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Gamma coherence and memory in 40 men. The figure shows the linear fit between long-term memory and four working memory tests, and the difference in coherence between monomodal and bimodal stimulation. Data are shown for the total brain coherence (ΔCT) and coherence in the anterior part of the brain only (ΔCA). LT Verbal Recall, Long-Term Verbal Recall Memory; Verbal Learning, Verbal Learning Memory; PRM, Pattern Recognition Memory; SRM, Spatial Recognition Memory; PAL, Paired Associates Learning; SOC, Stockings of Cambridge.
Source publication
HIGHLIGHTS Memory correlates with the difference between single and double-sensory evoked steady-state coherence in the gamma range (ΔC).
The correlation is most pronounced for the anterior brain region (ΔCA).
The correlation is not driven by birth size, education, speed of processing, or intelligence.
The sensitivity of ΔCA for detecting low memor...
Citations
... Participants of this cohort have been examined multiple times previously with regard to physiological state and cognitive skills, and the cohort is optimal for assessing agerelated changes in brain function from a life course perspective. Our published work has reported subtle age-related changes in brain structure [22], electrical activity [14,23,19,20], and cerebrovascular function [24] brought on by aging. For the current study, we examined participants who underwent repeated examinations at two time points five years apart, the first in 2015-2016 (T1) and the second in 2021-2022 (T2). ...
... The experimental setup was described previously [20,14,23,19]. Participants were seated comfortably in a dark room, with a 60 cm distance to a computer screen, which acted as the visual stimulator. ...
... In addition, the nature of the figure makes it more engaging to look at, which aids in improving the participant's attention. These are factors previously observed to be crucial to produce potentials in the gamma band [25][26][27], also in our laboratory [20,23]. ...
Aims:
Gamma oscillations (≈25-100 Hz) are believed to play an essential role in cognition, and aberrant gamma oscillations occur in brain aging and neurodegeneration. This study examined age-related changes in visually evoked gamma oscillations at two different time points 5 years apart and tested the hypothesis that the power of gamma oscillations correlated to cognitive skills.
Methods:
The cohort consists of elderly males belonging to the Metropolit 1953 Danish Male Birth Cohort (first visit, N=124; second visit, N=88) over a 5-year period from 63 to 68 years of age. Cognitive functions were assessed using a neuropsychological test battery measuring global cognition, intelligence, memory, and processing speed. The power of steady-state visual evoked potentials (SSVEP) was measured at 8 Hz (alpha) and 36 Hz (gamma) frequencies using EEG scalp electrodes.
Results:
Over the 5-year period cognitive performance remained relatively stable while the power of visually evoked gamma oscillations shifted from posterior to anterior brain regions with increasing age. A higher-than-average cognitive score was correlated with higher gamma power in parieto-occipital areas and lower in frontocentral areas, i.e., preserved distribution of the evoked activity.
Conclusions:
Our data reveal that the distribution of visually evoked gamma activity becomes distributed with age. Preserved posterior-occipital gamma power in participants with a high level of cognitive performance is consistent with a close association between the ability to produce gamma oscillations and cognition. The data may contribute to our understanding of the mechanisms that link evoked gamma activity and cognition in the aging brain.
... The participants were examined physiologically and cognitively at several time points throughout their lives, making them ideal for a longitudinal ageing study. Previous studies from this cohort have focused on age-related changes in brain structures [26], electrical activity [27][28][29][30] and cerebrovascular function [31]. For the present study, we recruited a subset of participants from the cohort who had been examined at three different timepoints 5 years apart, with the first examination taking place in 2011/2012 (T1), the second in 2015/2016 (T2) and the third in 2021/2022 (T3). ...
