Characterizing Population EEG Dynamics throughout Adulthood

Hashemi, Ali; Pino, Lou; Moffat, Graeme; Mathewson, Karen J.; Aimone, Chris; Bennett, Patrick J.; Schmidt, Louis A.; Sekuler, Allison B.

doi:10.1523/eneuro.0275-16.2016

Cited by 97 publications

(77 citation statements)

References 47 publications

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“…There are reports suggesting either increases (Rossini et al, ) or decreases in delta/theta power with increasing age, both of which have been found to be associated with cognitive impairments (Finnigan & Robertson, ; Stomrud et al, ). Non‐linear relationships with age have also been suggested, indicating reversal of delta power from decreases to increases in later life (Gomez et al, ; Hashemi et al, ). Typically such alterations are accompanied by complementary changes in high‐frequency power (alpha/beta) describing the overall shift in toward either slowing or speeding with age.…”

Section: Discussionsupporting

confidence: 90%

“…The findings related to spectral slowing in dementia are of particular importance because they appear in the direction opposite to what is typically seen with normal aging. Healthy elderly adults exhibit decreased low‐frequency power and increased high‐frequency power (Gomez, Perez‐Macias, Poza, Fernandez, & Hornero, ; Hashemi et al, ), indicating a shift toward faster oscillatory dynamics, contrasting with the patterns reported in dementia.…”

Section: Introductionmentioning

confidence: 99%

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Spontaneous oscillatory markers of cognitive status in two forms of dementia

Shah-Basak

Kielar

Deschamps

et al. 2018

Human Brain Mapping

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Abnormal oscillatory brain activity in dementia may indicate incipient neuronal/synaptic dysfunction, rather than frank structural atrophy. Leveraging a potential link between the degree of abnormal oscillatory activity and cognitive symptom severity, one could localize brain regions in a diseased but pre-atrophic state, which may be more amenable to interventions. In the current study, we evaluated the relationships among cognitive deficits, regional volumetric changes, and resting-state magnetoencephalography abnormalities in patients with mild cognitive impairment (MCI; N = 10; age: 75.9 AE 7.3) or primary progressive aphasia (PPA; N = 12; 69.7 AE 8.0), and compared them to normal aging [young (N = 18; 24.6 AE 3.5), older controls (N = 24; 67.2 AE 9.7]. Whole-brain source-level resting-state estimates of relative oscillatory power in the delta (1-4 Hz), theta (4-7 Hz), alpha (8-12 Hz), and beta (15-30 Hz) bands were combined with gray matter volumes and cognitive scores to examine between-group differences and brain-behavior correlations. Language and executive function (EF) abilities were impaired in patients with PPA, while episodic memory was impaired in MCI. Widespread oscillatory speeding and volumetric shrinkage was associated with normal aging, whereas the trajectory in PPA indicated widespread oscillatory slowing with additional volumetric reductions. Increases in delta and decreases in alpha power uniquely predicted group membership to PPA. Beyond volumetric reductions, more delta predicted poorer memory. In patients with MCI, no consistent group difference among oscillatory measures was found. The contributions of delta/alpha power on memory abilities were larger than volumetric differences. Spontaneous oscillatory abnormalities in association with cognitive symptom severity can serve as a marker of neuronal dysfunction in dementia, providing targets for promising treatments. K E Y W O R D S dementia, magnetoencephalography, mild cognitive impairment, normal aging, primary progressive aphasia, resting-state

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Spontaneous oscillatory markers of cognitive status in two forms of dementia

Shah-Basak

Kielar

Deschamps

et al. 2018

Human Brain Mapping

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“…It is also not known how well the active electrodes that we used in this study preform in movement situations, and some research has shown that data of similar quality can be measured with electrodes with no active amplification (Debener et al, 2012;Zink et al, 2016). Finally, consumer grade EEG hardware is becoming increasingly sophisticated, and very affordable Bluetooth EEG systems have been shown to measure research quality EEG and ERP data (Krigolson, Williams, Norton, Hassall, & Colino,2017;Hashemi et al, 2016). We are also testing how these systems can be integrated into our experimental setup to further increase portability and minimize obtrusiveness of the equipment.…”

Section: Discussionmentioning

confidence: 99%

Taking off the training wheels: Measuring auditory P3 during outdoor cycling using an active wet EEG system

Scanlon

Townsend

Cormier

et al. 2017

Preprint

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Mobile EEG allows the investigation of brain activity in increasingly complex environments. In this study, EEG equipment was adapted for use and transportation in a backpack while cycling.Participants performed an auditory oddball task while cycling outside and sitting in an isolated chamber inside the lab. Cycling increased EEG noise and marginally diminished alpha amplitude. However, this increased noise did not influence the ability to measure reliable event related potentials (ERP). The P3 was similar in topography, and morphology when outside on the bike, with a lower amplitude in the outside cycling condition. There was only a minor decrease in the statistical power to measure reliable ERP effects. Unexpectedly, when biking outside significantly decreased P2 and increased N1 amplitude were observed when evoked by both standards and targets compared with sitting in the lab. This may be due to attentional processes filtering the overlapping sounds between the tones used and similar environmental frequencies.This study established methods for mobile recording of ERP signals. Future directions include investigating auditory P2 filtering inside the laboratory.

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“…The peak frequency of alpha activity (i.e the frequency within the 8-12Hz, that has the maximal power) has been found to change across the life span, increasing from childhood to adulthood, and subsequently decreasing with age (Aurlien et al, 2004;Lindsley, 1939,Hashemi et al, 2016Bazanova & Vernon, 2014). There is evidence that the frequency of alpha activity is positively correlated to measures such as working performance (reviewed in Klimesch, 1999).…”

Section: Introductionmentioning

confidence: 99%

Cerebral peak alpha frequency predicts individual differences in pain sensitivity

et al. 2018

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The identification of neurobiological markers that predict individual predisposition to pain are not only important for development of effective pain treatments, but would also yield a more complete understanding of how pain is implemented in the brain. In the current study using electroencephalography (EEG), we investigated the relationship between the peak frequency of alpha activity over sensorimotor cortex and pain intensity during capsaicin-heat pain (C-HP), a prolonged pain model known to induce spinal central sensitization in primates. We found that peak alpha frequency (PAF) recorded during a pain-free period preceding the induction of prolonged pain correlated with subsequent pain intensity reports: slower peak frequency at pain-free state was associated with higher pain during the prolonged pain condition. Moreover, the degree to which PAF decreased between pain-free and prolonged pain states was correlated with pain intensity. These two metrics were statistically uncorrelated and in combination were able to account for 50% of the variability in pain intensity. Altogether, our findings suggest that pain-free state PAF over relevant sensory systems could serve as a marker of individual predisposition to prolonged pain. Moreover, slowing of PAF in response to prolonged pain could represent an objective marker for subjective pain intensity. Our findings potentially lead the way for investigations in clinical populations in which alpha oscillations and the brain areas contributing to their generation are used in identifying and formulating treatment strategies for patients more likely to develop chronic pain.

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Characterizing Population EEG Dynamics throughout Adulthood

Cited by 97 publications

References 47 publications

Spontaneous oscillatory markers of cognitive status in two forms of dementia

Spontaneous oscillatory markers of cognitive status in two forms of dementia

Taking off the training wheels: Measuring auditory P3 during outdoor cycling using an active wet EEG system

Cerebral peak alpha frequency predicts individual differences in pain sensitivity

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