attention deficit hyperactivity disorder (Ostlund et al, 2021) and older adults (Voytek et al, 2015;Tran et al, 2020) demonstrate shallower 1/ƒ slopes and deficits in information processing capacity relative to age-matched healthy controls. Mechanistically, shallower slopes may reflect altered GABAergic and glutamatergic activity in cortical circuitry, neurotransmitters associated with maintaining an optimal excitation/inhibition balance (Ostlund et al, 2021).…”

Spontaneous neural oscillations influence behavior and sensory representations by suppressing neuronal excitability

“…Several M/EEG studies observed a negative relationship between low-frequency power decrease and, what is reported as, narrowband gamma increase (Bauer et al, 2006;Kloosterman et al, 2019;van Ede et al, 2014;Wyart & Tallon-Baudry, 2009); though it remains unclear whether this high-frequency signal reflects genuine oscillatory activity or broadband power. Importantly, the negative relationship between low-and high-frequency power was recently linked to changes in cognitive function (Nir et al, 2007;Proskovec et al, 2019;Tran et al, 2020;Voytek et al, 2015).…”

“…While historically regarded as "noise", spontaneous neural oscillations strongly predict neural dynamics and behavior in health (Busch et al, 2009;Grabot & Kayser, 2020;Lange et al, 2013;Romei et al, 2008b;Samaha, Iemi, et al, 2020) and disease (age-related cognitive decline: Tran et al, 2020;Voytek et al, 2015;schizophrenia: Uhlhaas & Singer, 2010;autism: Simon & Wallace, 2016). Here, "spontaneous" oscillations are operationalized as neural activity occurring without ("ongoing") or preceding ("prestimulus") sensory stimulation, since activity fluctuations during these moments are presumed to be endogenously generated.…”