Hippocampal blood–brain barrier (BBB) permeability may increase in normal healthy ageing and contribute to neurodegenerative disease. To examine this hypothesis, we investigated the correlation between blood–brain barrier (BBB) permeability, regional brain volume, memory functions and health and lifestyle factors in The Metropolit 1953 Danish Male Birth Cohort. We used dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with a gadolinium-based contrast agent to assess BBB permeability in 77 participants in the cohort. BBB permeability was measured as K i values in the hippocampus, thalamus and white matter. Over a 10-year period, we observed progressive atrophy of both the left and right hippocampus ( p = 0.001). There was no significant correlation between current BBB permeability and hippocampal volume, prior atrophy or cognition. The hippocampus volume ratio was associated with better visual and verbal memory scores ( p < 0.01). Regional BBB differences revealed higher K i values in the hippocampus and white matter than in the thalamus ( p < 0.001). Participants diagnosed with type II diabetes had significantly higher BBB permeability in the white matter ( p = 0.015) and thalamus ( p = 0.016), which was associated with a higher Fazekas score ( p = 0.024). We do not find evidence that BBB integrity is correlated with age-related hippocampal atrophy or cognitive functions. The association between diabetes, white matter hyperintensities and increased BBB permeability is consistent with the idea that cerebrovascular disease compromises BBB integrity. Our findings suggest that the hippocampus is particularly prone to age-related atrophy, which may explain some of the cognitive changes that accompany older age, but this prior atrophy is not correlated with current BBB permeability.
... Elevated c-power is associated with the maintenance of multiple items in WM, indicating a role for c in WM as well as in perception. Additionally, previous research has shown that cortical oscillatory neural activity in the c-frequency range was related to attention control and that successful attentional processing depends on the c-phase [30][31][32][33][34]. Attention control is also an essential component of WM, especially for high-load WM tasks, and participates in the whole process of WM [10]. ...
Working memory (WM), a central component of general cognition, plays an essential role in human beings’ daily lives. WM impairments often occur in psychiatric, neurodegenerative, and neurodevelopmental disorders, mainly presenting as loss of high-load WM. In previous research, electroacupuncture (EA) has been shown to be an effective treatment for cognitive impairments. Frequency parameters are an important factor in therapeutic results, but the optimal frequency parameters of EA have not yet been identified. In this study, we chose theta-EA (θ-EA; 6 Hz) and gamma-EA (γ-EA; 40 Hz), corresponding to the transcranial alternating-current stimulation (tACS) frequency parameters at the Baihui (DU20) and Shenting (DU24) acupoints, in order to compare the effects of different EA frequencies on WM. We evaluated WM performance using visual 1-back, 2-back, and 3-back WM tasks involving digits. Each participant (N = 30) attended three different sessions in accordance with a within-subject crossover design. We performed θ-EA, γ-EA, and sham-EA in a counterbalanced order, conducting the WM task both before and after intervention. The results showed that d-prime (d′) under all three stimulation conditions had no significance in the 1-back and 2-back tasks. However, in the 3-back task, there was a significant improvement in d′ after intervention compared to d′ before intervention under θ-EA (F [1, 29] = 22.64; P<0.001), while we saw no significant difference in the γ-EA and sham-EA groups. Reaction times for hits (RT-hit) under all three stimulation conditions showed decreasing trends in 1-, 2-, and 3-back tasks but without statistically significant differences. These findings suggest that the application of θ-EA might facilitate high-load WM performance.
... In this study, we focus on high-frequency (i.e., gammaband) evoked brain activity. There are several reasons for focusing on gamma-band activity (see also Horwitz et al., 2017a). Cognitive function is related to brain activity at various frequencies (see, e.g., Hanslmayr et al., 2008;Roux and Uhlhaas, 2014). ...
... The study sample comprise of 40 men who were selected from the Metropolit Cohort which contains data on males born in Copenhagen in 1953 (Osler et al., 2006), aged 61-62 at the time of the data collection for the present study (see also Horwitz et al., 2017a). Therefore, the sample represents a homogenous sample (with respect to age, gender, and birth location) of elderly subjects. ...
... This group of people was also examined in Horwitz et al. (2017a) and represent a sub-sample of participants included in the analysis in Horwitz et al. (2017b). Furthermore, the present measurements were taken together with those used in Horwitz et al. (2017a). ...
