Age-Related Changes in 1/<i>f</i>Neural Electrophysiological Noise

Voytek, Bradley; Kramer, Mark A.; Case, John; Lepage, Kyle Q.; Tempesta, Zechari Ryan; Knight, Robert T.; Gazzaley, Adam

doi:10.1523/jneurosci.2332-14.2015

Cited by 591 publications

(846 citation statements)

References 69 publications

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“…This is in agreement with work demonstrating that aging leads to less focal spatial attention resources and, consequently, a greater dependence on cues providing location-based information (Greenwood & Parasuraman, 1999, 2004; Greenwood et al, 1997). Such findings are consistent with theories of aging describing greater neural noise (Voytek et al, 2015) or dedifferentiation (Hülür, Ram, Willis, Schaie, & Gerstorf, 2015; Li, Lindenberger, & Sikström, 2001; Li & Lindenberger, 1999) accompanying the aging process, leading to impairments in performance associated with spatial attention and other cognitive control processes.…”

Section: Discussionsupporting

confidence: 88%

Enhancing Spatial Attention and Working Memory in Younger and Older Adults

Rolle

Anguera

Skinner

et al. 2017

Journal of Cognitive Neuroscience

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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.

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Section: Discussionsupporting

confidence: 88%

Enhancing Spatial Attention and Working Memory in Younger and Older Adults

Rolle

Anguera

Skinner

et al. 2017

Journal of Cognitive Neuroscience

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“…While the physiological origin of alpha oscillations has not yet been fully elucidated, it is well accepted that alpha power decreases with increased population-level activity, as demonstrated by its negative correlation with broadband gamma power (Crone et al, 2001; Miller et al, 2009a; Potes et al, 2014) and the blood-oxygen-level dependent (BOLD) response (Mukamel et al, 2005). The mechanisms supporting these apparent interrelationships between alpha and broadband gamma power are still unclear (but see Podvalny et al 2015; Voytek et al 2015; Voytek and Knight 2015). At the same time, alpha power decreases are clearly not simply a direct reflection of population-level activity since alpha power decreases can be observed in the absence of population-level activity and in preparation for an upcoming stimulus (Romei et al, 2010; Mazaheri et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Alpha power indexes task-related networks on large and small scales: A multimodal ECoG study in humans and a non-human primate

et al. 2016

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Performing different tasks, such as generating motor movements or processing sensory input, requires the recruitment of specific networks of neuronal populations. Previous studies suggested that power variations in the alpha band (8–12 Hz) may implement such recruitment of task-specific populations by increasing cortical excitability in task-related areas while inhibiting population-level cortical activity in task-unrelated areas (Klimesch et al., 2007; Jensen and Mazaheri, 2010). However, the precise temporal and spatial relationships between the modulatory function implemented by alpha oscillations and population-level cortical activity remained undefined. Furthermore, while several studies suggested that alpha power indexes task-related populations across large and spatially separated cortical areas, it was largely unclear whether alpha power also differentially indexes smaller networks of task-related neuronal populations. Here we addressed these questions by investigating the temporal and spatial relationships of electrocorticographic (ECoG) power modulations in the alpha band and in the broadband gamma range (70–170 Hz, indexing population-level activity) during auditory and motor tasks in five human subjects and one macaque monkey. In line with previous research, our results confirm that broadband gamma power accurately tracks task-related behavior and that alpha power decreases in task-related areas. More importantly, they demonstrate that alpha power suppression lags population-level activity in auditory areas during the auditory task, but precedes it in motor areas during the motor task. This suppression of alpha power in task-related areas was accompanied by an increase in areas not related to the task. In addition, we show for the first time that these differential modulations of alpha power could be observed not only across widely distributed systems (e.g., motor vs. auditory system), but also within the auditory system. Specifically, alpha power was suppressed in the locations within the auditory system that most robustly responded to particular sound stimuli. Altogether, our results provide experimental evidence for a mechanism that preferentially recruits task-related neuronal populations by increasing cortical excitability in task-related cortical areas and decreasing cortical excitability in task-unrelated areas. This mechanism is implemented by variations in alpha power and is common to humans and the non-human primate under study. These results contribute to an increasingly refined understanding of the mechanisms underlying the selection of the specific neuronal populations required for task execution.

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“…Power Spectral Densities (PSDs) from EEG recordings follow a characteristic 1/ f distribution, so named because spectral power is inversely proportional to frequency. 1/ f distributions are ubiquitous in the brain and are a likely signature of balance between neural excitation and inhibition (E/I balance) [22, 23]. …”

Section: Discussionmentioning

confidence: 99%

A Quantitative Electrophysiological Biomarker of Duplication 15q11.2-q13.1 Syndrome

Frohlich

Şentürk²,

Saravanapandian

et al. 2016

PLoS ONE

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BackgroundDuplications of 15q11.2-q13.1 (Dup15q syndrome) are highly penetrant for autism spectrum disorder (ASD). A distinct electrophysiological (EEG) pattern characterized by excessive activity in the beta band has been noted in clinical reports. We asked whether EEG power in the beta band, as well as in other frequency bands, distinguished children with Dup15q syndrome from those with non-syndromic ASD and then examined the clinical correlates of this electrophysiological biomarker in Dup15q syndrome.MethodsIn the first study, we recorded spontaneous EEG from children with Dup15q syndrome (n = 11), age-and-IQ-matched children with ASD (n = 10) and age-matched typically developing (TD) children (n = 9) and computed relative power in 6 frequency bands for 9 regions of interest (ROIs). Group comparisons were made using a repeated measures analysis of variance. In the second study, we recorded spontaneous EEG from a larger cohort of individuals with Dup15q syndrome (n = 27) across two sites and examined age, epilepsy, and duplication type as predictors of beta power using simple linear regressions.ResultsIn the first study, spontaneous beta1 (12–20 Hz) and beta2 (20–30 Hz) power were significantly higher in Dup15q syndrome compared with both comparison groups, while delta (1–4 Hz) was significantly lower than both comparison groups. Effect sizes in all three frequency bands were large (|d| > 1). In the second study, we found that beta2 power was significantly related to epilepsy diagnosis in Dup15q syndrome.ConclusionsHere, we have identified an electrophysiological biomarker of Dup15q syndrome that may facilitate clinical stratification, treatment monitoring, and measurement of target engagement for future clinical trials. Future work will investigate the genetic and neural underpinnings of this electrophysiological signature as well as the functional consequences of excessive beta oscillations in Dup15q syndrome.

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Age-Related Changes in 1/fNeural Electrophysiological Noise

Cited by 591 publications

References 69 publications

Enhancing Spatial Attention and Working Memory in Younger and Older Adults

Enhancing Spatial Attention and Working Memory in Younger and Older Adults

Alpha power indexes task-related networks on large and small scales: A multimodal ECoG study in humans and a non-human primate

A Quantitative Electrophysiological Biomarker of Duplication 15q11.2-q13.1 Syndrome

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