Altered temporal correlations in parietal alpha and prefrontal theta oscillations in early-stage Alzheimer disease

Abstract

Encoding and retention of information in memory are associated with a sustained increase in the amplitude of neuronal oscillations for up to several seconds. We reasoned that coordination of oscillatory activity over time might be important for memory and, therefore, that the amplitude modulation of oscillations may be abnormal in Alzheimer disease (AD). To test this hypothesis, we measured magnetoencephalography (MEG) during eyes-closed rest in 19 patients diagnosed with early-stage AD and 16 agematched control subjects and characterized the autocorrelation structure of ongoing oscillations using detrended fluctuation analysis and an analysis of the life-and waiting-time statistics of oscillation bursts. We found that Alzheimer's patients had a strongly reduced incidence of alpha-band oscillation bursts with long life-or waiting-times (< 1 s) over temporo-parietal regions and markedly weaker autocorrelations on long time scales (1-25 seconds). Interestingly, the life-and waiting-times of theta oscillations over medial prefrontal regions were greatly increased. Whereas both temporo-parietal alpha and medial prefrontal theta oscillations are associated with retrieval and retention of information, metabolic and structural deficits in early-stage AD are observed primarily in temporo-parietal areas, suggesting that the enhanced oscillations in medial prefrontal cortex reflect a compensatory mechanism. Together, our results suggest that amplitude modulation of neuronal oscillations is important for cognition and that indices of amplitude dynamics of oscillations may prove useful as neuroimaging biomarkers of early-stage AD.Alzheimer's disease ͉ magnetoencephalography ͉ neuronal oscillations ͉ resting-state brain activity ͉ temporal correlations P sychological and neuroimaging data suggest that the brain performs many important functions during rest, such as retrieval and manipulation of information in short-term memory, and problem-solving and planning (1, 2). These resting-state functions may represent an essential aspect of human selfawareness and are susceptible to impairment in brain-related disorders including depression, schizophrenia, and dementia (3).Neuroimaging has identified anatomical patterns of activity that are remarkably consistent across resting-state experiments, most notably in the precuneus, lateral parietal and medial prefrontal cortices (4, 5). The existence of such a ''resting-state network'' has been suggested to reflect a ''default mode'' of brain operation in the absence of goal-directed behavior (6). Coordination of anatomically distributed activity during rest has been studied extensively by computing correlations between neuronal signals from different brain areas (Fig. 1). This approach has revealed aberrant resting-state networks in Alzheimer disease (AD) (7-9) and other disorders (4, 10, 11).For cognitive processing, coordination of local brain activity over time may be just as important as the coordination of simultaneous activity in anatomically distinct brain regions and may be refl...

Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws

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Long-Range Temporal Correlations in Resting-State Alpha Oscillations Predict Human Timing-Error Dynamics

“…More importantly, however, the result suggests that the functional organization of these areas, as reflected in the resting-state dynamics of ϳ10 Hz oscillations, play a prominent role in 1/f ␤ scaling in timing errors. Previous studies reporting a functional role of long-range temporal correlations in neuronal oscillations have done so by comparing different groups of participants, for example, control subjects and patients with Alzheimer's disease (Montez et al, 2009), epilepsy (Monto et al, 2007, depression (LinkenkaerHansen et al, 2005), or schizophrenia (Nikulin et al, 2012). We extended these findings by showing that describing time-series of oscillatory activity in normal participants with power-laws with variable exponents can predict power-laws in finger tapping sequences, suggesting that the brain's complex scale-free dynamics are directly or indirectly related to the scale-free dynamics in behavior.…”

“…The observed values for ␤ lie in the neighborhood of 1, suggesting that the signals have long-range temporal correlations (Chen et al, 1997;Rangarajan and Ding, 2000;Hennig et al, 2011;Torre et al, 2011). Other behavioral data showing evidence for power-law frequency scaling in the temporal organization of errors include size estimation and the detection of threshold stimuli (Gilden et al, 1995;Gilden, 1997;Monto et al, 2008). Long-range temporal correlations in man-made sequences outside the laboratory are also well documented, e.g., the loudness fluctuations in various types of music and speech (Voss and Clarke, 1975;Levitin et al, 2012).…”

On the early diagnosis of Alzheimer's Disease from multimodal signals: A survey

“…Increased delta and theta activity [202][203][204][205] in frontal and central areas [206] and decreased alpha activity in posterior and temporal regions [206] has been reported in several pieces of research, i.e. slower signals.…”