This study investigates the association between intelligence and brain power responses to a passive audiovisual stimulation. We measure the power of gamma-range steady-state responses (SSRs) as well as intelligence and other aspects of neurocognitive function in 40 healthy males born in 1953. The participants are a part of a Danish birth cohort study and the data therefore include additional information measured earlier in life. Our main power measure is the difference in power between a visual stimulation and a combined audiovisual stimulation. We hypothesize and establish empirically that the power measure is associated with intelligence. In particular, we find a highly significant correlation between the power measure and present intelligence scores. The association is robust to controlling for size-at-birth measures, length of education, speed of processing as well as a range of other potentially confounding factors. Interestingly, we find that intelligence scores measured earlier in life (childhood, youth, late midlife), are also correlated with the present-day power measure, suggesting a deep connection between intelligence and the power measure. Finally, we find that the power measure has a high sensitivity for detection of an intelligence score below the average.
... Coherence has been widely used as a non-invasive measure of functional connectivity between cortical areas. A related study found a correlation of steady-state gamma coherence evoked by different stimulation types with long-term memory capacity (Horwitz et al., 2017). Reduced EEG coherence is also a well-established feature in Alzheimer's disease with correlation with the degree of cognitive impairment. ...
Disrupted sleep is a contributing factor to cognitive ageing, while also being associated with neurodegenerative disorders. Little is known, however, about the relation of sleep and the gradual cognitive changes over the adult life course. Sleep electroencephalogram (EEG) patterns are potential markers of the cognitive progress. To test this hypothesis, we assessed sleep architecture and EEG of 167 men born in the Copenhagen Metropolitan Area in 1953, who, based on individual cognitive testing from early (~18 years) to late adulthood (~58 years), were divided into 85 subjects with negative and 82 with positive cognitive change over their adult life. Participants underwent standard polysomnography, including manual sleep scoring at age ~58 years. Features of sleep macrostructure were combined with a number of EEG features to distinguish between the two groups. EEG rhythmicity was assessed by spectral power analysis in frontal, central and occipital sites. Functional connectivity was measured by inter‐hemispheric EEG coherence. Group differences were assessed by analysis of covariance (p < 0.05), including education and severity of depression as potential covariates. Subjects with cognitive decline exhibited lower sleep efficiency, reduced inter‐hemispheric connectivity during rapid eye movement (REM) sleep, and slower EEG rhythms during stage 2 non‐REM sleep. Individually, none of these tendencies remained significant after multiple test correction; however, by combining them in a machine learning approach, the groups were separated with 72% accuracy (75% sensitivity, 67% specificity). Ongoing medical screenings are required to confirm the potential of sleep efficiency and sleep EEG patterns as signs of individual cognitive progress.
Objective:
A central concern in aging is the preservation of cognitive skills. Tools to detect cognitive decline are sparse. The aim of this study was to ascertain whether cognitive decline is accompanied by alterations in the temporal dynamics of steady-state visual evoked potentials (SSVEPs).
Methods:
We included 162 men from the Danish Metropolit birth cohort. Their cognitive trajectory was based on their intelligence test score at youth (age ~18), middle age (age ~56), and late middle age (age ~62). Subjects underwent cognitive tests and steady-state visual stimulation. Temporal dynamics of SSVEPs were assessed in terms of amplitude and phase coherence.
Results:
The latency and magnitude of the amplitude modulation of the 36-Hz response correlated negatively with subjects' cognition indices. Furthermore, negative cognition index was associated with loss of SSVEPs at 36 Hz, and both 8 Hz and 36 Hz in severe cases.
Conclusion:
Latency and magnitude of gamma frequency SSVEPs increase with cognitive decline. This suggests that the facilitation of SSVEPs first becomes problematic at gamma frequencies, then at alpha frequencies.
Significance:
Our data suggests that the temporal dynamics of SSVEPs can be used as an indicator of cognitive impairment. Furthermore, evoked gamma oscillations are especially vulnerable in cognitive decline.
